text stringlengths 559 401k | source stringlengths 13 121 |
|---|---|
The binomial approximation is useful for approximately calculating powers of sums of 1 and a small number x. It states that
(
1
+
x
)
α
≈
1
+
α
x
.
{\displaystyle (1+x)^{\alpha }\approx 1+\alpha x.}
It is valid when
|
x
|
<
1
{\displaystyle |x|<1}
and
|
α
x
|
≪
1
{\displaystyle |\alpha x|\ll 1}
where
x
{\displaystyle x}
and
α
{\displaystyle \alpha }
may be real or complex numbers.
The benefit of this approximation is that
α
{\displaystyle \alpha }
is converted from an exponent to a multiplicative factor. This can greatly simplify mathematical expressions (as in the example below) and is a common tool in physics.
The approximation can be proven several ways, and is closely related to the binomial theorem. By Bernoulli's inequality, the left-hand side of the approximation is greater than or equal to the right-hand side whenever
x
>
−
1
{\displaystyle x>-1}
and
α
≥
1
{\displaystyle \alpha \geq 1}
.
== Derivations ==
=== Using linear approximation ===
The function
f
(
x
)
=
(
1
+
x
)
α
{\displaystyle f(x)=(1+x)^{\alpha }}
is a smooth function for x near 0. Thus, standard linear approximation tools from calculus apply: one has
f
′
(
x
)
=
α
(
1
+
x
)
α
−
1
{\displaystyle f'(x)=\alpha (1+x)^{\alpha -1}}
and so
f
′
(
0
)
=
α
.
{\displaystyle f'(0)=\alpha .}
Thus
f
(
x
)
≈
f
(
0
)
+
f
′
(
0
)
(
x
−
0
)
=
1
+
α
x
.
{\displaystyle f(x)\approx f(0)+f'(0)(x-0)=1+\alpha x.}
By Taylor's theorem, the error in this approximation is equal to
α
(
α
−
1
)
x
2
2
⋅
(
1
+
ζ
)
α
−
2
{\textstyle {\frac {\alpha (\alpha -1)x^{2}}{2}}\cdot (1+\zeta )^{\alpha -2}}
for some value of
ζ
{\displaystyle \zeta }
that lies between 0 and x. For example, if
x
<
0
{\displaystyle x<0}
and
α
≥
2
{\displaystyle \alpha \geq 2}
, the error is at most
α
(
α
−
1
)
x
2
2
{\textstyle {\frac {\alpha (\alpha -1)x^{2}}{2}}}
. In little o notation, one can say that the error is
o
(
|
x
|
)
{\displaystyle o(|x|)}
, meaning that
lim
x
→
0
error
|
x
|
=
0
{\textstyle \lim _{x\to 0}{\frac {\textrm {error}}{|x|}}=0}
.
=== Using Taylor series ===
The function
f
(
x
)
=
(
1
+
x
)
α
{\displaystyle f(x)=(1+x)^{\alpha }}
where
x
{\displaystyle x}
and
α
{\displaystyle \alpha }
may be real or complex can be expressed as a Taylor series about the point zero.
f
(
x
)
=
∑
n
=
0
∞
f
(
n
)
(
0
)
n
!
x
n
f
(
x
)
=
f
(
0
)
+
f
′
(
0
)
x
+
1
2
f
″
(
0
)
x
2
+
1
6
f
‴
(
0
)
x
3
+
1
24
f
(
4
)
(
0
)
x
4
+
⋯
(
1
+
x
)
α
=
1
+
α
x
+
1
2
α
(
α
−
1
)
x
2
+
1
6
α
(
α
−
1
)
(
α
−
2
)
x
3
+
1
24
α
(
α
−
1
)
(
α
−
2
)
(
α
−
3
)
x
4
+
⋯
{\displaystyle {\begin{aligned}f(x)&=\sum _{n=0}^{\infty }{\frac {f^{(n)}(0)}{n!}}x^{n}\\f(x)&=f(0)+f'(0)x+{\frac {1}{2}}f''(0)x^{2}+{\frac {1}{6}}f'''(0)x^{3}+{\frac {1}{24}}f^{(4)}(0)x^{4}+\cdots \\(1+x)^{\alpha }&=1+\alpha x+{\frac {1}{2}}\alpha (\alpha -1)x^{2}+{\frac {1}{6}}\alpha (\alpha -1)(\alpha -2)x^{3}+{\frac {1}{24}}\alpha (\alpha -1)(\alpha -2)(\alpha -3)x^{4}+\cdots \end{aligned}}}
If
|
x
|
<
1
{\displaystyle |x|<1}
and
|
α
x
|
≪
1
{\displaystyle |\alpha x|\ll 1}
, then the terms in the series become progressively smaller and it can be truncated to
(
1
+
x
)
α
≈
1
+
α
x
.
{\displaystyle (1+x)^{\alpha }\approx 1+\alpha x.}
This result from the binomial approximation can always be improved by keeping additional terms from the Taylor series above. This is especially important when
|
α
x
|
{\displaystyle |\alpha x|}
starts to approach one, or when evaluating a more complex expression where the first two terms in the Taylor series cancel (see example).
Sometimes it is wrongly claimed that
|
x
|
≪
1
{\displaystyle |x|\ll 1}
is a sufficient condition for the binomial approximation. A simple counterexample is to let
x
=
10
−
6
{\displaystyle x=10^{-6}}
and
α
=
10
7
{\displaystyle \alpha =10^{7}}
. In this case
(
1
+
x
)
α
>
22
,
000
{\displaystyle (1+x)^{\alpha }>22,000}
but the binomial approximation yields
1
+
α
x
=
11
{\displaystyle 1+\alpha x=11}
. For small
|
x
|
{\displaystyle |x|}
but large
|
α
x
|
{\displaystyle |\alpha x|}
, a better approximation is:
(
1
+
x
)
α
≈
e
α
x
.
{\displaystyle (1+x)^{\alpha }\approx e^{\alpha x}.}
== Example ==
The binomial approximation for the square root,
1
+
x
≈
1
+
x
/
2
{\displaystyle {\sqrt {1+x}}\approx 1+x/2}
, can be applied for the following expression,
1
a
+
b
−
1
a
−
b
{\displaystyle {\frac {1}{\sqrt {a+b}}}-{\frac {1}{\sqrt {a-b}}}}
where
a
{\displaystyle a}
and
b
{\displaystyle b}
are real but
a
≫
b
{\displaystyle a\gg b}
.
The mathematical form for the binomial approximation can be recovered by factoring out the large term
a
{\displaystyle a}
and recalling that a square root is the same as a power of one half.
1
a
+
b
−
1
a
−
b
=
1
a
(
(
1
+
b
a
)
−
1
/
2
−
(
1
−
b
a
)
−
1
/
2
)
≈
1
a
(
(
1
+
(
−
1
2
)
b
a
)
−
(
1
−
(
−
1
2
)
b
a
)
)
≈
1
a
(
1
−
b
2
a
−
1
−
b
2
a
)
≈
−
b
a
a
{\displaystyle {\begin{aligned}{\frac {1}{\sqrt {a+b}}}-{\frac {1}{\sqrt {a-b}}}&={\frac {1}{\sqrt {a}}}\left(\left(1+{\frac {b}{a}}\right)^{-1/2}-\left(1-{\frac {b}{a}}\right)^{-1/2}\right)\\&\approx {\frac {1}{\sqrt {a}}}\left(\left(1+\left(-{\frac {1}{2}}\right){\frac {b}{a}}\right)-\left(1-\left(-{\frac {1}{2}}\right){\frac {b}{a}}\right)\right)\\&\approx {\frac {1}{\sqrt {a}}}\left(1-{\frac {b}{2a}}-1-{\frac {b}{2a}}\right)\\&\approx -{\frac {b}{a{\sqrt {a}}}}\end{aligned}}}
Evidently the expression is linear in
b
{\displaystyle b}
when
a
≫
b
{\displaystyle a\gg b}
which is otherwise not obvious from the original expression.
== Generalization ==
While the binomial approximation is linear, it can be generalized to keep the quadratic term in the Taylor series:
(
1
+
x
)
α
≈
1
+
α
x
+
(
α
/
2
)
(
α
−
1
)
x
2
{\displaystyle (1+x)^{\alpha }\approx 1+\alpha x+(\alpha /2)(\alpha -1)x^{2}}
Applied to the square root, it results in:
1
+
x
≈
1
+
x
/
2
−
x
2
/
8.
{\displaystyle {\sqrt {1+x}}\approx 1+x/2-x^{2}/8.}
=== Quadratic example ===
Consider the expression:
(
1
+
ϵ
)
n
−
(
1
−
ϵ
)
−
n
{\displaystyle (1+\epsilon )^{n}-(1-\epsilon )^{-n}}
where
|
ϵ
|
<
1
{\displaystyle |\epsilon |<1}
and
|
n
ϵ
|
≪
1
{\displaystyle |n\epsilon |\ll 1}
. If only the linear term from the binomial approximation is kept
(
1
+
x
)
α
≈
1
+
α
x
{\displaystyle (1+x)^{\alpha }\approx 1+\alpha x}
then the expression unhelpfully simplifies to zero
(
1
+
ϵ
)
n
−
(
1
−
ϵ
)
−
n
≈
(
1
+
n
ϵ
)
−
(
1
−
(
−
n
)
ϵ
)
≈
(
1
+
n
ϵ
)
−
(
1
+
n
ϵ
)
≈
0.
{\displaystyle {\begin{aligned}(1+\epsilon )^{n}-(1-\epsilon )^{-n}&\approx (1+n\epsilon )-(1-(-n)\epsilon )\\&\approx (1+n\epsilon )-(1+n\epsilon )\\&\approx 0.\end{aligned}}}
While the expression is small, it is not exactly zero.
So now, keeping the quadratic term:
(
1
+
ϵ
)
n
−
(
1
−
ϵ
)
−
n
≈
(
1
+
n
ϵ
+
1
2
n
(
n
−
1
)
ϵ
2
)
−
(
1
+
(
−
n
)
(
−
ϵ
)
+
1
2
(
−
n
)
(
−
n
−
1
)
(
−
ϵ
)
2
)
≈
(
1
+
n
ϵ
+
1
2
n
(
n
−
1
)
ϵ
2
)
−
(
1
+
n
ϵ
+
1
2
n
(
n
+
1
)
ϵ
2
)
≈
1
2
n
(
n
−
1
)
ϵ
2
−
1
2
n
(
n
+
1
)
ϵ
2
≈
1
2
n
ϵ
2
(
(
n
−
1
)
−
(
n
+
1
)
)
≈
−
n
ϵ
2
{\displaystyle {\begin{aligned}(1+\epsilon )^{n}-(1-\epsilon )^{-n}&\approx \left(1+n\epsilon +{\frac {1}{2}}n(n-1)\epsilon ^{2}\right)-\left(1+(-n)(-\epsilon )+{\frac {1}{2}}(-n)(-n-1)(-\epsilon )^{2}\right)\\&\approx \left(1+n\epsilon +{\frac {1}{2}}n(n-1)\epsilon ^{2}\right)-\left(1+n\epsilon +{\frac {1}{2}}n(n+1)\epsilon ^{2}\right)\\&\approx {\frac {1}{2}}n(n-1)\epsilon ^{2}-{\frac {1}{2}}n(n+1)\epsilon ^{2}\\&\approx {\frac {1}{2}}n\epsilon ^{2}((n-1)-(n+1))\\&\approx -n\epsilon ^{2}\end{aligned}}}
This result is quadratic in
ϵ
{\displaystyle \epsilon }
which is why it did not appear when only the linear terms in
ϵ
{\displaystyle \epsilon }
were kept.
== References == | Wikipedia/Binomial_approximation |
In mathematics and computational science, the Euler method (also called the forward Euler method) is a first-order numerical procedure for solving ordinary differential equations (ODEs) with a given initial value. It is the most basic explicit method for numerical integration of ordinary differential equations and is the simplest Runge–Kutta method. The Euler method is named after Leonhard Euler, who first proposed it in his book Institutionum calculi integralis (published 1768–1770).
The Euler method is a first-order method, which means that the local error (error per step) is proportional to the square of the step size, and the global error (error at a given time) is proportional to the step size.
The Euler method often serves as the basis to construct more complex methods, e.g., predictor–corrector method.
== Geometrical description ==
=== Purpose and why it works ===
Consider the problem of calculating the shape of an unknown curve which starts at a given point and satisfies a given differential equation. Here, a differential equation can be thought of as a formula by which the slope of the tangent line to the curve can be computed at any point on the curve, once the position of that point has been calculated.
The idea is that while the curve is initially unknown, its starting point, which we denote by
A
0
,
{\displaystyle A_{0},}
is known (see Figure 1). Then, from the differential equation, the slope to the curve at
A
0
{\displaystyle A_{0}}
can be computed, and so, the tangent line.
Take a small step along that tangent line up to a point
A
1
.
{\displaystyle A_{1}.}
Along this small step, the slope does not change too much, so
A
1
{\displaystyle A_{1}}
will be close to the curve. If we pretend that
A
1
{\displaystyle A_{1}}
is still on the curve, the same reasoning as for the point
A
0
{\displaystyle A_{0}}
above can be used. After several steps, a polygonal curve (
A
0
,
A
1
,
A
2
,
A
3
,
…
{\displaystyle A_{0},A_{1},A_{2},A_{3},\dots }
) is computed. In general, this curve does not diverge too far from the original unknown curve, and the error between the two curves can be made small if the step size is small enough and the interval of computation is finite.
=== First-order process ===
When given the values for
t
0
{\displaystyle t_{0}}
and
y
(
t
0
)
{\displaystyle y(t_{0})}
, and the derivative of
y
{\displaystyle y}
is a given function of
t
{\displaystyle t}
and
y
{\displaystyle y}
denoted as
y
′
(
t
)
=
f
(
t
,
y
(
t
)
)
{\displaystyle y'(t)=f{\bigl (}t,y(t){\bigr )}}
. Begin the process by setting
y
0
=
y
(
t
0
)
{\displaystyle y_{0}=y(t_{0})}
. Next, choose a value
h
{\displaystyle h}
for the size of every step along t-axis, and set
t
n
=
t
0
+
n
h
{\displaystyle t_{n}=t_{0}+nh}
(or equivalently
t
n
+
1
=
t
n
+
h
{\displaystyle t_{n+1}=t_{n}+h}
). Now, the Euler method is used to find
y
n
+
1
{\displaystyle y_{n+1}}
from
y
n
{\displaystyle y_{n}}
and
t
n
{\displaystyle t_{n}}
:
y
n
+
1
=
y
n
+
h
f
(
t
n
,
y
n
)
.
{\displaystyle y_{n+1}=y_{n}+hf(t_{n},y_{n}).}
The value of
y
n
{\displaystyle y_{n}}
is an approximation of the solution at time
t
n
{\displaystyle t_{n}}
, i.e.,
y
n
≈
y
(
t
n
)
{\displaystyle y_{n}\approx y(t_{n})}
. The Euler method is explicit, i.e. the solution
y
n
+
1
{\displaystyle y_{n+1}}
is an explicit function of
y
i
{\displaystyle y_{i}}
for
i
≤
n
{\displaystyle i\leq n}
.
=== Higher-order process ===
While the Euler method integrates a first-order ODE, any ODE of order
N
{\displaystyle N}
can be represented as a system of first-order ODEs. When given the ODE of order
N
{\displaystyle N}
defined as
y
(
N
+
1
)
(
t
)
=
f
(
t
,
y
(
t
)
,
y
′
(
t
)
,
…
,
y
(
N
)
(
t
)
)
,
{\displaystyle y^{(N+1)}(t)=f\left(t,y(t),y'(t),\ldots ,y^{(N)}(t)\right),}
as well as
h
{\displaystyle h}
,
t
0
{\displaystyle t_{0}}
, and
y
0
,
y
0
′
,
…
,
y
0
(
N
)
{\displaystyle y_{0},y'_{0},\dots ,y_{0}^{(N)}}
, we implement the following formula until we reach the approximation of the solution to the ODE at the desired time:
y
→
i
+
1
=
(
y
i
+
1
y
i
+
1
′
⋮
y
i
+
1
(
N
−
1
)
y
i
+
1
(
N
)
)
=
(
y
i
+
h
⋅
y
i
′
y
i
′
+
h
⋅
y
i
″
⋮
y
i
(
N
−
1
)
+
h
⋅
y
i
(
N
)
y
i
(
N
)
+
h
⋅
f
(
t
i
,
y
i
,
y
i
′
,
…
,
y
i
(
N
)
)
)
{\displaystyle {\vec {y}}_{i+1}={\begin{pmatrix}y_{i+1}\\y'_{i+1}\\\vdots \\y_{i+1}^{(N-1)}\\y_{i+1}^{(N)}\end{pmatrix}}={\begin{pmatrix}y_{i}+h\cdot y'_{i}\\y'_{i}+h\cdot y''_{i}\\\vdots \\y_{i}^{(N-1)}+h\cdot y_{i}^{(N)}\\y_{i}^{(N)}+h\cdot f\left(t_{i},y_{i},y'_{i},\ldots ,y_{i}^{(N)}\right)\end{pmatrix}}}
These first-order systems can be handled by Euler's method or, in fact, by any other scheme for first-order systems.
== First-order example ==
Given the initial value problem
y
′
=
y
,
y
(
0
)
=
1
,
{\displaystyle y'=y,\quad y(0)=1,}
we would like to use the Euler method to approximate
y
(
4
)
{\displaystyle y(4)}
.
=== Using step size equal to 1 (h = 1) ===
The Euler method is
y
n
+
1
=
y
n
+
h
f
(
t
n
,
y
n
)
.
{\displaystyle y_{n+1}=y_{n}+hf(t_{n},y_{n}).}
so first we must compute
f
(
t
0
,
y
0
)
{\displaystyle f(t_{0},y_{0})}
. In this simple differential equation, the function
f
{\displaystyle f}
is defined by
f
(
t
,
y
)
=
y
{\displaystyle f(t,y)=y}
. We have
f
(
t
0
,
y
0
)
=
f
(
0
,
1
)
=
1.
{\displaystyle f(t_{0},y_{0})=f(0,1)=1.}
By doing the above step, we have found the slope of the line that is tangent to the solution curve at the point
(
0
,
1
)
{\displaystyle (0,1)}
. Recall that the slope is defined as the change in
y
{\displaystyle y}
divided by the change in
t
{\displaystyle t}
, or
Δ
y
Δ
t
{\textstyle {\frac {\Delta y}{\Delta t}}}
.
The next step is to multiply the above value by the step size
h
{\displaystyle h}
, which we take equal to one here:
h
⋅
f
(
y
0
)
=
1
⋅
1
=
1.
{\displaystyle h\cdot f(y_{0})=1\cdot 1=1.}
Since the step size is the change in
t
{\displaystyle t}
, when we multiply the step size and the slope of the tangent, we get a change in
y
{\displaystyle y}
value. This value is then added to the initial
y
{\displaystyle y}
value to obtain the next value to be used for computations.
y
0
+
h
f
(
y
0
)
=
y
1
=
1
+
1
⋅
1
=
2.
{\displaystyle y_{0}+hf(y_{0})=y_{1}=1+1\cdot 1=2.}
The above steps should be repeated to find
y
2
{\displaystyle y_{2}}
,
y
3
{\displaystyle y_{3}}
and
y
4
{\displaystyle y_{4}}
.
y
2
=
y
1
+
h
f
(
y
1
)
=
2
+
1
⋅
2
=
4
,
y
3
=
y
2
+
h
f
(
y
2
)
=
4
+
1
⋅
4
=
8
,
y
4
=
y
3
+
h
f
(
y
3
)
=
8
+
1
⋅
8
=
16.
{\displaystyle {\begin{aligned}y_{2}&=y_{1}+hf(y_{1})=2+1\cdot 2=4,\\y_{3}&=y_{2}+hf(y_{2})=4+1\cdot 4=8,\\y_{4}&=y_{3}+hf(y_{3})=8+1\cdot 8=16.\end{aligned}}}
Due to the repetitive nature of this algorithm, it can be helpful to organize computations in a chart form, as seen below, to avoid making errors.
The conclusion of this computation is that
y
4
=
16
{\displaystyle y_{4}=16}
. The exact solution of the differential equation is
y
(
t
)
=
e
t
{\displaystyle y(t)=e^{t}}
, so
y
(
4
)
=
e
4
≈
54.598
{\displaystyle y(4)=e^{4}\approx 54.598}
. Although the approximation of the Euler method was not very precise in this specific case, particularly due to a large value step size
h
{\displaystyle h}
, its behaviour is qualitatively correct as the figure shows.
=== Using other step sizes ===
As suggested in the introduction, the Euler method is more accurate if the step size
h
{\displaystyle h}
is smaller. The table below shows the result with different step sizes. The top row corresponds to the example in the previous section, and the second row is illustrated in the figure.
The error recorded in the last column of the table is the difference between the exact solution at
t
=
4
{\displaystyle t=4}
and the Euler approximation. In the bottom of the table, the step size is half the step size in the previous row, and the error is also approximately half the error in the previous row. This suggests that the error is roughly proportional to the step size, at least for fairly small values of the step size. This is true in general, also for other equations; see the section Global truncation error for more details.
Other methods, such as the midpoint method also illustrated in the figures, behave more favourably: the global error of the midpoint method is roughly proportional to the square of the step size. For this reason, the Euler method is said to be a first-order method, while the midpoint method is second order.
We can extrapolate from the above table that the step size needed to get an answer that is correct to three decimal places is approximately 0.00001, meaning that we need 400,000 steps. This large number of steps entails a high computational cost. For this reason, higher-order methods are employed such as Runge–Kutta methods or linear multistep methods, especially if a high accuracy is desired.
== Higher-order example ==
For this third-order example, assume that the following information is given:
y
‴
+
4
t
y
″
−
t
2
y
′
−
(
cos
t
)
y
=
sin
t
t
0
=
0
y
0
=
y
(
t
0
)
=
2
y
0
′
=
y
′
(
t
0
)
=
−
1
y
0
″
=
y
″
(
t
0
)
=
3
h
=
0.5
{\displaystyle {\begin{aligned}&y'''+4ty''-t^{2}y'-(\cos {t})y=\sin {t}\\&t_{0}=0\\&y_{0}=y(t_{0})=2\\&y'_{0}=y'(t_{0})=-1\\&y''_{0}=y''(t_{0})=3\\&h=0.5\end{aligned}}}
From this we can isolate y''' to get the equation:
f
(
t
,
y
,
y
′
,
y
″
)
=
y
‴
=
sin
t
+
(
cos
t
)
y
+
t
2
y
′
−
4
t
y
″
{\displaystyle f\left(t,y,y',y''\right)=y'''=\sin {t}+(\cos {t})y+t^{2}y'-4ty''}
Using that we can get the solution for
y
→
1
{\displaystyle {\vec {y}}_{1}}
:
y
→
1
=
(
y
1
y
1
′
y
1
″
)
=
(
y
0
+
h
⋅
y
0
′
y
0
′
+
h
⋅
y
0
″
y
0
″
+
h
⋅
f
(
t
0
,
y
0
,
y
0
′
,
y
0
″
)
)
=
(
2
+
0.5
⋅
−
1
−
1
+
0.5
⋅
3
3
+
0.5
⋅
(
sin
0
+
(
cos
0
)
⋅
2
+
0
2
⋅
(
−
1
)
−
4
⋅
0
⋅
3
)
)
=
(
1.5
0.5
4
)
{\displaystyle {\vec {y}}_{1}={\begin{pmatrix}y_{1}\\y_{1}'\\y_{1}''\end{pmatrix}}={\begin{pmatrix}y_{0}+h\cdot y'_{0}\\y'_{0}+h\cdot y''_{0}\\y''_{0}+h\cdot f\left(t_{0},y_{0},y'_{0},y''_{0}\right)\end{pmatrix}}={\begin{pmatrix}2+0.5\cdot -1\\-1+0.5\cdot 3\\3+0.5\cdot \left(\sin {0}+(\cos {0})\cdot 2+0^{2}\cdot (-1)-4\cdot 0\cdot 3\right)\end{pmatrix}}={\begin{pmatrix}1.5\\0.5\\4\end{pmatrix}}}
And using the solution for
y
→
1
{\displaystyle {\vec {y}}_{1}}
, we can get the solution for
y
→
2
{\displaystyle {\vec {y}}_{2}}
:
y
→
2
=
(
y
2
y
2
′
y
2
″
)
=
(
y
1
+
h
⋅
y
1
′
y
1
′
+
h
⋅
y
1
″
y
1
″
+
h
⋅
f
(
t
1
,
y
1
,
y
1
′
,
y
1
″
)
)
=
(
1.5
+
0.5
⋅
0.5
0.5
+
0.5
⋅
4
4
+
0.5
⋅
(
sin
0.5
+
(
cos
0.5
)
⋅
1.5
+
0.5
2
⋅
0.5
−
4
⋅
0.5
⋅
4
)
)
=
(
1.75
2.5
0.9604...
)
{\displaystyle {\vec {y}}_{2}={\begin{pmatrix}y_{2}\\y_{2}'\\y_{2}''\end{pmatrix}}={\begin{pmatrix}y_{1}+h\cdot y'_{1}\\y'_{1}+h\cdot y''_{1}\\y''_{1}+h\cdot f\left(t_{1},y_{1},y'_{1},y''_{1}\right)\end{pmatrix}}={\begin{pmatrix}1.5+0.5\cdot 0.5\\0.5+0.5\cdot 4\\4+0.5\cdot \left(\sin {0.5}+(\cos {0.5})\cdot 1.5+0.5^{2}\cdot 0.5-4\cdot 0.5\cdot 4\right)\end{pmatrix}}={\begin{pmatrix}1.75\\2.5\\0.9604...\end{pmatrix}}}
We can continue this process using the same formula as long as necessary to find whichever
y
→
i
{\displaystyle {\vec {y}}_{i}}
desired.
== Derivation ==
The Euler method can be derived in a number of ways.
(1) Firstly, there is the geometrical description above.
(2) Another possibility is to consider the Taylor expansion of the function
y
{\displaystyle y}
around
t
0
{\displaystyle t_{0}}
:
y
(
t
0
+
h
)
=
y
(
t
0
)
+
h
y
′
(
t
0
)
+
1
2
h
2
y
″
(
t
0
)
+
O
(
h
3
)
.
{\displaystyle y(t_{0}+h)=y(t_{0})+hy'(t_{0})+{\tfrac {1}{2}}h^{2}y''(t_{0})+O\left(h^{3}\right).}
The differential equation states that
y
′
=
f
(
t
,
y
)
{\displaystyle y'=f(t,y)}
. If this is substituted in the Taylor expansion and the quadratic and higher-order terms are ignored, the Euler method arises.
The Taylor expansion is used below to analyze the error committed by the Euler method, and it can be extended to produce Runge–Kutta methods.
(3) A closely related derivation is to substitute the forward finite difference formula for the derivative,
y
′
(
t
0
)
≈
y
(
t
0
+
h
)
−
y
(
t
0
)
h
{\displaystyle y'(t_{0})\approx {\frac {y(t_{0}+h)-y(t_{0})}{h}}}
in the differential equation
y
′
=
f
(
t
,
y
)
{\displaystyle y'=f(t,y)}
. Again, this yields the Euler method.
A similar computation leads to the midpoint method and the backward Euler method.
(4) Finally, one can integrate the differential equation from
t
0
{\displaystyle t_{0}}
to
t
0
+
h
{\displaystyle t_{0}+h}
and apply the fundamental theorem of calculus to get:
y
(
t
0
+
h
)
−
y
(
t
0
)
=
∫
t
0
t
0
+
h
f
(
t
,
y
(
t
)
)
d
t
.
{\displaystyle y(t_{0}+h)-y(t_{0})=\int _{t_{0}}^{t_{0}+h}f{\bigl (}t,y(t){\bigr )}\,\mathrm {d} t.}
Now approximate the integral by the left-hand rectangle method (with only one rectangle):
∫
t
0
t
0
+
h
f
(
t
,
y
(
t
)
)
d
t
≈
h
f
(
t
0
,
y
(
t
0
)
)
.
{\displaystyle \int _{t_{0}}^{t_{0}+h}f{\bigl (}t,y(t){\bigr )}\,\mathrm {d} t\approx hf{\bigl (}t_{0},y(t_{0}){\bigr )}.}
Combining both equations, one finds again the Euler method.
This line of thought can be continued to arrive at various linear multistep methods.
== Local truncation error ==
The local truncation error of the Euler method is the error made in a single step. It is the difference between the numerical solution after one step,
y
1
{\displaystyle y_{1}}
, and the exact solution at time
t
1
=
t
0
+
h
{\displaystyle t_{1}=t_{0}+h}
. The numerical solution is given by
y
1
=
y
0
+
h
f
(
t
0
,
y
0
)
.
{\displaystyle y_{1}=y_{0}+hf(t_{0},y_{0}).}
For the exact solution, we use the Taylor expansion mentioned in the section Derivation above:
y
(
t
0
+
h
)
=
y
(
t
0
)
+
h
y
′
(
t
0
)
+
1
2
h
2
y
″
(
t
0
)
+
O
(
h
3
)
.
{\displaystyle y(t_{0}+h)=y(t_{0})+hy'(t_{0})+{\tfrac {1}{2}}h^{2}y''(t_{0})+O\left(h^{3}\right).}
The local truncation error (LTE) introduced by the Euler method is given by the difference between these equations:
L
T
E
=
y
(
t
0
+
h
)
−
y
1
=
1
2
h
2
y
″
(
t
0
)
+
O
(
h
3
)
.
{\displaystyle \mathrm {LTE} =y(t_{0}+h)-y_{1}={\tfrac {1}{2}}h^{2}y''(t_{0})+O\left(h^{3}\right).}
This result is valid if
y
{\displaystyle y}
has a bounded third derivative.
This shows that for small
h
{\displaystyle h}
, the local truncation error is approximately proportional to
h
2
{\displaystyle h^{2}}
. This makes the Euler method less accurate than higher-order techniques such as Runge–Kutta methods and linear multistep methods, for which the local truncation error is proportional to a higher power of the step size.
A slightly different formulation for the local truncation error can be obtained by using the Lagrange form for the remainder term in Taylor's theorem. If
y
{\displaystyle y}
has a continuous second derivative, then there exists a
ξ
∈
[
t
0
,
t
0
+
h
]
{\displaystyle \xi \in [t_{0},t_{0}+h]}
such that
L
T
E
=
y
(
t
0
+
h
)
−
y
1
=
1
2
h
2
y
″
(
ξ
)
.
{\displaystyle \mathrm {LTE} =y(t_{0}+h)-y_{1}={\tfrac {1}{2}}h^{2}y''(\xi ).}
In the above expressions for the error, the second derivative of the unknown exact solution
y
{\displaystyle y}
can be replaced by an expression involving the right-hand side of the differential equation. Indeed, it follows from the equation
y
′
=
f
(
t
,
y
)
{\displaystyle y'=f(t,y)}
that
y
″
(
t
0
)
=
∂
f
∂
t
(
t
0
,
y
(
t
0
)
)
+
∂
f
∂
y
(
t
0
,
y
(
t
0
)
)
f
(
t
0
,
y
(
t
0
)
)
.
{\displaystyle y''(t_{0})={\frac {\partial f}{\partial t}}{\bigl (}t_{0},y(t_{0}){\bigr )}+{\frac {\partial f}{\partial y}}{\bigl (}t_{0},y(t_{0}){\bigr )}\,f{\bigl (}t_{0},y(t_{0}){\bigr )}.}
== Global truncation error ==
The global truncation error is the error at a fixed time
t
i
{\displaystyle t_{i}}
, after however many steps the method needs to take to reach that time from the initial time. The global truncation error is the cumulative effect of the local truncation errors committed in each step. The number of steps is easily determined to be
t
i
−
t
0
h
{\textstyle {\frac {t_{i}-t_{0}}{h}}}
, which is proportional to
1
h
{\textstyle {\frac {1}{h}}}
, and the error committed in each step is proportional to
h
2
{\displaystyle h^{2}}
(see the previous section). Thus, it is to be expected that the global truncation error will be proportional to
h
{\displaystyle h}
.
This intuitive reasoning can be made precise. If the solution
y
{\displaystyle y}
has a bounded second derivative and
f
{\displaystyle f}
is Lipschitz continuous in its second argument, then the global truncation error (denoted as
|
y
(
t
i
)
−
y
i
|
{\displaystyle |y(t_{i})-y_{i}|}
) is bounded by
|
y
(
t
i
)
−
y
i
|
≤
h
M
2
L
(
e
L
(
t
i
−
t
0
)
−
1
)
{\displaystyle |y(t_{i})-y_{i}|\leq {\frac {hM}{2L}}\left(e^{L(t_{i}-t_{0})}-1\right)}
where
M
{\displaystyle M}
is an upper bound on the second derivative of
y
{\displaystyle y}
on the given interval and
L
{\displaystyle L}
is the Lipschitz constant of
f
{\displaystyle f}
. Or more simply, when
y
′
(
t
)
=
f
(
t
,
y
)
{\displaystyle y'(t)=f(t,y)}
, the value
L
=
max
(
|
d
d
y
[
f
(
t
,
y
)
]
|
)
{\textstyle L={\text{max}}{\bigl (}|{\frac {d}{dy}}{\bigl [}f(t,y){\bigr ]}|{\bigr )}}
(such that
t
{\displaystyle t}
is treated as a constant). In contrast,
M
=
max
(
|
d
2
d
t
2
[
y
(
t
)
]
|
)
{\textstyle M={\text{max}}{\bigl (}|{\frac {d^{2}}{dt^{2}}}{\bigl [}y(t){\bigr ]}|{\bigr )}}
where function
y
(
t
)
{\displaystyle y(t)}
is the exact solution which only contains the
t
{\displaystyle t}
variable.
The precise form of this bound is of little practical importance, as in most cases the bound vastly overestimates the actual error committed by the Euler method. What is important is that it shows that the global truncation error is (approximately) proportional to
h
{\displaystyle h}
. For this reason, the Euler method is said to be first order.
=== Example ===
If we have the differential equation
y
′
=
1
+
(
t
−
y
)
2
{\displaystyle y'=1+(t-y)^{2}}
, and the exact solution
y
=
t
+
1
t
−
1
{\displaystyle y=t+{\frac {1}{t-1}}}
, and we want to find
M
{\displaystyle M}
and
L
{\displaystyle L}
for when
2
≤
t
≤
3
{\displaystyle 2\leq t\leq 3}
.
L
=
max
(
|
d
d
y
[
f
(
t
,
y
)
]
|
)
=
max
2
≤
t
≤
3
(
|
d
d
y
[
1
+
(
t
−
y
)
2
]
|
)
=
max
2
≤
t
≤
3
(
|
2
(
t
−
y
)
|
)
=
max
2
≤
t
≤
3
(
|
2
(
t
−
[
t
+
1
t
−
1
]
)
|
)
=
max
2
≤
t
≤
3
(
|
−
2
t
−
1
|
)
=
2
{\displaystyle L={\text{max}}{\bigl (}|{\frac {d}{dy}}{\bigl [}f(t,y){\bigr ]}|{\bigr )}=\max _{2\leq t\leq 3}{\bigl (}|{\frac {d}{dy}}{\bigl [}1+(t-y)^{2}{\bigr ]}|{\bigr )}=\max _{2\leq t\leq 3}{\bigl (}|2(t-y)|{\bigr )}=\max _{2\leq t\leq 3}{\bigl (}|2(t-[t+{\frac {1}{t-1}}])|{\bigr )}=\max _{2\leq t\leq 3}{\bigl (}|-{\frac {2}{t-1}}|{\bigr )}=2}
M
=
max
(
|
d
2
d
t
2
[
y
(
t
)
]
|
)
=
max
2
≤
t
≤
3
(
|
d
2
d
t
2
[
t
+
1
1
−
t
]
|
)
=
max
2
≤
t
≤
3
(
|
2
(
−
t
+
1
)
3
|
)
=
2
{\displaystyle M={\text{max}}{\bigl (}|{\frac {d^{2}}{dt^{2}}}{\bigl [}y(t){\bigr ]}|{\bigr )}=\max _{2\leq t\leq 3}\left(|{\frac {d^{2}}{dt^{2}}}{\bigl [}t+{\frac {1}{1-t}}{\bigr ]}|\right)=\max _{2\leq t\leq 3}\left(|{\frac {2}{(-t+1)^{3}}}|\right)=2}
Thus we can find the error bound at t=2.5 and h=0.5:
error bound
=
h
M
2
L
(
e
L
(
t
i
−
t
0
)
−
1
)
=
0.5
⋅
2
2
⋅
2
(
e
2
(
2.5
−
2
)
−
1
)
=
0.42957
{\displaystyle {\text{error bound}}={\frac {hM}{2L}}\left(e^{L(t_{i}-t_{0})}-1\right)={\frac {0.5\cdot 2}{2\cdot 2}}\left(e^{2(2.5-2)}-1\right)=0.42957}
Notice that t0 is equal to 2 because it is the lower bound for t in
2
≤
t
≤
3
{\displaystyle 2\leq t\leq 3}
.
== Numerical stability ==
The Euler method can also be numerically unstable, especially for stiff equations, meaning that the numerical solution grows very large for equations where the exact solution does not. This can be illustrated using the linear equation
y
′
=
−
2.3
y
,
y
(
0
)
=
1.
{\displaystyle y'=-2.3y,\qquad y(0)=1.}
The exact solution is
y
(
t
)
=
e
−
2.3
t
{\displaystyle y(t)=e^{-2.3t}}
, which decays to zero as
t
→
∞
{\displaystyle t\to \infty }
. However, if the Euler method is applied to this equation with step size
h
=
1
{\displaystyle h=1}
, then the numerical solution is qualitatively wrong: It oscillates and grows (see the figure). This is what it means to be unstable. If a smaller step size is used, for instance
h
=
0.7
{\displaystyle h=0.7}
, then the numerical solution does decay to zero.
If the Euler method is applied to the linear equation
y
′
=
k
y
{\displaystyle y'=ky}
, then the numerical solution is unstable if the product
h
k
{\displaystyle hk}
is outside the region
{
z
∈
C
|
|
z
+
1
|
≤
1
}
,
{\displaystyle {\bigl \{}z\in \mathbf {C} \,{\big |}\,|z+1|\leq 1{\bigr \}},}
illustrated on the right. This region is called the (linear) stability region. In the example,
k
=
−
2.3
{\displaystyle k=-2.3}
, so if
h
=
1
{\displaystyle h=1}
then
h
k
=
−
2.3
{\displaystyle hk=-2.3}
which is outside the stability region, and thus the numerical solution is unstable.
This limitation — along with its slow convergence of error with
h
{\displaystyle h}
— means that the Euler method is not often used, except as a simple example of numerical integration. Frequently models of physical systems contain terms representing fast-decaying elements (i.e. with large negative exponential arguments). Even when these are not of interest in the overall solution, the instability they can induce means that an exceptionally small timestep would be required if the Euler method is used.
== Rounding errors ==
In step
n
{\displaystyle n}
of the Euler method, the rounding error is roughly of the magnitude
ε
y
n
{\displaystyle \varepsilon y_{n}}
where
ε
{\displaystyle \varepsilon }
is the machine epsilon. Assuming that the rounding errors are independent random variables, the expected total rounding error is proportional to
ε
h
{\textstyle {\frac {\varepsilon }{\sqrt {h}}}}
. Thus, for extremely small values of the step size the truncation error will be small but the effect of rounding error may be big. Most of the effect of rounding error can be easily avoided if compensated summation is used in the formula for the Euler method.
== Modifications and extensions ==
A simple modification of the Euler method which eliminates the stability problems noted above is the backward Euler method:
y
n
+
1
=
y
n
+
h
f
(
t
n
+
1
,
y
n
+
1
)
.
{\displaystyle y_{n+1}=y_{n}+hf(t_{n+1},y_{n+1}).}
This differs from the (standard, or forward) Euler method in that the function
f
{\displaystyle f}
is evaluated at the end point of the step, instead of the starting point. The backward Euler method is an implicit method, meaning that the formula for the backward Euler method has
y
n
+
1
{\displaystyle y_{n+1}}
on both sides, so when applying the backward Euler method we have to solve an equation. This makes the implementation more costly.
Other modifications of the Euler method that help with stability yield the exponential Euler method or the semi-implicit Euler method.
More complicated methods can achieve a higher order (and more accuracy). One possibility is to use more function evaluations. This is illustrated by the midpoint method which is already mentioned in this article:
y
n
+
1
=
y
n
+
h
f
(
t
n
+
1
2
h
,
y
n
+
1
2
h
f
(
t
n
,
y
n
)
)
{\displaystyle y_{n+1}=y_{n}+hf\left(t_{n}+{\tfrac {1}{2}}h,y_{n}+{\tfrac {1}{2}}hf(t_{n},y_{n})\right)}
.
This leads to the family of Runge–Kutta methods.
The other possibility is to use more past values, as illustrated by the two-step Adams–Bashforth method:
y
n
+
1
=
y
n
+
3
2
h
f
(
t
n
,
y
n
)
−
1
2
h
f
(
t
n
−
1
,
y
n
−
1
)
.
{\displaystyle y_{n+1}=y_{n}+{\tfrac {3}{2}}hf(t_{n},y_{n})-{\tfrac {1}{2}}hf(t_{n-1},y_{n-1}).}
This leads to the family of linear multistep methods. There are other modifications which uses techniques from compressive sensing to minimize memory usage
== In popular culture ==
In the film Hidden Figures, Katherine Johnson resorts to the Euler method in calculating the re-entry of astronaut John Glenn from Earth orbit.
== See also ==
Crank–Nicolson method
Gradient descent similarly uses finite steps, here to find minima of functions
List of Runge–Kutta methods
Linear multistep method
Numerical integration (for calculating definite integrals)
Numerical methods for ordinary differential equations
== Notes ==
== References ==
Atkinson, Kendall A. (1989). An Introduction to Numerical Analysis (2nd ed.). New York: John Wiley & Sons. ISBN 978-0-471-50023-0.
Ascher, Uri M.; Petzold, Linda R. (1998). Computer Methods for Ordinary Differential Equations and Differential-Algebraic Equations. Philadelphia: Society for Industrial and Applied Mathematics. ISBN 978-0-89871-412-8.
Butcher, John C. (2003). Numerical Methods for Ordinary Differential Equations. New York: John Wiley & Sons. ISBN 978-0-471-96758-3.
Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993). Solving ordinary differential equations I: Nonstiff problems. Berlin, New York: Springer-Verlag. ISBN 978-3-540-56670-0.
Iserles, Arieh (1996). A First Course in the Numerical Analysis of Differential Equations. Cambridge University Press. ISBN 978-0-521-55655-2.
Stoer, Josef; Bulirsch, Roland (2002). Introduction to Numerical Analysis (3rd ed.). Berlin, New York: Springer-Verlag. ISBN 978-0-387-95452-3.
Lakoba, Taras I. (2012), Simple Euler method and its modifications (PDF) (Lecture notes for MATH334), University of Vermont, retrieved 29 February 2012
Unni, M P. (2017). "Memory reduction for numerical solution of differential equations using compressive sensing". 2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA). IEEE CSPA. pp. 79–84. doi:10.1109/CSPA.2017.8064928. ISBN 978-1-5090-1184-1. S2CID 13082456.
== External links ==
Media related to Euler method at Wikimedia Commons
Euler method implementations in different languages by Rosetta Code
"Euler method", Encyclopedia of Mathematics, EMS Press, 2001 [1994] | Wikipedia/Euler's_method |
In numerical analysis, finite-difference methods (FDM) are a class of numerical techniques for solving differential equations by approximating derivatives with finite differences. Both the spatial domain and time domain (if applicable) are discretized, or broken into a finite number of intervals, and the values of the solution at the end points of the intervals are approximated by solving algebraic equations containing finite differences and values from nearby points.
Finite difference methods convert ordinary differential equations (ODE) or partial differential equations (PDE), which may be nonlinear, into a system of linear equations that can be solved by matrix algebra techniques. Modern computers can perform these linear algebra computations efficiently, and this, along with their relative ease of implementation, has led to the widespread use of FDM in modern numerical analysis.
Today, FDMs are one of the most common approaches to the numerical solution of PDE, along with finite element methods.
== Derive difference quotient from Taylor's polynomial ==
For a n-times differentiable function, by Taylor's theorem the Taylor series expansion is given as
f
(
x
0
+
h
)
=
f
(
x
0
)
+
f
′
(
x
0
)
1
!
h
+
f
(
2
)
(
x
0
)
2
!
h
2
+
⋯
+
f
(
n
)
(
x
0
)
n
!
h
n
+
R
n
(
x
)
,
{\displaystyle f(x_{0}+h)=f(x_{0})+{\frac {f'(x_{0})}{1!}}h+{\frac {f^{(2)}(x_{0})}{2!}}h^{2}+\cdots +{\frac {f^{(n)}(x_{0})}{n!}}h^{n}+R_{n}(x),}
Where n! denotes the factorial of n, and Rn(x) is a remainder term, denoting the difference between the Taylor polynomial of degree n and the original function.
Following is the process to derive an approximation for the first derivative of the function f by first truncating the Taylor polynomial plus remainder:
f
(
x
0
+
h
)
=
f
(
x
0
)
+
f
′
(
x
0
)
h
+
R
1
(
x
)
.
{\displaystyle f(x_{0}+h)=f(x_{0})+f'(x_{0})h+R_{1}(x).}
Dividing across by h gives:
f
(
x
0
+
h
)
h
=
f
(
x
0
)
h
+
f
′
(
x
0
)
+
R
1
(
x
)
h
{\displaystyle {f(x_{0}+h) \over h}={f(x_{0}) \over h}+f'(x_{0})+{R_{1}(x) \over h}}
Solving for
f
′
(
x
0
)
{\displaystyle f'(x_{0})}
:
f
′
(
x
0
)
=
f
(
x
0
+
h
)
−
f
(
x
0
)
h
−
R
1
(
x
)
h
.
{\displaystyle f'(x_{0})={f(x_{0}+h)-f(x_{0}) \over h}-{R_{1}(x) \over h}.}
Assuming that
R
1
(
x
)
{\displaystyle R_{1}(x)}
is sufficiently small, the approximation of the first derivative of f is:
f
′
(
x
0
)
≈
f
(
x
0
+
h
)
−
f
(
x
0
)
h
.
{\displaystyle f'(x_{0})\approx {f(x_{0}+h)-f(x_{0}) \over h}.}
This is similar to the definition of derivative, which is:
f
′
(
x
0
)
=
lim
h
→
0
f
(
x
0
+
h
)
−
f
(
x
0
)
h
.
{\displaystyle f'(x_{0})=\lim _{h\to 0}{\frac {f(x_{0}+h)-f(x_{0})}{h}}.}
except for the limit towards zero (the method is named after this).
== Accuracy and order ==
The error in a method's solution is defined as the difference between the approximation and the exact analytical solution. The two sources of error in finite difference methods are round-off error, the loss of precision due to computer rounding of decimal quantities, and truncation error or discretization error, the difference between the exact solution of the original differential equation and the exact quantity assuming perfect arithmetic (no round-off).
To use a finite difference method to approximate the solution to a problem, one must first discretize the problem's domain. This is usually done by dividing the domain into a uniform grid (see image). This means that finite-difference methods produce sets of discrete numerical approximations to the derivative, often in a "time-stepping" manner.
An expression of general interest is the local truncation error of a method. Typically expressed using Big-O notation, local truncation error refers to the error from a single application of a method. That is, it is the quantity
f
′
(
x
i
)
−
f
i
′
{\displaystyle f'(x_{i})-f'_{i}}
if
f
′
(
x
i
)
{\displaystyle f'(x_{i})}
refers to the exact value and
f
i
′
{\displaystyle f'_{i}}
to the numerical approximation. The remainder term of the Taylor polynomial can be used to analyze local truncation error. Using the Lagrange form of the remainder from the Taylor polynomial for
f
(
x
0
+
h
)
{\displaystyle f(x_{0}+h)}
, which is
R
n
(
x
0
+
h
)
=
f
(
n
+
1
)
(
ξ
)
(
n
+
1
)
!
(
h
)
n
+
1
,
x
0
<
ξ
<
x
0
+
h
,
{\displaystyle R_{n}(x_{0}+h)={\frac {f^{(n+1)}(\xi )}{(n+1)!}}(h)^{n+1}\,,\quad x_{0}<\xi <x_{0}+h,}
the dominant term of the local truncation error can be discovered. For example, again using the forward-difference formula for the first derivative, knowing that
f
(
x
i
)
=
f
(
x
0
+
i
h
)
{\displaystyle f(x_{i})=f(x_{0}+ih)}
,
f
(
x
0
+
i
h
)
=
f
(
x
0
)
+
f
′
(
x
0
)
i
h
+
f
″
(
ξ
)
2
!
(
i
h
)
2
,
{\displaystyle f(x_{0}+ih)=f(x_{0})+f'(x_{0})ih+{\frac {f''(\xi )}{2!}}(ih)^{2},}
and with some algebraic manipulation, this leads to
f
(
x
0
+
i
h
)
−
f
(
x
0
)
i
h
=
f
′
(
x
0
)
+
f
″
(
ξ
)
2
!
i
h
,
{\displaystyle {\frac {f(x_{0}+ih)-f(x_{0})}{ih}}=f'(x_{0})+{\frac {f''(\xi )}{2!}}ih,}
and further noting that the quantity on the left is the approximation from the finite difference method and that the quantity on the right is the exact quantity of interest plus a remainder, clearly that remainder is the local truncation error. A final expression of this example and its order is:
f
(
x
0
+
i
h
)
−
f
(
x
0
)
i
h
=
f
′
(
x
0
)
+
O
(
h
)
.
{\displaystyle {\frac {f(x_{0}+ih)-f(x_{0})}{ih}}=f'(x_{0})+O(h).}
In this case, the local truncation error is proportional to the step sizes. The quality and duration of simulated FDM solution depends on the discretization equation selection and the step sizes (time and space steps). The data quality and simulation duration increase significantly with smaller step size. Therefore, a reasonable balance between data quality and simulation duration is necessary for practical usage. Large time steps are useful for increasing simulation speed in practice. However, time steps which are too large may create instabilities and affect the data quality.
The von Neumann and Courant-Friedrichs-Lewy criteria are often evaluated to determine the numerical model stability.
== Example: ordinary differential equation ==
For example, consider the ordinary differential equation
u
′
(
x
)
=
3
u
(
x
)
+
2.
{\displaystyle u'(x)=3u(x)+2.}
The Euler method for solving this equation uses the finite difference quotient
u
(
x
+
h
)
−
u
(
x
)
h
≈
u
′
(
x
)
{\displaystyle {\frac {u(x+h)-u(x)}{h}}\approx u'(x)}
to approximate the differential equation by first substituting it for u'(x) then applying a little algebra (multiplying both sides by h, and then adding u(x) to both sides) to get
u
(
x
+
h
)
≈
u
(
x
)
+
h
(
3
u
(
x
)
+
2
)
.
{\displaystyle u(x+h)\approx u(x)+h(3u(x)+2).}
The last equation is a finite-difference equation, and solving this equation gives an approximate solution to the differential equation.
== Example: The heat equation ==
Consider the normalized heat equation in one dimension, with homogeneous Dirichlet boundary conditions
{
U
t
=
U
x
x
U
(
0
,
t
)
=
U
(
1
,
t
)
=
0
(boundary condition)
U
(
x
,
0
)
=
U
0
(
x
)
(initial condition)
{\displaystyle {\begin{cases}U_{t}=U_{xx}\\U(0,t)=U(1,t)=0&{\text{(boundary condition)}}\\U(x,0)=U_{0}(x)&{\text{(initial condition)}}\end{cases}}}
One way to numerically solve this equation is to approximate all the derivatives by finite differences. First partition the domain in space using a mesh
x
0
,
…
,
x
J
{\displaystyle x_{0},\dots ,x_{J}}
and in time using a mesh
t
0
,
…
,
t
N
{\displaystyle t_{0},\dots ,t_{N}}
. Assume a uniform partition both in space and in time, so the difference between two consecutive space points will be h and between two consecutive time points will be k. The points
u
(
x
j
,
t
n
)
=
u
j
n
{\displaystyle u(x_{j},t_{n})=u_{j}^{n}}
will represent the numerical approximation of
u
(
x
j
,
t
n
)
.
{\displaystyle u(x_{j},t_{n}).}
=== Explicit method ===
Using a forward difference at time
t
n
{\displaystyle t_{n}}
and a second-order central difference for the space derivative at position
x
j
{\displaystyle x_{j}}
(FTCS) gives the recurrence equation:
u
j
n
+
1
−
u
j
n
k
=
u
j
+
1
n
−
2
u
j
n
+
u
j
−
1
n
h
2
.
{\displaystyle {\frac {u_{j}^{n+1}-u_{j}^{n}}{k}}={\frac {u_{j+1}^{n}-2u_{j}^{n}+u_{j-1}^{n}}{h^{2}}}.}
This is an explicit method for solving the one-dimensional heat equation.
One can obtain
u
j
n
+
1
{\displaystyle u_{j}^{n+1}}
from the other values this way:
u
j
n
+
1
=
(
1
−
2
r
)
u
j
n
+
r
u
j
−
1
n
+
r
u
j
+
1
n
{\displaystyle u_{j}^{n+1}=(1-2r)u_{j}^{n}+ru_{j-1}^{n}+ru_{j+1}^{n}}
where
r
=
k
/
h
2
.
{\displaystyle r=k/h^{2}.}
So, with this recurrence relation, and knowing the values at time n, one can obtain the corresponding values at time n+1.
u
0
n
{\displaystyle u_{0}^{n}}
and
u
J
n
{\displaystyle u_{J}^{n}}
must be replaced by the boundary conditions, in this example they are both 0.
This explicit method is known to be numerically stable and convergent whenever
r
≤
1
/
2
{\displaystyle r\leq 1/2}
. The numerical errors are proportional to the time step and the square of the space step:
Δ
u
=
O
(
k
)
+
O
(
h
2
)
{\displaystyle \Delta u=O(k)+O(h^{2})}
=== Implicit method ===
Using the backward difference at time
t
n
+
1
{\displaystyle t_{n+1}}
and a second-order central difference for the space derivative at position
x
j
{\displaystyle x_{j}}
(The Backward Time, Centered Space Method "BTCS") gives the recurrence equation:
u
j
n
+
1
−
u
j
n
k
=
u
j
+
1
n
+
1
−
2
u
j
n
+
1
+
u
j
−
1
n
+
1
h
2
.
{\displaystyle {\frac {u_{j}^{n+1}-u_{j}^{n}}{k}}={\frac {u_{j+1}^{n+1}-2u_{j}^{n+1}+u_{j-1}^{n+1}}{h^{2}}}.}
This is an implicit method for solving the one-dimensional heat equation.
One can obtain
u
j
n
+
1
{\displaystyle u_{j}^{n+1}}
from solving a system of linear equations:
(
1
+
2
r
)
u
j
n
+
1
−
r
u
j
−
1
n
+
1
−
r
u
j
+
1
n
+
1
=
u
j
n
{\displaystyle (1+2r)u_{j}^{n+1}-ru_{j-1}^{n+1}-ru_{j+1}^{n+1}=u_{j}^{n}}
The scheme is always numerically stable and convergent but usually more numerically intensive than the explicit method as it requires solving a system of numerical equations on each time step. The errors are linear over the time step and quadratic over the space step:
Δ
u
=
O
(
k
)
+
O
(
h
2
)
.
{\displaystyle \Delta u=O(k)+O(h^{2}).}
=== Crank–Nicolson method ===
Finally, using the central difference at time
t
n
+
1
/
2
{\displaystyle t_{n+1/2}}
and a second-order central difference for the space derivative at position
x
j
{\displaystyle x_{j}}
("CTCS") gives the recurrence equation:
u
j
n
+
1
−
u
j
n
k
=
1
2
(
u
j
+
1
n
+
1
−
2
u
j
n
+
1
+
u
j
−
1
n
+
1
h
2
+
u
j
+
1
n
−
2
u
j
n
+
u
j
−
1
n
h
2
)
.
{\displaystyle {\frac {u_{j}^{n+1}-u_{j}^{n}}{k}}={\frac {1}{2}}\left({\frac {u_{j+1}^{n+1}-2u_{j}^{n+1}+u_{j-1}^{n+1}}{h^{2}}}+{\frac {u_{j+1}^{n}-2u_{j}^{n}+u_{j-1}^{n}}{h^{2}}}\right).}
This formula is known as the Crank–Nicolson method.
One can obtain
u
j
n
+
1
{\displaystyle u_{j}^{n+1}}
from solving a system of linear equations:
(
2
+
2
r
)
u
j
n
+
1
−
r
u
j
−
1
n
+
1
−
r
u
j
+
1
n
+
1
=
(
2
−
2
r
)
u
j
n
+
r
u
j
−
1
n
+
r
u
j
+
1
n
{\displaystyle (2+2r)u_{j}^{n+1}-ru_{j-1}^{n+1}-ru_{j+1}^{n+1}=(2-2r)u_{j}^{n}+ru_{j-1}^{n}+ru_{j+1}^{n}}
The scheme is always numerically stable and convergent but usually more numerically intensive as it requires solving a system of numerical equations on each time step. The errors are quadratic over both the time step and the space step:
Δ
u
=
O
(
k
2
)
+
O
(
h
2
)
.
{\displaystyle \Delta u=O(k^{2})+O(h^{2}).}
=== Comparison ===
To summarize, usually the Crank–Nicolson scheme is the most accurate scheme for small time steps. For larger time steps, the implicit scheme works better since it is less computationally demanding. The explicit scheme is the least accurate and can be unstable, but is also the easiest to implement and the least numerically intensive.
Here is an example. The figures below present the solutions given by the above methods to approximate the heat equation
U
t
=
α
U
x
x
,
α
=
1
π
2
,
{\displaystyle U_{t}=\alpha U_{xx},\quad \alpha ={\frac {1}{\pi ^{2}}},}
with the boundary condition
U
(
0
,
t
)
=
U
(
1
,
t
)
=
0.
{\displaystyle U(0,t)=U(1,t)=0.}
The exact solution is
U
(
x
,
t
)
=
1
π
2
e
−
t
sin
(
π
x
)
.
{\displaystyle U(x,t)={\frac {1}{\pi ^{2}}}e^{-t}\sin(\pi x).}
== Example: The Laplace operator ==
The (continuous) Laplace operator in
n
{\displaystyle n}
-dimensions is given by
Δ
u
(
x
)
=
∑
i
=
1
n
∂
i
2
u
(
x
)
{\displaystyle \Delta u(x)=\sum _{i=1}^{n}\partial _{i}^{2}u(x)}
.
The discrete Laplace operator
Δ
h
u
{\displaystyle \Delta _{h}u}
depends on the dimension
n
{\displaystyle n}
.
In 1D the Laplace operator is approximated as
Δ
u
(
x
)
=
u
″
(
x
)
≈
u
(
x
−
h
)
−
2
u
(
x
)
+
u
(
x
+
h
)
h
2
=:
Δ
h
u
(
x
)
.
{\displaystyle \Delta u(x)=u''(x)\approx {\frac {u(x-h)-2u(x)+u(x+h)}{h^{2}}}=:\Delta _{h}u(x)\,.}
This approximation is usually expressed via the following stencil
Δ
h
=
1
h
2
[
1
−
2
1
]
{\displaystyle \Delta _{h}={\frac {1}{h^{2}}}{\begin{bmatrix}1&-2&1\end{bmatrix}}}
and which represents a symmetric, tridiagonal matrix.
For an equidistant grid one gets a Toeplitz matrix.
The 2D case shows all the characteristics of the more general n-dimensional case. Each second partial derivative needs to be approximated similar to the 1D case
Δ
u
(
x
,
y
)
=
u
x
x
(
x
,
y
)
+
u
y
y
(
x
,
y
)
≈
u
(
x
−
h
,
y
)
−
2
u
(
x
,
y
)
+
u
(
x
+
h
,
y
)
h
2
+
u
(
x
,
y
−
h
)
−
2
u
(
x
,
y
)
+
u
(
x
,
y
+
h
)
h
2
=
u
(
x
−
h
,
y
)
+
u
(
x
+
h
,
y
)
−
4
u
(
x
,
y
)
+
u
(
x
,
y
−
h
)
+
u
(
x
,
y
+
h
)
h
2
=:
Δ
h
u
(
x
,
y
)
,
{\displaystyle {\begin{aligned}\Delta u(x,y)&=u_{xx}(x,y)+u_{yy}(x,y)\\&\approx {\frac {u(x-h,y)-2u(x,y)+u(x+h,y)}{h^{2}}}+{\frac {u(x,y-h)-2u(x,y)+u(x,y+h)}{h^{2}}}\\&={\frac {u(x-h,y)+u(x+h,y)-4u(x,y)+u(x,y-h)+u(x,y+h)}{h^{2}}}\\&=:\Delta _{h}u(x,y)\,,\end{aligned}}}
which is usually given by the following stencil
Δ
h
=
1
h
2
[
1
1
−
4
1
1
]
.
{\displaystyle \Delta _{h}={\frac {1}{h^{2}}}{\begin{bmatrix}&1\\1&-4&1\\&1\end{bmatrix}}\,.}
=== Consistency ===
Consistency of the above-mentioned approximation can be shown for highly regular functions, such as
u
∈
C
4
(
Ω
)
{\displaystyle u\in C^{4}(\Omega )}
.
The statement is
Δ
u
−
Δ
h
u
=
O
(
h
2
)
.
{\displaystyle \Delta u-\Delta _{h}u={\mathcal {O}}(h^{2})\,.}
To prove this, one needs to substitute Taylor Series expansions up to order 3 into the discrete Laplace operator.
=== Properties ===
==== Subharmonic ====
Similar to continuous subharmonic functions one can define subharmonic functions for finite-difference approximations
u
h
{\displaystyle u_{h}}
−
Δ
h
u
h
≤
0
.
{\displaystyle -\Delta _{h}u_{h}\leq 0\,.}
==== Mean value ====
One can define a general stencil of positive type via
[
α
N
α
W
−
α
C
α
E
α
S
]
,
α
i
>
0
,
α
C
=
∑
i
∈
{
N
,
E
,
S
,
W
}
α
i
.
{\displaystyle {\begin{bmatrix}&\alpha _{N}\\\alpha _{W}&-\alpha _{C}&\alpha _{E}\\&\alpha _{S}\end{bmatrix}}\,,\quad \alpha _{i}>0\,,\quad \alpha _{C}=\sum _{i\in \{N,E,S,W\}}\alpha _{i}\,.}
If
u
h
{\displaystyle u_{h}}
is (discrete) subharmonic then the following mean value property holds
u
h
(
x
C
)
≤
∑
i
∈
{
N
,
E
,
S
,
W
}
α
i
u
h
(
x
i
)
∑
i
∈
{
N
,
E
,
S
,
W
}
α
i
,
{\displaystyle u_{h}(x_{C})\leq {\frac {\sum _{i\in \{N,E,S,W\}}\alpha _{i}u_{h}(x_{i})}{\sum _{i\in \{N,E,S,W\}}\alpha _{i}}}\,,}
where the approximation is evaluated on points of the grid, and the stencil is assumed to be of positive type.
A similar mean value property also holds for the continuous case.
==== Maximum principle ====
For a (discrete) subharmonic function
u
h
{\displaystyle u_{h}}
the following holds
max
Ω
h
u
h
≤
max
∂
Ω
h
u
h
,
{\displaystyle \max _{\Omega _{h}}u_{h}\leq \max _{\partial \Omega _{h}}u_{h}\,,}
where
Ω
h
,
∂
Ω
h
{\displaystyle \Omega _{h},\partial \Omega _{h}}
are discretizations of the continuous domain
Ω
{\displaystyle \Omega }
, respectively the boundary
∂
Ω
{\displaystyle \partial \Omega }
.
A similar maximum principle also holds for the continuous case.
== The SBP-SAT method ==
The SBP-SAT (summation by parts - simultaneous approximation term) method is a stable and accurate technique for discretizing and imposing boundary conditions of a well-posed partial differential equation using high order finite differences.
The method is based on finite differences where the differentiation operators exhibit summation-by-parts properties. Typically, these operators consist of differentiation matrices with central difference stencils in the interior with carefully chosen one-sided boundary stencils designed to mimic integration-by-parts in the discrete setting. Using the SAT technique, the boundary conditions of the PDE are imposed weakly, where the boundary values are "pulled" towards the desired conditions rather than exactly fulfilled. If the tuning parameters (inherent to the SAT technique) are chosen properly, the resulting system of ODE's will exhibit similar energy behavior as the continuous PDE, i.e. the system has no non-physical energy growth. This guarantees stability if an integration scheme with a stability region that includes parts of the imaginary axis, such as the fourth order Runge-Kutta method, is used. This makes the SAT technique an attractive method of imposing boundary conditions for higher order finite difference methods, in contrast to for example the injection method, which typically will not be stable if high order differentiation operators are used.
== See also ==
== References ==
== Further reading ==
K.W. Morton and D.F. Mayers, Numerical Solution of Partial Differential Equations, An Introduction. Cambridge University Press, 2005.
Autar Kaw and E. Eric Kalu, Numerical Methods with Applications, (2008) [1]. Contains a brief, engineering-oriented introduction to FDM (for ODEs) in Chapter 08.07.
John Strikwerda (2004). Finite Difference Schemes and Partial Differential Equations (2nd ed.). SIAM. ISBN 978-0-89871-639-9.
Smith, G. D. (1985), Numerical Solution of Partial Differential Equations: Finite Difference Methods, 3rd ed., Oxford University Press
Peter Olver (2013). Introduction to Partial Differential Equations. Springer. Chapter 5: Finite differences. ISBN 978-3-319-02099-0..
Randall J. LeVeque, Finite Difference Methods for Ordinary and Partial Differential Equations, SIAM, 2007.
Sergey Lemeshevsky, Piotr Matus, Dmitriy Poliakov(Eds): "Exact Finite-Difference Schemes", De Gruyter (2016). DOI: https://doi.org/10.1515/9783110491326 .
Mikhail Shashkov: Conservative Finite-Difference Methods on General Grids, CRC Press, ISBN 0-8493-7375-1 (1996). | Wikipedia/Finite_difference_methods |
The Chinese Academy of Sciences (CAS; 中国科学院) is the national academy for natural sciences and the highest consultancy for science and technology of the People's Republic of China. It is the world's largest research organization, with 106 research institutes, 2 universities, 71,300 full-time employees, and 79 thousand graduate students.
The Chinese Academy of Sciences has historical origins in the Academia Sinica during the Republican era and was formerly also known by that name until the 1980s. The academy functions as the national scientific think tank and academic governing body, providing advisory and appraisal services on issues stemming from the national economy, social development, and science and technology progress. It is headquartered in Beijing, with affiliate institutes throughout China. It has also created hundreds of commercial enterprises, Lenovo being one of the most famous.
The academy also runs the University of Science and Technology of China and the University of the Chinese Academy of Sciences, both of which were among the world's top three academic institutions in the Nature Index rankings as of 2024.
== Membership ==
Membership of the Chinese Academy of Sciences, also known by the title Academician of the Chinese Academy of Sciences (中国科学院院士), is a lifelong honor given to Chinese scientists who have made significant achievements in various fields. According to the Bylaws for Members of the Chinese Academy of Sciences adopted in 1992 and recently amended in the year 2014, it is the highest academic title in China. A formal CAS member must hold Chinese citizenship, although foreign citizens may be elected as CAS foreign academicians. Members older than 80 are designated as "senior members" and may no longer hold leading positions in the organization. Academicians of the Chinese Academy of Sciences carry an obligation to advance science and technology, to advocate and uphold scientific spirit, to develop a scientific and technological workforce, to attend member meetings and receive consultation and evaluation tasks, and to promote international exchanges and cooperation. Academicians can give suggestions and influence Chinese state policy related to science and technology.
== History ==
In 1956, China formally began its computing program when it launched the Twelve-Year Science Plan and formed the Beijing Institute of Computing Technology under the CAS.: 100
In 1964, CAS debuted China's first self-developed large digital computer, the 119.: 101 The 119 was a core technology in facilitating China's first successful nuclear weapon test (Project 596), also in 1964.: 101
Beginning in 1972, CAS began promoting the idea of balancing applied research with more theoretical research and in having scientific exchanges with other developing countries.: 74
As vice premier, Deng Xiaoping in 1975 also sought to re-orient CAS towards more theoretical research, which had not been a focus during the Cultural Revolution.: 74 Deng emphasized that "the Academy of Sciences is an Academy of Sciences, not an Academy of Cabbage.": 74 Deng assigned CAS vice president Hu Yaobang to draft a plan for overhauling CAS.: 74 Deng and his aide Hu Qiaomu revised the draft and in September 1974 issued "The Outline Report on the Work of the Academy of Sciences".: 74 The Outline described scientific research in China as lagging behind the needs of socialist construction and the state of the advanced countries, and stated that to catch up, China should emphasize basic science in order to develop a sound theoretical foundation.: 74
This approach to scientific reform fell out of political favor in 1976 when Deng was purged, although it continued to be supported by many members within CAS.: 75 A month before Deng's political return in 1977 however, the Outline Report was revived and adopted as CAS's official policy.: 81
Shortly after his return, Deng hosted a series of meetings on science and education in which he stated that science should become the forerunner of China's modernization.: 82 Following these remarks, CAS prepared its goals for natural science disciplines to be achieved by 1985, stating that as a developing socialist country, China should strengthen basic scientific research through foreign exchanges.: 82
To further promote this agenda, Deng began a campaign to promote the National Science Conference.: 82 A team led by CAS vice president Fang Yi instructed schools, factories, and communes to organize youth-focused events celebrating science and technology.: 82
In 1977, the Department of Philosophy and Social Sciences was split off of CAS and reorganized into the Chinese Academy of Social Sciences and led by Hu Qiaomu.: 86–87
The Graduate School of the Chinese Academy of Sciences (CAS) was established in 2001 as a successor to the Graduate School of the University of Science and Technology of China (Beijing).The Ministry of Education (MOE) approved the Graduate School of the Chinese Academy of Sciences (CAS) application to change its name to the University of the Chinese Academy of Sciences (UCAS) on July 23, 2012. Additionally, the MOE recommended that CAS discontinue the operation of the CAS Graduate School. In 2023, the Pasteur Institute suspended ties with CAS.
== Organization ==
The Chinese Academy of Sciences maintains a large number of subordinate institutions nationwide.
=== Internal Organizations ===
According to the "Regulations on Functional Configuration, Internal Organizations and Staffing of the Chinese Academy of Sciences (CAS)", CAS has set up the following constitute departments at its headquarters:
Office of the Chinese Academy of Sciences
Bureau of Academic Departments
Bureau of Frontier Science and Basic Research
Bureau of Major Science and Technology Tasks
Bureau of Sustainable Development Research
Bureau of Science and Technology Basic Capabilities
Development Planning Bureau
Finance and Asset Management Bureau
Personnel Bureau
Party Committee of the Immediate Organs
Bureau of International Cooperation
Bureau of Supervision and Audit
Bureau of Retired Cadres Work
=== Directly Affiliated Institutions ===
==== Research Units Directly Affiliated to ====
===== Beijing units =====
Academy of Mathematics and Systems Science
Institute of Physics
Institute of Theoretical Physics
Institute of High Energy Physics, Chinese Academy of Sciences
Institute of Mechanics, Chinese Academy of Sciences
Institute of Acoustics, Chinese Academy of Sciences
Institute of Physical and Chemical Technology, Chinese Academy of Sciences
Institute of Chemistry, Chinese Academy of Sciences
National Center for Nanoscience
Ecological and Environmental Research Center
Institute of Process Engineering, Chinese Academy of Sciences
Institute of Geographic Sciences and Resources
National Astronomical Observatory
Yunnan Astronomical Observatory, Chinese Academy of Sciences
Xinjiang Astronomical Observatory
Changchun Artificial Satellite Observatory
Nanjing Institute of Astronomy and Optics Technology, Chinese Academy of Sciences
Institute of Geology and Geophysics, Chinese Academy of Sciences
Institute of Tibetan Plateau Studies, Chinese Academy of Sciences
Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences
Institute of Atmospheric Physics, Chinese Academy of Sciences
Institute of Botany, Chinese Academy of Sciences
Institute of Zoology, Chinese Academy of Sciences
Institute of Psychology
Institute of Microbiology, Chinese Academy of Sciences
Institute of Biophysics, Chinese Academy of Sciences
Institute of Genetics and Developmental Biology, Chinese Academy of Sciences
Agricultural Resources Research Center, Institute of Genetics and Developmental Biology
Beijing Institute of Genomics (National Center for Biological Information)
Institute of Computing Technology
Institute of Software Research
Institute of Semiconductors, Chinese Academy of Sciences
Institute of Microelectronics, Chinese Academy of Sciences
Institute of Space and Astronautical Information Innovation, Chinese Academy of Sciences
Institute of Automation
Institute of Electrical Engineering, Chinese Academy of Sciences
Institute of Engineering Thermophysics, Chinese Academy of Sciences
National Space Science Center
Institute of History of Natural Sciences, Chinese Academy of Sciences
Institute of Science and Technology Strategy Consulting, Chinese Academy of Sciences
Institute of Information Engineering, Chinese Academy of Sciences
Research and Education Center for Data and Communication Protection
Center for Space Application Engineering and Technology, Chinese Academy of Sciences
Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences
===== Shenyang Branch =====
Institute of Metals
Shenyang Institute of Applied Ecology, Chinese Academy of Sciences
Shenyang Institute of Automation, Chinese Academy of Sciences
Dalian Institute of Chemical Physics, Chinese Academy of Sciences
Institute of Oceanography, Chinese Academy of Sciences
Qingdao Institute of Bioenergy and Processes, Chinese Academy of Sciences
Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences
===== Changchun Branch =====
Changchun Institute of Optical Precision Machinery and Physics
Changchun Institute of Applied Chemistry
Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences
Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences
National Astronomical Observatory Changchun Artificial Satellite Observatory
===== Shanghai Branch =====
Shanghai Institute of Microsystems and Information Technology, Chinese Academy of Sciences
Shanghai Institute of Physics for Technology
Shanghai Institute of Optical Precision Machinery, Chinese Academy of Sciences
Shanghai Institute of Silicates, Chinese Academy of Sciences
Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences
Shanghai Institute of Applied Physics
Shanghai Astronomical Observatory
Center of Excellence for Molecular Cell Science, Chinese Academy of Sciences
Innovation Center of Excellence in Brain Science and Intelligent Technology
Innovation Center of Excellence in Molecular Plant Science
Shanghai Institute of Nutrition and Health
Shanghai Institute of Pharmaceutical Sciences
Shanghai Institute of Immunity and Infection
Shanghai Institutes for Advanced Studies
Chinese Academy of Sciences Institute of Microsatellite Innovation
Fujian Institute of Materials and Structures
Ningbo Institute of Materials Technology and Engineering
Institute of Urban Environment, Chinese Academy of Sciences
Hangzhou Institute of Medical Sciences
===== Nanjing Branch =====
Nanjing Institute of Geology and Paleontology
Nanjing Institute of Soil Research
Nanjing Institute of Geography and Lakes
Purple Mountain Observatory
Suzhou Institute of Nanotechnology and Nanobionics
Suzhou Institute of Biomedical Engineering and Technology
Ganjiang Innovation Research Institute, Chinese Academy of Sciences
===== Wuhan Branch =====
Wuhan Institute of Geotechnics, Chinese Academy of Sciences
Institute of Precision Measurement Science and Technological Innovation
Wuhan Institute of Virology
Institute of Aquatic Biology, Chinese Academy of Sciences
Wuhan Botanical Garden, Chinese Academy of Sciences
Institute of Water Engineering and Ecology, Chinese Academy of Sciences, Ministry of Water Resources
===== Guangzhou Branch =====
South China Sea Institute of Oceanography, Chinese Academy of Sciences
South China Botanical Garden (formerly South China Botanical Research Institute)
Guangzhou Energy Research Institute, Chinese Academy of Sciences
Guangzhou Institute of Geochemistry, Chinese Academy of Sciences
Guangzhou Institute of Geochemistry, Changsha Mineral Resources Exploration Center
Guangzhou Institute of Biomedicine and Health
Shenzhen Institute of Advanced Technology
Institute of Subtropical Agroecology, Chinese Academy of Sciences
Institute of Deep Sea Science and Engineering
===== Chengdu Branch =====
Chengdu Institute of Biology, Chinese Academy of Sciences
Chengdu Institute of Mountain Hazards and Environment
Institute of Photovoltaic Technology
Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences
===== Kunming Branch =====
Kunming Institute of Zoology
Kunming Institute of Botany
Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences
Institute of Geochemistry, Chinese Academy of Sciences
Yunnan Observatory
===== Xi'an Branch =====
Xi'an Institute of Optical Precision Machinery
National Timing Center, Chinese Academy of Sciences
Institute of Earth Environment, Chinese Academy of Sciences
Shanxi Institute of Coal Chemistry, Chinese Academy of Sciences
===== Lanzhou Branch =====
Institute of Modern Physics, Chinese Academy of Sciences
Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences
Northwest Institute of Ecological and Environmental Resources
Qinghai Salt Lake Research Institute, Chinese Academy of Sciences
Northwest Institute of Plateau Biology, Chinese Academy of Sciences
===== Xinjiang Branch =====
Xinjiang Institute of Physics and Chemistry Technology
Xinjiang Institute of Ecology and Geography
Xinjiang Observatory
==== Directly under the higher education institutions ====
University of Science and Technology of China
University of Chinese Academy of Sciences
==== Direct Management and Public Support Units ====
Science and Technology Innovation and Development Center
Administration of the Chinese Academy of Sciences
Computer Network Information Center
Documentation and Intelligence Center (National Science Library)
Chengdu Literature and Intelligence Center
Wuhan Center for Documentation and Intelligence
==== Direct News Publishing Units ====
China Science Daily
==== Other Directly Affiliated Institutions ====
Beijing Integrated Research Center
Qingdao Sanatorium of the Chinese Academy of Sciences (Zhiyuanlou Hotel)
Chinese Academy of Sciences Lushan Sanatorium (Poyangkou Hotel)
=== Enterprise units directly under the Chinese Academy of Sciences ===
The enterprise units directly under the Chinese Academy of Sciences are wholly owned or controlled by Chinese Academy of Sciences State-owned Assets Management Co.
Chinese Academy of Sciences Holdings Limited
Legend Holdings
China Science Industrial Group (Holdings) Limited
Oriental Science and Technology Holding Group Limited
China Science & Technology Publishing & Media Group
China Science and Technology Industry Investment Management
Beijing Zhongke Keji
Beijing CAS Software Center
Chinese Academy of Sciences Architectural Design and Research Institute
Beijing Zhongke Resources
Shenyang Institute of Computing Technology
Shenyang Scientific Instrument
Nanjing Astronomical Instrument
Guangzhou Chemistry
Guangzhou Electronic Technology
Chengdu Organic Chemistry
Chengdu Information Technology
Chinese Academy of Sciences Science and Technology Services
Shanghai Bike Clean Energy Technology
Shenzhen CAS Intellectual Property Investment
Guoke Jiahe (Beijing) Investment Management
Guoke Health Biotechnology
Chinese Academy of Sciences Innovation Incubation Investment
Guoke Health Management
Beijing Konowei Technology
Guoke Quantum Communication Network
Kasma Holdings
=== Co-builders ===
Shanghai: Shanghai University of Science and Technology
China National Petroleum Corporation: Institute of Seepage Fluid Mechanics, Chinese Academy of Sciences
China National Nuclear Corporation: China Institute of Atomic Energy Science
Shanghai Censhan Botanical Garden
Guangxi Zhuang Autonomous Region: Guangxi Institute of Botany, Chinese Academy of Sciences
Ministry of Water Resources: Institute of Water Engineering and Ecology, Chinese Academy of Sciences
Jiangxi Province: Lushan Botanical Garden, Chinese Academy of Sciences
Jiangsu Province: Institute of Botany, Chinese Academy of Sciences, Jiangsu Province
Shaanxi Province: Qinling National Botanical Garden, Chinese Academy of Sciences
Guangdong Province: Shenzhen University of Technology, Chinese Academy of Sciences Xianhu Botanical Garden
Ministry of Education: Research Center for Soil and Water Conservation and Ecological Environment, Chinese Academy of Sciences
Major Special Project Center of National Bureau of Defense Science, Technology and Industry (NDSTI)
=== Groups and Other Organizations ===
CAS Leading Group Office of Network Security and Informatization
Women's Working Committee of Chinese Academy of Sciences
CAS Youth League Committee
Trade Union of the Chinese Academy of Sciences
Association of Old Science and Technology Workers of the Chinese Academy of Sciences
Federation of Literature and Art of the Chinese Academy of Sciences
== Scientific integrity ==
On 26 February 2007, CAS published a Declaration of Scientific Ideology and set up a commission for scientific integrity to promote transparency, autonomy and accountability of scientific research in the country. Around that same time, the Ministry of Science and Technology also initiated measures to address misconduct in state-funded programs.
CAS also publishes the Early Warning List, which notes journals with a lack of rigor and possible predatory practices.
== Publications ==
Together with the National Natural Science Foundation of China, the academy publishes the peer-reviewed academic journal, Science China (also known as Science in China). Science China comprises seven series:
A: Mathematics
B: Chemistry
C: Life Sciences
D: Earth Sciences
E: Technological Sciences
F: Information Sciences
G: Physics, Mechanics and Astronomy
CAS also promotes the China Open Access Journals (COAJ) platform, a national variant of the international Directory of Open Access Journals (DOAJ).
== Awards ==
Since 1999, the CAS has issued the annual State Preeminent Science and Technology Award, presented by the President of China to the recipient.
== Ranking and reputation ==
CAS has been ranked the No. 1 research institute in the world by Nature Index since the list's inception in 2014 by Nature Portfolio.
It was the most productive institution publishing articles on sustainable development indexed in the Web of Science from 1981 to 2018 among all universities and research institutions in the world.
The academy also runs the University of Science and Technology of China and the University of the Chinese Academy of Sciences, both of which were among the world's top three universities in the Nature Index ranking as of 2024.
In 2024, Clarivate's Highly Cited Researchers list contained 308 CSA members. This made CSA researchers the largest group on the list by institution, and the sixth largest by country.
== International cooperation ==
The Institute of Remote Sensing and Digital Earth is a branch of CAS. The Institute of Remote Sensing and Digital Earth was a customer of Swedish Space Corporation (SSC), which provides data transmission services from satellites for a wide range of societal functions. It was reported by Reuters on 21 September 2020 that SSC decided not to renew the contracts with China to help operate Chinese satellites from SSC's ground stations, or seek new business with China.
== See also ==
Academia Sinica
CAS Star
CAS Space
China Science Publishing & Media
Chinese Academy of Engineering
Chinese Academy of Social Sciences
Chinese Science Citation Database
Hanlin Academy
History of science and technology in the People's Republic of China
International Journal of Software and Informatics (IJSI)
International Society of Zoological Sciences
Legend Holdings
Science and technology in China
Scientific publishing in China
Shanghai Academy of Social Sciences
ShanghaiTech University
University of Chinese Academy of Sciences
University of Science and Technology of China
University of Chinese Academy of Social Sciences
Academician of the Chinese Academy of Sciences
== References ==
=== Citations ===
=== Sources ===
== External links ==
Media related to Chinese Academy of Sciences at Wikimedia Commons
Official website | Wikipedia/Chinese_Academy_of_Sciences |
Socrates (; Ancient Greek: Σωκράτης, romanized: Sōkrátēs; c. 470 – 399 BC) was a Greek philosopher from Athens who is credited as the founder of Western philosophy and as among the first moral philosophers of the ethical tradition of thought. An enigmatic figure, Socrates authored no texts and is known mainly through the posthumous accounts of classical writers, particularly his students Plato and Xenophon. These accounts are written as dialogues, in which Socrates and his interlocutors examine a subject in the style of question and answer; they gave rise to the Socratic dialogue literary genre. Contradictory accounts of Socrates make a reconstruction of his philosophy nearly impossible, a situation known as the Socratic problem. Socrates was a polarizing figure in Athenian society. In 399 BC, he was accused of impiety and corrupting the youth. After a trial that lasted a day, he was sentenced to death. He spent his last day in prison, refusing offers to help him escape.
Plato's dialogues are among the most comprehensive accounts of Socrates to survive from antiquity. They demonstrate the Socratic approach to areas of philosophy including epistemology and ethics. The Platonic Socrates lends his name to the concept of the Socratic method, and also to Socratic irony. The Socratic method of questioning, or elenchus, takes shape in dialogue using short questions and answers, epitomized by those Platonic texts in which Socrates and his interlocutors examine various aspects of an issue or an abstract meaning, usually relating to one of the virtues, and find themselves at an impasse, completely unable to define what they thought they understood. Socrates is known for proclaiming his total ignorance; he used to say that the only thing he was aware of was his ignorance, seeking to imply that the realization of one's ignorance is the first step in philosophizing.
Socrates exerted a strong influence on philosophers in later antiquity and has continued to do so in the modern era. He was studied by medieval and Islamic scholars and played an important role in the thought of the Italian Renaissance, particularly within the humanist movement. Interest in him continued unabated, as reflected in the works of Søren Kierkegaard and Friedrich Nietzsche. Depictions of Socrates in art, literature, and popular culture have made him a widely known figure in the Western philosophical tradition.
== Sources and the Socratic problem ==
Socrates did not document his teachings. All that is known about him comes from the accounts of others: mainly the philosopher Plato and the historian Xenophon, who were both his pupils; the Athenian comic dramatist Aristophanes (Socrates's contemporary); and Plato's pupil Aristotle, who was born after Socrates's death. The often contradictory stories from these ancient accounts only serve to complicate scholars' ability to reconstruct Socrates's true thoughts reliably, a predicament known as the Socratic problem. The works of Plato, Xenophon, and other authors who use the character of Socrates as an investigative tool, are written in the form of a dialogue between Socrates and his interlocutors and provide the main source of information on Socrates's life and thought. Socratic dialogues (logos sokratikos) was a term coined by Aristotle to describe this newly formed literary genre. While the exact dates of their composition are unknown, some were probably written after Socrates's death. As Aristotle first noted, the extent to which the dialogues portray Socrates authentically is a matter of some debate.
=== Plato and Xenophon ===
An honest man, Xenophon was no trained philosopher. He could neither fully conceptualize nor articulate Socrates's arguments. He admired Socrates for his intelligence, patriotism, and courage on the battlefield. He discusses Socrates in four works: the Memorabilia, the Oeconomicus, the Symposium, and the Apology of Socrates. He also mentions a story featuring Socrates in his Anabasis. Oeconomicus recounts a discussion on practical household management. Like Plato's Apology, Xenophon's Apologia describes the trial of Socrates, but the works diverge substantially and, according to W. K. C. Guthrie, Xenophon's account portrays a Socrates of "intolerable smugness and complacency". Symposium is a dialogue of Socrates with other prominent Athenians during an after-dinner discussion, but is quite different from Plato's Symposium: there is no overlap in the guest list. In Memorabilia, he defends Socrates from the accusations of corrupting the youth and being against the gods; essentially, it is a collection of various stories gathered together to construct a new apology for Socrates.
Plato's representation of Socrates is not straightforward. Plato was a pupil of Socrates and outlived him by five decades. How trustworthy Plato is in representing the attributes of Socrates is a matter of debate; the view that he did not represent views other than Socrates's own is not shared by many contemporary scholars. A driver of this doubt is the inconsistency of the character of Socrates that he presents. One common explanation of this inconsistency is that Plato initially tried to accurately represent the historical Socrates, while later in his writings he was happy to insert his own views into Socrates's words. Under this understanding, there is a distinction between the Socratic Socrates of Plato's earlier works and the Platonic Socrates of Plato's later writings, although the boundary between the two seems blurred.
Xenophon's and Plato's accounts differ in their presentations of Socrates as a person. Xenophon's Socrates is duller, less humorous and less ironic than Plato's. Xenophon's Socrates also lacks the philosophical features of Plato's Socrates—ignorance, the Socratic method or elenchus—and thinks enkrateia (self-control) is of pivotal importance, which is not the case with Plato's Socrates. Generally, logoi Sokratikoi cannot help us to reconstruct the historical Socrates even in cases where their narratives overlap, as authors may have influenced each other's accounts.
=== Aristophanes and other sources ===
Writers of Athenian comedy, including Aristophanes, also commented on Socrates. Aristophanes's most important comedy with respect to Socrates is The Clouds, in which Socrates is a central character. In this drama, Aristophanes presents a caricature of Socrates that leans towards sophism, ridiculing Socrates as an absurd atheist. Socrates in Clouds is interested in natural philosophy, which conforms to Plato's depiction of him in Phaedo. What is certain is that by the age of 45, Socrates had already captured the interest of Athenians as a philosopher. It is not clear whether Aristophanes's work is useful in reconstructing the historical Socrates.
Other ancient authors who wrote about Socrates were Aeschines of Sphettus, Antisthenes, Aristippus, Bryson, Cebes, Crito, Euclid of Megara, Phaedo and Aristotle, all of whom wrote after Socrates's death. Aristotle was not a contemporary of Socrates; he studied under Plato at the latter's Academy for twenty years. Aristotle treats Socrates without the bias of Xenophon and Plato, who had an emotional tie with Socrates, and he scrutinizes Socrates's doctrines as a philosopher. Aristotle was familiar with the various written and unwritten stories of Socrates. His role in understanding Socrates is limited. He does not write extensively on Socrates; and, when he does, he is mainly preoccupied with the early dialogues of Plato. There are also general doubts on his reliability on the history of philosophy. Still, his testimony is vital in understanding Socrates.
=== The Socratic problem ===
In a seminal work titled "The Worth of Socrates as a Philosopher" (1818), the philosopher Friedrich Schleiermacher attacked Xenophon's accounts; his attack was widely accepted. Schleiermacher criticized Xenophon for his naïve representation of Socrates. Xenophon was a soldier, argued Schleiermacher, and was therefore not well placed to articulate Socratic ideas. Furthermore, Xenophon was biased in his depiction of his former friend and teacher: he believed Socrates was treated unfairly by Athens, and sought to prove his point of view rather than to provide an impartial account. The result, said Schleiermacher, was that Xenophon portrayed Socrates as an uninspiring philosopher. By the early twentieth century, Xenophon's account was largely rejected.
The philosopher Karl Joel, basing his arguments on Aristotle's interpretation of logos sokratikos, suggested that the Socratic dialogues are mostly fictional: according to Joel, the dialogues' authors were just mimicking some Socratic traits of dialogue. In the mid-twentieth century, philosophers such as Olof Gigon and Eugène Dupréel, based on Joel's arguments, proposed that the study of Socrates should focus on the various versions of his character and beliefs rather than aiming to reconstruct a historical Socrates. Later, ancient philosophy scholar Gregory Vlastos suggested that the early Socratic dialogues of Plato were more compatible with other evidence for a historical Socrates than his later writings, an argument that is based on inconsistencies in Plato's own evolving depiction of Socrates. Vlastos totally disregarded Xenophon's account except when it agreed with Plato's. More recently, Charles H. Kahn has reinforced the skeptical stance on the unsolvable Socratic problem, suggesting that only Plato's Apology has any historical significance.
== Biography ==
Socrates was born in 470 or 469 BC to Sophroniscus and Phaenarete, a stoneworker and a midwife, respectively, in the Athenian deme of Alopece; therefore, he was an Athenian citizen, having been born to relatively affluent Athenians. He lived close to his father's relatives and inherited, as was customary, part of his father's estate, securing a life reasonably free of financial concerns. His education followed the laws and customs of Athens. He learned the basic skills of reading and writing and, like most wealthy Athenians, received extra lessons in various other fields such as gymnastics, poetry and music. He was married twice (which came first is not clear): his marriage to Xanthippe took place when Socrates was in his fifties, and another marriage was with a daughter of Aristides, an Athenian statesman. He had three sons with Xanthippe. Socrates fulfilled his military service during the Peloponnesian War and distinguished himself in three campaigns, according to Plato.
Another incident that reflects Socrates's respect for the law is the arrest of Leon the Salaminian. As Plato describes in his Apology, Socrates and four others were summoned to the Tholos and told by representatives of the Thirty Tyrants (which began ruling in 404 BC) to arrest Leon for execution. Again Socrates was the sole abstainer, choosing to risk the tyrants' wrath and retribution rather than to participate in what he considered to be a crime.
Socrates attracted great interest from the Athenian public and especially the Athenian youth. He was notoriously ugly, having a flat turned-up nose, bulging eyes and a large belly; his friends joked about his appearance. Socrates was indifferent to material pleasures, including his own appearance and personal comfort. He neglected personal hygiene, bathed rarely, walked barefoot, and owned only one ragged coat. He moderated his eating, drinking, and sex, although he did not practice full abstention. Although Socrates was attracted to youth, as was common and accepted in ancient Greece, he resisted his passion for young men because, as Plato describes, he was more interested in educating their souls. Socrates did not seek sex from his disciples, as was often the case between older and younger men in Athens. Politically, he did not take sides in the rivalry between the democrats and the oligarchs in Athens; he criticized both. The character of Socrates as exhibited in Apology, Crito, Phaedo and Symposium concurs with other sources to an extent that gives confidence in Plato's depiction of Socrates in these works as being representative of the real Socrates.
Socrates died in Athens in 399 BC after a trial for impiety (asebeia) and the corruption of the young. He spent his last day in prison among friends and followers who offered him a route to escape, which he refused. He died the next morning, in accordance with his sentence, after drinking poison hemlock. According to the Phaedo, his last words were: “Crito, we owe a rooster to Asclepius. Don't forget to pay the debt.”
== Trial of Socrates ==
In 399 BC, Socrates was formally accused of corrupting the minds of the youth of Athens, and for asebeia (impiety), i.e. worshipping false gods and failing to worship the gods of Athens. At the trial, Socrates defended himself unsuccessfully. He was found guilty by a majority vote cast by a jury of hundreds of male Athenian citizens and, according to the custom, proposed his own penalty: that he should be given free food and housing by the state for the services he rendered to the city, or alternatively, that he be fined one mina of silver (according to him, all he had). The jurors declined his offer and ordered the death penalty.
Socrates was charged in a politically tense climate. In 404 BC, the Athenians had been crushed by Spartans at the decisive naval Battle of Aegospotami, and subsequently, the Spartans laid siege to Athens. They replaced the democratic government with a new, pro-oligarchic government, named the Thirty Tyrants. Because of their tyrannical measures, some Athenians organized to overthrow the Tyrants—and, indeed, they managed to do so briefly—until a Spartan request for aid from the Thirty arrived and a compromise was sought. When the Spartans left again, however, democrats seized the opportunity to kill the oligarchs and reclaim the government of Athens.
The accusations against Socrates were initiated by a poet, Meletus, who asked for the death penalty in accordance with the charge of asebeia. Other accusers were Anytus and Lycon. After a month or two, in late spring or early summer, the trial started and likely went on for most of one day. There were two main sources for the religion-based accusations. First, Socrates had rejected the anthropomorphism of traditional Greek religion by denying that the gods did bad things like humans do. Second, he seemed to believe in a daimonion—an inner voice with, as his accusers suggested, divine origin.
Plato's Apology starts with Socrates answering the various rumours against him that have given rise to the indictment. First, Socrates defends himself against the rumour that he is an atheist naturalist philosopher, as portrayed in Aristophanes's The Clouds; or a sophist. Against the allegations of corrupting the youth, Socrates answers that he has never corrupted anyone intentionally, since corrupting someone would carry the risk of being corrupted back in return, and that would be illogical, since corruption is undesirable. On the second charge, Socrates asks for clarification. Meletus responds by repeating the accusation that Socrates is an atheist. Socrates notes the contradiction between atheism and worshipping false gods. He then claims that he is "God's gift" to the Athenians, since his activities ultimately benefit Athens; thus, in condemning him to death, Athens itself will be the greatest loser. After that, he says that even though no human can reach wisdom, seeking it is the best thing someone can do, implying money and prestige are not as precious as commonly thought.
Socrates was given the chance to offer alternative punishments for himself after being found guilty. He could have requested permission to flee Athens and live in exile, but he did not do so. According to Xenophon, Socrates made no proposals, while according to Plato he suggested free meals should be provided for him daily in recognition of his worth to Athens or, more in earnest, that a fine should be imposed on him. The jurors favoured the death penalty by making him drink a cup of hemlock (a poisonous liquid). In return, Socrates warned jurors and Athenians that criticism of them by his many disciples was inescapable, unless they became good men. After a delay caused by Athenian religious ceremonies, Socrates spent his last day in prison. His friends visited him and offered him an opportunity to escape, which he declined.
The question of what motivated Athenians to convict Socrates remains controversial among scholars. There are two theories. The first is that Socrates was convicted on religious grounds; the second, that he was accused and convicted for political reasons. Another, more recent, interpretation synthesizes the religious and political theories, arguing that religion and state were not separate in ancient Athens.
The argument for religious persecution is supported by the fact that Plato's and Xenophon's accounts of the trial mostly focus on the charges of impiety. In those accounts, Socrates is portrayed as making no effort to dispute the fact that he did not believe in the Athenian gods. Against this argument stands the fact that many skeptics and atheist philosophers during this time were not prosecuted. According to the argument for political persecution, Socrates was targeted because he was perceived as a threat to democracy. It was true that Socrates did not stand for democracy during the reign of the Thirty Tyrants and that most of his pupils were against the democrats. The case for it being a political persecution is usually challenged by the existence of an amnesty that was granted to Athenian citizens in 403 BC to prevent escalation to civil war after the fall of the Thirty. However, as the text from Socrates's trial and other texts reveal, the accusers could have fuelled their rhetoric using events prior to 403 BC.
== Philosophy ==
=== Socratic method ===
A fundamental characteristic of Plato's Socrates is the Socratic method, or the method of refutation (elenchus). It is most prominent in the early works of Plato, such as Apology, Crito, Gorgias, Republic I, and others. The typical elenchus proceeds as follows. Socrates initiates a discussion about a topic with a known expert on the subject, usually in the company of some young men and boys, and by dialogue proves the expert's beliefs and arguments to be contradictory. Socrates initiates the dialogue by asking his interlocutor for a definition of the subject. As he asks more questions, the interlocutor's answers eventually contradict the first definition. The conclusion is that the expert did not really know the definition in the first place. The interlocutor may come up with a different definition. That new definition, in turn, comes under the scrutiny of Socratic questioning. With each round of question and answer, Socrates and his interlocutor hope to approach the truth. More often, they continue to reveal their ignorance. Since the interlocutors' definitions most commonly represent the mainstream opinion on a matter, the discussion places doubt on the common opinion.
Socrates also tests his own opinions through the Socratic method. Thus Socrates does not teach a fixed philosophical doctrine. Rather, he acknowledges his own ignorance while searching for truth with his pupils and interlocutors.
Scholars have questioned the validity and the exact nature of the Socratic method, or indeed if there even was a Socratic method. In 1982, the scholar of ancient philosophy Gregory Vlastos claimed that the Socratic method could not be used to establish the truth or falsehood of a proposition. Rather, Vlastos argued, it was a way to show that an interlocutor's beliefs were inconsistent. There have been two main lines of thought regarding this view, depending on whether it is accepted that Socrates is seeking to prove a claim wrong. According to the first line of thought, known as the constructivist approach, Socrates indeed seeks to refute a claim by this method, and the method helps in reaching affirmative statements. The non-constructivist approach holds that Socrates merely wants to establish the inconsistency between the premises and the conclusion of the initial argument.
=== Socratic priority of definition ===
Socrates starts his discussions by prioritizing the search for definitions. In most cases, Socrates initiates his discourse with an expert on a subject by seeking a definition—by asking, for example, what virtue, goodness, justice, or courage is. To establish a definition, Socrates first gathers clear examples of a virtue and then seeks to establish what they had in common. According to Guthrie, Socrates lived in an era when sophists had challenged the meaning of various virtues, questioning their substance; Socrates's quest for a definition was an attempt to clear the atmosphere from their radical skepticism.
Some scholars have argued that Socrates does not endorse the priority of definition as a principle, because they have identified cases where he does not do so. Some have argued that this priority of definition comes from Plato rather than Socrates. Philosopher Peter Geach, accepting that Socrates endorses the priority of definition, finds the technique fallacious. Αccording to Geach, one may know a proposition even if one cannot define the terms in which the proposition is stated.
=== Socratic ignorance ===
Plato's Socrates often claims that he is aware of his own lack of knowledge, especially when discussing ethical concepts such as arete (i.e., goodness, courage) since he does not know the nature of such concepts. For example, during his trial, with his life at stake, Socrates says: "I thought Evenus a happy man, if he really possesses this art (technē), and teaches for so moderate a fee. Certainly I would pride and preen myself if I knew (epistamai) these things, but I do not know (epistamai) them, gentlemen". In some of Plato's dialogues, Socrates appears to credit himself with some knowledge, and can even seem strongly opinionated for a man who professes his own ignorance.
There are varying explanations of the Socratic inconsistency (other than that Socrates is simply being inconsistent). One explanation is that Socrates is being either ironic or modest for pedagogical purposes: he aims to let his interlocutor to think for himself rather than guide him to a prefixed answer to his philosophical questions. Another explanation is that Socrates holds different interpretations of the meaning of "knowledge". Knowledge, for him, might mean systematic understanding of an ethical subject, on which Socrates firmly rejects any kind of mastery; or might refer to lower-level cognition, which Socrates may accept that he possesses. In any case, there is a consensus that Socrates accepts that acknowledging one's lack of knowledge is the first step towards wisdom.
Socrates is known for disavowing knowledge, a claim encapsulated in the saying "I know that I know nothing". This is often attributed to Socrates on the basis of a statement in Plato's Apology, though the same view is repeatedly found elsewhere in Plato's early writings on Socrates. In other statements, though, he implies or even claims that he does have knowledge. For example, in Plato's Apology Socrates says: "...but that to do injustice and disobey my superior, god or man, this I know to be evil and base..." (Apology, 29b6–7). In his debate with Callicles, he says: "...I know well that if you will agree with me on those things which my soul believes, those things will be the very truth..."
Whether Socrates genuinely thought he lacked knowledge or merely feigned a belief in his own ignorance remains a matter of debate. A common interpretation is that he was indeed feigning modesty. According to Norman Gulley, Socrates did this to entice his interlocutors to speak with him. On the other hand, Terence Irwin claims that Socrates's words should be taken literally.
Gregory Vlastos argues that there is enough evidence to refute both claims. In his view, for Socrates, there are two separate meanings of "knowledge": Knowledge-C and Knowledge-E (C stands for "certain", and E stands for elenchus, i.e. the Socratic method). Knowledge-C is something unquestionable whereas Knowledge-E is the knowledge derived from Socrates's elenchus. Thus, Socrates speaks the truth when he says he knows-C something, and he is also truthful when saying he knows-E, for example, that it is evil for someone to disobey his superiors, as he claims in Apology. Not all scholars have agreed with this semantic dualism. James H. Lesher has argued that Socrates claimed in various dialogues that one word is linked to one meaning (i.e. in Hippias Major, Meno, and Laches). Lesher suggests that although Socrates claimed that he had no knowledge about the nature of virtues, he thought that in some cases, people can know some ethical propositions.
=== Socratic irony ===
There is a widespread assumption that Socrates was an ironist, mostly based on the depiction of Socrates by Plato and Aristotle. Socrates's irony is so subtle and slightly humorous that it often leaves the reader wondering if Socrates is making an intentional pun. Plato's Euthyphro is filled with Socratic irony. The story begins when Socrates is meeting with Euthyphro, a man who has accused his own father of murder. When Socrates first hears the details of the story, he comments, "It is not, I think, any random person who could do this [prosecute one's father] correctly, but surely one who is already far progressed in wisdom". When Euthyphro boasts about his understanding of divinity, Socrates responds that it is "most important that I become your student". Socrates is commonly seen as ironic when using praise to flatter or when addressing his interlocutors.
Scholars are divided on why Socrates uses irony. According to an opinion advanced since the Hellenistic period, Socratic irony is a playful way to get the audience's attention. Another line of thought holds that Socrates conceals his philosophical message with irony, making it accessible only to those who can separate the parts of his statements which are ironic from those which are not. Gregory Vlastos has identified a more complex pattern of irony in Socrates. In Vlastos's view, Socrates's words have a double meaning, both ironic and not. One example is when he denies having knowledge. Vlastos suggests that Socrates is being ironic when he says he has no knowledge (where "knowledge" means a lower form of cognition); while, according to another sense of "knowledge", Socrates is serious when he says he has no knowledge of ethical matters. This opinion is not shared by many other scholars.
=== Socratic eudaimonism and intellectualism ===
For Socrates, the pursuit of eudaimonia motivates all human action, directly or indirectly. Virtue and knowledge are linked, in Socrates's view, to eudaimonia, but how closely he considered them to be connected is still debated. Some argue that Socrates thought that virtue and eudaimonia are identical. According to another view, virtue serves as a means to eudaimonia (the "identical" and "sufficiency" theses, respectively). Another point of debate is whether, according to Socrates, people desire what is in fact good—or, rather, simply what they perceive as good.
Moral intellectualism refers to the prominent role Socrates gave to knowledge. He believed that all virtue was based on knowledge (hence Socrates is characterized as a virtue intellectualist). He also believed that humans were guided by the cognitive power to comprehend what they desire, while diminishing the role of impulses (a view termed motivational intellectualism). In Plato's Protagoras (345c4–e6), Socrates implies that "no one errs willingly", which has become the hallmark of Socratic virtue intellectualism. In Socratic moral philosophy, priority is given to the intellect as being the way to live a good life; Socrates deemphasizes irrational beliefs or passions. Plato's dialogues that support Socrates's intellectual motivism—as this thesis is named—are mainly the Gorgias (467c–8e, where Socrates discusses the actions of a tyrant that do not benefit him) and Meno (77d–8b, where Socrates explains to Meno his view that no one wants bad things, unless they do not know what is good and bad in the first place). Scholars have been puzzled by Socrates's view that akrasia (acting because of one's irrational passions, contrary to one's knowledge or beliefs) is impossible. Most believe that Socrates left no space for irrational desires, although some claim that Socrates acknowledged the existence of irrational motivations, but denied they play a primary role in decision-making.
=== Religion ===
Socrates's religious nonconformity challenged the views of his times and his critique reshaped religious discourse for the coming centuries. In Ancient Greece, organized religion was fragmented, celebrated in a number of festivals for specific gods, such as the City Dionysia, or in domestic rituals, and there were no sacred texts. Religion intermingled with the daily life of citizens, who performed their personal religious duties mainly with sacrifices to various gods. Whether Socrates was a practicing man of religion or a 'provocateur atheist' has been a point of debate since ancient times; his trial included impiety accusations, and the controversy has not yet ceased.
Socrates discusses divinity and the soul mostly in Alcibiades, Euthyphro, and Apology. In Alcibiades Socrates links the human soul to divinity, concluding "Then this part of her resembles God, and whoever looks at this, and comes to know all that is divine, will gain thereby the best knowledge of himself." His discussions on religion always fall under the lens of his rationalism. Socrates, in Euthyphro, reaches a conclusion which takes him far from the age's usual practice: he considers sacrifices to the gods to be useless, especially when they are driven by the hope of receiving a reward in return. Instead, he calls for philosophy and the pursuit of knowledge to be the principal way of worshipping the gods. His rejection of traditional forms of piety, connecting them to self-interest, implied that Athenians should seek religious experience by self-examination.
Socrates argued that the gods were inherently wise and just, a perception far from traditional religion at that time. In Euthyphro, the Euthyphro dilemma arises. Socrates questions his interlocutor about the relationship between piety and the will of a powerful god: Is something good because it is the will of this god, or is it the will of this god because it is good? In other words, does piety follow the good, or the god? The trajectory of Socratic thought contrasts with traditional Greek theology, which took lex talionis (the eye for an eye principle) for granted. Socrates thought that goodness is independent from gods, and gods must themselves be pious.
Socrates affirms a belief in gods in Plato's Apology, where he says to the jurors that he acknowledges gods more than his accusers. For Plato's Socrates, the existence of gods is taken for granted; in none of his dialogues does he probe whether gods exist or not. In Apology, a case for Socrates being agnostic can be made, based on his discussion of the great unknown after death, and in Phaedo (the dialogue with his students in his last day) Socrates gives expression to a clear belief in the immortality of the soul. He also believed in oracles, divinations and other messages from gods. These signs did not offer him any positive belief on moral issues; rather, they were predictions of unfavorable future events.
In Xenophon's Memorabilia, Socrates constructs an argument close to the contemporary teleological intelligent-design argument. He claims that since there are many features in the universe that exhibit "signs of forethought" (e.g., eyelids), a divine creator must have created the universe. He then deduces that the creator should be omniscient and omnipotent and also that it created the universe for the advance of humankind, since humans naturally have many abilities that other animals do not. At times, Socrates speaks of a single deity, while at other times he refers to plural "gods". This has been interpreted to mean that he either believed that a supreme deity commanded other gods, or that various gods were parts, or manifestations, of this single deity.
The relationship of Socrates's religious beliefs with his strict adherence to rationalism has been subject to debate. Philosophy professor Mark McPherran suggests that Socrates interpreted every divine sign through secular rationality for confirmation. Professor of ancient philosophy A. A. Long suggests that it is anachronistic to suppose that Socrates believed the religious and rational realms were separate.
=== Socratic daimonion ===
In several texts (e.g., Plato's Euthyphro 3b5; Apology 31c–d; Xenophon's Memorabilia 1.1.2) Socrates claims he hears a daimōnic sign—an inner voice heard usually when he was about to make a mistake. Socrates gave a brief description of this daimonion at his trial (Apology 31c–d): "...The reason for this is something you have heard me frequently mention in different places—namely, the fact that I experience something divine and daimonic, as Meletus has inscribed in his indictment, by way of mockery. It started in my childhood, the occurrence of a particular voice. Whenever it occurs, it always deters me from the course of action I was intending to engage in, but it never gives me positive advice. It is this that has opposed my practicing politics, and I think its doing so has been absolutely fine." Modern scholarship has variously interpreted this Socratic daimōnion as a rational source of knowledge, an impulse, a dream or even a paranormal experience felt by an ascetic Socrates.
=== Virtue and knowledge ===
Socrates's theory of virtue states that all virtues are essentially one, since they are a form of knowledge. For Socrates, the reason a person is not good is because they lack knowledge. Since knowledge is united, virtues are united as well. Another famous dictum—"no one errs willingly"—also derives from this theory. In Protagoras, Socrates argues for the unity of virtues using the example of courage: if someone knows what the relevant danger is, they can undertake a risk. Aristotle comments: " ... Socrates the elder thought that the end of life was knowledge of virtue, and he used to seek for the definition of justice, courage, and each of the parts of virtue, and this was a reasonable approach, since he thought that all virtues were sciences, and that as soon as one knew [for example] justice, he would be just..."
=== Love ===
Some texts suggest that Socrates had love affairs with Alcibiades and other young persons; others suggest that Socrates's friendship with young boys sought only to improve them and were not sexual. In Gorgias, Socrates claims he was a dual lover of Alcibiades and philosophy, and his flirtatiousness is evident in Protagoras, Meno (76a–c) and Phaedrus (227c–d). However, the exact nature of his relationship with Alcibiades is not clear; Socrates was known for his self-restraint, while Alcibiades admits in the Symposium that he had tried to seduce Socrates but failed.
The Socratic theory of love is mostly deduced from Lysis, where Socrates discusses love at a wrestling school in the company of Lysis and his friends. They start their dialogue by investigating parental love and how it manifests with respect to the freedom and boundaries that parents set for their children. Socrates concludes that if Lysis is utterly useless, nobody will love him—not even his parents. While most scholars believe this text was intended to be humorous, it has also been suggested that Lysis shows Socrates held an egoistic view of love, according to which we only love people who are useful to us in some way. Other scholars disagree with this view, arguing that Socrates's doctrine leaves room for non-egoistic love for a spouse; still others deny that Socrates suggests any egoistic motivation at all. In Symposium, Socrates argues that children offer the false impression of immortality to their parents, and this misconception yields a form of unity among them. Scholars also note that for Socrates, love is rational.
Socrates, who claims to know only that he does not know, makes an exception (in Plato's Symposium), where he says he will tell the truth about Love, which he learned from a 'clever woman'. Classicist Armand D'Angour has made the case that Socrates was in his youth close to Aspasia, and that Diotima, to whom Socrates attributes his understanding of love in Symposium, is based on her; however, it is also possible that Diotima really existed.
=== Socratic philosophy of politics ===
While Socrates was involved in public political and cultural debates, it is hard to define his exact political philosophy. In Plato's Gorgias, he tells Callicles: "I believe that I'm one of a few Athenians—so as not to say I'm the only one, but the only one among our contemporaries—to take up the true political craft and practice the true politics. This is because the speeches I make on each occasion do not aim at gratification but at what's best." His claim illustrates his aversion for the established democratic assemblies and procedures such as voting—since Socrates saw politicians and rhetoricians as using tricks to mislead the public. He never ran for office or suggested any legislation. Rather, he aimed to help the city flourish by "improving" its citizens. As a citizen, he abided by the law. He obeyed the rules and carried out his military duty by fighting wars abroad. His dialogues, however, make little mention of contemporary political decisions, such as the Sicilian Expedition.
Socrates spent his time conversing with citizens, among them powerful members of Athenian society, scrutinizing their beliefs and bringing the contradictions of their ideas to light. Socrates believed he was doing them a favor since, for him, politics was about shaping the moral landscape of the city through philosophy rather than electoral procedures. There is a debate over where Socrates stood in the polarized Athenian political climate, which was divided between oligarchs and democrats. While there is no clear textual evidence, one widely held theory holds that Socrates leaned towards democracy: he disobeyed the one order that the oligarchic government of the Thirty Tyrants gave him; he respected the laws and political system of Athens (which were formulated by democrats); and, according to this argument, his affinity for the ideals of democratic Athens was a reason why he did not want to escape prison and the death penalty. On the other hand, there is some evidence that Socrates leaned towards oligarchy: most of his friends supported oligarchy, he was contemptuous of the opinion of the many and was critical of the democratic process, and Protagoras shows some anti-democratic elements. A less mainstream argument suggests that Socrates favoured democratic republicanism, a theory that prioritizes active participation in public life and concern for the city.
Yet another suggestion is that Socrates endorsed views in line with liberalism, a political ideology formed in the Age of Enlightenment. This argument is mostly based on Crito and Apology, where Socrates talks about the mutually beneficial relationship between the city and its citizens. According to Socrates, citizens are morally autonomous and free to leave the city if they wish—but, by staying within the city, they also accept the laws and the city's authority over them. On the other hand, Socrates has been seen as the first proponent of civil disobedience. Socrates's strong objection to injustice, along with his refusal to serve the Thirty Tyrants' order to arrest Leon, are suggestive of this line. As he says in Critias, "One ought never act unjustly, even to repay a wrong that has been done to oneself." Ιn the broader picture, Socrates's advice would be for citizens to follow the orders of the state, unless, after much reflection, they deem them to be unjust.
== Legacy ==
=== Classical antiquity ===
Socrates's impact was immense in philosophy after his death. With the exception of the Epicureans and the Pyrrhonists, almost all philosophical currents after Socrates traced their roots to him: Plato's Academy, Aristotle's Lyceum, the Cynics, and the Stoics. Interest in Socrates kept increasing until the third century AD. The various schools differed in response to fundamental questions such as the purpose of life or the nature of arete (virtue), since Socrates had not handed them an answer, and therefore, philosophical schools subsequently diverged greatly in their interpretation of his thought. He was considered to have shifted the focus of philosophy from a study of the natural world, as was the case for pre-Socratic philosophers, to a study of human affairs.
Immediate followers of Socrates were his pupils, Euclid of Megara, Aristippus, and Antisthenes, who drew differing conclusions among themselves and followed independent trajectories. The full doctrines of Socrates's pupils are difficult to reconstruct. Antisthenes had a profound contempt of material goods. According to him, virtue was all that mattered. Diogenes and the Cynics continued this line of thought. On the opposite end, Aristippus endorsed the accumulation of wealth and lived a luxurious life. After leaving Athens and returning to his home city of Cyrene, he founded the Cyrenaic philosophical school which was based on hedonism, and endorsing living an easy life with physical pleasures. His school passed to his grandson, bearing the same name. There is a dialogue in Xenophon's work in which Aristippus claims he wants to live without wishing to rule or be ruled by others. In addition, Aristippus maintained a skeptical stance on epistemology, claiming that we can be certain only of our own feelings. This view resonates with the Socratic understanding of ignorance. Euclid was a contemporary of Socrates. After Socrates's trial and death, he left Athens for the nearby town of Megara, where he founded a school, named the Megarians. His theory was built on the pre-Socratic monism of Parmenides. Euclid continued Socrates's thought, focusing on the nature of virtue.
The Stoics relied heavily on Socrates. They applied the Socratic method as a tool to avoid inconsistencies. Their moral doctrines focused on how to live a smooth life through wisdom and virtue. The Stoics assigned virtue a crucial role in attaining happiness and also prioritized the relation between goodness and ethical excellence, all of which echoed Socratic thought. At the same time, the philosophical current of Platonism claimed Socrates as its predecessor, in ethics and in its theory of knowledge. Arcesilaus, who became the head of the Academy about 80 years after its founding by Plato, radically changed the Academy's doctrine to what is now known as Academic Skepticism, centered on the Socratic philosophy of ignorance. The Academic Skeptics competed with the Stoics over who was Socrates's true heir with regard to ethics. While the Stoics insisted on knowledge-based ethics, Arcesilaus relied on Socratic ignorance. The Stoics' reply to Arcesilaus was that Socratic ignorance was part of Socratic irony (they themselves disapproved the use of irony), an argument that ultimately became the dominant narrative of Socrates in later antiquity.
While Aristotle considered Socrates an important philosopher, Socrates was not a central figure in Aristotelian thought. One of Aristotle's pupils, Aristoxenus even authored a book detailing Socrates's scandals.
The Epicureans were antagonistic to Socrates. They attacked him for superstition, criticizing his belief in his daimonion and his regard for the oracle at Delphi. They also criticized Socrates for his character and various faults, and focusing mostly on his irony, which was deemed inappropriate for a philosopher and unseemly for a teacher.
The Pyrrhonists were also antagonistic to Socrates, accusing him of being a prater about ethics, who engaged in mock humility, and who sneered at and mocked people.
=== Medieval world ===
Socratic thought found its way to the Islamic Middle East alongside that of Aristotle and the Stoics. Plato's works on Socrates, as well as other ancient Greek literature, were translated into Arabic by early Muslim scholars such as Al-Kindi, Jabir ibn Hayyan, and the Muʿtazila. For Muslim scholars, Socrates was hailed and admired for combining his ethics with his lifestyle, perhaps because of the resemblance in this regard with Muhammad's personality. Socratic doctrines were altered to match Islamic faith: according to Muslim scholars, Socrates made arguments for monotheism and for the temporality of this world and rewards in the next life. His influence in the Arabic-speaking world continues to the present day.
In medieval times, little of Socrates's thought survived in the Christian world as a whole; however, works on Socrates from Christian scholars such as Lactantius, Eusebius and Augustine were maintained in the Byzantine Empire, where Socrates was studied under a Christian lens. After the fall of Constantinople, many of the texts were brought back into the world of Roman Christianity, where they were translated into Latin. Overall, ancient Socratic philosophy, like the rest of classical literature before the Renaissance, was addressed with skepticism in the Christian world at first.
During the early Italian Renaissance, two different narratives of Socrates developed. On the one hand, the humanist movement revived interest in classical authors. Leonardo Bruni translated many of Plato's Socratic dialogues, while his pupil Giannozzo Manetti authored a well-circulated book, a Life of Socrates. They both presented a civic version of Socrates, according to which Socrates was a humanist and a supporter of republicanism. Bruni and Manetti were interested in defending secularism as a non-sinful way of life; presenting a view of Socrates that was aligned with Christian morality assisted their cause. In doing so, they had to censor parts of his dialogues, especially those which appeared to promote homosexuality or any possibility of pederasty (with Alcibiades), or which suggested that the Socratic daimon was a god. On the other hand, a different picture of Socrates was presented by Italian Neoplatonists, led by the philosopher and priest Marsilio Ficino. Ficino was impressed by Socrates's un-hierarchical and informal way teaching, which he tried to replicate. Ficino portrayed a holy picture of Socrates, finding parallels with the life of Jesus Christ. For Ficino and his followers, Socratic ignorance signified his acknowledgement that all wisdom is God-given (through the Socratic daimon).
=== Modern times ===
In early modern France, Socrates's image was dominated by features of his private life rather than his philosophical thought, in various novels and satirical plays. Some thinkers used Socrates to highlight and comment upon controversies of their own era, like Théophile de Viau who portrayed a Christianized Socrates accused of atheism, while for Voltaire, the figure of Socrates represented a reason-based theist. Michel de Montaigne wrote extensively on Socrates, linking him to rationalism as a counterweight to contemporary religious fanatics.
In the 18th century, German idealism revived philosophical interest in Socrates, mainly through Hegel's work. For Hegel, Socrates marked a turning point in the history of humankind by the introduction of the principle of free subjectivity or self-determination. While Hegel hails Socrates for his contribution, he nonetheless justifies the Athenian court, for Socrates's insistence upon self-determination would be destructive of the Sittlichkeit (a Hegelian term signifying the way of life as shaped by the institutions and laws of the State). Also, Hegel sees the Socratic use of rationalism as a continuation of Protagoras' focus on human reasoning (as encapsulated in the motto homo mensura: "man is the measure of all things"), but modified: it is our reasoning that can help us reach objective conclusions about reality. Also, Hegel considered Socrates as a predecessor of later ancient skeptic philosophers, even though he never clearly explained why.
Søren Kierkegaard considered Socrates his teacher, and authored his master's thesis on him, The Concept of Irony with Continual Reference to Socrates. There he argues that Socrates is not a moral philosopher but is purely an ironist. He also focused on Socrates's avoidance of writing: for Kierkegaard, this avoidance was a sign of humility, deriving from Socrates's acceptance of his ignorance. Not only did Socrates not write anything down, according to Kierkegaard, but his contemporaries misconstrued and misunderstood him as a philosopher, leaving us with an almost impossible task in comprehending Socratic thought. Only Plato's Apology was close to the real Socrates, in Kierkegaard's view. In his writings, he revisited Socrates quite frequently; in his later work, Kierkegaard found ethical elements in Socratic thought. Socrates was not only a subject of study for Kierkegaard, he was a model as well: Kierkegaard paralleled his task as a philosopher to Socrates. He writes, "The only analogy I have before me is Socrates; my task is a Socratic task, to audit the definition of what it is to be a Christian", with his aim being to bring society closer to the Christian ideal, since he believed that Christianity had become a formality, void of any Christian essence. Kierkegaard denied being a Christian, as Socrates denied possessing any knowledge.
Friedrich Nietzsche resented Socrates's contributions to Western culture. In his first book, The Birth of Tragedy (1872), Nietzsche held Socrates responsible for what he saw as the deterioration of ancient Greek civilization during the 4th century BC and after. For Nietzsche, Socrates turned the scope of philosophy from pre-Socratic naturalism to rationalism and intellectualism. He writes: "I conceive of [the Presocratics] as precursors to a reformation of the Greeks: but not of Socrates"; "with Empedocles and Democritus the Greeks were well on their way towards taking the correct measure of human existence, its unreason, its suffering; they never reached this goal, thanks to Socrates". The effect, Nietzsche proposed, was a perverse situation that had continued down to his day: our culture is a Socratic culture, he believed. In a later publication, The Twilight of the Idols (1887), Nietzsche continued his offensive against Socrates, focusing on the arbitrary linking of reason to virtue and happiness in Socratic thinking. He writes: "I try to understand from what partial and idiosyncratic states the Socratic problem is to be derived: his equation of reason = virtue = happiness. It was with this absurdity of a doctrine of identity that he fascinated: ancient philosophy never again freed itself [from this fascination]". From the late 19th century until the early 20th, the most common explanation of Nietzsche's hostility towards Socrates was his anti-rationalism; he considered Socrates the father of European rationalism. In the mid-20th century, philosopher Walter Kaufmann published an article arguing that Nietzsche admired Socrates. Current mainstream opinion is that Nietzsche was ambivalent towards Socrates.
Continental philosophers Hannah Arendt, Leo Strauss and Karl Popper, after experiencing the horrors of World War II, amidst the rise of totalitarian regimes, saw Socrates as an icon of individual conscience. Arendt, in Eichmann in Jerusalem (1963), suggests that Socrates's constant questioning and self-reflection could prevent the banality of evil. Strauss considers Socrates's political thought as paralleling Plato's. He sees an elitist Socrates in Plato's Republic as exemplifying why the polis is not, and could not be, an ideal way of organizing life, since philosophical truths cannot be digested by the masses. Popper takes the opposite view: he argues that Socrates opposes Plato's totalitarian ideas. For Popper, Socratic individualism, along with Athenian democracy, imply Popper's concept of the "open society" as described in his Open Society and Its Enemies (1945).
== See also ==
Codex Vaticanus Graecus 64 – Socratic Letters
De genio Socratis
List of cultural depictions of Socrates
List of barefooters
List of speakers in Plato's dialogues
== Notes ==
== Sources ==
== Further reading ==
Brun, Jean (1978). Socrate (in French) (6th ed.). Presses universitaires de France. pp. 39–40. ISBN 978-2-13-035620-2.
Benson, Hugh (1992). Essays on the philosophy of Socrates. New York: Oxford University Press. ISBN 978-0-19-506757-6. OCLC 23179683.
Rudebusch, George (2009). Socrates. Chichester, UK; Malden, MA: Wiley-Blackwell. ISBN 978-1-4051-5085-9. OCLC 476311710.
Taylor, C. C. W. (1998). Socrates. Oxford University Press. ISBN 978-0-19-287601-0.
Taylor, C. C. W. (2019). Socrates: A Very Short Introduction. Oxford University Press. ISBN 978-0-19-883598-1.
Vlastos, Gregory (1994). Socratic Studies. Cambridge University Press. ISBN 978-0-521-44735-5.
== External links ==
Socrates at the Indiana Philosophy Ontology Project
The Dialogues of Plato at Project Gutenberg | Wikipedia/Socrates |
Design studies can refer to any design-oriented studies but is more formally an academic discipline or field of study that pursues, through both theoretical and practical modes of inquiry, a critical understanding of design practice and its effects in society.
== Characteristics and scope ==
Design studies encompasses the study of both the internal practices of design and the external effects that design activity has on society, culture and the environment. Susan Yelavich explained design studies as embracing "two broad perspectives—one that focuses inward on the nature of design and one that looks outward to the circumstances that shape it, and conversely, the circumstances design changes, intentionally or not". This dual aspect is reflected in the complementary orientations of the two leading journals in the field. Design Studies (established 1979) is "the interdisciplinary journal of design research" and is "focused on developing understanding of design processes". Design Issues (established 1984) "examines design history, theory, and criticism" and "provokes inquiry into the cultural and intellectual issues surrounding design".
An interdisciplinary field, design studies includes many scholarship paradigms and uses an evolving set of methodologies and theories drawn from key thinkers from within the field itself. The field has connections with the humanities, the social sciences and the sciences, but many scholars regard design itself as a distinct discipline.
Design studies scholars recognize that design, as a practice, is only one facet of much larger circumstances. They examine and question the role of design in shaping past and present personal and cultural values, especially in light of how they shape the future.
The extensive scope of design studies is conveyed in two collected sets of readings: Design Studies: A Reader (2009) is a compilation of extracts from classic writings that laid the foundations of the field, and The Routledge Companion to Design Studies (2016) contains newer writings over a wide range of topics such as gender and sexuality, consumerism and responsibility, globalization and post-colonialism.
== History ==
=== Origins and early development ===
The origins of design studies lie in the rapid expansion of issues and topics around design since the 1960s, including its role as an academic discipline, its relationships with technological and social change, and its cultural and environmental impacts. As a field of studies it developed more specifically in the development of interaction between design history and design research. Debates about the role of design history and the nature of design research from the 1970s and 80s were brought together in 1992 when Victor Margolin argued in the journal Design Studies for the incorporation of design history into design research, in a combined approach to the study of design. Margolin noted the "dynamic crossings of intellectual boundaries" when considering developments in both fields at the time, and defined design studies as "that field of inquiry which addresses questions of how we make and use products in our daily lives and how we have done so in the past".
Margolin's argument triggered counterarguments and other suggestions about what constitutes design history and how to characterize the study of design as something more than a professional practice. In a reply to Margolin in the Journal of Design History in 1993, Adrian Forty argued that design history had consistently performed a vital role in examining questions around quality in design and was already embracing new lines of thought, for example from cultural studies and anthropology. The growing debate led to a special issue of the journal Design Issues in 1995 which focused attention on "some of the controversies and problems that surround the seemingly simple task of telling the history of design".
A shift from design history towards design studies continued to develop as the overlapping research methods and approaches to the study of design began to lead to broader questions of meaning, authority and power. The realization came that design history is only "but one component of what goes on in studying design, and to claim that all that is going on now could use the umbrella term 'design history' is not tenable".
=== Foundational figures ===
Reyner Banham (1922–1988)
Banham's Theory and Design in the First Machine Age and his journalistic articles written for New Society have been described by the British writer and design historian Penny Sparke as representing a major "shift in how material culture was seen. His writing focused on popular commodities as well as formal architecture.
Gui Bonsiepe (born 1934)
Bonsiepe is a German designer and professor for various universities including FH Koln; Carnegie Mellon; EUA, Chile; LBDI/FIESC, Brazil; Jan van Eyck Academy, Netherlands. His most influential work is Design and Democracy.
Richard Buchanan
American professor of design, management, and information systems and editor of the journal Design Issues. He is well known for "extending the application of design into new areas of theory and practice, writing, and teaching as well as practicing the concepts and methods of interaction design." As a co-editor of Discovering Design: Explorations in Design Studies with Victor Margolin, he brought together the fields of psychology, sociology, political theory, technology studies, rhetoric, and philosophy.
Nigel Cross (born 1942)
Cross is a British academic, design researcher and educator who has focused on design's intellectual space in the academic sphere. He is an emeritus professor of design studies in the Department of Design and Innovation, Faculty of Technology, at the UK's Open University, and emeritus editor-in-chief of Design Studies, the international journal of design research. In his 1982 journal article "Designerly Ways of Knowing" in Design Studies, Cross argued that design has its own intellectual and practical culture as a basis for education, contrasting it with cultures of science and arts and humanities.
Clive Dilnot
Originally educated as a fine artist, Dilnot later began studying social philosophy and the sociology of culture with Polish sociologist Zygmunt Bauman. Dilnot has worked on the history, theory, and criticism of the visual arts in their broadest terms. His teaching and writing have focused on design history, photography, criticism, and theory. Dilnot studied ethics in relation to design, and the role of design's capabilities in creating a humane world in his book, Ethics? Design? published in 2005.
Adrian Forty (born 1948)
Forty was Professor of Architectural History at The Bartlett, The Faculty of the Built Environment at University College London. Forty believed that the drive to define a new field, the field of design studies, was unnecessary due to the fact that the field of design history had not exhausted all of its possibilities. His book Objects of Desire explores how consumer goods relate to larger issues of social processes.
Tony Fry
Fry is a British design theorist and philosopher who writes on the relationship between design, unsustainability, and politics. Fry has taught design and cultural theory in Britain, the United States, Hong Kong and Australia. He is perhaps best known for his writing on defuturing, the destruction of the future by design.
John Heskett (1937–2014)
In the late 1970s, Heskett became a prominent member of a group of academics based in several of Britain's art schools (then part of the polytechnics) who helped develop the discipline of design history and theory, later to become subsumed under the broader banner of design studies. Heskett brought his deep knowledge of economics, politics and history to the project and worked alongside scholars from other disciplines to communicate the meaning and function of that increasingly important concept, 'design', both past and present.
Victor Margolin (1941–2019)
Considered one of the founders of design studies, Victor Margolin was professor emeritus of design history at the University of Illinois, Chicago. He was a co-editor of the academic design journal, Design Issues, and the author, editor, or co-editor of a number of books including Design Discourse, Discovering Design, The Idea of Design, The Designed World, and The Politics of the Artificial.
Victor Papanek (1923–1998)
An industrial designer, Papanek suggested that industrial design had lethal effects by virtue of creating new species of permanent garbage and by choosing materials and processes that pollute the air. His writing and teaching were consistently in favour of re-focusing design for the general good of humanity and the environment.
Elizabeth Sanders
As a practitioner, Sanders introduced many of the methods being used today to drive design from a human-centered perspective. She has practiced participatory design research within and between all the design disciplines. Her current research focuses on codesign processes for innovation, intervention, and transdisciplinary collaboration.
Penny Sparke
Sparke is a professor of design history and director of the Modern Interiors Research Centre (MIRC) at Kingston University, London. Along with Fiona Fisher, Sparke co-edited The Routledge Companion to Design Studies, a comprehensive collection of essays embracing the wide range of scholarship relating to design—theoretical, practice-related, and historical.
== Issues and concepts ==
Design studies inquires about the meanings and consequences of design. It studies the influence of designers and the effects design has on citizens and the environment. Victor Margolin distinguishes a degree in design from a degree in design studies by saying that "the former is about producing design, while the latter is about reflecting on design as it has been practiced, is currently practiced, and how it might be practiced".
Design studies urges a rethinking of design as a process, as a practice, and as a generator or products and systems that gives lives meaning and is imbricated in our economic and political systems. The study of design thinking explores the complexities inherent in the task of thinking about design. Design studies is also concerned with the relationship between design and gender, design and race, and design and culture. It studies design as ethics, its role in sustainability (social and environmental), and the nature of agency in design's construction the artificial.
=== Issues ===
==== Ethics ====
Design has the capacity of structuring life in certain ways and thus design should result in greater good for individuals and society but it doesn't always do so. Ethics deals with how our actions affect others and should affect others. Design studies sees ethics as central to design. Tony Fry, a leading figure in design studies, said that it is widely recognized that design is an ethical process but remains underdeveloped and marginal within design education.
Clive Dilnot's essay "Ethics in Design: Ten Questions" explores the relationship between design and ethics and why we need ethics in design. Dilnot discussed the ability of the designer to address the public as citizens and not as consumers, and about infusing "humane intelligence" into the made environment.
=== Concepts ===
==== The artificial ====
Clive Dilnot wrote that the artificial is by no means confined to technology. Today, it is combination of technical systems, the symbolic realm, including mind and the realm of human transformations and transmutations of nature. He gave the example of a genetically modified tomato that is neither purely natural nor purely artificial. It belongs rather to the extended realms of living things that are, as human beings ourselves are, a hybrid between these conditions.
Design studies scholars also reference sociologist Bruno Latour when investigating the dynamics of the artificial. Latour's concept of actor–network theory (ANT) portrays the social as an interdependent network of human individual actors and non-human, non-individual entities called actants.
==== Agency ====
Design plays a constitutive role in everyday life. The things people see and read, the objects they use, and the places they inhabit are all designed. These products (all artificial because they are made by people) constitute an increasingly large part of the world. The built environment is the physical infrastructure that enables behavior, activity, routines, habits, and rituals, which affect our agency. Jamer Hunt defined the built environment as the combination of all design work.
=== Decolonizing design ===
There have been protests that the field of design studies is not sufficiently "geared towards delivering the kinds of knowledge and understanding that are adequate to addressing the systemic problems that arise from the coloniality of power". Moves towards decolonizing design entail changing design discourse from within by challenging and critiquing the dominant status quo from spaces where marginal voices can be heard, by educating designers about the politics of what they do and create, and by posing alternatives to current (colonial) design practices, rooted in the contexts and histories of the Global South rather than just the North.
The argument is that design history and design research tend to have the strongest influences from the triad of Western Europe, North America, and Japan. The effect tends to be in line with the notion that history is written by the victors and thus design history is written by the economically powerful. Denise Whitehouse said, "While many countries produce local histories of design, the output is uneven and often driven by nationalist and trade agendas", although some academic groups such as the Japanese Design History Forum and the International Committee for Design History and Studies (ICDHS) attempt to draw together both western and non-western, post-communist, postcolonial, Asian, and Southern Hemisphere approaches, "to remap the scope and narrative concerns of design history".: 54–63 A special issue of the Design and Culture journal (Volume 10, Issue 1, 2018) was published on the topic of decolonizing design.
== Research methods ==
The following are some of the research methods that may be used in design studies.
=== Design ethnography ===
This form of research requires the scholar to partake in the use of, or observe others use, a designed object or system. Design ethnography has become a common tool where design is observed as a social practice. It describes a process in which a researcher will partake in traditional observant style ethnography, and observe potential users complete activities that can inform design opportunities and solutions. Other ethnographic techniques used by design studies scholars would fall more in line with anthropologists usage of the method. These techniques are observant and participant ethnography. The observant style requires the scholar to observe in an unobtrusive manner. Observations are recorded and further analyzed. The participant style requires the scholar to partake in the activities with their subject. This tactic enables the scholar to record what they see, but also what they themselves experience.
Design ethnography emerged out of a movement in the late 1980s by organizations such as Xerox/PARC (Palo Alto Research Center], Institute for Research on Learning and Jay Doblin & Associates toward social science approaches in their product design and development efforts. In the 1990s, the research and design consultancy E-Lab (founded by former Doblin employees) took this approach further, pioneering a multidisciplinary methodology guided by anthropology and ethnography. E-Lab challenged conventional market research by prioritizing real-world user experiences and behaviors uncovered through fieldwork, then analyzing the data for patterns organized by explanatory frameworks.
=== Actor-network theory ===
While it remains a broader theory or concept, actor-network theory can be used by design studies scholars as a research framework. When using this method, scholars will assess a designed object and consider the physical and nonphysical interactions which revolve around the object. The scholar will analyze what the object's impact is on psychological, societal, economical, and political worlds. This widened viewpoint allows the researcher to explore and map out the objects many interactions, identify its role within the network, and in what ways it is connected to stakeholders.
=== Semiotics, rhetorical analysis, and discourse theory ===
Design studies scholars may also analyze or research a designed object or system by studying it in terms of representations and their various meanings. Semiotics studies acts of communication between the designer, the thing, and the user or users. This concept branches out into a rhetorical analysis of the designed thing. Scholars such as Richard Buchanan argue that design can be studied in such a way due to the existence of a design argument. The design argument is made up by the designer, the user, and the applicability to "practical life". The scholar would pull these segments apart and thoroughly analyze each component and their interactions. Discourse analysis and Foucauldian discourse analysis can be adopted by the design studies scholar to further explore the above components. A Foucauldian approach specifically will analyze the power structures put in place, manipulated by, or used within a designed thing or object. This process can be particularly useful when the scholar intends to understand if the designed thing has agency or enables others to have agency.
== Societies ==
The Design Research Society (DRS) is a learned society committed to promoting and developing design research. It is the longest established, multi-disciplinary worldwide society for the design research community, founded in the UK in 1966. The purpose of the DRS is to promote "the study of and research into the process of designing in all its many fields".
The Design History Society is an organization that promotes the study of global design histories, and brings together and supports all those engaged in the subject—students, researchers, educators, designers, designer-makers, critics, and curators. The Society aims to play an important role in shaping an inclusive design history.
== References ==
== External links ==
=== Journals ===
CoDesign: "research and scholarship into principles, procedures and techniques relevant to collaboration in design or that relate to its theoretical underpinnings; encompassing collaborative, co-operative, participatory, socio-technical and community design".
Design and Culture: "reflects the state of scholarship in the field of design and nutures new or overlooked lines of inquiry that redefine our understanding of design".
Design Issues: "examines design history, theory, and criticism, and provokes inquiry into the cultural and intellectual issues surrounding design".
The Design Journal: "aims to publish thought-provoking work which will have a direct impact on design knowledge and which challenges assumptions and methods".
Design Studies: "focused on developing understanding of design processes; studies design activity across all domains of application, including engineering and product design, architectural and urban design, computer artefacts and systems design".
International Journal of Design: "devoted to publishing research papers in all fields of design, including industrial design, visual communication design, interface design, animation and game design, architectural design, urban design, and other design related fields".
Journal of Design History: "plays an active role in the development of design history, including the history of crafts and applied arts, as well as contributing to the broader fields of visual and material culture studies".
Journal of Design Research: "emphasising human aspects as a central issue of design through integrative studies of social sciences and design disciplines".
She Ji: The Journal of Design, Economies, and Innovation: "focusing on economics and innovation, design process, and design thinking in today's complex socio-technical environment".
Architecture: "aims to provide an advanced forum for studies related to architectural research, including landscape architecture, architecture design, civil engineering design, systems architecture, industrial design, community and regional planning, interior design, sustainable design, and technology, sustainability, pedagogy, visual culture and artistic practices of architecture". | Wikipedia/Design_studies |
Science of science policy (SoSP) is an emerging interdisciplinary research area that seeks to develop theoretical and empirical models of the scientific enterprise. This scientific basis can be used to help government, and society in general, make better R&D management decisions by establishing a scientifically rigorous, quantitative basis from which policy makers and researchers may assess the impacts of the nation's scientific and engineering enterprise, improve their understanding of its dynamics, and assess the likely outcomes. Examples of research in the science of science policy include models to understand the production of science, qualitative, quantitative and computational methods to estimate the impact of science, and processes for choosing from alternative science portfolios.: 5
== Federal SoSP effort ==
The federal government of the United States has long been a supporter of SoSP. In 2006, in response to Office of Science and Technology Policy Director John H. Marburger's challenge for a new "science of science policy," the National Science and Technology Council's Subcommittee on Social, Behavioral and Economic Sciences (SBE) established an Interagency Task Group on Science of Science Policy (ITG) to serve as part of the internal deliberative process of the Subcommittee. In 2008, the SoSP ITG developed and published The Science of Science Policy: A Federal Research Roadmap, which outlined the Federal efforts necessary for the long-term development of a science of science policy, and presented this Roadmap to the SoSP Community. The ITG's subsequent work has been guided by the questions outlined in the Roadmap and the action steps developed at the workshop. Furthermore, since 2007, the National Science Foundation, in support of academic research to advance the field, has awarded grants from the Science of Science and Innovation Policy (SciSIP) program. The SciSIP research supports and complements the Federal SoSP efforts by providing new tools with immediate relevance to policymakers.
== Science of Science and Innovation Policy program ==
The Science of Science and Innovation Policy (SciSIP) program was established at the National Science Foundation in 2005 in response to a call from John Marburger for a "specialist scholarly community" to study the science of science policy. The program has three major goals: advancing evidence-based science and innovation policy decision making; building a scientific community to study science and innovation policy; and leveraging the experience of other countries.
Between 2007 and 2011, over one hundred and thirty awards were made in five rounds of funding. The awardees include economists, sociologists, political scientists, and psychologists. Some of these awards are already showing results in the form of papers, presentations, software, and data development.
== See also ==
Metascience
Evidence-based policy
Evidence-based practices
== References ==
== Further reading == | Wikipedia/Science_of_science_policy |
A science museum is a museum devoted primarily to science. Older science museums tended to concentrate on static displays of objects related to natural history, paleontology, geology, industry and industrial machinery, etc. Modern trends in museology have broadened the range of subject matter and introduced many interactive exhibits. Modern science museums, increasingly referred to as 'science centres' or 'discovery centres', also feature technology.
While the mission statements of science centres and modern museums may vary, they are commonly places that make science accessible and encourage the excitement of discovery.
== History ==
As early as the Renaissance period, aristocrats collected curiosities for display. Universities, and in particular medical schools, also maintained study collections of specimens for their students. Scientists and collectors displayed their finds in private cabinets of curiosities. Such collections were the predecessors of modern natural history museums.
In 1683, the first purpose-built museum covering natural philosophy, the original Ashmolean museum (now called the Museum of the History of Science) in Oxford, England, was opened, although its scope was mixed.
This was followed in 1752 by the first dedicated science museum, the Museo de Ciencias Naturales, in Madrid, which almost did not survive Francoist Spain. Today, the museum works closely with the Spanish National Research Council (Consejo Superior de Investigaciones Científicas).
The Utrecht University Museum, established in 1836, and the Netherlands' foremost research museum, displays an extensive collection of 18th-century animal and human "rarities" in its original setting.
More science museums developed during the Industrial Revolution, when great national exhibitions showcased the triumphs of both science and industry. An example is the Great Exhibition in 1851 at The Crystal Palace, London, England, surplus items from which contributed to the Science Museum, London, founded in 1857.
In the United States of America, various natural history Societies established collections in the early 19th century. These later evolved into museums. A notable example is the New England Museum of Natural History (now the Museum of Science) which opened in Boston in 1864. Another was the Academy of Science, St. Louis, founded in 1856, the first scientific organisation west of the Mississippi. (Although the organisation managed scientific collections for several decades, a formal museum was not created until the mid-20th century.)
== Modern science museums ==
The modern interactive science museum appears to have been pioneered by Munich's Deutsches Museum (German Museum of Masterpieces of Science and Technology) in the early 20th century. This museum had moving exhibits where visitors were encouraged to push buttons and work levers. The concept was taken to the United States by Julius Rosenwald, chairman of Sears, Roebuck and Company, who visited the Deutsches Museum with his young son in 1911. He was so captivated by the experience that he decided to build a similar museum in his home town. The Ampère Museum, close to Lyon, was created in 1931 and is the first interactive scientific museum in France. Chicago's Museum of Science and Industry opened in phases between 1933 and 1940.
In 1959, the Museum of Science and Natural History (now the Saint Louis Science Center) was formally created by the Academy of Science of Saint Louis, featuring many interactive science and history exhibits, and in August 1969, Frank Oppenheimer dedicated his new Exploratorium in San Francisco almost completely to interactive science exhibits, building on the experience by publishing 'Cookbooks' that explain how to construct versions of the Exploratorium's exhibits.
The Ontario Science Centre, which opened in September 1969, continued the trend of featuring interactive exhibits rather than static displays.
In 1973, the first Omnimax cinema opened at the Reuben H. Fleet Space Theater and Science Center in San Diego's Balboa Park. The tilted-dome Space Theater doubled as a planetarium. The Science Centre was an exploratorium-style museum included as a small part of the complex. This combination of interactive science museum, planetarium and Omnimax theater pioneered a configuration that many major science museums now follow.
Also in 1973, the Association of Science-Technology Centers (ASTC) was founded as an international organisation to provide a collective voice, professional support, and programming opportunities for science centres, museums and related institutions.
The massive Cité des Sciences et de l'Industrie (City of Science and Industry) opened in Paris in 1986, and national centres soon followed in Denmark (Experimentarium), Sweden (Tom Tits Experiment), Finland (Heureka), and Spain (Museu de les Ciencies Principe Felipe). In the United Kingdom, the first interactive centres also opened in 1986 on a modest scale, with further developments more than a decade later, funded by the National Lottery for projects to celebrate the Millennium.
Since the 1990s, science museums and centres have been created or greatly expanded in Asia. Examples are Thailand's National Science Museum and Japan's Minato Science Museum.
== Science centres ==
Museums that brand themselves as science centres emphasise a hands-on approach, featuring interactive exhibits that encourage visitors to experiment and explore.
Recently, there has been a push for science museums to be more involved in science communication and educating the public about the scientific process. Microbiologist and science communicator Natalia Pasternak Taschner stated, "I believe that science museums can promote critical thinking, especially in teenagers and young adults, by teaching them about the scientific method and the process of science, and how by using this to develop knowledge and technology, we can be less wrong."
Urania was a science centre founded in Berlin in 1888. Most of its exhibits were destroyed during World War II, as were those of a range of German technical museums. The Academy of Science of Saint Louis (founded in 1856) created the Saint Louis Museum of Science and Natural History in 1959 (Saint Louis Science Center), but generally science centres are a product of the 1960s and later. In the United Kingdom, many were founded as Millennium projects, with funding from the National Lotteries Fund.
The first 'science centre' in the United States was the Science Center of Pinellas County, founded in 1959. The Pacific Science Center (one of the first large organisations to call itself a 'science centre' rather than a museum), opened in a Seattle World's Fair building in 1962.
In 1969, Oppenheimer's Exploratorium opened in San Francisco, California, and the Ontario Science Centre opened near Toronto, Ontario, Canada. By the early 1970s, COSI Columbus, then known as the Center of Science and Industry in Columbus, Ohio, had run its first 'camp-in'.
In 1983, the Smithsonian Institution invited visitors to the Discovery Room in the newly opened National Museum of Natural History Museum Support Center in Suitland, Maryland, where they could touch and handle formerly off-limits specimens.
The new-style museums banded together for mutual support. In 1971, 16 museum directors gathered to discuss the possibility of starting a new association; one more specifically tailored to their needs than the existing American Association of Museums (now the American Alliance of Museums). As a result of this, the Association of Science-Technology Centers was formally established in 1973, headquartered in Washington DC, but with an international organisational membership.
The corresponding European organisation is Ecsite, and in the United Kingdom, the Association of Science and Discovery Centres represents the interests of over 60 major science engagement organisations. The Asia Pacific Network of Science and Technology Centres (ASPAC) is an association initiated in 1997 with over 50 members from 20 countries across Asia and Australia (2022). Their regional sister organisations are the Network for the Popularization of Science and Technology in Latin America and The Caribbean (RedPOP), the North Africa and Middle East science centres (NAMES), and the Southern African Association of Science and Technology Centres (SAASTEC). In India, the National Council of Science Museums runs science centres at several places including Delhi, Bhopal, Nagpur and Ranchi. There are also a number of private Science Centres, including the Birla Science Museum and The Science Garage in Hyderabad.
== See also ==
List of science museums
Science education
Science festival
Science outreach
Physics Outreach
List of natural history museums
== References ==
== General references ==
Kaushik, R.,1996, "Effectiveness of Indian science centres as learning environments : a study of educational objectives in the design of museum experiences", Unpublished PhD thesis, University of Leicester, UK
Kaushik, R.,1996, "Non-science-adult-visitors in science centres: what is there for them to do?", Museological Review, Vol. 2, No. 1, p. 72–84.
Kaushik, R.,1996, "Health matters in science museums: a review" in Pearce, S. (ed.) New Research in Museum Studies, Vol. 6, Athlone Press, London/Atlantic Highlands, p. 186–193.
Kaushik, R.,1997, "Attitude development in science museums/centres", in Proceedings of the Nova Scotian Institute of Science, Vol. 40, No. 2, p. 1–12.
== Further reading ==
Holland, William Jacob (1911). "Museums of Science" . In Chisholm, Hugh (ed.). Encyclopædia Britannica. Vol. 19 (11th ed.). Cambridge University Press. pp. 64–69.
== External links == | Wikipedia/Science_museum |
The exact sciences or quantitative sciences, sometimes called the exact mathematical sciences, are those sciences "which admit of absolute precision in their results"; especially the mathematical sciences. Examples of the exact sciences are mathematics, optics, astronomy, and physics, which many philosophers from René Descartes, Gottfried Leibniz, and Immanuel Kant to the logical positivists took as paradigms of rational and objective knowledge. These sciences have been practiced in many cultures from antiquity to modern times. Given their ties to mathematics, the exact sciences are characterized by accurate quantitative expression, precise predictions and/or rigorous methods of testing hypotheses involving quantifiable predictions and measurements.
The distinction between the quantitative exact sciences and those sciences that deal with the causes of things is due to Aristotle, who distinguished mathematics from natural philosophy and considered the exact sciences to be the "more natural of the branches of mathematics." Thomas Aquinas employed this distinction when he said that astronomy explains the spherical shape of the Earth by mathematical reasoning while physics explains it by material causes. This distinction was widely, but not universally, accepted until the scientific revolution of the 17th century. Edward Grant has proposed that a fundamental change leading to the new sciences was the unification of the exact sciences and physics by Johannes Kepler, Isaac Newton, and others, which resulted in a quantitative investigation of the physical causes of natural phenomena.
== See also ==
Hard and soft science
Fundamental science
Demarcation problem
== References == | Wikipedia/Exact_sciences |
The hypothetico-deductive model or method is a proposed description of the scientific method. According to it, scientific inquiry proceeds by formulating a hypothesis in a form that can be falsifiable, using a test on observable data where the outcome is not yet known. A test outcome that could have and does run contrary to predictions of the hypothesis is taken as a falsification of the hypothesis. A test outcome that could have, but does not run contrary to the hypothesis corroborates the theory. It is then proposed to compare the explanatory value of competing hypotheses by testing how stringently they are corroborated by their predictions.
== Example ==
One example of an algorithmic statement of the hypothetico-deductive method is as follows:
One possible sequence in this model would be 1, 2, 3, 4. If the outcome of 4 holds, and 3 is not yet disproven, you may continue with 3, 4, 1, and so forth; but if the outcome of 4 shows 3 to be false, you will have to go back to 2 and try to invent a new 2, deduce a new 3, look for 4, and so forth.
Note that this method can never absolutely verify (prove the truth of) 2. It can only falsify 2. (This is what Einstein meant when he said, "No amount of experimentation can ever prove me right; a single experiment can prove me wrong.")
== Discussion ==
Additionally, as pointed out by Carl Hempel (1905–1997), this simple view of the scientific method is incomplete; a conjecture can also incorporate probabilities, e.g., the drug is effective about 70% of the time. Tests, in this case, must be repeated to substantiate the conjecture (in particular, the probabilities). In this and other cases, we can quantify a probability for our confidence in the conjecture itself and then apply a Bayesian analysis, with each experimental result shifting the probability either up or down. Bayes' theorem shows that the probability will never reach exactly 0 or 100% (no absolute certainty in either direction), but it can still get very close to either extreme. See also confirmation holism.
Qualification of corroborating evidence is sometimes raised as philosophically problematic. The raven paradox is a famous example. The hypothesis that 'all ravens are black' would appear to be corroborated by observations of only black ravens. However, 'all ravens are black' is logically equivalent to 'all non-black things are non-ravens' (this is the contrapositive form of the original implication). 'This is a green tree' is an observation of a non-black thing that is a non-raven and therefore corroborates 'all non-black things are non-ravens'. It appears to follow that the observation 'this is a green tree' is corroborating evidence for the hypothesis 'all ravens are black'.
Attempted resolutions may distinguish:
non-falsifying observations as to strong, moderate, or weak corroborations
investigations that do or do not provide a potentially falsifying test of the hypothesis.
Evidence contrary to a hypothesis is itself philosophically problematic. Such evidence is called a falsification of the hypothesis. However, under the theory of confirmation holism it is always possible to save a given hypothesis from falsification. This is so because any falsifying observation is embedded in a theoretical background, which can be modified in order to save the hypothesis. Karl Popper acknowledged this but maintained that a critical approach respecting methodological rules that avoided such immunizing stratagems is conducive to the progress of science.
Physicist Sean Carroll claims the model ignores underdetermination.
=== Versus other research models ===
The hypothetico-deductive approach contrasts with other research models such as the inductive approach or grounded theory. In the data percolation methodology,
the hypothetico-deductive approach is included in a paradigm of pragmatism by which four types of relations between the variables can exist: descriptive, of influence, longitudinal or causal. The variables are classified in two groups, structural and functional, a classification that drives the formulation of hypotheses and the statistical tests to be performed on the data so as to increase the efficiency of the research.
== See also ==
Confirmation bias
Deductive-nomological
Explanandum and explanans
Inquiry
Models of scientific inquiry
Philosophy of science
Pragmatism
Scientific method
Verifiability theory of meaning
Will to believe doctrine
=== Types of inference ===
Strong inference
Abductive reasoning
Deductive reasoning
Inductive reasoning
Analogy
== Citations ==
== References ==
Brody, Thomas A. (1993), The Philosophy Behind Physics, Springer Verlag, ISBN 0-387-55914-0. (Luis de la Peña and Peter E. Hodgson, eds.)
Bynum, W.F.; Porter, Roy (2005), Oxford Dictionary of Scientific Quotations, Oxford, ISBN 0-19-858409-1.
Godfrey-Smith, Peter (2003), Theory and Reality: An introduction to the philosophy of science, University of Chicago Press, ISBN 0-226-30063-3
Taleb, Nassim Nicholas (2007), The Black Swan, Random House, ISBN 978-1-4000-6351-2 | Wikipedia/Hypothetico-deductive_method |
Discovery science (also known as discovery-based science) is a scientific methodology which aims to find new patterns, correlations, and form hypotheses through the analysis of large-scale experimental data. The term “discovery science” encompasses various fields of study, including basic, translational, and computational science and research. Discovery-based methodologies are commonly contrasted with traditional scientific practice, the latter involving hypothesis formation before experimental data is closely examined. Discovery science involves the process of inductive reasoning or using observations to make generalisations, and can be applied to a range of science-related fields, e.g., medicine, proteomics, hydrology, psychology, and psychiatry.
== Overview ==
=== Purpose ===
Discovery science places an emphasis on 'basic' discovery, which can fundamentally change the status quo. For example, in the early years of water resources research, the use of discovery science was demonstrated by seeking to elucidate phenomena that was, until that point, unexplained. It did not matter how unusual these ideas may have been perceived to be. In this sense, discovery science is based on the attitude that ‘‘we must not allow our concepts of the earth, in so far as they transcend the reach of observation, to root themselves so deeply and so firmly in our minds that the process of uprooting them causes mental discomfort" (as stated by Davis in 1926). For discovery science to be utilised, there is a need to revert to creating and testing genuine hypotheses, rather than focusing on praising concepts that are already familiar. While researchers commonly feel that new hypotheses will naturally emerge inductively from curiosity in the relevant field, it should be acknowledged that hypotheses can be generated by models. Additionally, deductive testing must involve field observation, so that imperfect answers can be substituted with questions that are more clearly defined.
=== Tools ===
Hypothesis-driven studies can be transformed into discovery-driven studies with the help of newly available tools and technology-driven life science research. These tools have allowed for new questions to be asked, and new paradigms to be considered, particularly in the field of biology. However, some of these required tools are limited in the sense that they are inaccessible or too costly because the related technology is still being developed.
Data mining is the most common tool used in discovery science, and is applied to data from diverse fields of study such as DNA analysis, climate modelling, nuclear reaction modelling, and others. The use of data mining in discovery science follows a general trend of increasing use of computers and computational theory in all fields of science, and newer methods of data mining employ specialised machine learning algorithms for automated hypothesis forming and automated theorem proving.
== Applications ==
While computational methods are gaining interest, there is a decline in efforts to support critical care through basic and translational science, i.e., forms of discovery science which are essential for advancing understanding of pathophysiology. A loss of interest in basic and translational science may lead to a failure to discover and develop new therapies, which could have an impact on the critically ill. Within critical care, there is an aim to renew emphasis on basic, translational science through platforms such as medical journals and conferences, as well as the critical care medical curricula. Advances in discovery-based science thereby underlie key discoveries and development in medicine, constituting a 'pipeline' for leading-edge medical development.
=== Medicine ===
According to the AACR Cancer Progress Report 2021, discovery science has the potential to drive clinical breakthroughs. Since discovery science underlies key discoveries and development of new therapies for medicine, it remains important for advancing critical care. Numerous discoveries have increased life span and productivity, and decreased health-related costs, thereby revolutionising medical care. Resultantly, return on investment for discovery science has proven to be high. For example, its combination of computational methods with knowledge on inflammatory and genomic pathways has resulted in optimised clinical trials. Ultimately, discovery science is currently enabling a transition to the era of personalised medicine for treating complex syndromes, e.g., sepsis and ARDS. With a robust infrastructure, discovery science can resultantly revolutionise medical care and biological research.
=== Genomics ===
Discovery science has converged with clinical medicine and cancer genomics, and this convergence has been accelerated by recent advances in genome technologies and genomic information. The effect of cancer genomics has been noticeable in every area of cancer research. The majority of successful applications of genomic knowledge in today's clinical medicine involves a wealth of knowledge which has been gathered by a broad range of research and decades of work. Biological insights are required to inform drug discovery and to set a clear clinical path for development.
Historically, acquisition of such knowledge through functional and mechanistic studies has been uncoordinated, random, and inefficient. The process of moving from cancer genomic discoveries to personalised medicine involves some major scientific, logistical and regulatory hurdles. This includes patient consent, sample acquisition, clinical annotation and study design, all of which can lead to data generation and computational analyses. Additionally, functional and mechanistic studies remain a challenge, which can lead to drug and biomarker discovery and development, commercial challenges and genomics-informed clinical trials. Importantly, these key scientific challenges are interdependent with each other. Directed and streamlined approaches are sought to be developed for a rapid generation of biological discoveries, which can allow for cancer genomic discoveries to translate to the clinic. Delivering personalised cancer medicine benefits from traditional, unconstrained and non-directed academic exploration, with the goal of directing scientific inquiry to convert genomic discovery to diagnostic and therapeutic targets.
=== Proteomics ===
Another example of discovery science is proteomics, a technology-driven and technology limited discovery science. Technologies for proteomic analysis provide information that is useful in discovery science. Proteome analysis as a discovery science is applicable in biotechnology, e.g., it assists in 1) the discovery of biochemical pathways which can identify targets for therapies, 2) developing new processes for manufacturing biological materials, 3) monitoring manufacturing processes for the purpose of quality control, and 4) developing diagnostic tests and efficacious treatment strategies for clinical diseases. In the context of proteomics, current life-science research remains technology-limited, however, recent available tools have assisted in evolving such research from being hypothesis-driven to discovery-driven.
=== Hydrology ===
Field hydrology has experienced a decline in progress due to a change from discovery-based field work to the gathering of data for modal parameterisation. In field hydrology, models are not any more useful than an understanding of how systems work, and discovery science allows for this understanding. Several important examples of field-based inquiry and discovery have taken place in field hydrology. These include: identifying spatial patterns of soil moisture and how they relate to topography; interrogating such data through the use of geostatistics; and discovering the importance of macropore flow and hydrological connectivity. Some discovery-based questions that have been asked in field hydrology include 1) determining which parts of the watershed are most important in determining water delivery to the channel, 2) how the presence of 'old' water can be explained by groundwater travelling into the stream, and 3) how there can be an explanation for flashy hydrographs when there is no overland flow visible. Therefore, there is a need for discovery science in field hydrology, despite any unusual hydrological hypotheses that are formed.
=== Psychology ===
An example of discovery science being enhanced for human brain function can be seen in the 1000 Functional Connectomes Project (FCP). This project was launched in 2009 as a way of generating and collecting functional magnetic resonance imaging (fMRI) data from over 1,000 individuals. Similarly to decoding the human genome, the mapping of human brain function presents challenges to the functional neuroimaging community. For the first phase of discovery science, it is necessary to accumulate and share large-scale datasets for data mining. Traditionally, the neuroimaging community within psychology has focused on task-based and hypothesis-driven approaches, however, a powerful tool for discovery science has emerged in the form of resting-state functional MRI (R-fMRI). The potential of discovery science remains vast, e.g. 1) helping with decision-making and guiding clinical diagnoses by developing objective measures of brain functional integrity, 2) assessing the level of efficacy of treatment interventions, and 3) tracking responses to treatment. Among the scientific community, recruiting participation and achieving collaboration from the broad population is essential for successfully implementing discovery-based science in the context of human brain function.
== Methodology ==
Discovery-based methodologies are often viewed in contrast to traditional scientific practice, where hypotheses are formed before close examination of experimental data. However, from a philosophical perspective where all or most of the observable "low-hanging fruit" has already been plucked, examining the phenomenological world more closely than the senses alone (even augmented senses, e.g. via microscopes, telescopes, bifocals etc.) opens a new source of knowledge for hypothesis formation. This process is also known as inductive reasoning or the use of specific observations to make generalisations.
Discovery science is usually a complex process, and consequently does not follow a simple linear cause and effect pattern. This means that outcomes are uncertain, and it is expected to have disappointing results as a fundamental part of discovery science. In particular, this may apply to medicine for the critically ill, where disease syndromes may be complex and multi-factorial. In psychiatry, studying complex relationships between brain and behaviour requires a large-scale science. This calls for a need to conceptually switch from hypothesis-driven studies to hypothesis-generating research which is discovery-based. Normally, discovery-based approaches for research are initially hypothesis-free, however, hypothesis testing can be elevated to a new level that effectively supports traditional hypothesis-driven studies. Researchers hope that combining integrative analyses of data from a range of different levels can result in new classification approaches to enable personalised interventions. Some biologists, such as Leroy Hood, have suggested that the model of ‘discovery science’ is a model which certain research fields are heading towards. For example, it is believed that more information about gene function can be discovered, through the evolution of data-mining tools.
Discovery-based approaches are often referred to as “big data” approaches, because of the large-scale datasets that they involve analyses of. Big data includes large-scale homogenous study designs and highly variant datasets, and can be further divided into different kinds of datasets. For example, in neuropsychiatric studies, big data can be categorised as ‘broad’ or ‘deep’ data. Broad data is complex and heterogenous, as it is collected from multiple sources (e.g., labs and institutions) and uses different kinds of standards. On the other hand, deep data is collected at multiple levels, e.g., from genes to molecules, cells, circuits, behaviours, and symptoms. Broad data allows for population level inferences to be made; deep data is required for personalised medicine. However, combining broad and deep data and storing them in large-scale databases makes it practically impossible to rely on traditional statistical approaches. Instead, the use of discovery-based big data approaches can allow for the generation of hypotheses and offer an analytical tool with high-throughput for pattern recognition and data mining. It is in this way that discovery-based approaches can provide insight into causes and mechanisms of the area of study.
Although discovery-based and data-driven big data approaches can inform understanding of mechanisms behind the topic of concern, the success of these approaches depends on integrated analyses of the various types of relevant data, and the resultant insight provided. For example, when researching psychiatric dysfunction, it is important to integrate vast and complex data such as brain imaging, genomic data and behavioural data, to uncover any brain-behaviour connections that are relevant to psychiatric dysfunction. Therefore, there are challenges to integrating data and developing mining tools. Furthermore, validation of results is a big challenge for discovery-based science. Although it is possible for results to be statistically validated by independent datasets, tests of functionality affect ultimate validation. Collaborative efforts are therefore critical for success.
== References ==
Chen, J.; Call, G. B.; Beyer, E.; Bui, C.; Cespedes, A.; Chan, A.; Chan, J .; Chan, S.; Chhabra, A. (February 2005). "Discovery-Based Science Education: Functional Genomic Dissection in Drosophila by Undergraduate Researchers". PLOS Biology. 3 (2): e59. doi:10.1371/journal.pbio.0030059. PMC 548953. PMID 15719063. | Wikipedia/Discovery_science |
Medical diagnosis (abbreviated Dx, Dx, or Ds) is the process of determining which disease or condition explains a person's symptoms and signs. It is most often referred to as a diagnosis with the medical context being implicit. The information required for a diagnosis is typically collected from a history and physical examination of the person seeking medical care. Often, one or more diagnostic procedures, such as medical tests, are also done during the process. Sometimes the posthumous diagnosis is considered a kind of medical diagnosis.
Diagnosis is often challenging because many signs and symptoms are nonspecific. For example, redness of the skin (erythema), by itself, is a sign of many disorders and thus does not tell the healthcare professional what is wrong. Thus differential diagnosis, in which several possible explanations are compared and contrasted, must be performed. This involves the correlation of various pieces of information followed by the recognition and differentiation of patterns. Occasionally the process is made easy by a sign or symptom (or a group of several) that is pathognomonic.
Diagnosis is a major component of the procedure of a doctor's visit. From the point of view of statistics, the diagnostic procedure involves classification tests.
== Medical uses ==
A diagnosis, in the sense of diagnostic procedure, can be regarded as an attempt at classification of an individual's condition into separate and distinct categories that allow medical decisions about treatment and prognosis to be made. Subsequently, a diagnostic opinion is often described in terms of a disease or other condition. (In the case of a wrong diagnosis, however, the individual's actual disease or condition is not the same as the individual's diagnosis.) A total evaluation of a condition is often termed a diagnostic workup.
A diagnostic procedure may be performed by various healthcare professionals such as a physician, physiotherapist, dentist, podiatrist, optometrist, nurse practitioner, healthcare scientist or physician assistant. This article uses diagnostician as any of these person categories.
A diagnostic procedure (as well as the opinion reached thereby) does not necessarily involve elucidation of the etiology of the diseases or conditions of interest, that is, what caused the disease or condition. Such elucidation can be useful to optimize treatment, further specify the prognosis or prevent recurrence of the disease or condition in the future.
The initial task is to detect a medical indication to perform a diagnostic procedure. Indications include:
Detection of any deviation from what is known to be normal, such as can be described in terms of, for example, anatomy (the structure of the human body), physiology (how the body works), pathology (what can go wrong with the anatomy and physiology), psychology (thought and behavior) and human homeostasis (regarding mechanisms to keep body systems in balance). Knowledge of what is normal and measuring of the patient's current condition against those norms can assist in determining the patient's particular departure from homeostasis and the degree of departure, which in turn can assist in quantifying the indication for further diagnostic processing.
A complaint expressed by a patient.
The fact that a patient has sought a diagnostician can itself be an indication to perform a diagnostic procedure. For example, in a doctor's visit, the physician may already start performing a diagnostic procedure by watching the gait of the patient from the waiting room to the doctor's office even before she or he has started to present any complaints.
Even during an already ongoing diagnostic procedure, there can be an indication to perform another, separate, diagnostic procedure for another, potentially concomitant, disease or condition. This may occur as a result of an incidental finding of a sign unrelated to the parameter of interest, such as can occur in comprehensive tests such as radiological studies like magnetic resonance imaging or blood test panels that also include blood tests that are not relevant for the ongoing diagnosis.
== Procedure ==
General components which are present in a diagnostic procedure in most of the various available methods include:
Complementing the already given information with further data gathering, which may include questions of the medical history (potentially from other people close to the patient as well), physical examination and various diagnostic tests. A diagnostic test is any kind of medical test performed to aid in the diagnosis or detection of disease. Diagnostic tests can also be used to provide prognostic information on people with established disease.
Processing of the answers, findings or other results. Consultations with other providers and specialists in the field may be sought.
There are a number of methods or techniques that can be used in a diagnostic procedure, including performing a differential diagnosis or following medical algorithms.: 198 In reality, a diagnostic procedure may involve components of multiple methods.: 204
=== Differential diagnosis ===
The method of differential diagnosis is based on finding as many candidate diseases or conditions as possible that can possibly cause the signs or symptoms, followed by a process of elimination or at least of rendering the entries more or less probable by further medical tests and other processing, aiming to reach the point where only one candidate disease or condition remains as probable. The result may also remain a list of possible conditions, ranked in order of probability or severity. Such a list is often generated by computer-aided diagnosis systems.
The resultant diagnostic opinion by this method can be regarded more or less as a diagnosis of exclusion. Even if it does not result in a single probable disease or condition, it can at least rule out any imminently life-threatening conditions.
Unless the provider is certain of the condition present, further medical tests, such as medical imaging, are performed or scheduled in part to confirm or disprove the diagnosis but also to document the patient's status and keep the patient's medical history up to date.
If unexpected findings are made during this process, the initial hypothesis may be ruled out and the provider must then consider other hypotheses.
=== Pattern recognition ===
In a pattern recognition method the provider uses experience to recognize a pattern of clinical characteristics.: 198, It is mainly based on certain symptoms or signs being associated with certain diseases or conditions, not necessarily involving the more cognitive processing involved in a differential diagnosis.
This may be the primary method used in cases where diseases are "obvious", or the provider's experience may enable him or her to recognize the condition quickly. Theoretically, a certain pattern of signs or symptoms can be directly associated with a certain therapy, even without a definite decision regarding what is the actual disease, but such a compromise carries a substantial risk of missing a diagnosis which actually has a different therapy so it may be limited to cases where no diagnosis can be made.
=== Diagnostic criteria ===
The term diagnostic criteria designates the specific combination of signs and symptoms, and test results that the clinician uses to attempt to determine the correct diagnosis.
Some examples of diagnostic criteria, also known as clinical case definitions, are:
Amsterdam criteria for hereditary nonpolyposis colorectal cancer
McDonald criteria for multiple sclerosis
ACR criteria for systemic lupus erythematosus
Centor criteria for strep throat
=== Clinical decision support system ===
Clinical decision support systems are interactive computer programs designed to assist health professionals with decision-making tasks. The clinician interacts with the software utilizing both the clinician's knowledge and the software to make a better analysis of the patients data than either human or software could make on their own. Typically the system makes suggestions for the clinician to look through and the clinician picks useful information and removes erroneous suggestions. Some programs attempt to do this by replacing the clinician, such as reading the output of a heart monitor. Such automated processes are usually deemed a "device" by the FDA and require regulatory approval. In contrast, clinical decision support systems that "support" but do not replace the clinician are deemed to be "Augmented Intelligence" if it meets the FDA criteria that (1) it reveals the underlying data, (2) reveals the underlying logic, and (3) leaves the clinician in charge to shape and make the decision.
=== Other diagnostic procedure methods ===
Other methods that can be used in performing a diagnostic procedure include:
Usage of medical algorithms
An "exhaustive method", in which every possible question is asked and all possible data is collected.: 198
== Adverse effects ==
Diagnosis problems are the dominant cause of medical malpractice payments, accounting for 35% of total payments in a study of 25 years of data and 350,000 claims.
=== Overdiagnosis ===
Overdiagnosis is the diagnosis of "disease" that will never cause symptoms or death during a patient's lifetime. It is a problem because it turns people into patients unnecessarily and because it can lead to economic waste (overutilization) and treatments that may cause harm. Overdiagnosis occurs when a disease is diagnosed correctly, but the diagnosis is irrelevant. A correct diagnosis may be irrelevant because treatment for the disease is not available, not needed, or not wanted.
=== Errors ===
Most people will experience at least one diagnostic error in their lifetime, according to a 2015 report by the National Academies of Sciences, Engineering, and Medicine.
Causes and factors of error in diagnosis are:
the manifestation of disease are not sufficiently noticeable
a disease is omitted from consideration
too much significance is given to some aspect of the diagnosis
the condition is a rare disease with symptoms suggestive of many other conditions
the condition has a rare presentation
=== Lag time ===
When making a medical diagnosis, a lag time is a delay in time until a step towards diagnosis of a disease or condition is made. Types of lag times are mainly:
Onset-to-medical encounter lag time, the time from onset of symptoms until visiting a health care provider
Encounter-to-diagnosis lag time, the time from first medical encounter to diagnosis
Lag time due to delays in reading x-rays have been cited as a major challenge in care delivery. The Department of Health and Human Services has reportedly found that interpretation of x-rays is rarely available to emergency room physicians prior to patient discharge.
Long lag times are often called "diagnostic odyssey".
== History ==
The first recorded examples of medical diagnosis are found in the writings of Imhotep (2630–2611 BC) in ancient Egypt (the Edwin Smith Papyrus). A Babylonian medical textbook, the Diagnostic Handbook written by Esagil-kin-apli (fl.1069–1046 BC), introduced the use of empiricism, logic and rationality in the diagnosis of an illness or disease. Traditional Chinese Medicine, as described in the Yellow Emperor's Inner Canon or Huangdi Neijing, specified four diagnostic methods: inspection, auscultation-olfaction, inquiry and palpation. Hippocrates was known to make diagnoses by tasting his patients' urine and smelling their sweat.
== Word ==
Medical diagnosis or the actual process of making a diagnosis is a cognitive process. A clinician uses several sources of data and puts the pieces of the puzzle together to make a diagnostic impression. The initial diagnostic impression can be a broad term describing a category of diseases instead of a specific disease or condition. After the initial diagnostic impression, the clinician obtains follow up tests and procedures to get more data to support or reject the original diagnosis and will attempt to narrow it down to a more specific level. Diagnostic procedures are the specific tools that the clinicians use to narrow the diagnostic possibilities.
The plural of diagnosis is diagnoses. The verb is to diagnose, and a person who diagnoses is called a diagnostician.
=== Etymology ===
The word diagnosis is derived through Latin from the Greek word διάγνωσις (diágnōsis) from διαγιγνώσκειν (diagignṓskein), meaning "to discern, distinguish".
== Society and culture ==
=== Social context ===
Diagnosis can take many forms. It might be a matter of naming the disease, lesion, dysfunction or disability. It might be a management-naming or prognosis-naming exercise. It may indicate either degree of abnormality on a continuum or kind of abnormality in a classification. It is influenced by non-medical factors such as power, ethics and financial incentives for patient or doctor. It can be a brief summation or an extensive formulation, even taking the form of a story or metaphor. It might be a means of communication such as a computer code through which it triggers payment, prescription, notification, information or advice. It might be pathogenic or salutogenic. It is generally uncertain and provisional.
Once a diagnostic opinion has been reached, the provider is able to propose a management plan, which will include treatment as well as plans for follow-up. From this point on, in addition to treating the patient's condition, the provider can educate the patient about the etiology, progression, prognosis, other outcomes, and possible treatments of her or his ailments, as well as providing advice for maintaining health.
A treatment plan is proposed which may include therapy and follow-up consultations and tests to monitor the condition and the progress of the treatment, if needed, usually according to the medical guidelines provided by the medical field on the treatment of the particular illness.
Relevant information should be added to the medical record of the patient.
A failure to respond to treatments that would normally work may indicate a need for review of the diagnosis.
Nancy McWilliams identifies five reasons that determine the necessity for diagnosis:
diagnosis for treatment planning;
information contained in it related to prognosis;
protecting interests of patients;
a diagnosis might help the therapist to empathize with his patient;
might reduce the likelihood that some fearful patients will go-by the treatment.
== Types ==
Sub-types of diagnoses include:
Clinical diagnosis
A diagnosis made on the basis of medical signs and reported symptoms, rather than diagnostic tests
Laboratory diagnosis
A diagnosis based significantly on laboratory reports or test results, rather than the physical examination of the patient. For instance, a proper diagnosis of infectious diseases usually requires both an examination of signs and symptoms, as well as laboratory test results and characteristics of the pathogen involved.
Radiology diagnosis
A diagnosis based primarily on the results from medical imaging studies. Greenstick fractures are common radiological diagnoses.
Electrography diagnosis
A diagnosis based on measurement and recording of electrophysiologic activity.
Endoscopy diagnosis
A diagnosis based on endoscopic inspection and observation of the interior of a hollow organ or cavity of the body.
Tissue diagnosis
A diagnosis based on the macroscopic, microscopic, and molecular examination of tissues such as biopsies or whole organs. For example, a definitive diagnosis of cancer is made via tissue examination by a pathologist.
Principal diagnosis
The single medical diagnosis that is most relevant to the patient's chief complaint or need for treatment. Many patients have additional diagnoses.
Admitting diagnosis
The diagnosis given as the reason why the patient was admitted to the hospital; it may differ from the actual problem or from the discharge diagnoses, which are the diagnoses recorded when the patient is discharged from the hospital.
Differential diagnosis
A process of identifying all of the possible diagnoses that could be connected to the signs, symptoms, and lab findings, and then ruling out diagnoses until a final determination can be made.
Diagnostic criteria
Designates the combination of signs, symptoms, and test results that the clinician uses to attempt to determine the correct diagnosis. They are standards, normally published by international committees, and they are designed to offer the best sensitivity and specificity possible, respect the presence of a condition, with the state-of-the-art technology.
Prenatal diagnosis
Diagnosis work done before birth
Diagnosis of exclusion
A medical condition whose presence cannot be established with complete confidence from history, examination or testing. Diagnosis is therefore by elimination of all other reasonable possibilities.
Dual diagnosis
The diagnosis of two related, but separate, medical conditions or comorbidities. The term almost always referred to a diagnosis of a serious mental illness and a substance use disorder, however, the increasing prevalence of genetic testing has revealed many cases of patients with multiple concomitant genetic disorders.
Self-diagnosis
The diagnosis or identification of a medical conditions in oneself. Self-diagnosis is very common.
Remote diagnosis
A type of telemedicine that diagnoses a patient without being physically in the same room as the patient.
Nursing diagnosis
Rather than focusing on biological processes, a nursing diagnosis identifies people's responses to situations in their lives, such as a readiness to change or a willingness to accept assistance.
Computer-aided diagnosis
Providing symptoms allows the computer to identify the problem and diagnose the user to the best of its ability. Health screening begins by identifying the part of the body where the symptoms are located; the computer cross-references a database for the corresponding disease and presents a diagnosis.
Overdiagnosis
The diagnosis of "disease" that will never cause symptoms, distress, or death during a patient's lifetime
Wastebasket diagnosis
A vague, or even completely fake, medical or psychiatric label given to the patient or to the medical records department for essentially non-medical reasons, such as to reassure the patient by providing an official-sounding label, to make the provider look effective, or to obtain approval for treatment. This term is also used as a derogatory label for disputed, poorly described, overused, or questionably classified diagnoses, such as pouchitis and senility, or to dismiss diagnoses that amount to overmedicalization, such as the labeling of normal responses to physical hunger as reactive hypoglycemia.
Retrospective diagnosis
The labeling of an illness in a historical figure or specific historical event using modern knowledge, methods and disease classifications.
== See also ==
=== Lists ===
List of diagnostic classification and rating scales used in psychiatry
List of diseases
List of disorders
List of medical symptoms
Category:Diseases
== References ==
== External links ==
Media related to Medical diagnosis at Wikimedia Commons | Wikipedia/Medical_diagnosis |
Big science is a term used by scientists and historians of science to describe a series of changes in science which occurred in industrial nations during and after World War II, as scientific progress increasingly came to rely on large-scale projects usually funded by national governments or groups of governments. Individual or small group efforts, or small science, are still relevant today as theoretical results by individual authors may have a significant impact, but very often the empirical verification requires experiments using constructions, such as the Large Hadron Collider, costing between $5 and $10 billion.
== Development ==
While science and technology have always been important to and driven by warfare, the increase in military funding of science following the second World War was on a scale wholly unprecedented. James Conant, in a 1941 letter to Chemical Engineering News, said that World War II "is a physicist's war rather than a chemist's," a phrase that was cemented in the vernacular in post-war discussion of the role that those scientists played in the development of new weapons and tools, notably the proximity fuse, radar, and the atomic bomb. The bulk of these last two activities took place in a new form of research facility: the government-sponsored laboratory, employing thousands of technicians and scientists, managed by universities (in this case, the University of California and the Massachusetts Institute of Technology).
The need of a strong scientific research establishment was obvious in the shadow of the first atomic weapons to any country seeking to play a prominent role in world affairs. After the success of the Manhattan Project, governments became the chief patron of science, and the character of the scientific establishment underwent several key changes. This was especially marked in the United States and the Soviet Union during the Cold War, but also to a lesser extent in many other countries.
== Definitions ==
"Big science" usually implies one or more of these specific characteristics:
Big budgets: No longer required to rely on philanthropy or industry, scientists were able to use budgets on an unprecedented scale for basic research.
Big staffs: Similarly, the number of practitioners of science on any one project grew as well, creating difficulty, and often controversy, in the assignment of credit for scientific discoveries (the Nobel Prize system, for example, allows awarding only three individuals in any one topic per year, based on a 19th-century model of the scientific enterprise).
Big machines: Ernest Lawrence's cyclotron at his Radiation Laboratory in particular ushered in an era of massive machines (requiring massive staffs and budgets) as the tools of basic scientific research. The use of many machines, such as the many sequencers used during the Human Genome Project, might also fall under this definition.
Big laboratories: Because of the increase in cost to do basic science (with the increase of large machines), centralization of scientific research in large laboratories (such as Lawrence Berkeley National Laboratory or CERN) has become a cost-effective strategy, though questions over facility access have become prevalent.
Towards the end of the 20th century, not only projects in basic physics and astronomy, but also in life sciences became big sciences, such as the massive Human Genome Project. The heavy investment of government and industrial interests into academic science has also blurred the line between public and private research, where entire academic departments, even at public universities, are often financed by private companies. Not all Big Science is related to the military concerns which were at its origins.
== Criticism ==
The era of Big Science has provoked criticism that it undermines the basic principles of the scientific method. Increased government funding has often meant increased military funding, which some claim subverts the Enlightenment-era ideal of science as a pure quest for knowledge. For example, historian Paul Forman has argued that during World War II and the Cold War, the massive scale of defense-related funding prompted a shift in physics from basic to applied research.
Many scientists also complain that the requirement for increased funding makes a large part of the scientific activity filling out grant requests and other budgetary bureaucratic activity, and the intense connections between academic, governmental, and industrial interests have raised the question of whether scientists can be completely objective when their research contradicts the interests and intentions of their benefactors.
In addition, widespread sharing of scientific knowledge is necessary for rapid progress for both basic and applied sciences. However the sharing of data can be impeded for a number of reasons. For example, scientific findings can be classified by military interests or patented by corporate ones. Grant competitions, while they stimulate interest in a topic, can also increase secretiveness among scientists because application evaluators may value uniqueness more than incremental, collaborative inquiry.
== Historiography of Big Science ==
The popularization of the term "Big Science" is usually attributed to an article by Alvin M. Weinberg, then director of Oak Ridge National Laboratory, published in Science in 1961. This was a response to Dwight D. Eisenhower's farewell address, in which the departing U.S. president warned against the dangers of what he called the "military–industrial complex" and the potential "domination of the nation's scholars by Federal employment, project allocations, and the power of money". Weinberg compared the large-scale enterprise of science in the 20th century to the wonders of earlier civilization (the pyramids, the palace of Versailles):
When history looks at the 20th century, she will see science and technology as its theme; she will find in the monuments of Big Science—the huge rockets, the high-energy accelerators, the high-flux research reactors—symbols of our time just as surely as she finds in Notre Dame a symbol of the Middle Ages. ... We build our monuments in the name of scientific truth, they built theirs in the name of religious truth; we use our Big Science to add to our country's prestige, they used their churches for their cities' prestige; we build to placate what ex-President Eisenhower suggested could become a dominant scientific caste, they built to please the priests of Isis and Osiris.
Weinberg's article addressed criticisms of the way in which the era of Big Science could negatively affect science — such as astronomer Fred Hoyle's contention that excessive money for science would only make science fat and lazy — and encouraged, in the end, limiting Big Science only to the national laboratory system and preventing its incursion into the university system.
Since Weinberg's article there have been many historical and sociological studies on the effects of Big Science both in and out of the laboratory. Soon after that article, Derek J. de Solla Price gave a series of lectures that were published in 1963 as Little Science, Big Science. The book describes the historical and sociological transition from "small science" to "big science" and the qualitative differences between the two; it inspired the field of scientometrics as well as new perspectives on large-scale science in other fields.
The Harvard historian Peter Galison has written several books addressing the formation of big science. Major themes include the evolution of experimental design, from table-top experiments to today's large-scale collider projects; accompanying changes in standards of evidence; and discourse patterns across researchers whose expertise only partially overlaps. Galison introduced the notion of "trading zones," borrowed from the sociolinguistic study of pidgins, to characterize how such groups learn to interact.
Other historians have postulated many "precursors" to Big Science in earlier times: the Uraniborg of Tycho Brahe (in which massive astronomical instruments were made, often with little practical purpose) and the large cryogenics laboratory established by Heike Kamerlingh Onnes in 1904 have been cited as early examples of Big Science.
== References ==
== Further reading ==
Galison, Peter; Hevly, Bruce William, eds. (1994). Big Science: The Growth of Large Scale Research. Stanford University Press. ISBN 978-0-8047-1879-0.
Galison, Peter (1997). Image and Logic: A Material Culture of Microphysics. University of Chicago Press. ISBN 0-226-27917-0.
Kevles, Daniel (1971). The Physicists: the History of a Scientific Community in Modern America. Harvard University Press. ISBN 978-0-674-66656-6.
Wiener, Norbert (1988). The Human Use of Human Beings. Da Capo Press. ISBN 0-306-80320-8. | Wikipedia/Big_science |
Energy quality is a measure of the ease with which a form of energy can be converted to useful work or to another form of energy: i.e. its content of thermodynamic free energy. A high quality form of energy has a high content of thermodynamic free energy, and therefore a high proportion of it can be converted to work; whereas with low quality forms of energy, only a small proportion can be converted to work, and the remainder is dissipated as heat. The concept of energy quality is also used in ecology, where it is used to track the flow of energy between different trophic levels in a food chain and in thermoeconomics, where it is used as a measure of economic output per unit of energy. Methods of evaluating energy quality often involve developing a ranking of energy qualities in hierarchical order.
== Examples: Industrialization, Biology ==
The consideration of energy quality was a fundamental driver of industrialization from the 18th through 20th centuries. Consider for example the industrialization of New England in the 18th century. This refers to the construction of textile mills containing power looms for weaving cloth. The simplest, most economical and straightforward source of energy was provided by water wheels, extracting energy from a millpond behind a dam on a local creek. If another nearby landowner also decided to build a mill on the same creek, the construction of their dam would lower the overall hydraulic head to power the existing waterwheel, thus hurting power generation and efficiency. This eventually became an issue endemic to the entire region, reducing the overall profitability of older mills as newer ones were built. The search for higher quality energy was a major impetus throughout the 19th and 20th centuries. For example, burning coal to make steam to generate mechanical energy would not have been imaginable in the 18th century; by the end of the 19th century, the use of water wheels was long outmoded. Similarly, the quality of energy from electricity offers immense advantages over steam, but did not become economic or practical until the 20th century.
The above example focused on the economic impacts of the exploitation of energy. A similar scenario plays out in nature and biology, where living organisms can extract energy of varying quality from nature, ultimately driven by solar energy as the primary driver of thermodynamic disequilibrium on Earth. The ecological balance of ecosystems is predicated on the energy flows through the system. For example, rainwater drives the erosion of rocks, which liberates chemicals that can be used as nutrients; these are taken up by plankton, using solar energy to grow and thrive; whales obtain energy by eating plankton, thus indirectly using solar energy as well, but this time in a much more concentrated and higher quality form.
Water wheels are also driven by rainwater, via the solar evaporation-condensation water cycle; thus ultimately, industrial cloth-making was driven by the day-night cycle of solar irradiation. This is a holistic view of energy sources as a system-in-the-large. Thus, discussions of energy quality can sometimes be found in the Humanities, such as dialectics, Marxism and postmodernism. This is effectively because disciplines such as economics failed to recognize the thermodynamic inputs into the economy (now recognized as thermoeconomics), while disciplines such as physics and engineering were unable to address either the economic impacts of human activity, or the impacts of thermodynamic flows in biological ecosystems. Thus, the broad-stroke, global system-in-the-large discussions were taken up by those best trained for the nebulous, non-specific reasoning that such complex systems require. The resulting mismatch of vocabulary and outlook across disciplines can lead to considerable contention.
== History ==
According to Ohta (1994, pp. 90–91) the ranking and scientific analysis of energy quality was first proposed in 1851 by William Thomson under the concept of "availability". This concept was continued in Germany by Z. Rant, who developed it under the title, "die Exergie" (the exergy). It was later continued and standardised in Japan. Exergy analysis now forms a common part of many industrial and ecological energy analyses. For example, I.Dincer and Y.A. Cengel (2001, p. 132) state that energy forms of different qualities are now commonly dealt with in steam power engineering industry. Here the "quality index" is the relation of exergy to the energy content (Ibid.). However energy engineers were aware that the notion of heat quality involved the notion of value – for example A. Thumann wrote, "The essential quality of heat is not the amount but rather its 'value'" (1984, p. 113) – which brings into play the question of teleology and wider, or ecological-scale goal functions. In an ecological context S.E. Jorgensen and G.Bendoricchio say that exergy is used as a goal function in ecological models, and expresses energy "with a built-in measure of quality like energy" (2001, p. 392).
== Energy quality evaluation methods ==
There appear to be two main kinds of methodology used for the calculation of energy quality. These can be classed as either receiver or donor methods. One of the main differences that distinguishes these classes is the assumption of whether energy quality can be upgraded in an energy transformation process.
Receiver methods: view energy quality as a measure and indicator of the relative ease with which energy converts from one form to another. That is, how much energy is received from a transformation or transfer process. For example, A. Grubler [1] used two types of indicators of energetic quality pars pro toto: the hydrogen/carbon (H/C) ratio, and its inverse, the carbon intensity of energy. Grubler used the latter as an indicator of relative environmental quality. However Ohta says that in multistage industrial conversion systems, such as a hydrogen production system using solar energy, the energy quality is not upgraded (1994, p. 125).
Donor methods: view energy quality as a measure of the amount of energy used in an energy transformation, and that goes into sustaining a product or service (H.T.Odum 1975, p. 3). That is how much energy is donated to an energy transformation process. These methods are used in ecological physical chemistry, and ecosystem evaluation. From this view, in contrast with that outlined by Ohta, energy quality is upgraded in the multistage trophic conversions of ecological systems. Here, upgraded energy quality has a greater capacity to feedback and control lower grades of energy quality. Donor methods attempt to understand the usefulness of an energetic process by quantifying the extent to which higher quality energy controls lower quality energy.
== Energy quality in physical-chemical science (direct energy transformations) ==
=== Constant energy form but variable energy flow ===
T. Ohta suggested that the concept of energy quality may be more intuitive if one considers examples where the form of energy remains constant but the amount of energy flowing, or transferred is varied. For instance if we consider only the inertial form of energy, then the energy quality of a moving body is higher when it moves with a greater velocity. If we consider only the heat form of energy, then a higher temperature has higher quality. And if we consider only the light form of energy then light with higher frequency has greater quality (Ohta 1994, p. 90). All these differences in energy quality are therefore easily measured with the appropriate scientific instrument.
=== Variable energy form, but constant energy flow ===
The situation becomes more complex when the form of energy does not remain constant. In this context Ohta formulated the question of energy quality in terms of the conversion of energy of one form into another, that is the transformation of energy. Here, energy quality is defined by the relative ease with which the energy transforms, from form to form.
If energy A is relatively easier to convert to energy B but energy B is relatively harder to convert to energy A, then the quality of energy A is defined as being higher than that of B. The ranking of energy quality is also defined in a similar way. (Ohta 1994, p. 90).
Nomenclature: Prior to Ohta's definition above, A. W. Culp produced an energy conversion table describing the different conversions from one energy to another. Culp's treatment made use of a subscript to indicate which energy form is being talked about. Therefore, instead of writing "energy A", like Ohta above, Culp referred to "Je", to specify electrical form of energy, where "J" refers to "energy", and the "e" subscript refers to electrical form of energy. Culp's notation anticipated Scienceman's (1997) later maxim that all energy should be specified as form energy with the appropriate subscript.
== Energy quality in biophysical economics (indirect energy transformations) ==
The notion of energy quality was also recognised in the economic sciences. In the context of biophysical economics energy quality was measured by the amount of economic output generated per unit of energy input (C.J. Cleveland et al. 2000). The estimation of energy quality in an economic context is also associated with embodied energy methodologies. Another example of the economic relevance of the energy quality concept is given by Brian Fleay. Fleay says that the "Energy Profit Ratio (EPR) is one measure of energy quality and a pivotal index for assessing the economic performance of fuels. Both the direct and indirect energy inputs embodied in goods and services must be included in the denominator." (2006; p. 10) Fley calculates the EPR as the energy output/energy input.
== Ranking energy quality ==
=== Energy abundance and relative transformation ease as measure of hierarchical rank and/or hierarchical position ===
Ohta sought to order energy form conversions according to their quality and introduced a hierarchical scale for ranking energy quality based on the relative ease of energy conversion (see table to right after Ohta, p. 90). It is evident that Ohta did not analyse all forms of energy. For example, water is left out of his evaluation. It is important to note that the ranking of energy quality is not determined solely with reference to the efficiency of the energy conversion. This is to say that the evaluation of "relative ease" of an energy conversion is only partly dependent on transformation efficiency. As Ohta wrote, "the turbine generator and the electric motor have nearly the same efficiency, therefore we cannot say which has the higher quality" (1994, p. 90). Ohta therefore also included, 'abundance in nature' as another criterion for the determination energy quality rank. For example, Ohta said that, "the only electrical energy which exists in natural circumstances is lightning, while many mechanical energies exist." (Ibid.). (See also table 1. in Wall's article for another example ranking of energy quality).
=== Transformity as an energy measure of hierarchical rank ===
Like Ohta, H.T.Odum also sought to order energy form conversions according to their quality, however his hierarchical scale for ranking was based on extending ecological system food chain concepts to thermodynamics rather than simply relative ease of transformation . For H.T.Odum energy quality rank is based on the amount of energy of one form required to generate a unit of another energy form. The ratio of one energy form input to a different energy form output was what H.T.Odum and colleagues called transformity: "the EMERGY per unit energy in units of emjoules per joule" (H.T.Odum 1988, p. 1135).
== See also ==
== References == | Wikipedia/Energy_quality |
Theory choice was a main problem in the philosophy of science in the early 20th century, and under the impact of the new and controversial theories of relativity and quantum physics, came to involve how scientists should choose between competing theories.
The classical answer would be to select the theory which was best verified, against which Karl Popper argued that competing theories should be subjected to comparative tests and the one chosen which survived the tests. If two theories could not, for practical reasons, be tested one should prefer the one with the highest degree of empirical content, said Popper in The Logic of Scientific Discovery.
Mathematician and physicist Henri Poincaré instead, like many others, proposed simplicity as a criterion. One should choose the mathematically simplest or most elegant approach. Many have sympathized with this view, but the problem is that the idea of simplicity is highly intuitive and even personal, and that no one has managed to formulate it in precise and acceptable terms.
Popper's solution was subsequently criticized by Thomas S. Kuhn in The Structure of Scientific Revolutions. He denied that competing theories (or paradigms) could be compared in the way that Popper had claimed, and substituted instead what can be briefly described as pragmatic success. This led to an intense discussion with Imre Lakatos and Paul Feyerabend the best known participants.
The discussion has continued, but no general and uncontroversial solution to the problem of formulating objective criteria to decide which is the best theory has so far been formulated. The main criteria usually proposed are to choose the theory which provides the best (and novel) predictions, the one with the highest explanatory potential, the one which offers better problems or the most elegant and simple one. Alternatively a theory may be preferable if it is better integrated into the rest of contemporary knowledge. | Wikipedia/Theory_choice |
Research funding is a term generally covering any funding for scientific research, in the areas of natural science, technology, and social science. Different methods can be used to disburse funding, but the term often connotes funding obtained through a competitive process, in which potential research projects are evaluated and only the most promising receive funding. It is often measured via Gross domestic expenditure on R&D (GERD).
Most research funding comes from two major sources: corporations (through research and development departments) and government (primarily carried out through universities and specialized government agencies; often known as research councils). A smaller amount of scientific research is funded by charitable foundations, especially in relation to developing cures for diseases such as cancer, malaria, and AIDS.
According to the Organisation for Economic Co-operation and Development (OECD), more than 60% of research and development in scientific and technical fields is carried out by industry, and 20% and 10% respectively by universities and government. Comparatively, in countries with less GDP such as Portugal and Mexico, the industry contribution is significantly lower. The government funding proportion in certain industries is higher, and it dominates research in social science and humanities. In commercial research and development, all but the most research-oriented corporations focus more heavily on near-term commercialization possibilities rather than "blue-sky" ideas or technologies (such as nuclear fusion).
== History ==
Conducting research requires funds. The funding trend for research has gone from a closed patronage system to which only few could contribute, to an open system with multiple funding possibilities.
In the early Zhou dynasty (-c. 6th century to 221 BCE), government officials used their resources to fund schools of thought of which they were patron. The bulk of their philosophies are still relevant, including Confucianism, Legalism and Taoism.
During the Mayan Empire (-c. 1200–1250), scientific research was funded for religious purposes. Research there developed a Venus Table, showing precise astronomical data about the position of Venus in the sky. In Cairo (-c. 1283), the Mamluk Sultan Qalawun funded a monumental hospital, patronizing the medical sciences over the religious sciences. Furthermore, Tycho Brahe was given an estate (-c. 1576 – 1580) by his royal patron King Frederik II, which was used to build Uraniborg, an early research institute.
=== The age of the academies ===
In 1700–1799, scientific academies became central creators of scientific knowledge. Funded by state sponsorship, academic societies were free to manage scientific developments. Membership was exclusive in terms of gender, race and class, but academies opened the world of research up beyond the traditional patronage system.
In 1799, Louis-Nicolas Robert patented the paper machine. When he quarreled over invention ownership, he sought financing from the Fourdrinier brothers. In 19th century Europe, businessmen financed the application of science to industry.
In the eighteenth and nineteenth centuries, as the pace of technological progress increased before and during the Industrial Revolution, most scientific and technological research was carried out by individual inventors using their own funds. A system of patents was developed to allow inventors a period of time (often twenty years) to commercialize their inventions and recoup a profit, although in practice many found this difficult.
The Manhattan Project (1942 – 1946) had cost $27 billion and employed 130,000 people, many of them scientists charged with producing the first nuclear weapons. In 1945, 70 scientists signed the Szilard petition, asking President Truman to make a demonstration of the power of the bomb before using it. Most of the signers lost their jobs in military research.
In the twentieth century, scientific and technological research became increasingly systematized, as corporations developed, and discovered that continuous investment in research and development could be a key element of competitive success. It remained the case, however, that imitation by competitors - circumventing or simply flouting patents, especially those registered abroad - was often just as successful a strategy for companies focused on innovation in matters of organization and production technique, or even in marketing.
In 2025, many funders make research outcomes transparent and accessible in data repositories or Open-access. Some researchers turn to crowdfunding in search of new projects to fund. Private and public foundations, governments, and others sponsor opportunities for researchers. As new funding sources become available, the research community grows and becomes accessible to a wider, and more diverse group of scientists.
== Methodology to measure science funding ==
The guidelines for R&D data collections are laid down in the Frascati Manual published by the OECD. In the publication, R&D denotes three type of activity: basic research, applied research and experimental development. This definition does not cover innovation but it may feed into the innovative process. Business sector innovation has a dedicated OECD manual.
The most frequently used measurement for R&D is Gross domestic expenditure on R&D (GERD). GERD is often represented in GERD-to-GDP ratios, as it allows for easier comparisons between countries. The data collection for GERD is based on reporting by performers. GERD differentiates according to the funding sector (business, enterprise, government, higher education, private non-profit, rest of the world) and the sector of performance (all funding sectors with the exception of rest of the world as GERD only measures activity within the territory of a country). The two may coincide for example when government funds government performed R&D.
Government funded science also may be measured by the Government budget appropriations and outlays for R&D (GBAORD/ GBARD). GBARD is a funder-based method, it denotes what governments committed to R&D (even if final payment might be different). GERD-source of funding-government and GBARD are not directly comparable. On data collection, GERD is performer based, GBARD is funder. The level of government considered also differs: GERD may include spending by all levels of the government (federal – state – local), whereas GBARD excludes the local level and often lacks state level data. On geographic coverage, GERD takes into account performance within the territory of a country whereas GBARD also payments to the Rest of the world.
Comparisons on the effectiveness of both the different sources of funding and sectors of performance as well as their interplay have been made. The analysis often boils down to whether public and private finance show crowding-in or crowding-out patterns.
== Funding types: public and private ==
=== Public/State Funding ===
Public funding refers to activities financed by tax-payers money. This is primarily the case when the source of funds is channeled through government agencies. Higher education institutions are usually not completely publicly financed as they charge tuition fees and may receive funds from non-public sources.
==== Rationale for funding ====
R&D is a costly, and long-term investment to which disruptions are harmful.
The public sector has multiple reasons to fund science. The private sector is said to focus on the closer to the market stage of R&D policy, where appropriability hence private returns are high. Basic research is weak on appropriability and so remains risky and under-financed. Consequently, although governmental sponsorship of research may provide support across the R&D value chain, it is often characterized as a market failure induced intervention. Market incentives to invest in early-stage research are low. The theory of public goods seconds this argument. Publicly funded research often supports research fields where social rate of return may be higher than private rate of return. Appropriability potential is the potential for an entity to capture the value of an innovation or research outcome. The general free rider problem of public goods is a threat especially in case of global public goods such as climate change research, which may lower incentives to invest by both the private sector but also other governments.
In endogenous growth theories, R&D contributes to growth. Some have depicted this relationship in the inverse, claiming that growth drives innovation. As of 2013, science workers applying their (tacit) knowledge may be considered an economic driver. When this knowledge and/or human capital emigrates, countries face the so-called brain–drain. Science policy can assist to avoid this as large shares of governmental R&D is spent on researchers and supporting staff personnel salaries. In this sense, science funding is not only discretionary spending but also has elements of entitlement spending.
R&D funded and especially performed by the State may allow greater influence over its direction. This is particularly important in the case of R&D contributing to public goods. However, the ability of governments have been criticized over whether they are best positioned to pick winners and losers. In the EU, dedicated safeguards have been enacted under a dedicated form of competition law called State Aid. State Aid safeguards business activities from governmental interventions. This invention was largely driven by the German ordoliberal school as to eliminate state subsidies advocated by the French dirigiste. Threats to global public goods has refueled the debate on the role of governments beyond a mere market failure fixer, the so-called mission-driven policies.
==== Funding modalities ====
Governments may fund science through different instruments such as: direct subsidies, tax credits, loans, financial instruments, regulatory measures, public procurement etc. While direct subsidies have been the prominent instrument to fund business R&D, since the 2008 financial crisis a shift has taken place in OECD countries in the direction of tax breaks. The explanation seems to lay in the theoretical argument that firms know better, and in the practical benefit of lower administrative burden of such schemes. Depending on the funding type, different modalities to distribute the research funds may be used. For regulatory measures, often the competition/antitrust authorities will rule on exemptions. In case of block funding the funds may be directly allocated to given institutions such as higher education institutions with relative autonomy over their use. For competitive grants, governments are often assisted by research councils to distribute the funds. Research councils are (usually public) bodies that provide research funding in the form of research grants or scholarships. These include arts councils and research councils for the funding of science.
==== List of research councils ====
An incomplete list of national and international pan-disciplinary public research councils:
==== Conditionality ====
In addition to project deliverables, funders also increasingly introduce new eligibility requirements alongside traditional ones such as research integrity/ethics.
The 2016 Open Science movement, tied funding increasingly tied to data management plans and making data FAIR. The Open Science requirement complements Open Access mandates which in 2025 are widespread.
The gender dimension also gained ground in recent years. The European Commission mandates research applicants to adopt gender equality plans across their organization. The UK Research and Innovation Global Challenges Research Fund mandates a gender equality statement.
As of 2022, the European Commission also introduced a "Do No Significant Harm" principle to the Framework Program which aims to curb the environmental footprint of scientific projects. "Do No Significant Harm" has been criticized as coupled with other eligibility requirements it is often characterized as red-tape. Since 2020, European Commission has been trying to simplify the Framework Program with limited success. Simplification attempts were also taken by the UK Research and Innovation.
==== Process ====
Often scientists apply for research funding which a granting agency may (or may not) approve to financially support. These grants require a lengthy process as the granting agency can inquire about the researcher(s)'s background, the facilities used, the equipment needed, the time involved, and the overall potential of the scientific outcome. The process of grant writing and grant proposing is a somewhat delicate process for both the grantor and the grantee: the grantors want to choose the research that best fits their scientific principles, and the individual grantees want to apply for research in which they have the best chances but also in which they can build a body of work towards future scientific endeavors.
As of 2009, the Engineering and Physical Sciences Research Council in the United Kingdom devised an alternative method of fund-distribution: the sandpit.
Most universities have research administration offices to facilitate the interaction between the researcher and the granting agency. "Research administration is all about service—service to our faculty, to our academic units, to the institution, and to our sponsors. To be of service, we first have to know what our customers want and then determine whether or not we are meeting those needs and expectations."
In the United States of America, the National Council of University Research Administrators serves its members and advances the field of research administration through education and professional development programs, the sharing of knowledge and experience, and by fostering a professional, collegial, and respected community.
==== Hard money versus soft money ====
In academic contexts, hard money may refer to funding received from a government or other entity at regular intervals, thus providing a steady inflow of financial resources to the beneficiary. The antonym, soft money, refers to funding provided only through competitive research grants and the writing of grant proposals.
Hard money is usually issued by the government for the advancement of certain projects or for the benefit of specific agencies. Community healthcare, for instance, may be supported by the government by providing hard money. Since funds are disbursed regularly and continuously, the offices in charge of such projects are able to achieve their objectives more effectively than if they had been issued one-time grants.
Individual jobs at a research institute may be classified as "hard-money positions" or "soft-money positions"; the former are expected to provide job security because their funding is secure in the long term, whereas individual "soft-money" positions may come and go with fluctuations in the number of grants awarded to an institution.
=== Private funding: industrial/philanthropy/crowdfunding ===
Private funding for research comes from philanthropists, crowd-funding, private companies, non-profit foundations, and professional organizations. Philanthropists and foundations have been pouring millions of dollars into a wide variety of scientific investigations, including basic research discovery, disease cures, particle physics, astronomy, marine science, and the environment. Privately funded research has been adept at identifying important and transformative areas of scientific research. Many large technology companies spend billions of dollars on research and development each year to gain an innovative advantage over their competitors, though only about 42% of this funding goes towards projects that are considered substantially new, or capable of yielding radical breakthroughs. New scientific start-up companies initially seek funding from crowd-funding organizations, venture capitalists, and angel investors, gathering preliminary results using rented facilities, but aim to eventually become self-sufficient.
Europe and the United States have both reiterated the need for further private funding within universities. The European Commission highlights the need for private funding via research in policy areas such the European Green Deal and Europe's role in the digital age.
== Criticism of science funding ==
The source of funding may introduce conscious or unconscious biases into a researcher's work. This is highly problematic due to academic freedom in case of universities and regulatory capture in case of government-funded R&D.
=== Conflict of Interest ===
Disclosure of potential conflicts of interest (COIs) is used by journals to guarantee credibility and transparency of the scientific process. Conflict of interest disclosure, however, is not systematically nor consistently dealt with by journals that publish scientific research results.
When research is funded by the same agency that can be expected to gain from a favorable outcome there is a potential for biased results and research shows that results are indeed more favorable than would be expected from a more objective view of the evidence. A 2003 systematic review studied the scope and impact of industry sponsorship in biomedical research. The researchers found financial relationships among industry, scientific investigators, and academic institutions widespread. Results showed a statistically significant association between industry sponsorship and pro-industry conclusions and concluded that "Conflicts of interest arising from these ties can influence biomedical research in important ways". A British study found that a majority of the members on national and food policy committees receive funding from food companies.
In an effort to cut costs, the pharmaceutical industry has turned to the use of private, nonacademic research groups (i.e., contract research organizations [CROs]) which can do the work for less money than academic investigators. In 2001 CROs came under criticism when the editors of 12 major scientific journals issued a joint editorial, published in each journal, on the control over clinical trials exerted by sponsors, particularly targeting the use of contracts which allow sponsors to review the studies prior to publication and withhold publication of any studies in which their product did poorly. They further criticized the trial methodology stating that researchers are frequently restricted from contributing to the trial design, accessing the raw data, and interpreting the results.
The Cochrane Collaboration, a worldwide group that aims to provide compiled scientific evidence to aid well informed health care decisions, conducts systematic reviews of randomized controlled trials of health care interventions and tries to disseminate the results and conclusions derived from them. A few more recent reviews have also studied the results of non-randomized, observational studies. The systematic reviews are published in the Cochrane Library. A 2011 study done to disclose possible conflicts of interests in underlying research studies used for medical meta-analyses reviewed 29 meta-analyses and found that conflicts of interest in the studies underlying the meta-analyses were rarely disclosed. The 29 meta-analyses reviewed an aggregate of 509 randomized controlled trials. Of these, 318 trials reported funding sources with 219 (69%) industry funded. 132 of the 509 trials reported author disclosures of conflict of interest, with 91 studies (69%) disclosing industry financial ties with one or more authors. However, the information was seldom reflected in the meta-analyses. Only two (7%) reported funding sources and none reported author-industry ties. The authors concluded, "without acknowledgment of COI due to industry funding or author industry financial ties from RCTs included in meta-analyses, readers' understanding and appraisal of the evidence from the meta-analysis may be compromised."
In 2003 researchers looked at the association between authors' published positions on the safety and efficacy in assisting with weight loss of olestra, a fat substitute manufactured by the Procter & Gamble (P&G), and their financial relationships with the food and beverage industry. They found that supportive authors were significantly more likely than critical or neutral authors to have financial relationships with P&G and all authors disclosing an affiliation with P&G were supportive. The authors of the study concluded: "Because authors' published opinions were associated with their financial relationships, obtaining noncommercial funding may be more essential to maintaining objectivity than disclosing personal financial interests."
A 2005 study in the journal Nature surveyed 3247 US researchers who were all publicly funded (by the National Institutes of Health). Out of the scientists questioned, 15.5% admitted to altering design, methodology or results of their studies due to pressure of an external funding source.
=== Regulatory capture ===
Private funding also may be channeled to public funders. In 2022, a news story broke following the resignation of Eric Lander, former director of the Office of Science and Technology Policy (OSTP) at the Biden administration, that the charity of former Google executive Eric Schmidt, Schmidt Futures, paid the salary of a number employees of the OSTP. Ethics inquiries were initiated in the OSTP.
=== Efficiency of funding ===
The traditional measurement for efficiency of funding are publication output, citation impact, number of patents, number of PhDs awarded etc. However, the use of journal impact factor has generated a publish-or-perish culture and a theoretical model has been established whose simulations imply that peer review and over-competitive research funding foster mainstream opinion to monopoly. Calls have been made to reform research assessment, most notably in the San Francisco Declaration on Research Assessment and the Leiden Manifesto for research metrics. The current system also has limitations to measure excellence in the Global South. Novel measurement systems such as the Research Quality Plus has been put forward to better emphasize local knowledge and contextualization in the evaluation of excellence. A wide range of interventions has been proposed to improve science funding. Open peer review can improve the quality of scholarly peer review. A systematic review found a scarcity of randomized controlled trials on peer review interventions.
Another question is how to allocate funds to different disciplines, institutions, or researchers. A recent study by Wayne Walsh found that "prestigious institutions had on average 65% higher grant application success rates and 50% larger award sizes, whereas less-prestigious institutions produced 65% more publications and had a 35% higher citation impact per dollar of funding."
== Trends ==
In endogenous growth theories R&D contributes to economic growth. Therefore, countries have strong incentives to maintain investments in R&D.
=== By country ===
Different countries spend vastly different amounts on research, in both absolute and relative terms. For instance, South Korea and Israel spend more than 4% of their GDP while many less developed countries spend less than 1%. In developed economies, GERD is financed mainly by the business sector, whereas the government and the university sector dominates in less-developed economies. In some countries, funding from the Rest of the World makes up 20-30% of total GERD, probably due to FDI and foreign aid, but only in Mali it is the main source of fund. Private non-profit is not the main source of fund in any countries, but it reaches 10% of total GERD in Columbia and Honduras.
When comparing annual GERD and GDP Growth, it can be seen that countries with lower GERD are often growing faster. However, as most of these countries are developing, their growth is probably driven by other factors of production. On the other hand, developed countries who have higher GERD also produce positive growth rates. GERD in these countries has a more substantial contribution to growth rate.
=== Recessions ===
In crisis, business R&D tends to act procyclically. As R&D is a long-term investments and so disruptions should be avoided. Keynesian countercyclical reactions were advocated for after the 2008 financial crisis, but this was difficult to achieve for some countries. Due to the nature of COVID-19, the pandemic accelerated publicly funded R&D spending in 2020, primarily into the pharmaceutical industry. A fall is expected in spending for 2021, although not below 2020 levels. The pandemic made health research and sectors with strategic value-chain dependencies the main target of science funding.
== See also ==
Adversary evaluation
Scientific funding advisory bodies (category)
Funding bias
Industry funding of academic research
Intellectual inbreeding
Logology (science)
Metascience
Science policy
Scientific pluralism
Self-Organized Funding Allocation
Tertiary education#Statistics
== References ==
== Further reading ==
Eisfeld-Reschke, Jörg, Herb, Ulrich, & Wenzlaff, Karsten (2014). Research Funding in Open Science. In S. Bartling & S. Friesike (Eds.), Opening Science (pp. 237–253). Heidelberg: Springer. doi:10.1007/978-3-319-00026-8_16
Herb, Ulrich (2014-07-31). "Open science's final frontier". Research Europe Magazine. Archived from the original on 2014-09-03. Retrieved 2014-08-30.
Martinson, Brian C.; De Vries, Raymond; et al. (2005). "Scientists behaving badly". Nature. 435 (7043): 737–738. Bibcode:2005Natur.435..737M. doi:10.1038/435737a. PMID 15944677. S2CID 4341622.
Mello, Michelle M.; et al. (2005). "Academic Medical Centers' Standards for Clinical-Trial Agreements with Industry". New England Journal of Medicine. 352 (21): 2202–2210. doi:10.1056/nejmsa044115. PMID 15917385. S2CID 8283797.
Odlyzko, Andrew (1995-10-04). "The Decline of Unfettered Research". Retrieved 2007-11-02.
== External links ==
Where to Search for Funding | Science | AAAS, from Science Careers, from the Journal Science.
ResearchCrossroads Aggregated funding data from the National Institutes of Health, the National Science Foundation, NSF, private foundations and the European Union
Seventh Framework Programme (2007–2013) The European Unions's programme for funding and promoting research at the European level
CORDIS - the official website of the European Unions's programme for funding and promoting research This website contains comprehensive information on research projects already funded.
Research Councils UK The portal for the UK-based Research Councils. | Wikipedia/Funding_of_science |
During the Renaissance, great advances occurred in geography, astronomy, chemistry, physics, mathematics, manufacturing, anatomy and engineering. The collection of ancient scientific texts began in earnest at the start of the 15th century and continued up to the Fall of Constantinople in 1453, and the invention of printing allowed a faster propagation of new ideas. Nevertheless, some have seen the Renaissance, at least in its initial period, as one of scientific backwardness. Historians like George Sarton and Lynn Thorndike criticized how the Renaissance affected science, arguing that progress was slowed for some amount of time. Humanists favored human-centered subjects like politics and history over study of natural philosophy or applied mathematics. More recently, however, scholars have acknowledged the positive influence of the Renaissance on mathematics and science, pointing to factors like the rediscovery of lost or obscure texts and the increased emphasis on the study of language and the correct reading of texts.
Marie Boas Hall coined the term Scientific Renaissance to designate the early phase of the Scientific Revolution, 1450–1630. More recently, Peter Dear has argued for a two-phase model of early modern science: a Scientific Renaissance of the 15th and 16th centuries, focused on the restoration of the natural knowledge of the ancients; and a Scientific Revolution of the 17th century, when scientists shifted from recovery to innovation.
== Context ==
During and after the Renaissance of the 12th century, Europe experienced an intellectual revitalization, especially with regard to the investigation of the natural world. In the 14th century, however, a series of events that would come to be known as the Crisis of the Late Middle Ages was underway. When the Black Death came, it wiped out so many lives it affected the entire system. It brought a sudden end to the previous period of massive scientific change. The plague killed 25–50% of the people in Europe, especially in the crowded conditions of the towns, where the heart of innovations lay. Recurrences of the plague and other disasters caused a continuing decline of population for a century.
== The Renaissance ==
The 14th century saw the beginning of the cultural movement of the Renaissance. By the early 15th century, an international search for ancient manuscripts was underway and would continue unabated until the Fall of Constantinople in 1453, when many Byzantine scholars had to seek refuge in the West, particularly Italy. Likewise, the invention of the printing press was to have great effect on European society: the facilitated dissemination of the printed word democratized learning and allowed a faster propagation of new ideas.
Initially, there were no new developments in physics or astronomy, and the reverence for classical sources further enshrined the Aristotelian and Ptolemaic views of the universe. Renaissance philosophy lost much of its rigor as the rules of logic and deduction were seen as secondary to intuition and emotion. At the same time, Renaissance humanism stressed that nature came to be viewed as an animate spiritual creation that was not governed by laws or mathematics. Only later, when no more manuscripts could be found, did humanists turn from collecting to editing and translating them, and new scientific work began with the work of such figures as Copernicus, Cardano, and Vesalius.
== Important developments ==
=== Alchemy and chemistry ===
While differing in some respects, alchemy and chemistry often had similar goals during the Renaissance period, and together they are sometimes referred to as chymistry. Alchemy is the study of the transmutation of materials through obscure processes. Although it is often viewed as a pseudoscientific endeavor, many of its practitioners utilized widely accepted scientific theories of their times to formulate hypotheses about the constituents of matter and the ways matter could be changed. One of the main aims of alchemists was to find a method of creating gold and other precious metals from the transmutation of base materials. A common belief of alchemists was that there is an essential substance from which all other substances formed, and that if you could reduce a substance to this original material, you could then construct it into another substance, like lead to gold. Medieval alchemists worked with two main elements or "principles", sulphur and mercury.
Paracelsus was a chymist and physician of the Renaissance period who believed that, in addition to sulphur and mercury, salt served as one of the primary alchemical principles from which everything else was made. Paracelsus was also instrumental in helping to put chemical practices to practical medicinal use through a recognition that the body operates through processes which may be seen as chemical in nature. These lines of thinking directly conflicted with many long-held traditional beliefs, such as those popularized by Aristotle; however, Paracelsus was insistent that questioning principles of nature was essential to continue the general growth of knowledge.
Despite its frequent basis in what may be considered scientific practices by modern standards, numerous factors caused chymistry as a discipline to remain separate from general academia until near the end of the Renaissance, when it finally began appearing as a portion of some university education.: 104–115 The commercial nature of chymistry at the time, along with the lack of classical basis for the practice, were some of the contributing factors which led to the general view of the discipline as a craft rather than a respectable academic discipline.
=== Astronomy ===
The astronomy of the late Middle Ages was based on the geocentric model described by Claudius Ptolemy in antiquity. Probably very few practicing astronomers or astrologers actually read Ptolemy's Almagest, which had been translated into Latin by Gerard of Cremona in the 12th century. Instead they relied on introductions to the Ptolemaic system such as the De sphaera mundi of Johannes de Sacrobosco and the genre of textbooks known as Theorica planetarum. For the task of predicting planetary motions they turned to the Alfonsine tables, a set of astronomical tables based on the Almagest models but incorporating some later modifications, mainly the trepidation model attributed to Thabit ibn Qurra. Contrary to popular belief, astronomers of the Middle Ages and Renaissance did not resort to "epicycles on epicycles" in order to correct the original Ptolemaic models—until one comes to Copernicus himself.
Sometime around 1450, mathematician Georg Purbach (1423–1461) began a series of lectures on astronomy at the University of Vienna. Regiomontanus (1436–1476), who was then one of his students, collected his notes on the lecture and later published them as Theoricae novae planetarum in the 1470s. This "New Theorica" replaced the older theorica as the textbook of advanced astronomy. Purbach also began to prepare a summary and commentary on the Almagest. He died after completing only six books, however, and Regiomontanus continued the task, consulting a Greek manuscript brought from Constantinople by Cardinal Bessarion. When it was published in 1496, the Epitome of the Almagest made the highest levels of Ptolemaic astronomy widely accessible to many European astronomers for the first time.
The last major event in Renaissance astronomy is the work of Nicolaus Copernicus (1473–1543). He was among the first generation of astronomers to be trained with the Theoricae novae and the Epitome. Shortly before 1514 he began to revive Aristarchus's idea that the Earth revolves around the Sun. He spent the rest of his life attempting a mathematical proof of heliocentrism. When De revolutionibus orbium coelestium was finally published in 1543, Copernicus was on his deathbed. A comparison of his work with the Almagest shows that Copernicus was in many ways a Renaissance scientist rather than a revolutionary, because he followed Ptolemy's methods and even his order of presentation. Not until the works of Johannes Kepler (1571–1630) and Galileo Galilei (1564–1642) was Ptolemy's manner of doing astronomy superseded. The use of more advanced tables and mathematics would provide the impetus for the establishment of the Gregorian calendar in 1582 (primarily to reform the calculation of the date of Easter), replacing the Julian calendar, which had several errors.: 69–72
=== Mathematics ===
The accomplishments of Greek mathematicians survived throughout Late Antiquity and the Middle Ages through a long and indirect history. Much of the work of Euclid, Archimedes, and Apollonius, along with later authors such as Hero and Pappus, were copied and studied in both Byzantine culture and in Islamic centers of learning. Translations of these works began already in the 12th century, with the work of translators in Spain and Sicily, working mostly from Arabic and Greek sources into Latin. Two of the most prolific were Gerard of Cremona and William of Moerbeke.
The greatest of all translation efforts, however, took place in the 15th and 16th centuries in Italy, as attested by the numerous manuscripts dating from this period currently found in European libraries. Virtually all leading mathematicians of the era were obsessed with the need for restoring the mathematical works of the ancients. Not only did humanists assist mathematicians with the retrieval of Greek manuscripts, they also took an active role in translating these work into Latin, often commissioned by religious leaders such as Nicholas V and Cardinal Bessarion.
Some of the leading figures in this effort include Regiomontanus, who made a copy of the Latin Archimedes and had a program for printing mathematical works; Commandino (1509–1575), who likewise produced an edition of Archimedes, as well as editions of works by Euclid, Hero, and Pappus; and Maurolyco (1494–1575), who not only translated the work of ancient mathematicians but added much of his own work to these. Their translations ensured that the next generation of mathematicians would be in possession of techniques far in advance of what it was generally available during the Middle Ages.
It must be borne in mind that the mathematical output of the 15th and 16th centuries was not exclusively limited to the works of the ancient Greeks. Some mathematicians, such as Tartaglia and Luca Paccioli, welcomed and expanded on the medieval traditions of both Islamic scholars and people like Jordanus and Fibonnacci. Giordano Bruno was also one to critique the works of people like Aristotle, whom he believed to have a flawed logic and developed a mathematical doctrine for the computation of partial physics, with Bruno attempting to transform theories of nature.
=== Physics ===
The progress being made in math was complemented by advancements in physics, with people like Galileo attempting to bridge the gap between the two fields and question Aristotelian ideas. The revived investigation of physics opened up many opportunities in subfields like mechanics, optics, navigation, and cartography.: 79–89
Mechanical theories had originated with the Greeks, especially Aristotle and Archimedes.: 79–82 Mechanics and philosophy had been related disciplines in ancient Greece, and only in the Renaissance did the two subjects begin to split.: 79–82 A lot of the work of developing new mechanical ideas and theories was carried out by Italians such as Rafael Bombelli, though the Fleming Simon Stevin also provided many ideas.: 79–82 Galileo also contributed to the advancement of this field with a treatise on mechanics in 1593, helping to develop ideas on relativity, freely falling bodies, and accelerated linear motion, though he lacked the means to properly communicate his findings at the time. In June 1609, Galileo's interests shifted to his telescopic investigations after having been close to revolutionizing the science of mechanics.
Navigation was an important topic of the time, and many innovations were made that, with the introduction of better ships and applications of the compass, would later lead to geographical discoveries.: 89–91 The calculations involved in navigation proved to be difficult, with the technology of the time unable to accuately predict weather or determine one's geographic position. Determining one's longitude proved especially challenging, since one's local time need to be calculated on the basis of an astronomical observation.: 89–91 One theory that was tested was to record the time of an eclipse and use Regiomontanus' Ephemerides to compare it with Nuremberg time or Zacuto's Almanach perpetuum to compare it with Salamanca time, though the margin of error in such calculations was unacceptably great (around 25.5 degrees).: 89–91 Until longitude could be accurately determined, navigators had to rely on dead reckoning, with its many uncertainties.: 89–91
=== Medicine ===
With the Renaissance came an increase in experimental investigation, principally in the field of dissection and body examination, thus advancing our knowledge of human anatomy. The development of modern neurology began in the 16th century with Andreas Vesalius, who described the anatomy of the brain and other organs; he had little knowledge of the brain's function, thinking that it resided mainly in the ventricles. Understanding of medical sciences and diagnosis improved, but with little direct benefit to health care. Few effective drugs existed, beyond opium and quinine. William Harvey provided a refined and complete description of the circulatory system. The most useful tomes in medicine, used both by students and expert physicians, were materiae medicae and pharmacopoeiae.
=== Geography and the New World ===
In the history of geography, the key classical text was the Geographia of Claudius Ptolemy (2nd century). It was translated into Latin in the 15th century by Jacopo d'Angelo. It was widely read in manuscript and went through many print editions after it was first printed in 1475. Regiomontanus worked on preparing an edition for print prior to his death; his manuscripts were consulted by later mathematicians in Nuremberg. Ptolemy's Geographia became the basis for most maps made in Europe throughout the 15th century. Even as new knowledge began to replace the content of old maps, the rediscovery of Ptolemy's mapping system, including the use of coordinates and projection, helped to redefine the overall field of cartography as a scientific pursuit rather than an artistic one.
The information provided by Ptolemy, as well as Pliny the Elder and other classical sources, was soon seen to be in contradiction to the lands explored in the Age of Discovery. The new discoveries revealed shortcomings in classical knowledge; they also opened European imagination to new possibilities. In particular, Christopher Columbus' voyage to the New World in 1492 helped set the tone for what would soon after become a wave of European expansion. Thomas More's Utopia was inspired partly by the discovery of the New World. Most maps developed prior to this period grossly underestimated the extent of the lands separating Europe from India on a westward route through the New World; however, through contributions of explorers such as Ferdinand Magellan, efforts were made to create more accurate maps during this period.
== See also ==
Continuity thesis
The Copernican Question
Renaissance magic
Renaissance technology
== Notes ==
== References ==
Dear, Peter. Revolutionizing the Sciences: European Knowledge and Its Ambitions, 1500–1700. Princeton: Princeton University Press, 2001.
Debus, Allen G. Man and Nature in the Renaissance. Cambridge: Cambridge University Press, 1978.
Grafton, Anthony, et al. New Worlds, Ancient Texts: The Power of Tradition and the Shock of Discovery. Cambridge: Belknap Press of Harvard University Press, 1992.
Hall, Marie Boas. The Scientific Renaissance, 1450–1630. New York: Dover Publications, 1962, 1994.
== External links ==
Renaissance science and technology at Britannica.com | Wikipedia/Science_in_the_Renaissance |
The economics of science aims to understand the impact of science on the advance of technology, to explain the behavior of scientists, and to understand the efficiency or inefficiency of scientific institutions and science markets.
The importance of the economics of science is substantially due to the importance of science as a driver of technology and technology as a driver of productivity and growth. Believing that science matters, economists have attempted to understand the behavior of scientists and the
operation of scientific institutions.
== Science as a public good ==
Economists consider “science” as the search and production of knowledge using known starting conditions. Knowledge can be considered a public good, due to the fact that its utility to society is not diminished with additional consumption (non-rivalry), and once the knowledge is shared with the public it becomes very hard to restrict access to it or use of it (non-excludable). Traditional public economic theory asserts that competitive markets provide poor incentives for production of a public good because the producers cannot reap the benefits of use of their product, and thus costs will be higher than benefits. Economists have identified several possible reasons as to why producers of science might determine that the private costs they incur in the production process are larger than the benefits that they intend to reap, even though the benefits to society are greater than these costs. Firstly, the technological barriers to production are extremely high, which makes the market very risky. Technological barriers refer to the cost of research and development of new scientific knowledge, which becomes increasingly expensive as technology continues to play a more prominent role in this type of development. Secondly, due to the non-excludable nature of scientific knowledge, producers worry that they will be unable to enforce property rights on their produced goods. This will result in others being able to benefit from the scientific knowledge without having to bear the cost of the research and development, which would in turn make the potential return on investment too small to incentivize participation in the market. Therefore, science can be understood as the production of a public good, and can be studied within the framework of public economics.
However, certain economists argue that a non-market mechanism has developed to correct the problem of indefinable property rights, such that scientists are incentivized to produce knowledge in a socially responsible way. Economist Paula Stephen refers to this mechanism as a reward system based primarily on a concept that she calls “priority of discovery.” Robert Merton argues that the goal of scientists is to establish “priority of discovery” by being the first to report a new discovery, which then results in the reward of recognition. The scientific community only bestows this reward on the person who discovers the new piece of knowledge first, and thus this sets up a winner-takes-all type of system that incentivizes producers to participate in the market of scientific knowledge. Stephen particularly notes that “Compensation in science is generally composed of two parts: one portion is paid regardless of the individual's success in races, the other is priority-based and reflects the value of the winner's contribution to science.” The first part that Stephens identifies corresponds to the salary that a professor in academia would expect to make over the course of his or her career; these salaries are notoriously flat, with one study noting that a full professor can expect to make only 70% more than a newly hired assistant professor. However, Stephen argues that the second part of compensation, that which is reaped when a scientist establishes priority of discovery, then the earnings profile becomes much less flat as the scientist gains prestige, journalistic citations, paid speaking invitations, and other such rewards. However, she notes that this theory had yet to be empirically tested at the time of writing. Furthermore, her analysis only applies to the world of academia, whereas industry is also a major source of scientific knowledge production.
== Government interventions ==
The field of public economics posits that should market failures occur, the government might be able to intervene to correct these market failures. When speaking about the production of scientific knowledge, the government has several options for intervening in the market to attempt to correct the failure. In the United States, two of the most historically popular and most extensively studied options are the patent system and tax incentives.
=== The patent system ===
In the United States, the Patent and Trademark Office issues patents that give the holder of the patent exclusive, defined property rights to their product for 20 years. From an economic perspective, the value of the patent is that it increases the marginal benefit of the firm that is producing the scientific knowledge. To graphically display this concept, the accompanying figure depicts the marginal benefit and marginal cost curves of a firm in the market for science. The vertical axis displays the marginal cost and marginal benefit of each additional dollar spent on research and development. The horizontal access displays the amount of money spent on research and development in total. Research and development is assumed to have diminishing returns. For simplicity's sake, all curves are assumed to be linear, and the marginal cost curve is assumed to be constant. A firm will maximize their profits by producing where marginal cost intersects marginal benefit. In the absence of any government intervention, the firm will produce where at RD0, where private marginal benefit (MB0) intersects MC. However, if scientific knowledge is assumed to be a public good, then RD0 is too low a quantity to satisfy the social need. The optimal amount of R&D is at RD1. The value of the introduction of the patent system is that it allows the marginal benefit curve for the firm to shift upward to MB1 so that the private benefit to the firm now produces the socially optimal quantity. The additional revenue is collected from society, as society now pays higher prices for the knowledge given the monopoly power of the producing firm.
In practice, patent law has been correlated with increased R&D expenditure, indicating that this form of government intervention is in fact incentivizing production. However, this type of government intervention does not allow particularly precise targeting of the optimal level of R&D production, and several economists argue that the benefit of 20 years of monopoly power is too high. This argument has particular relevance to current debates regarding the production of life-saving pharmaceuticals.
=== Tax incentives ===
In 1954, the Internal Revenue Service incorporated an exemption for research costs such that firms could have research costs deducted from their yearly taxes. From an economic perspective, the value of the tax incentive is that it decreases the marginal cost of the firm that is producing the scientific knowledge. To graphically display this concept, the accompanying figure depicts the marginal benefit and marginal cost curves of a firm in the market for science. The vertical axis displays the marginal cost and benefit of each additional dollar spent on research and development. The horizontal access displays the amount of money spent on research and development in total. Research and development is assumed to have diminishing rate of return. For simplicity's sake, all curves are assumed to be linear, and the marginal cost curve is assumed to be constant. A firm will maximize their profits by producing where marginal cost intersects marginal benefit. In the absence of any government intervention, the firm will produce where at RD0, where private marginal benefit (PMB0) intersects MC. However, if scientific knowledge is assumed to be a public good, then RD0 is too low a quantity to satisfy the social need. The optimal amount of R&D is at RD1, which is where the marginal cost curve intersects the social marginal benefit (not depicted on this graph). The value of the tax incentive is that it allows the marginal cost curve for the firm to shift downward so that the private cost to the firm now produces the socially optimal quantity. The rest of the cost is now borne by society, in the form of the lost tax revenue.
Tax incentives allow slightly more precise targeting than the patent system. However, the concern still remains that tax incentives exacerbate inequality by producing financial windfalls for firms that might already be very prosperous. Furthermore, empirical studies have been limited, although a 1996 report from the Congressional Office of Technological Assessment found that for every dollar lost in tax revenue, there was a dollar increasing in private R&D spending.
== See also ==
Author-level metrics
Economics of scientific knowledge
== References == | Wikipedia/Economics_of_science |
The March for Science (formerly known as the Scientists' March on Washington) was an international series of rallies and marches held on Earth Day. The inaugural march was held on April 22, 2017, in Washington, D.C., and more than 600 other cities across the world. According to organizers, the march was a non-partisan movement to celebrate science and the role it plays in everyday lives. The goals of the marches and rallies were to emphasize that science upholds the common good and to call for evidence-based policy in the public's best interest. The March for Science organizers, estimated global attendance at 1.07 million, with 100,000 participants estimated for the main March in Washington, D.C., 70,000 in Boston, 60,000 in Chicago, 50,000 in Los Angeles, 50,000 in San Francisco, 20,000 in Seattle, 14,000 in Phoenix, and 11,000 in Berlin.
A second March for Science was held April 14, 2018. 230 satellite events around the world participated in the 2nd annual event, including New York City, Abuja, Nigeria, and Baraut, India. A third March for Science took place on May 22, 2019, this time with 150 locations around the world participating.
The March for Science organizers and supporters said that support for science should be nonpartisan. The march was organized by scientists skeptical of the agenda of the Trump administration, and critical of Trump administration policies widely viewed as hostile to science. The march's website stated that an "American government that ignores science to pursue ideological agendas endangers the world."
Particular issues of science policy raised by the marchers include support for evidence-based policymaking, as well as support for government funding for scientific research, government transparency, and government acceptance of the scientific consensus on climate change and evolution. The march was part of growing political activity by American scientists in the wake of the November 2016 elections and the 2017 Women's March.
Robert N. Proctor, a historian of science at Stanford University, stated that the March for Science was "pretty unprecedented in terms of the scale and breadth of the scientific community that's involved" and was rooted in "a broader perception of a massive attack on sacred notions of truth that are sacred to the scientific community."
== Background ==
=== Donald Trump ===
In 2012, Donald Trump referred to climate change as a hoax. As a presidential candidate, he promised to resume construction of the Keystone XL Pipeline and roll back U.S. Environmental Protection Agency (EPA) regulations adopted by the Obama administration.
After Trump's election, his first transition team sought out specific U.S. Department of Energy (DOE) employees who had worked on climate change during the Obama administration. Prior to Trump's inauguration, many climate scientists began downloading climate data from government websites that they feared might be deleted by the Trump administration. Other actions taken or promised by the Trump administration inspired the march, including pulling out of the Paris Agreement, the stances of his Cabinet nominees, the freezing of research grants, and a gag order placed on scientists in the EPA regarding dissemination of their research findings. In February 2017, William Happer, a possible Trump science advisor with skeptical views on human caused global warming, described an area of climate science as "really more like a cult" and its practitioners "glassy-eyed". ScienceInsider reported Trump's first budget request as "A grim budget day for U.S. science" because it contained major funding cuts to NOAA's research and satellite programs, the EPA's Office of Research and Development, the DOE's Office of Science and energy programs, the U.S. Geological Survey, the National Institutes of Health, and other science agencies.
=== International solidarity ===
International sister marches were planned for countries around the world. These both supported American scientists and climate scientists more generally, and protested against other impingements on academic freedom internationally, such as government action against the Central European University in Hungary and the closure of educational institutes and dismissal of academics in the 2016–17 Turkish purges, as well as local issues.
== Planning and participants ==
A major source of inspiration behind the planning of the march was the 2017 Women's March of January 21, 2017. The specific idea to create a march originated from a Reddit discussion thread about the removal of references to climate change from the White House website. In the discussion, an anonymous poster named "Beaverteeth92" made a comment regarding the need for a "Scientist's March on Washington". Dozens of Reddit users responded positively to the proposal. Jonathan Berman, a postdoctoral fellow at the University of Texas Health Science Center and a participant in the original conversation, created a Facebook page, Twitter feed and website to organize a march. The Facebook group grew from 200 members to 300,000 in less than a week, growing to 800,000 members. Individual scientists have both applauded and criticized this development.
It was announced on March 30 that Bill Nye, Mona Hanna-Attisha, and Lydia Villa-Komaroff would headline the march, and serve as honorary co-chairs. The protest was set to occur on Earth Day, with satellite rallies planned in hundreds of cities across the world.
For the inaugural march in Washington, D.C., the National Committee consisted of (in alphabetic order):
Sofia Ahsanuddin, Valorie V. Aquino, Jonathan Berman, Teon L. Brooks, Beka Economopoulos, Kate Gage, Kristen Gunther, Kishore Hari, Sloane Henningsen, Rachael Holloway, Aaron Huertas, Ayana Elizabeth Johnson, Rosalyn LaPier, Julia MacFall, Adam Miller, Lina Miller, Caitlin Pharo, Jennifer Redig, Joanna Spencer-Segal, Lucky Tran, Courtnie Weber, Caroline Weinberg, and Amanda Yang.
These are the roles of the National Committee along with their teams:
During the annual meeting of the American Association for the Advancement of Science (AAAS), the largest scientific organization in the US, scientists held the "Rally to Stand Up for Science" at Copley Square, Boston, on February 19. The same month, the AAAS announced its support for the march. By mid-March, some 100 science organizations endorsed the March for Science, including many scientific societies. Endorsers of the march included the American Geophysical Union, American Association of Geographers, American Association of Physical Anthropologists, Society for Neuroscience, Society for Freshwater Science, American Statistical Association, Association for Psychological Science, American Sociological Association, Electrochemical Society, Entomological Society of America, California Academy of Sciences, and the Monterey Bay Aquarium.
The University of Delaware Center for Political Communication conducted a survey of 1,040 members of March for Science Facebook groups or pages from March 31 to April 18 to study their motivations for joining the march. Respondents cited the following as reasons for marching:
Before April, enthusiasts found existing knitting patterns for a hat shaped like a brain and proposed it as a symbol of solidarity for the march in analogy with the pussyhat project.
== Participation ==
The primary march, organized by Earth Day Network and March for Science, in Washington, D.C., began at 10 AM with a rally and teach-in on the grounds of the Washington Monument, featuring speeches by concerned citizens alternating with scientists and engineers; including Denis Hayes, co-founder of the first Earth Day in 1970 and Bill Nye. No politicians spoke at the rally. At 2 PM the crowd of thousands, in spite of the steady rain throughout the day, proceeded down Constitution Avenue to 3rd Street, NW between the National Mall and the west front of the United States Capitol.
Protesters gathered in over a hundred cities across the globe, with an estimated 70,000 participants in Boston, Massachusetts, and over 150,000 in several cities in California.
== Reception ==
Professor Robert Proctor of Stanford University said that the March for Science was similar to other efforts by scientists such as Physicians for Social Responsibility; however, the scale was larger because "there's a broader perception of a massive attack on sacred notions of truth that are sacred to the scientific community."
=== Support ===
On January 26, 2017, U.S. Senator Bernie Sanders of Vermont expressed his support for the march, congratulating "those scientists and researchers who are fighting back". U.S. Representative Bill Foster of Illinois, a physicist and the only current member of Congress with a Ph.D. in a natural sciences field, will join the march, "not as a Democratic member of Congress, but as a scientist." Foster said that he viewed the march as political, but not partisan, saying, "if you see a specific policy that is inconsistent with the known principles of science, every citizen who is also a scientist should speak out."
In February the AAAS and other science groups announced their support for the march. Rush Holt Jr., the chief executive officer of the AAAS, expressed support for scientist involvement in politics. Holt also emphasizes the importance of "appreciation for and understanding of science in the general population".
What's so interesting is it's the first time, I think, anybody can point to in decades where there has been a spontaneous effort to defend the idea of science. It's not a march pro or con GMOs or pro or con nuclear power. It's about the value of science and the power of evidence. People are understandably and correctly outraged that in so many areas of public policy ideology is crowding out evidence, that evidence seems to be optional in the fashioning of public policy, and that you have officials using phrases like alternative fact.
=== Criticism ===
The march received a torrent of criticism from conservative publications for the perceived left-wing bias and orientation of the event. Donald Trump's science adviser, climate change denier William Happer stated that "there's no reason to assume the president is against science" and dismissed the march as a cult.
A number of scientists voiced concerns over the march. Theoretical physicist Sylvester James Gates warned that "such a politically charged event might send a message to the public that scientists are driven by ideology more than by evidence". Writing in The New York Times, Robert S. Young argued that the march will "reinforce the narrative from skeptical conservatives that scientists are an interest group and politicize their data, research and findings for their own ends" and that it would be better for scientists to "march into local civic groups, churches, county fairs and, privately, into the offices of elected officials." Matthew Nisbet, writing for Skeptical Inquirer magazine right after the first march in 2017, states that it is not the least educated but the "best educated and most scientifically literate who are prone to biased reasoning and false beliefs about contentious science issues". In his opinion this will mean that the March will only deepen "partisan differences, while jeopardizing trust and impartiality and credibility of scientists". Nisbet feels that confidence in scientists is strong, and they should "use this capital wisely and effectively".
Responding to criticism surrounding the political nature of the march, meteorologist and columnist Eric Holthaus wrote that the scientific field "has always been political" and referred to the example of Galileo Galilei's confrontation with the political order. Holthaus wrote that the scientists must also protest when "truth itself is being called into question".
Discussing science's role in policy and government, Rush Holt points out a fallacy in viewing science and politics as philosophically incompatible: "The ethic in the profession is that you stick to your science, and if you're interested in how science affects public policy or public questions, just let the facts speak for themselves. Of course, there's a fallacy there, too. Facts are, by themselves, voiceless."
San Francisco Lead Organizer Kristen Ratan debated Jerry Coyne on KQED's Forum regarding his criticism of the March and remarked that the millennial generation is just finding its feet with regard to activism and should be encouraged. Ratan also distinguished between being political and being partisan and suggested that while the March for Science is a political act, it is by no means partisan, which implies blind allegiance to one party over another. Ratan reiterated that the March For Science supports evidence-based policy-making regardless of party or affiliation.
== Follow-up ==
Following the march, the organizers of the March for Science encouraged people to a "Week of Action" with an outline of daily actions.
The following spring, Science not Silence: Voices from the March for Science Movement, was published by MIT Press. The book, edited by Stephanie Fine Sasse and Lucky Tran, featured stories and images from marches held around the globe. It was selected as one of the "World's Best Human Rights Books" of Spring 2018 by Hong Kong Free Press.
In July 2018, March for Science created and hosted the SIGNS (Science in Government, Institutions & Society) Summit in Chicago, Illinois. The summit was co-hosted by Field Museum and brought together organizers from satellite marches to connect, strategize, and develop skills to bring back to their communities. The program featured notable figures, including talks by Fabio Rojas, Brian Nord, Adia Benton, and Dana R. Fisher, as well as a poetry reading by Ed Roberson. Many sessions were recorded and are available to view online.
== See also ==
== References ==
== External links ==
Official website
Earth Day Network (April 22, 2017). "March for Science Earth Day 2017 in Washington, D.C." Retrieved April 25, 2017 – via YouTube. (5:39:07)
Rucht, Dieter (February 8, 2018). Standing Up For Science (Documentary). Retrieved February 23, 2018 – via YouTube. (00:45:28) | Wikipedia/March_for_Science |
Science is a systematic method for obtaining knowledge that is natural, measurable or consisting of systematic principles, generally through testable explanations and predictions.
Science may also refer to:
== Branches ==
Typical divisions of science include:
Natural science, the use of the scientific method to study the universe
Social science, the use of the scientific method to study society
Applied science, the study of technology
In addition, when used more generally by ignoring the testability requirement:
Formal science, the study of rules, logic, and formal systems of information
== Literature ==
Science (journal), the academic journal of the American Association for the Advancement of Science
Science (1979–1986 magazine), a general science magazine published by the AAAS as Science 80, merged into Discover
The Sciences, a popular science magazine published by the New York Academy of Sciences from 1961 to 2001
== Music ==
S.C.I.E.N.C.E., a 1997 album by Incubus
Science (album), a 2006 album by Thomas Dybdahl
"Science", a song by System of a Down from Toxicity
== Other uses ==
Chico Science (1966–1997), a Brazilian singer and composer
Kieron "Science" Harvey, a housemate in British Big Brother series 6
"Science" (Brass Eye), a 1997 television episode
Science (film), a 2010 stand-up show and film by Ricky Gervais
Science (sculpture), a 1925 work by Charles Keck
Science (UIL test), an academic competition in Texas, US
Science Channel, a television channel owned by Discovery Networks
Science Ltd, a company founded and owned by artist Damien Hirst
Science Inc., a Los Angeles–based startup studio that develops, invests in, and acquires businesses
Science Party, Australian political party
== See also ==
Index of branches of science
Big Science (disambiguation) | Wikipedia/Science_(disambiguation) |
In the applied sciences, normative science is a type of information that is developed, presented, or interpreted based on an assumed, usually unstated, preference for a particular outcome, policy or class of policies or outcomes. Regular or traditional science does not presuppose a policy preference, but normative science, by definition, does. Common examples of such policy preferences are arguments that pristine ecosystems are preferable to human altered ones, that native species are preferable to nonnative species, and that higher biodiversity is preferable to lower biodiversity.
In more general philosophical terms, normative science is a form of inquiry, typically involving a community of inquiry and its accumulated body of provisional knowledge, that seeks to discover good ways of achieving recognized aims, ends, goals, objectives, or purposes. Many political debates revolve around arguments over which of the many "good ways" shall be selected. For example, when presented as scientific information, words such as ecosystem health, biological integrity, and environmental degradation are typically examples of normative science because they each presuppose a policy preference and are therefore a type of policy advocacy.
== See also ==
== References == | Wikipedia/Normative_science |
In philosophy of science, an observation is said to be "theory-laden" when shaped by the investigator's theoretical presuppositions. The thesis is chiefly associated with the late 1950s–early 1960s work of Norwood Russell Hanson, Thomas Kuhn, and Paul Feyerabend, though it was likely first put forth some 50 years earlier, at least implicitly, by Pierre Duhem.
Semantic theory-ladenness refers to the impact of theoretical assumptions on the meaning of observational terms, while perceptual theory-ladenness refers to their impact on the perceptual experience itself. Theory-ladenness is also relevant for measurement outcomes: the data thus acquired may be said to be theory-laden since it is meaningless by itself unless interpreted as the outcome of the measurement processes involved.
Theory-ladenness poses a problem for the confirmation of scientific theories since the observational evidence may already implicitly presuppose the thesis it is supposed to justify. This effect can present a challenge for reaching scientific consensus if the disagreeing parties make different observations due to their different theoretical backgrounds.
== Forms ==
Two forms of theory-ladenness should be kept separate: (a) The semantic form: the meaning of observational terms is
partially determined by theoretical presuppositions; (b) The perceptual form: the theories held by the investigator, at a very basic cognitive level, impinge on the perceptions of the investigator. The former may be referred to as semantic and the latter as perceptual theory-ladenness.
In a book showing the theory-ladenness of psychiatric evidences, Massimiliano Aragona (Il mito dei fatti, 2009) distinguished three forms of theory-ladenness. The "weak form" was already affirmed by Karl Popper (it is weak because he maintains the idea of theoretical progress directed to the truth of scientific theories). The "strong" form was sustained by Kuhn and Feyerabend, with their notion of incommensurability.
However, Kuhn was a moderate relativist and maintained the Kantian view that although reality is not directly knowable, it manifests itself "resisting" to our interpretations. On the contrary, Feyerabend completely reversed the relationship between observations and theories, introducing an "extra-strong" form of theory-ladenness in which "anything goes".
== Measurement outcomes ==
Van Fraassen distinguishes between observations, phenomena (observed entities) and appearances (the contents of measurement outcomes). An example of an appearance is the temperature of 38°C of a patient as measured using a thermometer. The number "38" is meaningless by itself unless we interpret it as the outcome of a measurement process. Such an interpretation implicitly assumes various other theses about how the thermometer was used, how thermometers work etc. All appearances are theory-laden in this sense. But in many cases this does not pose serious practical problems as long as the presumed theses are either correct or only contain mistakes irrelevant to the intended application.
== Problem of confirmation ==
Theory-ladenness is particularly relevant for the problem of confirmation of scientific theories. According to the scientific method, observational evidence is needed to develop scientific theories and to test their predictions. But if an observation is theory-laden then it already implicitly presumes various theses and therefore cannot act as neutral arbitrator between theories which affirm (or deny) the presumed theses. This is akin to the informal fallacy of begging the question.
== Problem of scientific consensus ==
Theory-ladenness also poses problems for scientific consensus. Different researchers may initially hold different background beliefs. Ideally, the observations they make in the course of their research would enable each of them to discern which of these beliefs are false. So they would eventually reach an agreement on the central issues. But their different background beliefs may cause them to make different observations despite the fact that both observe the same phenomena. In such a case the disagreement happens not just on the level of the supported theories but also on the level of the supporting observational evidence that is supposed to arbitrate between the theories. Under those circumstances, gathering more theory-laden evidence would only deepen the problem instead of solving it.
The problem of unresolved disagreements is more severe in the social sciences and philosophy than in the natural sciences. For example, disagreements in ethics or in metaphysics often end in a clash of the brute intuitions which act as evidence for or against the competing theories. But it is an open question to which extent these disagreements are due to theory-ladenness or other factors.
== See also ==
Confirmation holism
Duhem–Quine thesis
Observation
Metaphysics of presence
== References == | Wikipedia/Theory-ladenness |
A writing system comprises a set of symbols, called a script, as well as the rules by which the script represents a particular language. The earliest writing appeared during the late 4th millennium BC. Throughout history, each independently invented writing system gradually emerged from a system of proto-writing, where a small number of ideographs were used in a manner incapable of fully encoding language, and thus lacking the ability to express a broad range of ideas.
Writing systems are generally classified according to how its symbols, called graphemes, relate to units of language. Phonetic writing systems – which include alphabets and syllabaries – use graphemes that correspond to sounds in the corresponding spoken language. Alphabets use graphemes called letters that generally correspond to spoken phonemes. They are typically divided into three sub-types: Pure alphabets use letters to represent both consonant and vowel sounds, abjads generally only use letters representing consonant sounds, and abugidas use letters representing consonant–vowel pairs. Syllabaries use graphemes called syllabograms that represent entire syllables or moras. By contrast, logographic (or morphographic) writing systems use graphemes that represent the units of meaning in a language, such as its words or morphemes. Alphabets typically use fewer than 100 distinct symbols, while syllabaries and logographies may use hundreds or thousands respectively.
== Background: relationship with language ==
According to most contemporary definitions, writing is a visual and tactile notation representing language. As such, the use of writing by a community presupposes an analysis of the structure of language at some level. The symbols used in writing correspond systematically to functional units of either a spoken or signed language. This definition excludes a broader class of symbolic markings, such as drawings and maps. A text is any instance of written material, including transcriptions of spoken material. The act of composing and recording a text is referred to as writing, and the act of viewing and interpreting the text as reading.
The relationship between writing and language more broadly has been the subject of philosophical analysis as early as Aristotle (384–322 BC). While the use of language is universal across human societies, writing is not; writing emerged much more recently, and was independently invented in only a handful of locations throughout history. While most spoken languages have not been written, all written languages have been predicated on an existing spoken language. When those with signed languages as their first language read writing associated with a spoken language, this functions as literacy in a second, acquired language. A single language (e.g. Hindustani) can be written using multiple writing systems, and a writing system can also represent multiple languages. For example, Chinese characters have been used to write multiple languages throughout the Sinosphere – including the Vietnamese language from at least the 13th century, until their replacement with the Latin-based Vietnamese alphabet in the 20th century.
In the first several decades of modern linguistics as a scientific discipline, linguists often characterized writing as merely the technology used to record speech – which was treated as being of paramount importance, for what was seen as the unique potential for its study to further the understanding of human cognition.
== General terminology ==
While researchers of writing systems generally use some of the same core terminology, precise definitions and interpretations can vary by author, often depending on the theoretical approach being employed.
A grapheme is the basic functional unit of a writing system. Graphemes are generally defined as minimally significant elements which, when taken together, comprise the set of symbols from which texts may be constructed. All writing systems require a set of defined graphemes, collectively called a script. The concept of the grapheme is similar to that of the phoneme in the study of spoken languages. Likewise, as many sonically distinct phones may function as the same phoneme depending on the speaker, dialect, and context, many visually distinct glyphs (or graphs) may be identified as the same grapheme. These variant glyphs are known as the allographs of a grapheme: For example, the lowercase letter ⟨a⟩ may be represented by the double-storey |a| and single-storey |ɑ| shapes, or others written in cursive, block, or printed styles. The choice of a particular allograph may be influenced by the medium used, the writing instrument used, the stylistic choice of the writer, the preceding and succeeding graphemes in the text, the time available for writing, the intended audience, and the largely unconscious features of an individual's handwriting.
Orthography (lit. 'correct writing') refers to the rules and conventions for writing shared by a community, including the ordering of and relationship between graphemes. Particularly for alphabets, orthography includes the concept of spelling. For example, English orthography includes uppercase and lowercase forms for 26 letters of the Latin alphabet (with these graphemes corresponding to various phonemes), punctuation marks (mostly non-phonemic), and other symbols, such as numerals. Writing systems may be regarded as complete if they are able to represent all that may be expressed in the spoken language, while a partial writing system cannot represent the spoken language in its entirety.
== History ==
In each instance, writing emerged from systems of proto-writing, though historically most proto-writing systems did not produce writing systems. Proto-writing uses ideographic and mnemonic symbols to communicate, but lacks the capability to fully encode language. Examples include:
The Jiahu symbols (c. 7th millennium BC) carved into tortoise shells, found in 24 Neolithic graves excavated at Jiahu in northern China.
The Vinča symbols (c. 6th–5th millennia BC) found on artefacts of the Vinča culture of Central and Southeast Europe.
The Indus script (c. 2600 – c. 2000 BC) found on different types of artefacts produced by the Indus Valley Civilization on the Indian subcontinent.
Quipu (15th century AD), a system of knotted cords used as mnemonic devices by the Inca Empire in South America.
Writing has been invented independently multiple times in human history – first emerging between 3400 and 3200 BC as cuneiform, a system initially used to write the Sumerian language in southern Mesopotamia; it was later adapted to write Akkadian as its speakers spread throughout the region, with Akkadian writing appearing in significant quantities c. 2350 BC. Cuneiform was closely followed by Egyptian hieroglyphs. It is generally agreed that the two systems were invented independently from one another; both evolved from proto-writing systems with the earliest coherent texts dated c. 2600 BC. Chinese characters emerged independently in the Yellow River valley c. 1200 BC. There is no evidence of contact between China and the literate peoples of the Near East, and the Mesopotamian and Chinese approaches for representing sound and meaning are distinct. The Mesoamerican writing systems, including Olmec and the Maya script, were also invented independently.
With each independent invention of writing, the ideographs used in proto-writing were decoupled from the direct representation of ideas, and gradually came to represent words instead. This occurred via application of the rebus principle, where a symbol was appropriated to represent an additional word that happened to be similar in pronunciation to the word for the idea originally represented by the symbol. This allowed words without concrete visualizations to be represented by symbols for the first time; the gradual shift from ideographic symbols to those wholly representing language took place over centuries, and required the conscious analysis of a given language by those attempting to write it.
Alphabetic writing descends from previous morphographic writing, and first appeared before 2000 BC to write a Semitic language spoken in the Sinai Peninsula. Most of the world's alphabets either descend directly from this Proto-Sinaitic script, or were directly inspired by its design. Descendants include the Phoenician alphabet (c. 1050 BC), and its child in the Greek alphabet (c. 800 BC). The Latin alphabet, which descended from the Greek alphabet, is by far the most common script used by writing systems.
== Classification by basic linguistic unit ==
Writing systems are most often categorized according to what units of language a system's graphemes correspond to. At the most basic level, writing systems can be either phonographic (lit. 'sound writing') when graphemes represent units of sound in a language, or morphographic ('form writing') when graphemes represent units of meaning (such as words or morphemes). Depending on the author, the older term logographic ('word writing') is often used, either with the same meaning as morphographic, or specifically in reference to systems where the basic unit being written is the word. Recent scholarship generally prefers morphographic over logographic, with the latter seen as potentially vague or misleading – in part because systems usually operate on the level of morphemes, not words.
Many classifications define three primary categories, where phonographic systems are subdivided into syllabic and alphabetic (or segmental) systems. Syllabaries use symbols called syllabograms to represent syllables or moras. Alphabets use symbols called letters that correspond to spoken phonemes (or more technically, to diaphonemes). Alphabets are generally classified into three subtypes, with abjads having letters for consonants, pure alphabets having letters for both consonants and vowels, and abugidas having characters that correspond to consonant–vowel pairs. David Diringer proposed a five-fold classification of writing systems, comprising pictographic scripts, ideographic scripts, analytic transitional scripts, phonetic scripts, and alphabetic scripts.
In practice, writing systems are classified according to the primary type of symbols used, and typically include exceptional cases where symbols function differently. For example, logographs found within phonetic systems like English include the ampersand ⟨&⟩ and the numerals ⟨0⟩, ⟨1⟩, etc. – which correspond to specific words (and, zero, one, etc.) and not to the underlying sounds. Most writing systems can be described as mixed systems that feature elements of both phonography and morphography.
=== Logographic systems ===
A logogram is a character that represents a morpheme within a language. Chinese characters represent the only major logographic writing systems still in use: they have historically been used to write the varieties of Chinese, as well as Japanese, Korean, Vietnamese, and other languages of the Sinosphere. As each character represents a single unit of meaning, thousands are required to write all the words of a language. If the logograms do not adequately represent all meanings and words of a language, written language can be confusing or ambiguous to the reader.
Logograms are sometimes conflated with ideograms, symbols which graphically represent abstract ideas; most linguists now reject this characterization: Chinese characters are often semantic–phonetic compounds, which include a component related to the character's meaning, and a component that gives a hint for its pronunciation.
=== Syllabaries ===
A syllabary is a set of written symbols (called syllabograms) that represent either syllables or moras – a unit of prosody that is often but not always a syllable in length. Syllabaries are best suited to languages with relatively simple syllable structure, since a different symbol is needed for every syllable. Japanese, for example, contains about 100 moras, which are represented by moraic hiragana. By contrast, English features complex syllable structures with a relatively large inventory of vowels and complex consonant clusters – for a total of 15–16 thousand distinct syllables. Some syllabaries have larger inventories: the Yi script contains 756 different symbols.
=== Alphabets ===
An alphabet uses symbols (called letters) that correspond to the phonemes of a language, e.g. its vowels and consonants. However, these correspondences are rarely uncomplicated, and spelling is often mediated by other factors than just which sounds are used by a speaker. The word alphabet is derived from alpha and beta, the names for the first two letters in the Greek alphabet. An abjad is an alphabet whose letters only represent the consonantal sounds of a language. They were the first alphabets to develop historically, with most used to write Semitic languages, and originally deriving from the Proto-Sinaitic script. The morphology of Semitic languages is particularly suited to this approach, as the denotation of vowels is generally redundant. Optional markings for vowels may be used for some abjads, but are generally limited to applications like education. Many pure alphabets were derived from abjads through the addition of dedicated vowel letters, as with the derivation of the Greek alphabet from the Phoenician alphabet c. 800 BC. Abjad is the word for "alphabet" in Arabic, and analogously derives from the traditional order of letters in the Arabic alphabet ('alif, bā', jīm, dāl).
An abugida is a type of alphabet with symbols corresponding to consonant–vowel pairs, where basic symbols for each consonant are associated with an inherent vowel by default, and other possible vowels for each consonant are indicated via predictable modifications made to the basic symbols. In an abugida, there may be a sign for k with no vowel, but also one for ka (if a is the inherent vowel), and ke is written by modifying the ka sign in a way consistent with how la would be modified to get le. In many abugidas, modification consists of the addition of a vowel sign; other possibilities include rotation of the basic sign, or addition of diacritics.
While true syllabaries have one symbol per syllable and no systematic visual similarity, the graphic similarity in most abugidas stems from their origins as abjads – with added symbols comprising markings for different vowels added onto a pre-existing base symbol. The largest single group of abugidas is the Brahmic family of scripts, however, which includes nearly all the scripts used in India and Southeast Asia. The name abugida was derived by linguist Peter T. Daniels (b. 1951) from the first four characters of an order of the Geʽez script, which is used for certain Nilo-Saharan and Afro-Asiatic languages of Ethiopia and Eritrea.
=== Featural systems ===
Originally proposed as a category by Geoffrey Sampson (b. 1944), a featural system uses symbols representing sub-phonetic elements – e.g. those traits that can be used to distinguish between and analyse a language's phonemes, such as their voicing or place of articulation. The only prominent example of a featural system is the hangul script used to write Korean, where featural symbols are combined into letters, which are in turn joined into syllabic blocks. Many scholars, including John DeFrancis (1911–2009), reject a characterization of hangul as a featural system – with arguments including that Korean writers do not themselves think in these terms when writing – or question the viability of Sampson's category altogether.
As hangul was consciously created by literate experts, Daniels characterizes it as a "sophisticated grammatogeny" – a writing system intentionally designed for a specific purpose, as opposed to having evolved gradually over time. Other featural grammatogenies include shorthands developed by professionals and constructed scripts created by hobbyists and creatives, like the Tengwar script designed by J. R. R. Tolkien to write the Elven languages he also constructed. Many of these feature advanced graphic designs corresponding to phonological properties. The basic unit of writing in these systems can map to anything from phonemes to words. It has been shown that even the Latin script has sub-character features.
== Classification by graphical properties ==
=== Linearity ===
All writing is linear in the broadest sense – i.e., the spatial arrangement of symbols indicates the order in which they should be read. On a more granular level, systems with discontinuous marks like diacritics can be characterized as less linear than those without. In the initial historical distinction, linear writing systems (e.g. the Phoenician alphabet) generally form glyphs as a series of connected lines or strokes, while systems that generally use discrete, more pictorial marks (e.g. cuneiform) are sometimes termed non-linear. The historical abstraction of logographs into phonographs is often associated with a linearization of the script.
In Braille, raised bumps on the writing substrate are used to encode non-linear symbols. The original system – which Louis Braille (1809–1852) invented in order to allow people with visual impairments to read and write – used characters that corresponded to the letters of the Latin alphabet. Moreover, that Braille is equivalent to visual writing systems in function demonstrates that the phenomenon of writing is fundamentally spatial in nature, not merely visual.
=== Directionality and orientation ===
Writing systems may be characterized by how text is graphically divided into lines, which are to be read in sequence:
Axis
Whether lines of text are laid out as horizontal rows or vertical columns
Lining
How each line is positioned relative to the one previous on the medium – in practice only vertical scripts vary whether columns are read in a left- or rightward order, as all horizontal scripts sequence rows from top to bottom
Directionality
How individual lines are read – whether starting from the left or right on a horizontal axis, or from the top or bottom on a vertical axis
In left-to-right scripts (LTR), horizontal rows are sequenced from top to bottom on a page, with each row read from left to right. Right-to-left scripts (RTL), which use the opposite directionality, include the Arabic alphabet.
Egyptian hieroglyphs were written either left-to-right or right-to-left, with the animal and human glyphs turned to face the beginning of the line. The early alphabet did not have a fixed direction, and was written both vertically and horizontally; it was most commonly written boustrophedonically: starting in one horizontal direction, then turning at the end of the line and reversing direction.
The right-to-left direction of the Phoenician alphabet initially stabilized after c. 800 BC. Left-to-right writing has an advantage that, since most people are right-handed, the hand does not interfere with what is being written (which, when inked, may not have dried yet) as the hand is to the right side of the pen. The Greek alphabet and its successors settled on a left-to-right pattern, from the top to the bottom of the page. Other scripts, such as Arabic and Hebrew, came to be written right to left. Scripts that historically incorporate Chinese characters have traditionally been written vertically in columns arranged from right to left, while a horizontal direction from left to right was only widely adopted in the 20th century due to Western influence.
Several scripts used in the Philippines and Indonesia, such as Hanunoo, are traditionally written with lines moving away from the writer, from bottom to top, but are read left to right; ogham is written from bottom to top, commonly on the corner of a stone. The ancient Libyco-Berber alphabet was also written from bottom to top.
== See also ==
Bidirectional text
Complex text layout (CTL)
Defective script
Digraphia
Epigraphy
Formal language
ISO 15924
Pasigraphy
Penmanship
Palaeography
Script (Unicode)
Transcription (linguistics)
X-SAMPA
== Notes ==
== References ==
=== Sources ===
== Further reading ==
== External links ==
The World's Writing Systems – all 294 known writing systems, each with a typographic reference glyph and Unicode status | Wikipedia/Writing_systems |
Nature Geoscience is a monthly peer-reviewed scientific journal published by the Nature Publishing Group. The Chief Editor is Tamara Goldin, who took over from Heike Langenberg in February 2020. It was established in January 2008.
== Scope ==
The journal covers all aspects of the Earth sciences, including theoretical research, modelling, and field work. Significant related work in other fields, such as atmospheric sciences, geology, geophysics, climatology, oceanography, palaeontology, and space science, is also published.
== Abstracting and indexing ==
The journal is abstracted and indexed by:
CAB Abstracts
Chemical Abstracts Service/CASSI
Science Citation Index
Current Contents/Physical, Chemical & Earth Sciences
GeoRef
According to the Journal Citation Reports, the journal has a 2020 impact factor of 16.908.
== See also ==
List of scientific journals in earth and atmospheric sciences
== References ==
== External links ==
Official website | Wikipedia/Nature_Geoscience |
The theory of impetus, developed in the Middle Ages, attempts to explain the forced motion of a body, what it is, and how it comes about or ceases. It is important to note that in ancient and medieval times, motion was always considered absolute, relative to the Earth as the center of the universe.
The theory of impetus is an auxiliary or secondary theory of Aristotelian dynamics, put forth initially to explain projectile motion against gravity. Aristotelian dynamics of forced (in antiquity called “unnatural”) motion states that a body (without a moving soul) only moves when an external force is constantly driving it. The greater the force acting, the proportionally greater the speed of the body. If the force stops acting, the body immediately returns to the natural state of rest. As we know today, this idea is wrong. It also states—as clearly formulated by John of Jadun in his work Quaestiones super 8 libros Physicorum Aristotelis from 1586—that not only motion but also force is transmitted to the medium, such that this force propagates continuously from layer to layer of air, becoming weaker and weaker until it finally dies out. This is how the body finally comes to rest.
Although the medieval philosophers, beginning with John Philoponus, held to the intuitive idea that only a direct application of force could cause and maintain motion, they recognized that Aristotle's explanation of unnatural motion could not be correct. They therefore developed the concept of impetus. Impetus was understood to be a force inherent in a moving body that had previously been transferred to it by an external force during a previous direct contact.
The explanation of modern mechanics is completely different. First of all, motion is not absolute but relative, namely relative to a reference frame (observer), which in turn can move itself relative to another reference frame. For example, the speed of a bird flying relative to the earth is completely different than if you look at it from a moving car. Second, the observed speed of a body that is not subject to an external force never changes, regardless of who is observing it. The permanent state of a body is therefore uniform motion. Its continuity requires no external or internal force, but is based solely on the inertia of the body. If a force acts on a moving or stationary body, this leads to a change in the observed speed. The state of rest is merely a limiting case of motion. The term “impetus” as a force that maintains motion therefore has no equivalence in modern mechanics. At most, it comes close to the modern term “linear momentum” of a mass. This is because it is linear momentum as the product of mass and velocity that maintains motion due to the inertia of the mass (conservation of linear momentum). But momentum is not a force; rather, a force is the cause of a change in the momentum of a body, and vice versa.
After impetus was introduced by John Philoponus in the 6th century, and elaborated by Nur ad-Din al-Bitruji at the end of the 12th century. The theory was modified by Avicenna in the 11th century and Abu'l-Barakāt al-Baghdādī in the 12th century, before it was later established in Western scientific thought by Jean Buridan in the 14th century. It is the intellectual precursor to the concepts of inertia, momentum and acceleration in classical mechanics.
== Aristotelian theory ==
Aristotelian physics is the form of natural philosophy described in the works of the Greek philosopher Aristotle (384–322 BC). In his work Physics, Aristotle intended to establish general principles of change that govern all natural bodies, both living and inanimate, celestial and terrestrial – including all motion, quantitative change, qualitative change, and substantial change.
Aristotle describes two kinds of motion: "violent" or "unnatural motion", such as that of a thrown stone, in Physics (254b10), and "natural motion", such as of a falling object, in On the Heavens (300a20). In violent motion, as soon as the agent stops causing it, the motion stops also: in other words, the natural state of an object is to be at rest, since Aristotle does not address friction.
== Hipparchus' theory ==
In the 2nd century, Hipparchus assumed that the throwing force is transferred to the body at the time of the throw, and that the body dissipates it during the subsequent up-and-down motion of free fall. This is according to the Neoplatonist Simplicius of Cilicia, who quotes Hipparchus in his book Aristotelis De Caelo commentaria 264, 25 as follows: "Hipparchus says in his book On Bodies Carried Down by Their Weight that the throwing force is the cause of the upward motion of [a lump of] earth thrown upward as long as this force is stronger than that of the thrown body; the stronger the throwing force, the faster the upward motion. Then, when the force decreases, the upward motion continues at a decreased speed until the body begins to move downward under the influence of its own weight, while the throwing force still continues in some way. As this decreases, the velocity of the fall increases and reaches its highest value when this force is completely dissipated." Thus, Hipparchus does not speak of a continuous contact between the moving force and the moving body, or of the function of air as an intermediate carrier of motion, as Aristotle claims.
== Philoponan theory ==
In the 6th century, John Philoponus partly accepted Aristotle's theory that "continuation of motion depends on continued action of a force," but modified it to include his idea that the hurled body acquires a motive power or inclination for forced movement from the agent producing the initial motion and that this power secures the continuation of such motion. However, he argued that this impressed virtue was temporary: that it was a self-expending inclination, and thus the violent motion produced comes to an end, changing back into natural motion.
In his book On Aristotle Physics 641, 12; 641, 29; 642, 9 Philoponus first argues explicitly against Aristotle's explanation that a thrown stone, after leaving the hand, cannot be propelled any further by the air behind it. Then he continues: "Instead, some immaterial kinetic force must be imparted to the projectile by the thrower. Whereby the pushed air contributes either nothing or only very little to this motion. But if moving bodies are necessarily moved in this way, it is clear that the same process will take place much more easily if an arrow or a stone is thrown necessarily and against its tendency into empty space, and that nothing is necessary for this except the thrower." This last sentence is intended to show that in empty space—which Aristotle rejects—and contrary to Aristotle's opinion, a moving body would continue to move. It should be pointed out that Philoponus in his book uses two different expressions for impetus: kinetic capacity (dynamis) and kinetic force (energeia). Both expressions designate in his theory a concept, which is close to the today's concept of energy, but they are far away from the Aristotelian conceptions of potentiality and actuality.
Philoponus' theory of imparted force cannot yet be understood as a principle of inertia. For while he rightly says that the driving quality is no longer imparted externally but has become an internal property of the body, he still accepts the Aristotelian assertion that the driving quality is a force (power) that now acts internally and to which velocity is proportional. In modern physics since Newton, however, velocity is a quality that persists in the absence of forces.
== Ockham's and Marchia's theory ==
The first one to grasp this persistent motion by itself was William of Ockham. In his Commentary on the Sentences, Book 2, Question 26, M, written in 1318, he first argues: "If someone standing at point C were to fire a projectile aimed at point B, while another person standing at point F were to throw a projectile at point C, so that at some point M the two projectiles would meet, it would be necessary, according to the Aristotelian explanation, for the same portion of air at point M to be moved simultaneously in two different directions." The impossibility of this, according to Ockham, invalidates the Aristotelian explanation of the movement of projectiles. So Ockham goes on to say: "I say therefore that that which moves (ipsum movens) ... after the separation of the moving body from the original projector, is the body moved by itself (ipsum motum secundum se) and not by any power in it or relative to it (virtus absoluta in eo vel respectiva), ... ." It has been claimed by some historians that by rejecting the basic Aristotelian principle "Everything that moves is moved by something else." (Omne quod moventur ab alio movetur.), Ockham took the first step toward the principle of inertia.
Around 1320, Francis de Marchia developed a detailed and elaborate theory of his virtus derelicta. Marchia described virtus derelicta as force impressed on a projectile that gradually passes away and is consumed by the movement it generates. It is a form that is "not simply permanent, nor simply fluent, but almost medial", staying for some time in the body, but then fading away. This is different from Buridan's impetus (see below), which is a permanent state (res permanens) that is only diminished or destroyed by an opposing force—the resistance of the medium or the gravity of the projectile, which tends in a direction opposite to its motion. Buridan rightly says that without these opposing forces, the projectile would continue to move at constant speed forever.
== Iranian theories ==
In the 11th century, Avicenna (Ibn Sīnā) discussed Philoponus' theory in The Book of Healing, in Physics IV.14 he says:
When we independently verify the issue (of projectile motion), we find the most correct doctrine is the doctrine of those who think that the moved object acquires an inclination from the mover
Ibn Sīnā agreed that an impetus is imparted to a projectile by the thrower, but unlike Philoponus, who believed that it was a temporary virtue that would decline even in a vacuum, he viewed it as persistent, requiring external forces such as air resistance to dissipate it. Ibn Sina made distinction between 'force' and 'inclination' (called "mayl"), and argued that an object gained mayl when the object is in opposition to its natural motion. Therefore, he concluded that continuation of motion is attributed to the inclination that is transferred to the object, and that object will be in motion until the mayl is spent. He also claimed that a projectile in a vacuum would not stop unless it is acted upon, which is consistent with Newton's concept of inertia. This idea (which dissented from the Aristotelian view) was later described as "impetus" by Jean Buridan, who may have been influenced by Ibn Sina.
== Arabic theories ==
In the 12th century, Hibat Allah Abu'l-Barakat al-Baghdaadi adopted Philoponus' theory of impetus. In his Kitab al-Mu'tabar, Abu'l-Barakat stated that the mover imparts a violent inclination (mayl qasri) on the moved and that this diminishes as the moving object distances itself from the mover. Like Philoponus, and unlike Ibn Sina, al-Baghdaadi believed that the mayl self-extinguishes itself.
He also proposed an explanation of the acceleration of falling bodies where "one mayl after another" is successively applied, because it is the falling body itself which provides the mayl, as opposed to shooting a bow, where only one violent mayl is applied. According to Shlomo Pines, al-Baghdaadi's theory was
the oldest negation of Aristotle's fundamental dynamic law [namely, that a constant force produces a uniform motion], [and is thus an] anticipation in a vague fashion of the fundamental law of classical mechanics [namely, that a force applied continuously produces acceleration].
Jean Buridan and Albert of Saxony later refer to Abu'l-Barakat in explaining that the acceleration of a falling body is a result of its increasing impetus.
== Buridanist impetus ==
In the 14th century, Jean Buridan postulated the notion of motive force, which he named impetus.
When a mover sets a body in motion he implants into it a certain impetus, that is, a certain force enabling a body to move in the direction in which the mover starts it, be it upwards, downwards, sidewards, or in a circle. The implanted impetus increases in the same ratio as the velocity. It is because of this impetus that a stone moves on after the thrower has ceased moving it. But because of the resistance of the air (and also because of the gravity of the stone) which strives to move it in the opposite direction to the motion caused by the impetus, the latter will weaken all the time. Therefore the motion of the stone will be gradually slower, and finally the impetus is so diminished or destroyed that the gravity of the stone prevails and moves the stone towards its natural place. In my opinion one can accept this explanation because the other explanations prove to be false whereas all phenomena agree with this one. Buridan gives his theory a mathematical value: impetus = weight x velocity.
Buridan's pupil Dominicus de Clavasio in his 1357 De Caelo, as follows:
When something moves a stone by violence, in addition to imposing on it an actual force, it impresses in it a certain impetus. In the same way gravity not only gives motion itself to a moving body, but also gives it a motive power and an impetus, ...
Buridan's position was that a moving object would only be arrested by the resistance of the air and the weight of the body which would oppose its impetus. Buridan also maintained that impetus was proportional to speed; thus, his initial idea of impetus was similar in many ways to the modern concept of momentum. Buridan saw his theory as only a modification to Aristotle's basic philosophy, maintaining many other peripatetic views, including the belief that there was still a fundamental difference between an object in motion and an object at rest. Buridan also maintained that impetus could be not only linear, but also circular in nature, causing objects (such as celestial bodies) to move in a circle.
Buridan pointed out that neither Aristotle's unmoved movers nor Plato's souls are in the Bible, so he applied impetus theory to the eternal rotation of the celestial spheres by extension of a terrestrial example of its application to rotary motion in the form of a rotating millwheel that continues rotating for a long time after the originally propelling hand is withdrawn, driven by the impetus impressed within it. He wrote on the celestial impetus of the spheres as follows:
God, when He created the world, moved each of the celestial orbs as He pleased, and in moving them he impressed in them impetuses which moved them without his having to move them any more...And those impetuses which he impressed in the celestial bodies were not decreased or corrupted afterwards, because there was no inclination of the celestial bodies for other movements. Nor was there resistance which would be corruptive or repressive of that impetus.
However, by discounting the possibility of any resistance either due to a contrary inclination to move in any opposite direction or due to any external resistance, he concluded their impetus was therefore not corrupted by any resistance. Buridan also discounted any inherent resistance to motion in the form of an inclination to rest within the spheres themselves, such as the inertia posited by Averroes and Aquinas. For otherwise that resistance would destroy their impetus, as the anti-Duhemian historian of science Annaliese Maier maintained the Parisian impetus dynamicists were forced to conclude because of their belief in an inherent inclinatio ad quietem or inertia in all bodies.
This raised the question of why the motive force of impetus does not therefore move the spheres with infinite speed. One impetus dynamics answer seemed to be that it was a secondary kind of motive force that produced uniform motion rather than infinite speed, rather than producing uniformly accelerated motion like the primary force did by producing constantly increasing amounts of impetus. However, in his Treatise on the heavens and the world in which the heavens are moved by inanimate inherent mechanical forces, Buridan's pupil Oresme offered an alternative Thomist inertial response to this problem. His response was to posit a resistance to motion inherent in the heavens (i.e. in the spheres), but which is only a resistance to acceleration beyond their natural speed, rather than to motion itself, and was thus a tendency to preserve their natural speed.
Buridan's thought was followed up by his pupil Albert of Saxony (1316–1390), by writers in Poland such as John Cantius, and the Oxford Calculators. Their work in turn was elaborated by Nicole Oresme who pioneered the practice of demonstrating laws of motion in the form of graphs.
== The tunnel experiment and oscillatory motion ==
The Buridan impetus theory developed one of the most important thought experiments in the history of science, the 'tunnel-experiment'. This experiment incorporated oscillatory and pendulum motion into dynamical analysis and the science of motion for the first time. It also established one of the important principles of classical mechanics. The pendulum was crucially important to the development of mechanics in the 17th century. The tunnel experiment also gave rise to the more generally important axiomatic principle of Galilean, Huygenian and Leibnizian dynamics, namely that a body rises to the same height from which it has fallen, a principle of gravitational potential energy. As Galileo Galilei expressed this fundamental principle of his dynamics in his 1632 Dialogo:
The heavy falling body acquires sufficient impetus [in falling from a given height] to carry it back to an equal height.
This imaginary experiment predicted that a cannonball dropped down a tunnel going straight through the Earth's centre and out the other side would pass the centre and rise on the opposite surface to the same height from which it had first fallen, driven upwards by the gravitationally created impetus it had continually accumulated in falling to the centre. This impetus would require a violent motion correspondingly rising to the same height past the centre for the now opposing force of gravity to destroy it all in the same distance which it had previously required to create it. At this turning point the ball would then descend again and oscillate back and forth between the two opposing surfaces about the centre infinitely in principle. The tunnel experiment provided the first dynamical model of oscillatory motion, specifically in terms of A-B impetus dynamics.
This thought-experiment was then applied to the dynamical explanation of a real world oscillatory motion, namely that of the pendulum. The oscillating motion of the cannonball was compared to the motion of a pendulum bob by imagining it to be attached to the end of an immensely long cord suspended from the vault of the fixed stars centred on the Earth. The relatively short arc of its path through the distant Earth was practically a straight line along the tunnel. Real world pendula were then conceived of as just micro versions of this 'tunnel pendulum', but with far shorter cords and bobs oscillating above the Earth's surface in arcs corresponding to the tunnel as their oscillatory midpoint was dynamically assimilated to the tunnel's centre.
Through such 'lateral thinking', its lateral horizontal motion that was conceived of as a case of gravitational free-fall followed by violent motion in a recurring cycle, with the bob repeatedly travelling through and beyond the motion's vertically lowest but horizontally middle point that substituted for the Earth's centre in the tunnel pendulum. The lateral motions of the bob first towards and then away from the normal in the downswing and upswing become lateral downward and upward motions in relation to the horizontal rather than to the vertical.
The orthodox Aristotelians saw pendulum motion as a dynamical anomaly, as 'falling to rest with difficulty.' Thomas Kuhn wrote in his 1962 The Structure of Scientific Revolutions on the impetus theory's novel analysis it was not falling with any dynamical difficulty at all in principle, but was rather falling in repeated and potentially endless cycles of alternating downward gravitationally natural motion and upward gravitationally violent motion. Galileo eventually appealed to pendulum motion to demonstrate that the speed of gravitational free-fall is the same for all unequal weights by virtue of dynamically modelling pendulum motion in this manner as a case of cyclically repeated gravitational free-fall along the horizontal in principle.
The tunnel experiment was a crucial experiment in favour of impetus dynamics against both orthodox Aristotelian dynamics without any auxiliary impetus theory and Aristotelian dynamics with its H-P variant. According to the latter two theories, the bob cannot possibly pass beyond the normal. In orthodox Aristotelian dynamics there is no force to carry the bob upwards beyond the centre in violent motion against its own gravity that carries it to the centre, where it stops. When conjoined with the Philoponus auxiliary theory, in the case where the cannonball is released from rest, there is no such force because either all the initial upward force of impetus originally impressed within it to hold it in static dynamical equilibrium has been exhausted, or if any remained it would act in the opposite direction and combine with gravity to prevent motion through and beyond the centre. The cannonball being positively hurled downwards could not possibly result in an oscillatory motion either. Although it could then possibly pass beyond the centre, it could never return to pass through it and rise back up again. It would be logically possible for it to pass beyond the centre if upon reaching the centre some of the constantly decaying downward impetus remained and still was sufficiently stronger than gravity to push it beyond the centre and upwards again, eventually becoming weaker than gravity. The ball would then be pulled back towards the centre by its gravity but could not then pass beyond the centre to rise up again, because it would have no force directed against gravity to overcome it. Any possibly remaining impetus would be directed 'downwards' towards the centre, in the same direction it was originally created.
Thus pendulum motion was dynamically impossible for both orthodox Aristotelian dynamics and also for H-P impetus dynamics on this 'tunnel model' analogical reasoning. It was predicted by the impetus theory's tunnel prediction because that theory posited that a continually accumulating downwards force of impetus directed towards the centre is acquired in natural motion, sufficient to then carry it upwards beyond the centre against gravity, and rather than only having an initially upwards force of impetus away from the centre as in the theory of natural motion. So the tunnel experiment constituted a crucial experiment between three alternative theories of natural motion.
Impetus dynamics was to be preferred if the Aristotelian science of motion was to incorporate a dynamical explanation of pendulum motion. It was also to be preferred more generally if it was to explain other oscillatory motions, such as the to and fro vibrations around the normal of musical strings in tension, such as those of a guitar. The analogy made with the gravitational tunnel experiment was that the tension in the string pulling it towards the normal played the role of gravity, and thus when plucked (i.e. pulled away from the normal) and then released, it was the equivalent of pulling the cannonball to the Earth's surface and then releasing it. Thus the musical string vibrated in a continual cycle of the alternating creation of impetus towards the normal and its destruction after passing through the normal until this process starts again with the creation of fresh 'downward' impetus once all the 'upward' impetus has been destroyed.
This positing of a dynamical family resemblance of the motions of pendula and vibrating strings with the paradigmatic tunnel-experiment, the origin of all oscillations in the history of dynamics, was one of the greatest imaginative developments of medieval Aristotelian dynamics in its increasing repertoire of dynamical models of different kinds of motion.
Shortly before Galileo's theory of impetus, Giambattista Benedetti modified the growing theory of impetus to involve linear motion alone:
... [Any] portion of corporeal matter which moves by itself when an impetus has been impressed on it by any external motive force has a natural tendency to move on a rectilinear, not a curved, path.
Benedetti cites the motion of a rock in a sling as an example of the inherent linear motion of objects, forced into circular motion.
== See also ==
Conatus
Physics in the medieval Islamic world
History of science
== References and footnotes ==
== Bibliography ==
Clagett, Marshall (1959). Science of Mechanics in the Middle Ages. University of Wisconsin Press.
Crombie, Alistair Cameron (1959). The History of Science From Augustine to Galileo. Dover Publications. ISBN 9780486288505. {{cite book}}: ISBN / Date incompatibility (help)
Duhem, Pierre. [1906–13]: Etudes sur Leonard de Vinci
Duhem, Pierre, History of Physics, Section IX, XVI and XVII in The Catholic Encyclopedia[1]
Drake, Stillman; Drabkin, I. E. (1969). Mechanics in Sixteenth Century Italy. University of Wisconsin Press. ISBN 9781101203736.
Galilei, Galileo (1590). De Motu. translated in On Motion and on Mechanics. Drabkin & Drake.
Galilei, Galileo (1953). Dialogo. Translated by Stillman Drake. University of California Press.
Galilei, Galileo (1974). Discorsi. Translated by Stillman Drake.
Grant, Edward (1996). The Foundations of Modern Science in the Middle Ages. Cambridge University Press. ISBN 0-521-56137-X.
Hentschel, Klaus (2009). "Zur Begriffs- und Problemgeschichte von 'Impetus'". In Yousefi, Hamid Reza; Dick, Christiane (eds.). Das Wagnis des Neuen. Kontexte und Restriktionen der Wissenschaft. Nordhausen: Bautz. pp. 479–499. ISBN 978-3-88309-507-3.
Koyré, Alexandre. Galilean Studies.
Kuhn, Thomas (1957). The Copernican Revolution.
Kuhn, Thomas (1970) [1962]. The Structure of Scientific Revolutions.
Moody, E. A. (1966). "Galileo and his precursors". In Golino (ed.). Galileo Reappraised. University of California Press.
Moody, E. A. (1951). "Galileo and Avempace: The Dynamics of the Leaning Tower Experiment". Journal of the History of Ideas. 12 (2): 163–193. doi:10.2307/2707514. JSTOR 2707514. | Wikipedia/Theory_of_impetus |
The Houston Museum of Natural Science (abbreviated as HMNS) is a natural history museum located on the northern border of Hermann Park in Houston, Texas, United States. The museum was established in 1909 by the Houston Museum and Scientific Society, an organization whose goals were to provide a free institution for the people of Houston focusing on education and science. The museum complex consists of a central facility with four floors of natural science halls and exhibits, the Burke Baker Planetarium, the Cockrell Butterfly Center, and the Wortham Giant Screen Theatre (formerly known as the Wortham IMAX Theatre). In 2022, the museum received 1,520,000 visitors, making it the seventh most-visited museum in the United States and the third most-visited science museum in the U.S.. HMNS is the most visited museum in the country outside of the New York City or Washington, D.C. metropolitan areas. Much of the museum's popularity is attributed to its large number of special or guest exhibits.
== History ==
The initial museum organization was called the Houston Museum and Scientific Society, Inc., and was created in 1909. The museum's primary collection was acquired between 1914 and 1930. This included the purchase of a natural-history collection assembled by Henry Philemon Attwater and a donation from collector John Milsaps, the latter of which formed the core of the museum's gem and mineral collection. First housed in Houston's city auditorium, the collection was subsequently housed in the Central Library for seven years, and then at a site in the Houston Zoo in 1929. The museum's now wide-ranging education programs began in 1947 and, in its second year, hosted 12,000 children.
The museum was officially renamed the Houston Museum of Natural Science in 1960. Construction of the current facility in Hermann Park began in 1964 and was completed in 1969.
By the 1980s, the museum's permanent displays included a dinosaur exhibit, a space museum, and exhibits on geology, biology, petroleum science, technology, and geography. In 1988, the Challenger Learning Center was opened in memory of the Space Shuttle Challenger crew members that were lost during the shuttle's tenth mission. The center's aim is to teach visitors about space exploration. The Wortham IMAX Theatre and the offsite George Observatory were opened in 1989.
Museum attendance was more than one million visitors in 1990. HMNS trustees determined that new state-of-the-art facilities, additional space, and renovations to current exhibits were needed because of the increased attendance. Between 1991 and 1994, a number of exhibit halls were renovated and the expansion of the Sterling Hall of Research was completed. The Cockrell Butterfly Center and the Brown Hall of Entomology opened in July 1994.
In March 2007, the museum opened the HMNS Woodlands X-ploration Station, located in the Woodlands Mall. The facility was home to an interactive Dig Pit, where children could excavate a mock Triceratops, a variety of living exhibits, fossils, and minerals. The Woodlands location closed on September 7, 2009, less than a month before HMNS opened a satellite museum in Sugar Land, Texas.
HMNS celebrated its 100th year in 2009. During that year, the museum offered a multitude of family programs, lectures, free events, and kids' classes as part of the "Fun Hundred" celebration.
On October 3, 2009, HMNS opened its satellite museum in Telfair, Sugar Land. The building and surrounding land that became HMNS at Sugar Land was once part of the Central Unit, a Texas Department of Criminal Justice prison that had been unoccupied for several decades.
In March 2012, the Wortham IMAX Theatre was converted from 70 mm film to 3D digital and renamed the Wortham Giant Screen Theatre.
In June 2012, HMNS opened a new 230,000-square-foot (21,000 m2) wing to house its paleontology hall, more than doubling the size of the original museum. Paleoartist, Julius Csotonyi, created fourteen murals based closely on concept drawings by HMNS Curator of Paleontology, Robert Bakker, for the new paleontology hall. The Morian Hall of Paleontology contains more than 60 large skeleton mounts, including three Tyrannosaurus rex and three large Quetzalcoatlus.
== Permanent Exhibits ==
The Foucault pendulum, demonstrating the Earth's rotation. The length of the pendulum's cable is over 60 feet (18 m) long.
Cullen Hall of Gems & Minerals, featuring a large exhibit of over 750 crystallized mineral specimens and rare gemstones.
Lester and Sue Smith Gem Vault, showcasing some of the most exquisite finely cut gems in jewelry.
Farish Hall of Texas Wildlife exhibits animals and wildlife native to Texas. The hall contains a video wall that displays the plants, animals and topography of the seven biotic regions of the state.
Evelyn and Herbert Frensley Hall of African Wildlife, a display of taxidermied animals, including one of only two okapis exhibited in North America. Opening in 1969, the hall allows visitors to explore the seven biomes of the continent of Africa. Contains over 120 specimens, including 42 species of birds and 28 species of mammals are on display.
Strake Hall of Malacology, with many specimens of mollusks.
Morian Hall of Paleontology, the largest paleontology hall in the United States. Contains over 60 major skeleton mounts, including three Tyrannosaurus rex, a Diplodocus and the most complete Triceratops skeleton ever discovered. It also houses one of the largest trilobite collections in existence. Robert Bakker serves as Curator of Paleontology.
John P. McGovern Hall of the Americas, showing more than 50 cultures worth of pre-Columbian archaeological artifacts.
Welch Chemistry Hall, with interactive chemistry related displays and a periodic table of elements with a sample of each element.
Wiess Energy Hall, with displays themed around energetics, petroleum geology, and oil exploration. Renovated and expanded in 2017, the hall consists of 16 sections, including a working replica of an offshore drilling rig drill floor, a 15K resolution video depicting the history of energy, the "Geovator" (a simulated trip into the rock beneath Houston and back in time to the Cretaceous Period), the "Eagle Ford Shale Experience" (a simulated journey to Karnes County, TX, to experience the hydraulic fracturing of an oil well from inside the cracked rock), "Energy City," (a 1/150th scale white model depicting the entire energy value chain brought to life through projection mapping using 32 laser projectors), and Renewable and Future Energy Sources.
Hall of Ancient Egypt opened in May 2013 and contains many millennia-old artifacts and features recreations of Egyptian temples and mummies from this ancient primary civilization.
Cockrell Sundial opened in 1989 and is one of the world's largest sundials. It includes lenses on a special chrome ball on top of the gnomon so that at solar noon on the equinoxes and solstices, sunlight shines through and casts an image of the Sun. Large sunspots can be seen by holding a white card in the beam and moving until it is focus.
Earth Forum, which opened in 2002, is a computer-aided and hands-on exhibit teaching about Earth and its processes. The "Earth Update" Archived 2018-10-15 at the Wayback Machine software was developed by Rice University with NASA funding.
== Facilities ==
Burke Baker Planetarium presents a range of science and astronomy shows. As of 2016, the planetarium is equipped with the Digistar 5 fulldome projection system. It is one of the first 8k planetariums in the United States.
Originally opened in 1969 with a Spitz Space Transit Planetarium, the Planetarium upgraded to an Evans & Sutherland Digistar 1 vector display in 1988, and was the first in the U.S. and third in the world to adopt multiple-projector digital image capability using the Sky-Skan SkyVision system in 1998. That allowed it to show fulldome movies, many of which were created by HMNS staff. Since 2004 its outreach program, "Discovery Dome", takes the planetarium experience on the road, reaching over 40,000 students per year in classrooms and special events in portable digital domes.
Cockrell Butterfly Center, a butterfly zoo located in museum complex. Opened in 1994, the center is housed in a three-story glass building filled with tropical plants and butterflies. The center exhibits a large range of live butterflies, including the migratory monarchs and their tropical cousins. The Cockrell Butterfly Center was reopened in May 2007 after being overhauled to make the exhibit more interactive; there are now games for children and a live insect zoo in the Brown Hall of Entomology.
Wortham Giant Screen Theatre, a 394-seat theater presenting various educational films in 4K digital with advanced 3D technology on its 60 by 80 feet (18 by 24 m) screen.
George Observatory, an astronomy observatory equipped with three domed telescopes, including a 36-inch (910 mm) Gueymard Research Telescope and a solar telescope. The facility is located south of Sugar Land, Texas, at Brazos Bend State Park. The observatory also houses a portion of the Challenger Learning Center for Space Science Education.
== References ==
=== Bibliography ===
Csotonyi, Julius, and Steve White. (2014). The Paleoart of Julius Csotonyi. Titan Books. ISBN 978-1781169124.
Sumners, Carolyn, and Patricia Reiff, "Creating Fulldome Experiences in the new Digital Planetarium", NASA Office of Space Science Education and Public Outreach Conference, ASP Conference Series Volume 319, 2004, ISBN 1-58381-181-8.
White, Steve. (2014). Dinosaur Art: The World's Greatest Paleoart. Titan Books. ISBN 978-0857685841.
Wilson, Wendell E., Joel A. Bartsch, and Mark Mauthner. (2004). Masterpieces of the Mineral World: Treasures from the Houston Museum of Natural Science. The Mineralogical Record in association with Harry N. Abrams, Inc. ISBN 978-0810967519.
== External links ==
Houston Museum of Natural Science
Houston Museum of Natural Science at the Wayback Machine (archive index)
Houston Museum of Natural Science at Google Cultural Institute
Challenger Center Organization | Wikipedia/Houston_Museum_of_Natural_Science |
The feminist method is a means of conducting investigations and generating theory from an explicitly feminist standpoint. Feminist methodologies are varied, but tend to have a few common aims or characteristics, including seeking to overcome biases in research, bringing about social change, displaying human diversity, and acknowledging the position of the researcher. Questioning normal scientific reasoning is another form of the feminist method.
Each of these methods must consist of different parts including: collection of evidence, testing of theories, presentation of data, and room for rebuttals. How research is scientifically backed up affects the results. Like consciousness raising, some feminist methods affect the collective emotions of women, when things like political statistics are more of a structural result When knowledge is either constructed by experiences, or discovered, it needs to both be reliable and valid.
Strong feminist supporters of this are Nancy Hartsock, Hilary Rose, and finally Sandra Harding. Feminist sociologists have made important contributions to this debate as they began to criticize positivism as a philosophical framework and, more specifically, its most acute methodological instrument—that of quantitative methods for its practice of detached and objective scientific research and the objectification of research subjects (Graham 1983b; Reinharz 1979).
More recently, feminist scholars have argued that quantitative methods are compatible with a feminist approach, so long as they are attentive to feminist theory. These methodological critiques were well placed against a backdrop of feminist scholarship struggling to find a place for alternative values within the academy. Such concerns emerged from a sense of despair and anger that knowledge, both academic and popular, was based on men's lives, male ways of thinking, and directed toward the problems articulated by men. Dorothy Smith (1974) argued that "sociology ... has been based on and built up within the male social universe".
== Objectivity and the construction of the Other ==
Feminist methods have, in large part, been scaffolded as a rebuttal to existing research methods that operate under imperialist, racist, and patriarchal assumptions about the research subject. By pointing out the biased perspectives and assumptions of researchers, feminist scholars work to elucidate the ways in which the idea of objectivity has operated merely as a stand-in for the white, male perspective, and how feminist methods, in contrast, work to produce knowledge in which “the researcher appears to us not as an invisible, anonymous voice of authority, but as a real, historical individual with concrete, specific desires and interests.”
Also inherent in the traditional researcher-subject relationship is the subject-object relationship, for the researcher becomes the autonomous subject when they study other humans as objects, as in this case the “subject” is ironically objectified through the process of scientific investigation, which does not take into account their agency or the will of their community. Subjects are also simultaneously “Othered” by Western researchers who exotify their ways of life through “a Western discourse about the Other which is supported by ‘institutions, vocabulary, scholarship, imagery, doctrines, even colonial bureaucracies and colonial styles.’”
Reinharz therefore posits that the destruction of the Other and the remodeling of the traditional subject-object relationship must occur simultaneously through explicit engagement with three different actors in feminist research: the researcher, the reader, and the people being studied. In this way, productive, feminist methods attempt to “demystify” and “decolonize” research through recognizing how traditional methods construct the Other and are cloaked in a false objectivity, and subsequently to deconstruct these narratives in order to “talk more creatively about research with particular groups and communities – women, the economically oppressed, ethnic minorities and indigenous peoples.”
== Questioning biological sex as a scientific construct ==
Through questioning science Anne Fausto-Sterling came up with alternatives to the concept of having only two sexes, male and female. She argues that through biological development there is a possibility of having five sexes instead of two. She believes there are male, female, merm (male pseudohermaphrodites, i.e. when testicular tissue is present), ferm (female pseudohermaphrodites, i.e. when ovarian tissue is present), and herm (true hermaphrodites, i.e. when both testicular and ovarian tissue is present).
== Emotion ==
Alison Jaggar disputes the dichotomy between reason and emotion and argues that rationality needs emotion. She states emotions are normally associated with women and rationality is associated with men. She also claims that there are many theories as to the origins of emotions, and in the long run listening to emotions might lead to better decisions.
== References == | Wikipedia/Feminist_method |
The term citizen science (synonymous to terms like community science, crowd science, crowd-sourced science, civic science, participatory monitoring, or volunteer monitoring) is research conducted with participation from the general public, or amateur/nonprofessional researchers or participants of science, social science and many other disciplines. There are variations in the exact definition of citizen science, with different individuals and organizations having their own specific interpretations of what citizen science encompasses. Citizen science is used in a wide range of areas of study including ecology, biology and conservation, health and medical research, astronomy, media and communications and information science.
There are different applications and functions of "citizen science" in research projects. Citizen science can be used as a methodology where public volunteers help in collecting and classifying data, improving the scientific community's capacity. Citizen science can also involve more direct involvement from the public, with communities initiating projects researching environment and health hazards in their own communities.
Participation in citizen science projects also educates the public about the scientific process and increases awareness about different topics. Some schools have students participate in citizen science projects for this purpose as a part of the teaching curriculums.
== Background ==
The first use of the term "citizen science" can be found in a January 1989 issue of MIT Technology Review, which featured three community-based labs studying environmental issues. In the 21st century, the number of citizen science projects, publications, and funding opportunities has increased. Citizen science has been used more over time, a trend helped by technological advancements. Digital citizen science platforms, such as Zooniverse and iNaturalist, store large amounts of data for many projects and are a place where volunteers can learn how to contribute to projects. For some projects, participants are instructed to collect and enter data, such as what species they observed, into large digital global databases. For other projects, participants help classify data on digital platforms. Citizen science data is also being used to develop machine learning algorithms. An example is using volunteer-classified images to train machine learning algorithms to identify species. While global participation and global databases are found on online platforms, not all locations always have the same amount of data from contributors. Concerns over potential data quality issues, such as measurement errors and biases, in citizen science projects are recognized in the scientific community and there are statistical solutions and best practices available which can help.
== Definition ==
The term "citizen science" has multiple origins, as well as differing concepts. "Citizen" is used in the general sense, as meaning in "citizen of the world", or the general public, rather than the legal term citizen of sovereign countries. It was first defined independently in the mid-1990s by Rick Bonney in the United States and Alan Irwin in the United Kingdom. Alan Irwin, a British sociologist, defines citizen science as "developing concepts of scientific citizenship which foregrounds the necessity of opening up science and science policy processes to the public". Irwin sought to reclaim two dimensions of the relationship between citizens and science: 1) that science should be responsive to citizens' concerns and needs; and 2) that citizens themselves could produce reliable scientific knowledge. The American ornithologist Rick Bonney, unaware of Irwin's work, defined citizen science as projects in which nonscientists, such as amateur birdwatchers, voluntarily contributed scientific data. This describes a more limited role for citizens in scientific research than Irwin's conception of the term.
The terms citizen science and citizen scientists entered the Oxford English Dictionary (OED) in June 2014. "Citizen science" is defined as "scientific work undertaken by members of the general public, often in collaboration with or under the direction of professional scientists and scientific institutions". "Citizen scientist" is defined as: (a) "a scientist whose work is characterized by a sense of responsibility to serve the best interests of the wider community (now rare)"; or (b) "a member of the general public who engages in scientific work, often in collaboration with or under the direction of professional scientists and scientific institutions; an amateur scientist". The first use of the term "citizen scientist" can be found in the magazine New Scientist in an article about ufology from October 1979.
Muki Haklay cites, from a policy report for the Wilson Center entitled "Citizen Science and Policy: A European Perspective", an alternate first use of the term "citizen science" by R. Kerson in the magazine MIT Technology Review from January 1989. Quoting from the Wilson Center report: "The new form of engagement in science received the name 'citizen science'. The first recorded example of the use of the term is from 1989, describing how 225 volunteers across the US collected rain samples to assist the Audubon Society in an acid-rain awareness raising campaign."
A Green Paper on Citizen Science was published in 2013 by the European Commission's Digital Science Unit and Socientize.eu, which included a definition for citizen science, referring to "the general public engagement in scientific research activities when citizens actively contribute to science either with their intellectual effort or surrounding knowledge or with their tools and resources. Participants provide experimental data and facilities for researchers, raise new questions and co-create a new scientific culture."
Citizen science may be performed by individuals, teams, or networks of volunteers. Citizen scientists often partner with professional scientists to achieve common goals. Large volunteer networks often allow scientists to accomplish tasks that would be too expensive or time-consuming to accomplish through other means.
Many citizen-science projects serve education and outreach goals. These projects may be designed for a formal classroom environment or an informal education environment such as museums.
Citizen science has evolved over the past four decades. Recent projects place more emphasis on scientifically sound practices and measurable goals for public education. Modern citizen science differs from its historical forms primarily in the access for, and subsequent scale of, public participation; technology is credited as one of the main drivers of the recent explosion of citizen science activity.
In March 2015, the Office of Science and Technology Policy published a factsheet entitled "Empowering Students and Others through Citizen Science and Crowdsourcing". Quoting: "Citizen science and crowdsourcing projects are powerful tools for providing students with skills needed to excel in science, technology, engineering, and math (STEM). Volunteers in citizen science, for example, gain hands-on experience doing real science, and in many cases take that learning outside of the traditional classroom setting". The National Academies of Science cites SciStarter as a platform offering access to more than 2,700 citizen science projects and events, as well as helping interested parties access tools that facilitate project participation.
In May 2016, a new open-access journal was started by the Citizen Science Association along with Ubiquity Press called Citizen Science: Theory and Practice (CS:T&P). Quoting from the editorial article titled "The Theory and Practice of Citizen Science: Launching a New Journal", "CS:T&P provides the space to enhance the quality and impact of citizen science efforts by deeply exploring the citizen science concept in all its forms and across disciplines. By examining, critiquing, and sharing findings across a variety of citizen science endeavors, we can dig into the underpinnings and assumptions of citizen science and critically analyze its practice and outcomes."
In February 2020, Timber Press, an imprint of Workman Publishing Company, published The Field Guide to Citizen Science as a practical guide for anyone interested in getting started with citizen science.
=== Alternative definitions ===
Other definitions for citizen science have also been proposed. For example, Bruce Lewenstein of Cornell University's Communication and S&TS departments describes three possible definitions:
The participation of nonscientists in the process of gathering data according to specific scientific protocols and in the process of using and interpreting that data.
The engagement of nonscientists in true decision-making about policy issues that have technical or scientific components.
The engagement of research scientists in the democratic and policy process.
Scientists and scholars who have used other definitions include Frank N. von Hippel, Stephen Schneider, Neal Lane and Jon Beckwith. Other alternative terminologies proposed are "civic science" and "civic scientist".
Further, Muki Haklay offers an overview of the typologies of the level of citizen participation in citizen science, which range from "crowdsourcing" (level 1), where the citizen acts as a sensor, to "distributed intelligence" (level 2), where the citizen acts as a basic interpreter, to "participatory science", where citizens contribute to problem definition and data collection (level 3), to "extreme citizen science", which involves collaboration between the citizen and scientists in problem definition, collection and data analysis.
A 2014 Mashable article defines a citizen scientist as: "Anybody who voluntarily contributes his or her time and resources toward scientific research in partnership with professional scientists."
In 2016, the Australian Citizen Science Association released their definition, which states "Citizen science involves public participation and collaboration in scientific research with the aim to increase scientific knowledge."
In 2020, a group of birders in the Pacific Northwest of North America, eBird Northwest, has sought to rename "citizen science" to the use of "community science", "largely to avoid using the word 'citizen' when we want to be inclusive and welcoming to any birder or person who wants to learn more about bird watching, regardless of their citizen status."
=== Related fields ===
In a Smart City era, Citizen Science relies on various web-based tools, such as WebGIS, and becomes Cyber Citizen Science. Some projects, such as SETI@home, use the Internet to take advantage of distributed computing. These projects are generally passive. Computation tasks are performed by volunteers' computers and require little involvement beyond initial setup. There is disagreement as to whether these projects should be classified as citizen science.
The astrophysicist and Galaxy Zoo co-founder Kevin Schawinski stated: "We prefer to call this [Galaxy Zoo] citizen science because it's a better description of what you're doing; you're a regular citizen but you're doing science. Crowd sourcing sounds a bit like, well, you're just a member of the crowd and you're not; you're our collaborator. You're pro-actively involved in the process of science by participating."
Compared to SETI@home, "Galaxy Zoo volunteers do real work. They're not just passively running something on their computer and hoping that they'll be the first person to find aliens. They have a stake in science that comes out of it, which means that they are now interested in what we do with it, and what we find."
Citizen policy may be another result of citizen science initiatives. Bethany Brookshire (pen name SciCurious) writes: "If citizens are going to live with the benefits or potential consequences of science (as the vast majority of them will), it's incredibly important to make sure that they are not only well informed about changes and advances in science and technology, but that they also ... are able to ... influence the science policy decisions that could impact their lives." In "The Rightful Place of Science: Citizen Science", editors Darlene Cavalier and Eric Kennedy highlight emerging connections between citizen science, civic science, and participatory technology assessment.
=== Benefits and limitations ===
The general public's involvement in scientific projects has become a means of encouraging curiosity and greater understanding of science while providing an unprecedented engagement between professional scientists and the general public. In a research report published by the U.S. National Park Service in 2008, Brett Amy Thelen and Rachel K. Thiet mention the following concerns, previously reported in the literature, about the validity of volunteer-generated data:
Some projects may not be suitable for volunteers, for instance, when they use complex research methods or require a great deal of (often repetitive) work.
If volunteers lack proper training in research and monitoring protocols, the data they collect might introduce bias into the dataset.
The question of data accuracy, in particular, remains open. John Losey, who created the Lost Ladybug citizen science project, has argued that the cost-effectiveness of citizen science data can outweigh data quality issues, if properly managed.
In December 2016, authors M. Kosmala, A. Wiggins, A. Swanson and B. Simmons published a study in the journal Frontiers in Ecology and the Environment called "Assessing Data Quality in Citizen Science". The abstract describes how ecological and environmental citizen science projects have enormous potential to advance science. Citizen science projects can influence policy and guide resource management by producing datasets that are otherwise not feasible to generate. In the section "In a Nutshell" (pg3), four condensed conclusions are stated. They are:
They conclude that as citizen science continues to grow and mature, a key metric of project success they expect to see will be a growing awareness of data quality. They also conclude that citizen science will emerge as a general tool helping "to collect otherwise unobtainable high-quality data in support of policy and resource management, conservation monitoring, and basic science."
A study of Canadian lepidoptera datasets published in 2018 compared the use of a professionally curated dataset of butterfly specimen records with four years of data from a citizen science program, eButterfly. The eButterfly dataset was used as it was determined to be of high quality because of the expert vetting process used on site, and there already existed a dataset covering the same geographic area consisting of specimen data, much of it institutional. The authors note that, in this case, citizen science data provides both novel and complementary information to the specimen data. Five new species were reported from the citizen science data, and geographic distribution information was improved for over 80% of species in the combined dataset when citizen science data was included.
Several recent studies have begun to explore the accuracy of citizen science projects and how to predict accuracy based on variables like expertise of practitioners. One example is a 2021 study by Edgar Santos-Fernandez and Kerrie Mengersen of the British Ecological Society, who utilized a case study which used recent R and Stan programming software to offer ratings of the accuracy of species identifications performed by citizen scientists in Serengeti National Park, Tanzania. This provided insight into possible problems with processes like this which include, "discriminatory power and guessing behaviour". The researchers determined that methods for rating the citizen scientists themselves based on skill level and expertise might make studies they conduct more easy to analyze.
Studies that are simple in execution are where citizen science excels, particularly in the field of conservation biology and ecology. For example, in 2019, Sumner et al. compared the data of vespid wasp distributions collected by citizen scientists with the 4-decade, long-term dataset established by the BWARS. They set up the Big Wasp Survey from 26 August to 10 September 2017, inviting citizen scientists to trap wasps and send them for identification by experts where data was recorded. The results of this study showed that the campaign garnered over 2,000 citizen scientists participating in data collection, identifying over 6,600 wasps. This experiment provides strong evidence that citizen science can generate potentially high-quality data comparable to that of expert data collection, within a shorter time frame. Although the experiment was to originally test the strength of citizen science, the team also learned more about Vespidae biology and species distribution in the United Kingdom. With this study, the simple procedure enabled citizen science to be executed in a successful manner. A study by J. Cohn describes that volunteers can be trained to use equipment and process data, especially considering that a large proportion of citizen scientists are individuals who are already well-versed in the field of science.
The demographics of participants in citizen science projects are overwhelmingly White adults, of above-average income, having a university degree. Other groups of volunteers include conservationists, outdoor enthusiasts, and amateur scientists. As such, citizen scientists are generally individuals with a pre-understanding of the scientific method and how to conduct sensible and just scientific analysis.
== Ethics ==
Various studies have been published that explore the ethics of citizen science, including issues such as intellectual property and project design.(e.g.) The Citizen Science Association (CSA), based at the Cornell Lab of Ornithology, and the European Citizen Science Association (ECSA), based in the Museum für Naturkunde in Berlin, have working groups on ethics and principles.
In September 2015, ECSA published its Ten Principles of Citizen Science, which have been developed by the "Sharing best practice and building capacity" working group of ECSA, led by the Natural History Museum, London with input from many members of the association.
The medical ethics of internet crowdsourcing has been questioned by Graber & Graber in the Journal of Medical Ethics. In particular, they analyse the effect of games and the crowdsourcing project Foldit. They conclude: "games can have possible adverse effects, and that they manipulate the user into participation".
In March 2019, the online journal Citizen Science: Theory and Practice launched a collection of articles on the theme of Ethical Issues in Citizen Science. The articles are introduced with (quoting): "Citizen science can challenge existing ethical norms because it falls outside of customary methods of ensuring that research is conducted ethically. What ethical issues arise when engaging the public in research? How have these issues been addressed, and how should they be addressed in the future?"
In June 2019, East Asian Science, Technology and Society: An International Journal (EASTS) published an issue titled "Citizen Science: Practices and Problems" which contains 15 articles/studies on citizen science, including many relevant subjects of which ethics is one. Quoting from the introduction "Citizen, Science, and Citizen Science": "The term citizen science has become very popular among scholars as well as the general public, and, given its growing presence in East Asia, it is perhaps not a moment too soon to have a special issue of EASTS on the topic."
Use of citizen science volunteers as de facto unpaid laborers by some commercial ventures have been criticized as exploitative.
Ethics in citizen science in the health and welfare field, has been discussed in terms of protection versus participation. Public involvement researcher Kristin Liabo writes that health researcher might, in light of their ethics training, be inclined to exclude vulnerable individuals from participation, to protect them from harm. However, she argues these groups are already likely to be excluded from participation in other arenas, and that participation can be empowering and a possibility to gain life skills that these individuals need. Whether or not to become involved should be a decision these individuals should be involved in and not a researcher decision.
== Economic worth ==
In the research paper "Can citizen science enhance public understanding of science?" by Bonney et al. 2016, statistics which analyse the economic worth of citizen science are used, drawn from two papers: i) Sauermann and Franzoni 2015, and
ii) Theobald et al. 2015. In "Crowd science user contribution patterns and their implications" by Sauermann and Franzoni (2015), seven projects from the Zooniverse web portal are used to estimate the monetary value of the citizen science that had taken place. The seven projects are: Solar Stormwatch, Galaxy Zoo Supernovae, Galaxy Zoo Hubble, Moon Zoo, Old Weather, The Milky Way Project and Planet Hunters. Using data from 180 days in 2010, they find a total of 100,386 users participated, contributing 129,540 hours of unpaid work. Estimating at a rate of $12 an hour (an undergraduate research assistant's basic wage), the total contributions amount to $1,554,474, an average of $222,068 per project. The range over the seven projects was from $22,717 to $654,130.
In "Global change and local solutions: Tapping the unrealized potential of citizen science for biodiversity research" by Theobald et al. 2015, the authors surveyed 388 unique biodiversity-based projects. Quoting: "We estimate that between 1.36 million and 2.28 million people volunteer annually in the 388 projects we surveyed, though variation is great" and that "the range of in-kind contribution of the volunteerism in our 388 citizen science projects as between $667 million to $2.5 billion annually."
Worldwide participation in citizen science continues to grow. A list of the top five citizen science communities compiled by Marc Kuchner and Kristen Erickson in July 2018 shows a total of 3.75 million participants, although there is likely substantial overlap between the communities.
== Relations with education and academia ==
There have been studies published which examine the place of citizen science within education.(e.g.) Teaching aids can include books and activity or lesson plans.(e.g.). Some examples of studies are:
From the Second International Handbook of Science Education, a chapter entitled: "Citizen Science, Ecojustice, and Science Education: Rethinking an Education from Nowhere", by Mueller and Tippins (2011), acknowledges in the abstract that: "There is an emerging emphasis in science education on engaging youth in citizen science." The authors also ask: "whether citizen science goes further with respect to citizen development." The abstract ends by stating that the "chapter takes account of the ways educators will collaborate with members of the community to effectively guide decisions, which offers promise for sharing a responsibility for democratizing science with others."
From the journal Democracy and Education, an article entitled: "Lessons Learned from Citizen Science in the Classroom" by authors Gray, Nicosia and Jordan (GNJ; 2012) gives a response to a study by Mueller, Tippins and Bryan (MTB) called "The Future of Citizen Science". GNJ begins by stating in the abstract that "The Future of Citizen Science": "provides an important theoretical perspective about the future of democratized science and K12 education." But GRB state: "However, the authors (MTB) fail to adequately address the existing barriers and constraints to moving community-based science into the classroom." They end the abstract by arguing: "that the resource constraints of scientists, teachers, and students likely pose problems to moving true democratized science into the classroom."
In 2014, a study was published called "Citizen Science and Lifelong Learning" by R. Edwards in the journal Studies in the Education of Adults. Edwards begins by writing in the abstract that citizen science projects have expanded over recent years and engaged citizen scientists and professionals in diverse ways. He continues: "Yet there has been little educational exploration of such projects to date." He describes that "there has been limited exploration of the educational backgrounds of adult contributors to citizen science". Edwards explains that citizen science contributors are referred to as volunteers, citizens or as amateurs. He ends the abstract: "The article will explore the nature and significance of these different characterisations and also suggest possibilities for further research."
In the journal Microbiology and Biology Education a study was published by Shah and Martinez (2015) called "Current Approaches in Implementing Citizen Science in the Classroom". They begin by writing in the abstract that citizen science is a partnership between inexperienced amateurs and trained scientists. The authors continue: "With recent studies showing a weakening in scientific competency of American students, incorporating citizen science initiatives in the curriculum provides a means to address deficiencies". They argue that combining traditional and innovative methods can help provide a practical experience of science. The abstract ends: "Citizen science can be used to emphasize the recognition and use of systematic approaches to solve problems affecting the community."
In November 2017, authors Mitchell, Triska and Liberatore published a study in PLOS One titled "Benefits and Challenges of Incorporating Citizen Science into University Education". The authors begin by stating in the abstract that citizen scientists contribute data with the expectation that it will be used. It reports that citizen science has been used for first year university students as a means to experience research. They continue: "Surveys of more than 1500 students showed that their environmental engagement increased significantly after participating in data collection and data analysis." However, only a third of students agreed that data collected by citizen scientists was reliable. A positive outcome of this was that the students were more careful of their own research. The abstract ends: "If true for citizen scientists in general, enabling participants as well as scientists to analyse data could enhance data quality, and so address a key constraint of broad-scale citizen science programs."
Citizen science has also been described as challenging the "traditional hierarchies and structures of knowledge creation".
== History ==
While citizen science developed at the end of the 20th century, characteristics of citizen science are not new. Prior to the 20th century, science was often the pursuit of gentleman scientists, amateur or self-funded researchers such as Sir Isaac Newton, Benjamin Franklin, and Charles Darwin. Women citizen scientists from before the 20th century include Florence Nightingale who "perhaps better embodies the radical spirit of citizen science". Before the professionalization of science by the end of the 19th century, most pursued scientific projects as an activity rather than a profession itself, an example being amateur naturalists in the 18th and 19th centuries.
During the British colonization of North America, American Colonists recorded the weather, offering much of the information now used to estimate climate data and climate change during this time period. These people included John Campanius Holm, who recorded storms in the mid-1600s, as well as George Washington, Thomas Jefferson, and Benjamin Franklin who tracked weather patterns during America's founding. Their work focused on identifying patterns by amassing their data and that of their peers and predecessors, rather than specific professional knowledge in scientific fields. Some consider these individuals to be the first citizen scientists, some consider figures such as Leonardo da Vinci and Charles Darwin to be citizen scientists, while others feel that citizen science is a distinct movement that developed later on, building on the preceding history of science.
By the mid-20th century, however, science was dominated by researchers employed by universities and government research laboratories. By the 1970s, this transformation was being called into question. Philosopher Paul Feyerabend called for a "democratization of science". Biochemist Erwin Chargaff advocated a return to science by nature-loving amateurs in the tradition of Descartes, Newton, Leibniz, Buffon, and Darwin—science dominated by "amateurship instead of money-biased technical bureaucrats".
A study from 2016 indicates that the largest impact of citizen science is in research on biology, conservation and ecology, and is utilized mainly as a methodology of collecting and classifying data.
=== Amateur astronomy ===
Astronomy has long been a field where amateurs have contributed throughout time, all the way up to the present day.
Collectively, amateur astronomers observe a variety of celestial objects and phenomena sometimes with equipment that they build themselves. Common targets of amateur astronomers include the Moon, planets, stars, comets, meteor showers, and a variety of deep-sky objects such as star clusters, galaxies, and nebulae. Observations of comets and stars are also used to measure the local level of artificial skyglow. One branch of amateur astronomy, amateur astrophotography, involves the taking of photos of the night sky. Many amateurs like to specialize in the observation of particular objects, types of objects, or types of events that interest them.
The American Association of Variable Star Observers has gathered data on variable stars for educational and professional analysis since 1911 and promotes participation beyond its membership on its Citizen Sky website.
Project PoSSUM is a relatively new organization, started in March 2012, which trains citizen scientists of many ages to go on polar suborbital missions. On these missions, they study noctilucent clouds with remote sensing, which reveals interesting clues about changes in the upper atmosphere and the ozone due to climate change. This is a form of citizen science which trains younger generations to be ambitious, participating in intriguing astronomy and climate change science projects even without a professional degree.
=== Butterfly counts ===
Butterfly counts have a long tradition of involving individuals in the study of butterflies' range and their relative abundance. Two long-running programs are the UK Butterfly Monitoring Scheme (started in 1976) and the North American Butterfly Association's Butterfly Count Program (started in 1975). There are various protocols for monitoring butterflies and different organizations support one or more of transects, counts and/or opportunistic sightings. eButterfly is an example of a program designed to capture any of the three types of counts for observers in North America. Species-specific programs also exist, with monarchs the prominent example. Two examples of this involve the counting of monarch butterflies during the fall migration to overwintering sites in Mexico: (1) Monarch Watch is a continent-wide project, while (2) the Cape May Monarch Monitoring Project is an example of a local project.
=== Ornithology ===
Citizen science projects have become increasingly focused on providing benefits to scientific research. The North American Bird Phenology Program (historically called the Bird Migration and Distribution records) may have been the earliest collective effort of citizens collecting ornithological information in the U.S. The program, dating back to 1883, was started by Wells Woodbridge Cooke. Cooke established a network of observers around North America to collect bird migration records. The Audubon Society's Christmas Bird Count, which began in 1900, is another example of a long-standing tradition of citizen science which has persisted to the present day, now containing a collection of six million handwritten migration observer cards that date back to the 19th century. Participants input this data into an online database for analysis. Citizen scientists help gather data that will be analyzed by professional researchers, and can be used to produce bird population and biodiversity indicators.
Raptor migration research relies on the data collected by the hawkwatching community. This mostly volunteer group counts migrating accipiters, buteos, falcons, harriers, kites, eagles, osprey, vultures and other raptors at hawk sites throughout North America during the spring and fall seasons. The daily data is uploaded to hawkcount.org where it can be viewed by professional scientists and the public.
Other programs in North America include Project FeederWatch, which is affiliated with the Cornell Lab of Ornithology.
Such indices can be useful tools to inform management, resource allocation, policy and planning. For example, European breeding bird survey data provide input for the Farmland Bird Index, adopted by the European Union as a structural indicator of sustainable development. This provides a cost-effective alternative to government monitoring.
Similarly, data collected by citizen scientists as part of BirdLife Australia's has been analysed to produce the first-ever Australian Terrestrial Bird Indices.
In the UK, the Royal Society for the Protection of Birds collaborated with a children’s TV show to create a national birdwatching day in 1979; the campaign has continued for over 40 years and in 2024, over 600,000 people counted almost 10 million birds during the Big Garden Birdwatch weekend.
Most recently, more programs have sprung up worldwide, including NestWatch, a bird species monitoring program which tracks data on reproduction. This might include studies on when and how often nesting occurs, counting eggs laid and how many hatch successfully, and what proportion of hatchlings survive infancy. Participation in this program is extremely easy for the general public to join. Using the recently created nest watch app which is available on almost all devices, anyone can begin to observe their local species, recording results every 3 to 4 days within the app. This forms a continually-growing database which researchers can view and utilize to understand trends within specific bird populations.
=== Citizen oceanography ===
The concept of citizen science has been extended to the ocean environment for characterizing ocean dynamics and tracking marine debris. For example, the mobile app Marine Debris Tracker is a joint partnership of National Oceanic and Atmospheric Administration and the University of Georgia. Long term sampling efforts such as the continuous plankton recorder has been fitted on ships of opportunity since 1931. Plankton collection by sailors and subsequent genetic analysis was pioneered in 2013 by Indigo V Expeditions as a way to better understand marine microbial structure and function.
=== Coral reefs ===
Citizen science in coral reef studies developed in the 21st century.
Underwater photography has become more popular since the development of moderate priced digital cameras with waterproof housings in the early 2000s, resulting on millions of pictures posted every year on various websites and social media. This mass of documentation has great scientific potential, as millions of tourists possess a much superior coverage power than professional scientists, who cannot spend so much time in the field.
As a consequence, several participative sciences programs have been developed, supported by geotagging and identification web sites such as iNaturalist. The Monitoring through many eyes project collates thousands of underwater images of the Great Barrier Reef and provides an interface for elicitation of reef health indicators.
The National Oceanic and Atmospheric Administration (NOAA) also offers opportunities for volunteer participation. By taking measurements in The United States' National Marine Sanctuaries, citizens contribute data to marine biology projects. In 2016, NOAA benefited from 137,000 hours of research.
There also exist protocols for auto-organization and self-teaching aimed at biodiversity-interested snorkelers, in order for them to turn their observations into sound scientific data, available for research. This kind of approach has been successfully used in Réunion island, allowing for tens of new records and even new species.
=== Freshwater fish ===
Aquarium hobbyists and their respective organizations are very passionate about fish conservation and often more knowledgeable about specific fish species and groups than scientific researchers. They have played an important role in the conservation of freshwater fishes by discovering new species, maintaining extensive databases with ecological information on thousands of species (such as for catfish, Mexican freshwater fishes, killifishes, cichlids), and successfully keeping and providing endangered and extinct-in-the-wild species for conservation projects. The CARES (Conservation, Awareness, Recognition, Encouragement, and Support) preservation program is the largest hobbyist organization containing over 30 aquarium societies and international organizations, and encourages serious aquarium hobbyists to devote tank space to the most threatened or extinct-in-the-wild species to ensure their survival for future generations.
=== Amphibians ===
Citizen scientists also work to monitor and conserve amphibian populations. One recent project is FrogWatch USA, organized by the Association of Zoos and Aquariums. Participants are invited to educate themselves on their local wetlands and help to save amphibian populations by reporting the data on the calls of local frogs and toads. The project already has over 150,000 observations from more than 5000 contributors. Participants are trained by program coordinators to identify calls and utilize this training to report data they find between February and August of each "monitoring season". Data is used to monitor diversity, invasion, and long-term shifts in population health within these frog and toad communities.
=== Rocky reefs ===
Reef Life Survey is a marine life monitoring programme based in Hobart, Tasmania. The project uses recreational divers that have been trained to make fish and invertebrate counts, using an approximate 50 m constant depth transect of tropical and temperate reefs, which might include coral reefs. Reef Life Survey is international in its scope, but the data collectors are predominantly from Australia. The database is available to marine ecology researchers, and is used by several marine protected area managements in Australia, New Zealand, American Samoa and the eastern Pacific. Its results have also been included in the Australian Ocean DATA Network.
=== Agriculture ===
Farmer participation in experiments has a long tradition in agricultural science. There are many opportunities for citizen engagement in different parts of food systems. Citizen science is actively used for crop variety selection for climate adaptation, involving thousands of farmers. Citizen science has also played a role in furthering sustainable agriculture.
=== Art history ===
Citizen science has a long tradition in natural science. Today, citizen science projects can also be found in various fields of science like art history. For example, the Zooniverse project AnnoTate is a transcription tool developed to enable volunteers to read and transcribe the personal papers of British-born and émigré artists. The papers are drawn from the Tate Archive. Another example of citizen science in art history is ARTigo. ARTigo collects semantic data on artworks from the footprints left by players of games featuring artwork images. From these footprints, ARTigo automatically builds a semantic search engine for artworks.
=== Biodiversity ===
Citizen science has made significant contributions to the analysis of biodiversity across the world. A majority of data collected has been focused primarily on species occurrence, abundance and phenology, with birds being primarily the most popular group observed. There is growing efforts to expand the use of citizen science across other fields. Past data on biodiversity has had limitations in the quantity of data to make any meaningful broad connections to losses in biodiversity. Recruiting citizens already out in the field opens a tremendous amount of new data. For example, thousands of farmers reporting the changes in biodiversity in their farms over many years has provided a large amount of relevant data concerning the effect of different farming methods on biodiversity. Another example, is WomSAT, a citizen science project that collects data on wombat roadkill and sarcoptic mange incidence and distribution, to support conservation efforts for the species.
Citizen science can be used to great effect in addition to the usual scientific methods in biodiversity monitoring. The typical active method of species detection is able to collect data on the broad biodiversity of areas while citizen science approaches has shown to be more effective at identifying invasive species. In combination, this provides an effective strategy of monitoring the changes in biodiversity of ecosystems.
=== Health and welfare ===
In the research fields of health and welfare, citizen science is often discussed in other terms, such as "public involvement", "user engagement", or "community member involvement". However the meaning is similar to citizen science, with the exception that citizens are not often involved in collecting data but more often involved in prioritisation of research ideas and improving methodology, e.g. survey questions. In the last decades, researchers and funders have gained awareness of the benefits from involving citizens in the research work, but the involvement of citizens in a meaningful way is not a common practice. There is an ongoing discussion on how to evaluate citizen science in health and welfare research.
One aspect to consider in citizen science in health and welfare, that stands out compared to in other academic fields, is who to involve. When research concerns human experiences, representation of a group becomes important. While it is commonly acknowledged that the people involved need to have lived experience of the concerned topic, representation is still an issue, and researchers are debating whether this is a useful concept in citizen science.
== Modern technology ==
Newer technologies have increased the options for citizen science. Citizen scientists can build and operate their own instruments to gather data for their own experiments or as part of a larger project. Examples include amateur radio, amateur astronomy, Six Sigma Projects, and Maker activities. Scientist Joshua Pearce has advocated for the creation of open-source hardware based scientific equipment that both citizen scientists and professional scientists, which can be replicated by digital manufacturing techniques such as 3D printing. Multiple studies have shown this approach radically reduces scientific equipment costs. Examples of this approach include water testing, nitrate and other environmental testing, basic biology and optics. Groups such as Public Lab, which is a community where citizen scientists can learn how to investigate environmental concerns using inexpensive DIY techniques, embody this approach.
Video technology is much used in scientific research. The Citizen Science Center in the Nature Research Center wing of the North Carolina Museum of Natural Sciences has exhibits on how to get involved in scientific research and become a citizen scientist. For example, visitors can observe birdfeeders at the Prairie Ridge Ecostation satellite facility via live video feed and record which species they see.
Since 2005, the Genographic Project has used the latest genetic technology to expand our knowledge of the human story, and its pioneering use of DNA testing to engage and involve the public in the research effort has helped to create a new breed of "citizen scientist". Geno 2.0 expands the scope for citizen science, harnessing the power of the crowd to discover new details of human population history. This includes supporting, organization and dissemination of personal DNA testing. Like amateur astronomy, citizen scientists encouraged by volunteer organizations like the International Society of Genetic Genealogy have provided valuable information and research to the professional scientific community.
With unmanned aerial vehicles, further citizen science is enabled. One example is the ESA's AstroDrone smartphone app for gathering robotic data with the Parrot AR.Drone.
Citizens in Space (CIS), a project of the United States Rocket Academy, seeks to combine citizen science with citizen space exploration. CIS is training citizen astronauts to fly as payload operators on suborbital reusable spacecraft that are now in development. CIS will also be developing, and encouraging others to develop, citizen-science payloads to fly on suborbital vehicles. CIS has already acquired a contract for 10 flights on the Lynx suborbital vehicle, being developed by XCOR Aerospace, and plans to acquire additional flights on XCOR Lynx and other suborbital vehicles in the future.
CIS believes that "The development of low-cost reusable suborbital spacecraft will be the next great enabler, allowing citizens to participate in space exploration and space science."
The website CitizenScience.gov was started by the U.S. government to "accelerate the use of crowdsourcing and citizen science" in the United States. Following the internet's rapid increase of citizen science projects, this site is one of the most prominent resource banks for citizen scientists and government supporters alike. It features three sections: a catalog of existing citizen science projects which are federally supported, a toolkit to help federal officials as they develop and maintain their future projects, and several other resources and projects. This was created as the result of a mandate within the Crowdsourcing and Citizen Science Act of 2016 (15 USC 3724).
=== Internet ===
The Internet has been a boon to citizen science, particularly through gamification. One of the first Internet-based citizen science experiments was NASA's Clickworkers, which enabled the general public to assist in the classification of images, greatly reducing the time to analyze large data sets. Another was the Citizen Science Toolbox, launched in 2003, of the Australian Coastal Collaborative Research Centre. Mozak is a game in which players create 3D reconstructions from images of actual human and mouse neurons, helping to advance understanding of the brain. One of the largest citizen science games is Eyewire, a brain-mapping puzzle game developed at the Massachusetts Institute of Technology that now has over 200,000 players. Another example is Quantum Moves, a game developed by the Center for Driven Community Research at Aarhus University, which uses online community efforts to solve quantum physics problems. The solutions found by players can then be used in the lab to feed computational algorithms used in building a scalable quantum computer.
More generally, Amazon's Mechanical Turk is frequently used in the creation, collection, and processing of data by paid citizens. There is controversy as to whether or not the data collected through such services is reliable, as it is subject to participants' desire for compensation. However, use of Mechanical Turk tends to quickly produce more diverse participant backgrounds, as well as comparably accurate data when compared to traditional collection methods.
The internet has also enabled citizen scientists to gather data to be analyzed by professional researchers. Citizen science networks are often involved in the observation of cyclic events of nature (phenology), such as effects of global warming on plant and animal life in different geographic areas, and in monitoring programs for natural-resource management. On BugGuide.Net, an online community of naturalists who share observations of arthropod, amateurs and professional researchers contribute to the analysis. By October 2022, BugGuide has over 1,886,513 images submitted by 47,732 contributors.
Not counting iNaturalist and eBird, the Zooniverse is home to the internet's largest, most popular and most successful citizen science projects. The Zooniverse and the suite of projects it contains is produced, maintained and developed by the Citizen Science Alliance (CSA). The member institutions of the CSA work with many academic and other partners around the world to produce projects that use the efforts and ability of volunteers to help scientists and researchers deal with the flood of data that confronts them. On 29 June 2015, the Zooniverse released a new software version with a project-building tool allowing any registered user to create a project. Project owners may optionally complete an approval process to have their projects listed on the Zooniverse site and promoted to the Zooniverse community. A NASA/JPL picture to the right gives an example from one of Zooniverse's projects The Milky Way Project.
The website CosmoQuest has as its goal "To create a community of people bent on together advancing our understanding of the universe; a community of people who are participating in doing science, who can explain why what they do matters, and what questions they are helping to answer."
CrowdCrafting enables its participants to create and run projects where volunteers help with image classification, transcription, geocoding and more. The platform is powered by PyBossa software, a free and open-source framework for crowdsourcing.
Project Soothe is a citizen science research project based at the University of Edinburgh. The aim of this research is to create a bank of soothing images, submitted by members of the public, which can be used to help others through psychotherapy and research in the future. Since 2015, Project Soothe has received over 600 soothing photographs from people in 23 countries. Anyone aged 12 years or over is eligible to participate in this research in two ways: (1) By submitting soothing photos that they have taken with a description of why the images make them feel soothed (2) By rating the photos that have been submitted by people worldwide for their soothability.
The internet has allowed for many individuals to share and upload massive amounts of data. Using the internet citizen observatories have been designed as a platform to both increase citizen participation and knowledge of their surrounding environment by collecting whatever relevant data is focused by the program. The idea is making it easier and more exciting for citizens to get and stay involved in local data collection.
The invention of social media has aided in providing massive amounts of information from the public to create citizen science programs. In a case study by Andrea Liberatore, Erin Bowkett, Catriona J. MacLeod, Eric Spurr, and Nancy Longnecker, the New Zealand Garden Bird Survey is conducted as one such project with the aid of social media. It examines the influence of utilizing a Facebook group to collect data from citizen scientists as the researchers work on the project over the span of a year. The authors claim that this use of social media greatly helps with the efficiency of this study and makes the atmosphere feel more communal.
=== Smartphone ===
The bandwidth and ubiquity afforded by smartphones has vastly expanded the opportunities for citizen science. Examples include iNaturalist, Chronolog, the San Francisco project, the WildLab, Project Noah, and Aurorasurus. Due to their ubiquity, for example, Twitter, Facebook, and smartphones have been useful for citizen scientists, having enabled them to discover and propagate a new type of aurora dubbed "STEVE" in 2016.
There are also apps for monitoring birds, marine wildlife and other organisms, and the "Loss of the Night". Chronolog, another citizen science initiative, uses smartphone photography to crowdsource environmental monitoring through timelapses. By positioning their cameras at designated photo stations and submitting images, participants contribute to long-term ecological records at parks and conservation sites across 48 U.S. states and 10 countries. Restoration professionals and other land stewards use this data to measure ecosystem health and understand the effectiveness of conservation interventions like habitat restoration, controlled burns, removal of invasive species, planting of native species, and efforts to improve water quality.
"The Crowd and the Cloud" is a four-part series broadcast during April 2017, which examines citizen science. It shows how smartphones, computers and mobile technology enable regular citizens to become part of a 21st-century way of doing science. The programs also demonstrate how citizen scientists help professional scientists to advance knowledge, which helps speed up new discoveries and innovations. The Crowd & The Cloud is based upon work supported by the U.S. National Science Foundation.
=== Seismology ===
Since 1975, in order to improve earthquake detection and collect useful information, the European-Mediterranean Seismological Centre monitors the visits of earthquake eyewitnesses to its website and relies on Facebook and Twitter. More recently, they developed the LastQuake mobile application which notifies users about earthquakes occurring around the world, alerts people when earthquakes hit near them, gathers citizen seismologists' testimonies to estimate the felt ground shaking and possible damages.
=== Hydrology ===
Citizen science has been used to provide valuable data in hydrology (catchment science), notably flood risk, water quality, and water resource management. A growth in internet use and smartphone ownership has allowed users to collect and share real-time flood-risk information using, for example, social media and web-based forms. Although traditional data collection methods are well-established, citizen science is being used to fill the data gaps on a local level, and is therefore meaningful to individual communities. Data collected from citizen science can also compare well to professionally collected data. It has been demonstrated that citizen science is particularly advantageous during a flash flood because the public are more likely to witness these rarer hydrological events than scientists.
=== Plastics and pollution ===
Citizen science includes projects that help monitor plastics and their associated pollution. These include The Ocean Cleanup, #OneLess, The Big Microplastic Survey, EXXpedition and Alliance to End Plastic Waste. Ellipsis seeks to map the distribution of litter using aerial data mapping by unmanned aerial vehicles and machine learning software. A Zooniverse project called The Plastic Tide (now finished) helped train an algorithm used by Ellipsis.
Examples of relevant articles (by date):
Citizen Science Promotes Environmental Engagement: (quote) "Citizen science projects are rapidly gaining popularity among the public, in which volunteers help gather data on species that can be used by scientists in research. And it's not just adults who are involved in these projects – even kids have collected high-quality data in the US."
Tackling Microplastics on Our Own: (quote) "Plastics, ranging from the circles of soda can rings to microbeads the size of pinheads, are starting to replace images of sewage for a leading cause of pollution – especially in the ocean". Further, "With recent backing from the Crowdsourcing and Citizen Science Act, citizen science is increasingly embraced as a tool by US Federal agencies."
Citizen Scientists Are Tracking Plastic Pollution Worldwide: (quote) "Scientists who are monitoring the spread of tiny pieces of plastic throughout the environment are getting help from a small army of citizen volunteers – and they're finding bits of polymer in some of the most remote parts of North America."
Artificial intelligence and citizen scientists: Powering the clean-up of Asia Pacific's beaches:(quote) "The main objective is to support citizen scientists cleaning up New Zealand beaches and get a better understanding of why litter is turning up, so preventive and proactive action can be taken."
Citizen science could help address Canada's plastic pollution problem: (quote) "But citizen engagement and participation in science goes beyond beach cleanups, and can be used as a tool to bridge gaps between communities and scientists. These partnerships between scientists and citizen scientists have produced real world data that have influenced policy changes."
Examples of relevant scientific studies or books include (by date):
Distribution and abundance of small plastic debris on beaches in the SE Pacific (Chile): a study supported by a citizen science project: (quote) "The citizen science project 'National Sampling of Small Plastic Debris' was supported by schoolchildren from all over Chile who documented the distribution and abundance of small plastic debris on Chilean beaches. Thirty-nine schools and nearly 1,000 students from continental Chile and Easter Island participated in the activity."
Incorporating citizen science to study plastics in the environment: (quote) "Taking advantage of public interest in the impact of plastic on the marine environment, successful Citizen Science (CS) programs incorporate members of the public to provide repeated sampling for time series as well as synoptic collections over wide geographic regions."
Marine anthropogenic litter on British beaches: A 10-year nationwide assessment using citizen science data: (quote) "Citizen science projects, whereby members of the public gather information, offer a low-cost method of collecting large volumes of data with considerable temporal and spatial coverage. Furthermore, such projects raise awareness of environmental issues and can lead to positive changes in behaviours and attitudes."
Determining Global Distribution of Microplastics by Combining Citizen Science and In-Depth Case Studies: (quote) "Our first project involves the general public through citizen science. Participants collect sand samples from beaches using a basic protocol, and we subsequently extract and quantify microplastics in a central laboratory using the standard operating procedure."
Risk Perception of Plastic Pollution: Importance of Stakeholder Involvement and Citizen Science: (quote) "The chapter finally discusses how risk perception can be improved by greater stakeholder involvement and utilization of citizen science and thereby improve the foundation for timely and efficient societal measures."
Assessing the citizen science approach as tool to increase awareness on the marine litter problem: (quote) "This paper provides a quantitative assessment of students' attitude and behaviors towards marine litter before and after their participation to SEACleaner, an educational and citizen science project devoted to monitor macro- and micro-litter in an Area belonging to Pelagos Sanctuary."
Spatial trends and drivers of marine debris accumulation on shorelines in South Eleuthera, The Bahamas using citizen science: (quote) "This study measured spatial distribution of marine debris stranded on beaches in South Eleuthera, The Bahamas. Citizen science, fetch modeling, relative exposure index and predictive mapping were used to determine marine debris source and abundance."
Making citizen science count: Best practices and challenges of citizen science projects on plastics in aquatic environments: (quote) "Citizen science is a cost-effective way to gather data over a large geographical range while simultaneously raising public awareness on the problem".
White and wonderful? Microplastics prevail in snow from the Alps to the Arctic: (quote) "In March 2018, five samples were taken at different locations on Svalbard (Fig. 1A and Table 1) by citizen scientists embarking on a land expedition by ski-doo (Aemalire project). The citizens were instructed on contamination prevention and equipped with protocol forms, prerinsed 2-liter stainless steel containers (Ecotanca), a porcelain mug, a steel spoon, and a soup ladle for sampling."
=== Citizen sensing ===
Citizen sensing can be a form of citizen science: (quote) "The work of citizen sensing, as a form of citizen science, then further transforms Stengers's notion of the work of science by moving the experimental facts and collectives where scientific work is undertaken out of the laboratory of experts and into the world of citizens." Similar sensing activities include Crowdsensing and participatory monitoring. While the idea of using mobile technology to aid this sensing is not new, creating devices and systems that can be used to aid regulation has not been straightforward. Some examples of projects that include citizen sensing are:
Citizen Sense (2013–2018): (quote) "Practices of monitoring and sensing environments have migrated to everyday participatory applications, where users of smart phones and networked devices are able to engage with modes of environmental observation and data collection."
Breathe Project: (quote) "We use the best available science and technology to better understand the quality of the air we breathe and provide opportunities for citizens to engage and take action."
The Bristol Approach to Citizen Sensing: (quote) "Citizen Sensing is about empowering people and places to understand and use smart tech and data from sensors to tackle the issues they care about, connect with other people who can help, and take positive, practical action."
Luftdaten.info: (quote) "You and thousands of others around the world install self-built sensors on the outside their home. Luftdaten.info generates a continuously updated particular matter map from the transmitted data."
CitiSense: (quote) "CitiSense aims to co-develop a participatory risk management system (PRMS) with citizens, local authorities and organizations which enables them to contribute to advanced climate services and enhanced urban climate resilience as well as receive recommendations that support their security."
A group of citizen scientists in a community-led project targeting toxic smoke from wood burners in Bristol, has recorded 11 breaches of World Health Organization daily guidelines for ultra-fine particulate pollution over a period of six months.
In a £7M programme funded by water regulator Ofwat, citizen scientists are being trained to test for pollution and over-abstraction in 10 river catchment areas in the UK. Sensors will be used and the information gathered will be available in a central visualisation platform. The project is led by The Rivers Trust and United Utilities and includes volunteers such as anglers testing the rivers they use. The Angling Trust provides the pollution sensors, with Kristian Kent from the Trust saying: "Citizen science is a reality of the world in the future, so they’re not going to be able to just sweep it under the carpet."
River water quality in the U.K. has been tested by a combined total of over 7,000 volunteers in so-called "blitzes" run over two weekends in 2024. The research by the NGO Earthwatch Europe gathered data from 4,000 freshwater sites and used standardised testing equipment provide by the NGO and Imperial College. The second blitz in October 2024 included testing for chemical pollutants, such as antibiotics, agricultural chemicals and pesticides. Results from 4,531 volunteers showed that over 61% of the freshwater sites "were in a poor state because of high levels of the nutrients phosphate and nitrate, the main source of which is sewage effluent and agricultural runoff". The data gathered through robust volunteer testing is analysed and put into a report helping provide the Environment Agency with information it does not have.
=== COVID-19 pandemic ===
Resources for computer science and scientific crowdsourcing projects concerning COVID-19 can be found on the internet or as apps. Some such projects are listed below:
The distributed computing project Folding@home launched a program in March 2020 to assist researchers around the world who were working on finding a cure and learning more about the coronavirus pandemic. The initial wave of projects were meant to simulate potentially druggable protein targets from SARS-CoV-2 (and also its predecessor and close relation SARS-CoV, about which there is significantly more data available). In 2024, the project has been extended to look at other health issues including Alzheimer’s and cancer. The project asks volunteers to download the app and donate computing power for simulations.
The distributed computing project Rosetta@home also joined the effort in March 2020. The project uses computers of volunteers to model SARS-CoV-2 virus proteins to discover possible drug targets or create new proteins to neutralize the virus. Researchers revealed that with the help of Rosetta@home, they had been able to "accurately predict the atomic-scale structure of an important coronavirus protein weeks before it could be measured in the lab." In 2022, the parent Boinc company thanked contributors for donating their computer power and helping work on the de novo protein design including vaccine development.
The OpenPandemics – COVID-19 project is a partnership between Scripps Research and IBM's World Community Grid for a distributed computing project that "will automatically run a simulated experiment in the background [of connected home PCs] which will help predict the effectiveness of a particular chemical compound as a possible treatment for COVID-19". The project asked volunteers to donate unused computing power. In 2024, the project was looking at targeting the DNA polymerase of the cytomegalovirus to identify binders.
The Eterna OpenVaccine project enables video game players to "design an mRNA encoding a potential vaccine against the novel coronavirus." In mid-2021, it was noted that the project had helped create a library of potential vaccine molecules to be tested at Stanford University; SU researchers also noted that importance of volunteers discussing the games and exchanging ideas.
In March 2020, the EU-Citizen.Science project had "a selection of resources related to the current COVID19 pandemic. It contains links to citizen science and crowdsourcing projects"
The COVID-19 Citizen Science project was "a new initiative by University of California, San Francisco physician-scientists" that "will allow anyone in the world age 18 or over to become a citizen scientist advancing understanding of the disease." By 2024, the Eureka platform had over 100,000 participants.
The CoronaReport digital journalism project was "a citizen science project which democratizes the reporting on the Coronavirus, and makes these reports accessible to other citizens." It was developed by the University of Edinburgh and asked people affected by Covid to share the social effects of the pandemic.
The COVID Symptom Tracker was a crowdsourced study of the symptoms of the virus. It was created in the UK by King’s College London and Guy’s and St Thomas’ Hospitals. It had two million downloads by April 2020. Within three months, information from the app had helped identify six variations of Covid. Government funding ended in early 2022, but due to the large number of volunteers, Zoe decided to continue the work to study general health. By February 2023, over 75,000 people had downloaded the renamed Zoe Habit Tracker.
The Covid Near You epidemiology tool "uses crowdsourced data to visualize maps to help citizens and public health agencies identify current and potential hotspots for the recent pandemic coronavirus, COVID-19." The site was launched in Boston in March 2020; at the end of 2020 it was rebranded to Outbreaks Near Me and tracked both Covid and flu.
The We-Care project is a novel initiative by University of California, Davis researchers that uses anonymity and crowdsourced information to alert infected users and slow the spread of COVID-19.
COVID Radar was an app in the Netherlands, active between April 2020 and February 2022, with which users anonymously answered a short daily questionnaire asking about their symptoms, behavior, coronavirus test results, and vaccination status. Symptoms and behavior were visualized on a map and users received feedback on their individual risk and behaviors relative to the national mean. The app had over 250,000 users, who filled out the questionnaire over 8.5 million times. Research from this app continued to be used in 2024.
For coronavirus studies and information that can help enable citizen science, many online resources are available through open access and open science websites, including an intensive care medicine e-book chapter hosted by EMCrit and portals run by the Cambridge University Press, the Europe branch of the Scholarly Publishing and Academic Resources Coalition, The Lancet, John Wiley and Sons, and Springer Nature.
There have been suggestions that the pandemic and subsequent lockdown has boosted the public’s awareness and interest in citizen science, with more people around the world having the motivation and the time to become involved in helping to investigate the illness and potentially move on to other areas of research.
== Around the world ==
The Citizen Science Global Partnership was created in 2022; the partnership brings together networks from Australia, Africa, Asia, Europe, South America and the USA.
=== Africa ===
In South Africa (SA), citizen science projects include: the Stream Assessment Scoring System (miniSASS) which "encourages enhanced catchment management for water security in a climate stressed society."
The South African National Biodiversity Institute is partnered with iNaturalist as a platform for biodiversity observations using digital photography and geolocation technology to monitor biodiversity. Such partnerships can reduce duplication of effort, help standardise procedures and make the data more accessible.
Also in SA, "Members of the public, or 'citizen scientists' are helping researchers from the University of Pretoria to identify Phytophthora species present in the fynbos."
In June 2016, citizen science experts from across East Africa gathered in Nairobi, Kenya, for a symposium organised by the Tropical Biology Association (TBA) in partnership with the Centre for Ecology & Hydrology (CEH). The aim was "to harness the growing interest and expertise in East Africa to stimulate new ideas and collaborations in citizen science." Rosie Trevelyan of the TBA said: "We need to enhance our knowledge about the status of Africa's species and the threats facing them. And scientists can't do it all on their own. At the same time, citizen science is an extremely effective way of connecting people more closely to nature and enrolling more people in conservation action".
The website Zooniverse hosts several African citizen science projects, including: Snapshot Serengeti, Wildcam Gorongosa and Jungle Rhythms.
Nigeria has the Ibadan Bird Club whose to aim is to "exchange ideas and share knowledge about birds, and get actively involved in the conservation of birds and biodiversity."
In Namibia, Giraffe Spotter.org is "project that will provide people with an online citizen science platform for giraffes".
Within the Republic of the Congo, the territories of an indigenous people have been mapped so that "the Mbendjele tribe can protect treasured trees from being cut down by logging companies". An Android open-source app called Sapelli was used by the Mbendjele which helped them map "their tribal lands and highlighted trees that were important to them, usually for medicinal reasons or religious significance. Congolaise Industrielle des Bois then verified the trees that the tribe documented as valuable and removed them from its cutting schedule. The tribe also documented illegal logging and poaching activities."
In West Africa, the eradication of the recent outbreak of Ebola virus disease was partly helped by citizen science. "Communities learnt how to assess the risks posed by the disease independently of prior cultural assumptions, and local empiricism allowed cultural rules to be reviewed, suspended or changed as epidemiological facts emerged." "Citizen science is alive and well in all three Ebola-affected countries. And if only a fraction of the international aid directed at rebuilding health systems were to be redirected towards support for citizen science, that might be a fitting memorial to those who died in the epidemic."
The CitSci Africa Association held its International Conference in February 2024 in Nairobi.
=== Asia ===
The Hong Kong Birdwatching Society was established in 1957, and is the only local civil society aiming at appreciating and conserving Hong Kong birds and their natural environment. Their bird surveys go back to 1958, and they carry out a number of Citizen Science events such as their yearly sparrow census.
The Bird Count India partnership consists of a large number of organizations and groups involved in birdwatching and bird surveys. They coordinate a number of Citizen Science projects such as the Kerala Bird Atlas and Mysore city Bird Atlas that map the distribution and abundance of birds of entire Indian states.
RAD@home Collaboratory is an Indian citizen science research programme in astronomy & astrophysics. Launched on 15 April 2013 this programme uses hybrid model, social media platforms and in-person training of the interested participants. Recently in 2022, the Collaboratory reported discovery of an active galactic nucleus, a radio galaxy named RAD12, spewing a large unipolar radio bubble on to its merging companion galaxy.
The Taiwan Roadkill Observation Network was founded in 2011 and has more than 16,000 members as of 2019. It is a citizen science project where roadkill across Taiwan is photographed and sent to the Endemic Species Research Institute for study. Its primary goal has been to set up an eco-friendly path to mitigate roadkill challenges and popularize a national discourse on environmental issues and civil participation in scientific research. The members of the Taiwan Roadkill Observation Network volunteer to observe animals' corpses that are by caused by roadkill or by other reasons. Volunteers can then upload pictures and geographic locations of the roadkill to an internet database or send the corpses to the Endemic Species Research as specimens.Because members come from different areas of the island, the collection of data serves as an animal distribution map of the island. According to the geographical data and pictures of corpses collected by the members, the community itself and the sponsor, the Endemic Species Center could find out the hotspots and the reasons for the animals' deaths. One of the most renowned cases is that the community successfully detected rabies cases due to the huge collection of data. The corpses of Melogale moschata had accumulated for years and are thought to be carriers of rabies. Alarmed by this, the government authority took actions to prevent the prevalence of rabies in Taiwan.In another case in 2014, some citizen scientists discovered birds that had died from unknown causes near an agricultural area. The Taiwan Roadkill Observation Network cooperated with National Pingtung University of Science and Technology and engaged citizen scientists to collect bird corpses. The volunteers collected 250 bird corpses for laboratory tests, which confirmed that the bird deaths were attributable to pesticides used on crops. This prompted the Taiwanese government to restrict pesticides, and the Bill of Pesticide Management amendment was passed after the third reading in the Legislative Yuan, establishing a pesticide control system. The results indicated that Taiwan Roadkill Observation Network had developed a set of shared working methods and jointly completed certain actions. Furthermore, the community of the Taiwan Roadkill Observation Network had made real changes to road design to avoid roadkill, improved the management of usage of pesticide, epidemic prevention, as well as other examples. By mid-2024, volunteers had observed over 293,000 animals. The network, the largest citizen science project in Taiwan, noted that more than half of roadkill were amphibians (eg, frogs), while one third are reptiles and birds.
The AirBox Project was launched in Taiwan to create a participatory ecosystem with a focus on PM2.5 monitoring through AirBox devices. By the end of 2014, the public had paid more attention to the PM2.5 levels because the air pollution problem had become worse, especially in central and southern Taiwan. High PM2.5 levels are harmful to our health, with respiratory problems as an example. These pollution levels aroused public concern and led to an intensive debate about air pollution sources. Some experts suggested that air quality was affected by pollutants from mainland China, while some environmentalists believed that it was the result of industrialization, because of, for example, exhaust fumes from local power plants or factories. However, no one knew the answer because of insufficient data.Dr. Ling-Jyh Chen, a researcher of the Institute of Information Science, Academia Sinica, launched The AirBox Project. His original idea was inspired by a popular Taiwanese slogan "Save Your Environment by Yourself". As an expert in a Participatory Sensing system, he decided to take this ground-up approach to collect PM2.5 level data, and thus through open data and data analysis to have a better understanding of the possible air pollution sources. Using this ecosystem, huge amounts of data was collected from AirBox devices. This data was instantly available online, informing people of PM2.5 levels. They could then take the proper actions, such as wearing a mask or staying at home, preventing themselves from going out into the polluted environment.Data can also be analyzed to understand the possible sources of pollution and provide recommendations for improving the situation. There are four main steps to this project: i) Develop the AirBox device. Developing a device that could correctly collect the data of the PM2.5 level was time-consuming. It had taken more than three years to develop an AirBox that can be easily used, but with both high accuracy and low cost. ii) The widespread installation of AirBoxes. In the beginning, very few people were willing to install it at their homes because of their concerns about the possible harm to their health, power consumption and maintenance. Because of this, AirBoxes were only installed in a relatively small area. But with help from Taiwan's LASS (Location Aware Sensing System) community, AirBoxes appeared in all parts of Taiwan. As of February 2017, there are more than 1,600 AirBoxes installed in more than 27 countries. iii) Open Source and Data Analysis. All measurement results were released and visualized in real-time to the public through different media. Data can be analyzed to trace pollution sources. By December 2019, there were over 4,000 AirBoxes installed across the country.
Japan has a long history of citizen science involvement, the 1,200-year-old tradition of collecting records on cherry blossom flowering probably being the world's longest-running citizen science project. One of the most influential citizen science projects has also come out of Japan: Safecast. Dedicated to open citizen science for the environment, Safecast was established in the wake of the Fukushima nuclear disaster, and produces open hardware sensors for radiation and air-pollution mapping. Presenting this data via a global open data network and maps
As technology and public interest grew, the CitizenScience.Asia group was set up in 2022; it grew from an initial hackathon in Hong Kong which worked on the 2016 Zika scare. The network is part of Citizen Science Global Partnership.
=== Europe ===
The English naturalist Charles Darwin (1809–1882) is widely regarded to have been one of the earliest citizen science contributors in Europe (see § History). A century later, citizen science was experienced by adolescents in Italy during the 1980s, working on urban energy usages and air pollution.
In his book "Citizen Science", Alan Irwin considers the role that scientific expertise can play in bringing the public and science together and building a more scientifically active citizenry, empowering individuals to contribute to scientific development. Since then a citizen science green paper was published in 2013, and European Commission policy directives have included citizen science as one of five strategic areas with funding allocated to support initiatives through the 'Science With and For Society (SwafS)', a strand of the Horizon 2020 programme. This includes significant awards such as the EU Citizen Science Project, which is creating a hub for knowledge sharing, coordination, and action. The European Citizen Science Association (ECSA) was set up in 2014 to encourage the growth of citizen science across Europe, to increase public participation in scientific processes, mainly by initiating and supporting citizen science projects as well as conducting research. ECSA has a membership of over 250 individual and organisational members from over 30 countries across the European Union and beyond.
Examples of citizen science organisations and associations based in Europe include the Biosphere Expeditions (Ireland), Bürger schaffen Wissen (Germany), Citizen Science Lab at Leiden University (Netherlands), Ibercivis (See External Links), Österreich forscht (Austria). Other organisations can be found here: EU Citizen Science.
The European Citizen Science Association was created in 2014.
In 2023, the European Union Prize for Citizen Science was established. Bestowed through Ars Electronica, the prize was designed to honor, present and support "outstanding projects whose social and political impact advances the further development of a pluralistic, inclusive and sustainable society in Europe".
=== Latin America ===
In 2015, the Asháninka people from Apiwtxa, which crosses the border between Brazil and Peru, began using the Android app Sapelli to monitor their land. The Ashaninka have "faced historical pressures of disease, exploitation and displacement, and today still face the illegal invasion of their lands by loggers and hunters. This monitoring project shows how the Apiwtxa Ashaninka from the Kampa do Rio Amônia Indigenous Territory, Brazil, are beginning to use smartphones and technological tools to monitor these illegal activities more effectively."
In Argentina, two smartphone Android applications are available for citizen science. i) AppEAR has been developed at the Institute of Limnology and was launched in May 2016. Joaquín Cochero is a researcher who developed an "application that appeals to the collaboration of users of mobile devices in collecting data that allow the study of aquatic ecosystems" (translation). Cochero stated: "Not much of citizen science in Argentina, just a few more oriented to astronomy specific cases. As ours is the first. And I have volunteers from different parts of the country that are interested in joining together to centralize data. That's great because these types of things require many people participate actively and voluntarily" (translation). ii) eBird was launched in 2013, and has so far identified 965 species of birds. eBird in Argentina is "developed and managed by the Cornell Lab of Ornithology at Cornell University, one of the most important ornithological institutions in the world, and locally presented recently with the support of the Ministry of Science, Technology and Productive Innovation of the Nation (MINCyT)" (translation).
Projects in Brazil include: i) Platform and mobile app 'Missions' has been developed by IBM in their São Paulo research lab with Brazil's Ministry for Environment and Innovation (BMEI). Sergio Borger, an IBM team lead in São Paulo, devised the crowdsourced approach when BMEI approached the company in 2010. They were looking for a way to create a central repository for the rainforest data. Users can upload photos of a plant species and its components, enter its characteristics (such as color and size), compare it against a catalog photo and classify it. The classification results are juried by crowdsourced ratings. ii) Exoss Citizen Science is a member of Astronomers Without Borders and seeks to explore the southern sky for new meteors and radiants. Users can report meteor fireballs through uploading pictures on to a webpage or by linking to YouTube. iii) The Information System on Brazilian Biodiversity (SiBBr) was launched in 2014 "aiming to encourage and facilitate the publication, integration, access and use of information about the biodiversity of the country." Their initial goal "was to gather 2.5 million occurrence records of species from biological collections in Brazil and abroad up to the end of 2016. It is now expected that SiBBr will reach nine million records in 2016." Andrea Portela said: "In 2016, we will begin with the citizen science. They are tools that enable anyone, without any technical knowledge, to participate. With this we will achieve greater engagement with society. People will be able to have more interaction with the platform, contribute and comment on what Brazil has." iv) The Brazilian Marine Megafauna Project (Iniciativa Pro Mar) is working with the European CSA towards its main goal, which is the "sensibilization of society for marine life issues" and concerns about pollution and the over-exploitation of natural resources. Having started as a project monitoring manta ray, it now extends to whale shark and educating schools and divers within the Santos area. Its social media activities include a live streaming of a citizen science course to help divers identify marine megafauna. v) A smartphone app called Plantix has been developed by the Leibniz Centre for Agricultural Landscape Research (ZALF) which helps Brazilian farmers discover crop diseases quicker and helps fight them more efficiently. Brazil is a very large agricultural exporter, but between 10 and 30% of crops fail because of disease. "The database currently includes 175 frequently occurring crop diseases and pests as well as 40,000 photos. The identification algorithm of the app improves with every image which records a success rate of over 90 per cent as of approximately 500 photos per crop disease." vi) In an Atlantic Ocean forest region in Brazil, an effort to map the genetic riches of soil is under way. The Drugs From Dirt initiative, based at the Rockefeller University, seeks to turn up bacteria that yield new types of antibiotics – the Brazilian region being particularly rich in potentially useful bacterial genes. Approximately a quarter of the 185 soil samples have been taken by Citizen Scientists without which the project could not run.
In Chile citizen science projects include (some websites in Spanish): i) Testing new cancer therapies with scientists from the Science Foundation for Life. ii) Monitoring the population of the Chilean bumblebee. iii) Monitoring the invasive ladybird Chinita arlequín. iv) Collecting rain water data. v) Monitoring various pollinating fly populations. vi) Providing information and field data on the abundance and distribution of various species of rockfish. vii) Investigating the environmental pollution by plastic litter.
Projects in Colombia include (some websites in Spanish): i) The Communications Project of the Humboldt Institute along with the Organization for Education and Environmental Protection initiated projects in the Bogotá wetlands of Cordoba and El Burro, which have a lot of biodiversity. ii) In the Model Forest of Risaralda, the Colombia 'proyecto de Ciencia Abierta y Colaborativa' promotes citizen participation in research related to how the local environment is adapting to climate change. The first meeting took place in the Flora and Fauna Sanctuary Otún Quimbaya. iii) The Citizen Network Environmental Monitoring (CLUSTER), based in the city of Bucaramanga, seeks to engage younger students in data science, who are trained in building weather stations with open repositories based on free software and open hardware data. iv) The Symposium on Biodiversity has adapted the CS tool iNaturalist for use in Colombia. v) The Sinchi Amazonic Institute of Scientific Research seeks to encourage the development and diffusion of knowledge, values and technologies on the management of natural resources for ethnic groups in the Amazon. This research should further the use of participatory action research schemes and promoting participation communities.
Since 2010, the Pacific Biodiversity Institute (PBI) seeks "volunteers to help identify, describe and protect wildland complexes and roadless areas in South America". The PBI "are engaged in an ambitious project with our Latin American conservation partners to map all the wildlands in South America, to evaluate their contribution to global biodiversity and to share and disseminate this information."
In Mexico, a citizen science project has monitored rainfall data that is linked to a hydrologic payment for ecosystem services project.
== Conferences ==
The first Conference on Public Participation in Scientific Research was held in Portland, Oregon, in August 2012. Citizen science is now often a theme at large conferences, such as the annual meeting of the American Geophysical Union.
In 2010, 2012 and 2014 there were three Citizen Cyberscience summits, organised by the Citizen Cyberscience Centre in Geneva and University College London. The 2014 summit was hosted in London and attracted over 300 participants.
In November 2015, the ETH Zürich and University of Zürich hosted an international meeting on the "Challenges and Opportunities in Citizen Science".
The first citizen science conference hosted by the Citizen Science Association was in San Jose, California, in February 2015 in partnership with the AAAS conference. The Citizen Science Association conference, CitSci 2017, was held in Saint Paul, Minnesota, United States, between 17 and 20 May 2017. The conference had more than 600 attendees. The next CitSci was in March 2019 in Raleigh, North Carolina.
The platform "Österreich forscht" hosts the annual Austrian citizen science conference since 2015.
== In popular culture ==
Barbara Kingsolver’s 2012 novel Flight Behaviour looks at the effects of citizen science on a housewife in Appalachia, when her interest in butterflies brings her into contact with scientists and academics.
== See also ==
== References ==
== Further reading ==
Web, Cameron; Williams, Craig; Sousa, Larissa Braz; Doherty, Seamus; Fricker, Stephen Robert (11 December 2019). "As heat strikes, here's one way to help fight disease-carrying and nuisance mosquitoes". The Conversation. "The Mozzie Monitors program marks the first time formal mosquito trapping has been combined with citizen science." (Australian project)
Franzoni, Chiara; Sauermann, Henry (February 2014). "Crowd science: The organization of scientific research in open collaborative projects". Research Policy. 43 (1): 1–20. doi:10.1016/j.respol.2013.07.005. hdl:11311/754644. SSRN 2167538.
Dick Kasperowsik (interviewed by Ulrich Herb): Citizen Science as democratization of science? In: telepolis, 2016, 27 August
Ridley, Matt. (8 February 2012) "Following the Crowd to Citizen Science". The Wall Street Journal
Young, Jeffrey R. (28 May 2010). "Crowd Science Reaches New Heights", The Chronicle of Higher Education
Sauermann, Henry; Franzoni, Chiara (20 January 2015). "Crowd science user contribution patterns and their implications". Proceedings of the National Academy of Sciences. 112 (3): 679–684. Bibcode:2015PNAS..112..679S. doi:10.1073/pnas.1408907112. PMC 4311847. PMID 25561529. SSRN 2545945.
Bourjon, Philippe; Ducarme, Frédéric; Quod, Jean-Pascal; Sweet, Michael (2018). "Involving recreational snorkelers in inventory improvement or creation: a case study in the Indian Ocean". Cahiers de Biologie Marine. 59: 451–460. doi:10.21411/CBM.A.B05FC714.
Albagli, Sarita; Iwama, Allan Yu (2022). "Citizen science and the right to research: building local knowledge of climate change impacts". Humanities and Social Sciences Communications. 9 (1): 1–13. doi:10.1057/s41599-022-01040-8.
Fritz, Steffen; See, Linda; Carlson, Tyler; Haklay, Mordechai (Muki); Oliver, Jessie L.; Fraisl, Dilek; Mondardini, Rosy; Brocklehurst, Martin; Shanley, Lea A.; Schade, Sven; Wehn, Uta; Abrate, Tommaso; Anstee, Janet; Arnold, Stephan; Billot, Matthew; Campbell, Jillian; Espey, Jessica; Gold, Margaret; Hager, Gerid; He, Shan; Hepburn, Libby; Hsu, Angel; Long, Deborah; Masó, Joan; McCallum, Ian; Muniafu, Maina; Moorthy, Inian; Obersteiner, Michael; Parker, Alison J.; Weisspflug, Maike; West, Sarah (2019). "Citizen science and the United Nations Sustainable Development Goals". Nature Sustainability. 2 (10): 922–930. Bibcode:2019NatSu...2..922F. doi:10.1038/s41893-019-0390-3.
== External links ==
Media related to Citizen science at Wikimedia Commons
"Controversy over the term 'citizen science'". CBC News. 13 August 2021. Retrieved 15 April 2023. | Wikipedia/Citizen_science |
In science, objectivity refers to attempts to do higher quality research by eliminating personal biases (or prejudices), irrational emotions and false beliefs, while focusing mainly on proven facts and evidence. It is often linked to observation as part of the scientific method. It is thus related to the aim of testability and reproducibility. To be considered objective, the results of measurement must be communicated from person to person, and then demonstrated for third parties, as an advance in a collective understanding of the world. Such demonstrable knowledge has ordinarily conferred demonstrable powers of prediction or technology.
The problem of philosophical objectivity is contrasted with personal subjectivity, sometimes exacerbated by the overgeneralization of a hypothesis to the whole. For example, Newton's law of universal gravitation appears to be the norm for the attraction between celestial bodies, but it was later refined and extended—and philosophically superseded—by the more general theory of relativity.
== History ==
The scientific method was argued for by Enlightenment philosopher Francis Bacon, rose to popularity with the discoveries of Isaac Newton and his followers, and continued into later eras. In the early eighteenth century, there existed an epistemic virtue in science which has been called truth-to-nature.: 55–58 This ideal was practiced by Enlightenment naturalists and scientific atlas-makers, and involved active attempts to eliminate any idiosyncrasies in their representations of nature in order to create images thought best to represent "what truly is".: 59–60 : 84–85 Judgment and skill were deemed necessary in order to determine the "typical", "characteristic", "ideal", or "average".: 87 In practicing, truth-to-nature naturalists did not seek to depict exactly what was seen; rather, they sought a reasoned image.: 98
In the latter half of the nineteenth-century, objectivity in science was born when a new practice of mechanical objectivity appeared.: 121 "'Let nature speak for itself' became the watchword of a new brand of scientific objectivity.": 81 It was at this time that idealized representations of nature, which were previously seen as a virtue, were now seen as a vice.: 120 Scientists began to see it as their duty to actively restrain themselves from imposing their own projections onto nature.: 81 The aim was to liberate representations of nature from subjective, human interference and in order to achieve this scientists began using self-registering instruments, cameras, wax molds, and other technological devices.: 121
In the twentieth century trained judgment: 309 supplemented mechanical objectivity as scientists began to recognize that, in order for images or data to be of any use, scientists needed to be able to see scientifically; that is, to interpret images or data and identify and group them according to particular professional training, rather than to simply depict them mechanically.: 311–314 Since the latter half of the nineteenth century, objectivity has come to involve a combination of trained judgment and mechanical objectivity.
== Objectivity in measurement ==
Another methodological aspect is the avoidance of bias, which can involve cognitive bias, cultural bias, or sampling bias. Methods for avoiding or overcoming such biases include random sampling and double-blind trials. However, objectivity in measurement can be unobtainable in certain circumstances. Even the most quantitative social sciences such as economics employ measures that are constructs (conventions, to employ the term coined by Pierre Duhem).
== The role of the scientific community ==
Various scientific processes, such as peer reviews, the discussions at scientific conferences, and other meetings where scientific results are presented, are part of a social process whose purpose is to strengthen the objective aspect of the scientific method.
Next to unintentional and systematic error, there is always the possibility of deliberate misrepresentation of scientific results, whether for gain, fame, or ideological motives. When such cases of scientific fraud come to light, they usually give rise to an academic scandal, but it is unknown how much fraud goes undiscovered. For important results, other groups will try to repeat the experiment. If they consistently fail, they will bring these negative results into the scientific debate.
== Critiques of scientific objectivity ==
A critical argument on scientific objectivity and positivism is that all science has a degree of interpretivism.: 29 In the 1920s, Percy Bridgman's The Logic of Modern Physics and the operationalism presented was centered in such recognition.: 29
=== Thomas Kuhn's The Structure of Scientific Revolutions ===
Based on a historical review of the development of certain scientific theories in his book, The Structure of Scientific Revolutions, scientist and historian Thomas Kuhn raised some philosophical objections to claims of the possibility of scientific understanding being truly objective. In Kuhn's analysis, scientists in different disciplines organise themselves into de facto paradigms within which scientific research is done, junior scientists are educated, and scientific problems are determined.
When observational data arises which appears to contradict or falsify a given scientific paradigm, scientists within that paradigm historically have not immediately rejected it, as Karl Popper's philosophical theory of falsificationism would have them do. Instead they have gone to considerable lengths to resolve the apparent conflict without rejecting the paradigm. Through ad hoc variations to the theory and sympathetic interpretation of the data, supporting scientists will resolve the apparent conundrum. In extreme cases, they may ignore the data altogether. Thus, the failure of a scientific paradigm will go into crisis when a significant portion of scientists working in the field lose confidence in it. The corollary of this observation is that a paradigm is contingent on the social order amongst scientists at the time it gains ascendancy.
Kuhn's theory has been criticised by scientists such as Richard Dawkins and Alan Sokal as presenting a relativist view of scientific progress.
=== Donna Haraway's Situated Knowledges ===
In Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective (1988), Donna Haraway argues that objectivity in science and philosophy is traditionally understood as a kind of disembodied and transcendent "conquering gaze from nowhere.": 581 She argues that this kind of objectivity, in which the subject is split apart and distanced from the object, is an impossible "illusion, a god trick.": 583–587 She demands a re-thinking of objectivity in such a way that, while still striving for "faithful accounts of the real world,": 579 we must also acknowledge our perspective within the world. She calls this new kind of knowledge-making "situated knowledges." Objectivity, she argues, "turns out to be about particular and specific embodiment and ... not about the false vision promising transcendence of all limits and responsibility". This new objectivity, "allows us to become answerable for what we learn how to see.": 581–583
== See also ==
Objectivity (philosophy)
== References ==
=== Sources ===
Dawkins, Richard (2003). A Devil's Chaplain: Selected essays. Phoenix.
Kuhn, Thomas (1962). The structure of scientific revolutions. University of Chicago Press, 3rd Ed., 1996.
Latour, Bruno (1987). Science in Action. Cambridge, Mass: Harvard University Press.
Polanyi, Michael (1958). Personal knowledge, towards a post-critical philosophy. London: Routledge.
Sokal, Alan & Bricmont, Jean (1999). Intellectual Impostures: Postmodern philosophers' abuse of science. London: Profile Books.
== Further reading ==
Gaukroger, S. (2001). Objectivity, History of. IN: Smelser, N. J. & Baltes, P. B. (eds.) International Encyclopedia of the Social and Behavioral Sciences. Oxford. (pp. 10785–10789).
Porter, Theodore M. (1995). Trust in Numbers: The Pursuit of Objectivity in Science and Public Life. Princeton University Press.
Restivo, Sal. (20XX). Science, Society, and Values: Toward a Sociology of Objectivity. Lehigh University Press.
Reiss, Julian; Sprenger, Jan (6 November 2017) [First published 25 August 2014]. "Scientific Objectivity". In Zalta, Edward N. (ed.). Stanford Encyclopedia of Philosophy (Winter 2017 ed.). Stanford University: The Metaphysics Research Lab. ISSN 1095-5054. Retrieved 31 May 2018. | Wikipedia/Objectivity_(science) |
Popular science (also called pop-science or popsci) is an interpretation of science intended for a general audience. While science journalism focuses on recent scientific developments, popular science is more broad ranging. It may be written by professional science journalists or by scientists themselves. It is presented in many forms, including books, film and television documentaries, magazine articles, and web pages.
== History ==
Before the modern specialization and professionalization of science, there was often little distinction between "science" and "popular science", and works intended to share scientific knowledge with a general reader existed as far back as Greek and Roman antiquity. Without these popular works, much of the scientific knowledge of the era might have been lost. For example, none of the original works of the Greek astronomer Eudoxus (4th century BC) have survived, but his contributions were largely preserved due to the didactic poem Phenomena written a century later and commented on by Hipparchus. Explaining science in poetic form was not uncommon, and as recently as 1791, Erasmus Darwin wrote The Botanic Garden, two long poems intended to interest and educate readers in botany. Many Greek and Roman scientific handbooks were written for the lay audience, and this "handbook" tradition continued right through to the invention of the printing press, with much later examples including books of secrets such as Giambattista Della Porta's Magia Naturalis (1558) and Isabella Cortese's Secreti (1561).
The 17th century saw the beginnings of the modern scientific revolution and the consequent need for explicit popular science writing. Although works such as Galileo's The Assayer (1632) and Robert Hooke's Micrographia (1665) were read by both scientists and the public, Newton's Principia (1687) was incomprehensible for most readers, so popularizations of Newton's ideas soon followed. Popular science writing surged in countries such as France, where books such as Fontenelle's Conversations on the Plurality of Worlds (1686) were best-sellers.
By 1830, astronomer John Herschel had recognized the need for the specific genre of popular science. In a letter to philosopher William Whewell, he wrote that the general public needed "digests of what is actually known in each particular branch of science... to give a connected view of what has been done, and what remains to be accomplished." Indeed, as the British population became not just increasingly literate but also well-educated, there was growing demand for science titles. Mary Somerville became an early and highly successful science writer of the nineteenth century. Her On the Connexion of the Physical Sciences (1834), intended for the mass audience, sold quite well. Arguably one of the first books in modern popular science, it contained few diagrams and very little mathematics. Ten editions of the book were published, and it was translated into multiple languages. It was the most popular science title from the publisher John Murray until On the Origin of Species (1859) by Charles Darwin.
== Role ==
Popular science is a bridge between scientific literature as a professional medium of scientific research, and the realms of popular political and cultural discourse. The goal of the genre is often to capture the methods and accuracy of science while making the language more accessible. Many science-related controversies are discussed in popular science books and publications, such as the long-running debates over biological determinism and the biological components of intelligence, stirred by popular books such as The Mismeasure of Man and The Bell Curve.
The purpose of scientific literature is to inform and persuade peers regarding the validity of observations and conclusions and the forensic efficacy of methods. Popular science attempts to inform and convince scientific outsiders (sometimes along with scientists in other fields) of the significance of data and conclusions and to celebrate the results. Statements in the scientific literature are often qualified and tentative, emphasizing that new observations and results are consistent with and similar to established knowledge wherein qualified scientists are assumed to recognize the relevance. By contrast, popular science emphasizes uniqueness and generality, taking a tone of factual authority absent from the scientific literature.
== Common threads ==
Some usual features of popular science productions include:
Entertainment value or personal relevance to the audience
Emphasis on uniqueness and radicalness
Exploring ideas overlooked by specialists or falling outside established disciplines
Generalized, simplified science concepts
Presented for an audience with little or no science background, hence explaining general concepts more thoroughly
Synthesis of new ideas that cross multiple fields and offer new applications in other academic specialties
Use of metaphors and analogies to explain difficult or abstract scientific concepts
== Criticism ==
The purpose of scientific literature is to inform and persuade peers regarding the validity of observations and conclusions and the forensic efficacy of methods. Popular science attempts to inform and convince scientific outsiders (sometimes along with scientists in other fields) of the significance of data and conclusions and to celebrate the results. Statements in the scientific literature are often qualified and tentative, emphasizing that new observations and results are consistent with and similar to established knowledge wherein qualified scientists are assumed to recognize the relevance. By contrast, popular science often emphasizes uniqueness and generality and may have a tone of factual authority absent from the scientific literature. Comparisons between original scientific reports, derivative science journalism, and popular science typically reveals at least some level of distortion and oversimplification.
== See also ==
List of science communicators
List of popular science mass media outlets
== Notes and references ==
== General bibliography ==
Andreas W. Daum, Varieties of Popular Science and the Transformations of Public Knowledge: Some Historical Reflections". Isis. A Journal of the History of Science Society, 100 (June 2009), 319–332.
McRae, Murdo William (editor). The Literature of Science: Perspectives on Popular Scientific Writing. The University of Georgia Press: Athens, 1993. ISBN 0-8203-1506-0.
== External links ==
Media related to Popular science at Wikimedia Commons
The dictionary definition of popular science at Wiktionary | Wikipedia/Popular_science |
Historical method is the collection of techniques and guidelines that historians use to research and write histories of the past. Secondary sources, primary sources and material evidence such as that derived from archaeology may all be drawn on, and the historian's skill lies in identifying these sources, evaluating their relative authority, and combining their testimony appropriately in order to construct an accurate and reliable picture of past events and environments.
In the philosophy of history, the question of the nature, and the possibility, of a sound historical method is raised within the sub-field of epistemology. The study of historical method and of different ways of writing history is known as historiography.
Though historians agree in very general and basic principles, in practice "specific canons of historical proof are neither widely observed nor generally agreed upon" among professional historians. Some scholars of history have observed that there are no particular standards for historical fields such as religion, art, science, democracy, and social justice as these are by their nature 'essentially contested' fields, such that they require diverse tools particular to each field beforehand in order to interpret topics from those fields.
== Source criticism ==
Source criticism (or information evaluation) is the process of evaluating the qualities of an information source, such as its validity, reliability, and relevance to the subject under investigation.
Gilbert J. Garraghan and Jean Delanglez (1946) divide source criticism into six inquiries:
When was the source, written or unwritten, produced (date)?
Where was it produced (localization)?
By whom was it produced (authorship)?
From what pre-existing material was it produced (analysis)?
In what original form was it produced (integrity)?
What is the evidential value of its contents (credibility)?
The first four are known as higher criticism; the fifth, lower criticism; and, together, external criticism. The sixth and final inquiry about a source is called internal criticism. Together, this inquiry is known as source criticism.
R. J. Shafer on external criticism: "It sometimes is said that its function is negative, merely saving us from using false evidence; whereas internal criticism has the positive function of telling us how to use authenticated evidence."
Noting that few documents are accepted as completely reliable, Louis Gottschalk sets down the general rule, "for each particular of a document the process of establishing credibility should be separately undertaken regardless of the general credibility of the author". An author's trustworthiness in the main may establish a background probability for the consideration of each statement, but each piece of evidence extracted must be weighed individually.
=== Procedures for contradictory sources ===
Bernheim (1889) and Langlois & Seignobos (1898) proposed a seven-step procedure for source criticism in history:
If the sources all agree about an event, historians can consider the event proven.
However, majority does not rule; even if most sources relate events in one way, that version will not prevail unless it passes the test of critical textual analysis.
The source whose account can be confirmed by reference to outside authorities in some of its parts can be trusted in its entirety if it is impossible similarly to confirm the entire text.
When two sources disagree on a particular point, the historian will prefer the source with most "authority"—that is the source created by the expert or by the eyewitness.
Eyewitnesses are, in general, to be preferred especially in circumstances where the ordinary observer could have accurately reported what transpired and, more specifically, when they deal with facts known by most contemporaries.
If two independently created sources agree on a matter, the reliability of each is measurably enhanced.
When two sources disagree and there is no other means of evaluation, then historians take the source which seems to accord best with common sense.
Subsequent descriptions of historical method, outlined below, have attempted to overcome the credulity built into the first step formulated by the nineteenth century historiographers by stating principles not merely by which different reports can be harmonized but instead by which a statement found in a source may be considered to be unreliable or reliable as it stands on its own.
=== Core principles for determining reliability ===
The following core principles of source criticism were formulated by two Scandinavian historians, Olden-Jørgensen (1998) and Thurén Torsten (1997):
Human sources may be relics such as a fingerprint; or narratives such as a statement or a letter. Relics are more credible sources than narratives.
Any given source may be forged or corrupted. Strong indications of the originality of the source increase its reliability.
The closer a source is to the event which it purports to describe, the more one can trust it to give an accurate historical description of what actually happened.
An eyewitness is more reliable than testimony at second hand, which is more reliable than hearsay at further remove, and so on.
If a number of independent sources contain the same message, the credibility of the message is strongly increased.
The tendency of a source is its motivation for providing some kind of bias. Tendencies should be minimized or supplemented with opposite motivations.
If it can be demonstrated that the witness or source has no direct interest in creating bias then the credibility of the message is increased.
==== Criteria of authenticity ====
Historians sometimes have to deal with deciding what is genuine and what is not in a source. For such circumstances, there are external and internal "criteria of authenticity" that are applicable. These are technical tools for evaluating sources and separating 'genuine' sources or content from forgeries or manipulation.
External criteria involve issues relating to establishing authorship of a source or range of sources. It involves things like if an author wrote something themselves, if other sources attribute authorship to the source, agreement of independent manuscript copies on the content of a source.
Internal criteria involve formalities, style, and language for an author; if a source varies from the environment it was produced, inconsistencies of time or chronology, textual transmission of a source, interpolations in a source, insertions or deletions in a source.
=== Eyewitness evidence ===
R. J. Shafer (1974) offers this checklist for evaluating eyewitness testimony:
Is the real meaning of the statement different from its literal meaning? Are words used in senses not employed today? Is the statement meant to be ironic (i.e., mean other than it says)?
How well could the author observe the thing he reports? Were his senses equal to the observation? Was his physical location suitable to sight, hearing, touch? Did he have the proper social ability to observe: did he understand the language, have other expertise required (e.g., law, military); was he not being intimidated by his wife or the secret police?
How did the author report?, and what was his ability to do so?
Regarding his ability to report, was he biased? Did he have proper time for reporting? Proper place for reporting? Adequate recording instruments?
When did he report in relation to his observation? Soon? Much later? Fifty years is much later as most eyewitnesses are dead and those who remain may have forgotten relevant material.
What was the author's intention in reporting? For whom did he report? Would that audience be likely to require or suggest distortion to the author?
Are there additional clues to intended veracity? Was he indifferent on the subject reported, thus probably not intending distortion? Did he make statements damaging to himself, thus probably not seeking to distort? Did he give incidental or casual information, almost certainly not intended to mislead?
Do his statements seem inherently improbable: e.g., contrary to human nature, or in conflict with what we know?
Remember that some types of information are easier to observe and report on than others.
Are there inner contradictions in the document?
Louis Gottschalk adds an additional consideration: "Even when the fact in question may not be well-known, certain kinds of statements are both incidental and probable to such a degree that error or falsehood seems unlikely. If an ancient inscription on a road tells us that a certain proconsul built that road while Augustus was princeps, it may be doubted without further corroboration that that proconsul really built the road, but would be harder to doubt that the road was built during the principate of Augustus. If an advertisement informs readers that 'A and B Coffee may be bought at any reliable grocer's at the unusual price of fifty cents a pound,' all the inferences of the advertisement may well be doubted without corroboration except that there is a brand of coffee on the market called 'A and B Coffee.'"
=== Indirect witnesses ===
Garraghan (1946) says that most information comes from "indirect witnesses", people who were not present on the scene but heard of the events from someone else. Gottschalk says that a historian may sometimes use hearsay evidence when no primary texts are available. He writes, "In cases where he uses secondary witnesses...he asks: (1) On whose primary testimony does the secondary witness base his statements? (2) Did the secondary witness accurately report the primary testimony as a whole? (3) If not, in what details did he accurately report the primary testimony? Satisfactory answers to the second and third questions may provide the historian with the whole or the gist of the primary testimony upon which the secondary witness may be his only means of knowledge. In such cases the secondary source is the historian's 'original' source, in the sense of being the 'origin' of his knowledge. Insofar as this 'original' source is an accurate report of primary testimony, he tests its credibility as he would that of the primary testimony itself." Gottschalk adds, "Thus hearsay evidence would not be discarded by the historian, as it would be by a law court merely because it is hearsay."
=== Oral tradition ===
Gilbert Garraghan (1946) maintains that oral tradition may be accepted if it satisfies either two "broad conditions" or six "particular conditions", as follows:
Broad conditions stated.
The tradition should be supported by an unbroken series of witnesses, reaching from the immediate and first reporter of the fact to the living mediate witness from whom we take it up, or to the one who was the first to commit it to writing.
There should be several parallel and independent series of witnesses testifying to the fact in question.
Particular conditions formulated.
The tradition must report a public event of importance, such as would necessarily be known directly to a great number of persons.
The tradition must have been generally believed, at least for a definite period of time.
During that definite period it must have gone without protest, even from persons interested in denying it.
The tradition must be one of relatively limited duration. [Elsewhere, Garraghan suggests a maximum limit of 150 years, at least in cultures that excel in oral remembrance.]
The critical spirit must have been sufficiently developed while the tradition lasted, and the necessary means of critical investigation must have been at hand.
Critical-minded persons who would surely have challenged the tradition – had they considered it false – must have made no such challenge.
Other methods of verifying oral tradition may exist, such as comparison with the evidence of archaeological remains.
More recent evidence concerning the potential reliability or unreliability of oral tradition has come out of fieldwork in West Africa and Eastern Europe.
=== Anonymous sources ===
Historians do allow for the use of anonymous texts to establish historical facts.
== Synthesis: historical reasoning ==
Once individual pieces of information have been assessed in context, hypotheses can be formed and established by historical reasoning.
=== Argument to the best explanation ===
C. Behan McCullagh (1984) lays down seven conditions for a successful argument to the best explanation:
The statement, together with other statements already held to be true, must imply yet other statements describing present, observable data. (We will henceforth call the first statement 'the hypothesis', and the statements describing observable data, 'observation statements'.)
The hypothesis must be of greater explanatory scope than any other incompatible hypothesis about the same subject; that is, it must imply a greater variety of observation statements.
The hypothesis must be of greater explanatory power than any other incompatible hypothesis about the same subject; that is, it must make the observation statements it implies more probable than any other.
The hypothesis must be more plausible than any other incompatible hypothesis about the same subject; that is, it must be implied to some degree by a greater variety of accepted truths than any other, and be implied more strongly than any other; and its probable negation must be implied by fewer beliefs, and implied less strongly than any other.
The hypothesis must be less ad hoc than any other incompatible hypothesis about the same subject; that is, it must include fewer new suppositions about the past which are not already implied to some extent by existing beliefs.
It must be disconfirmed by fewer accepted beliefs than any other incompatible hypothesis about the same subject; that is, when conjoined with accepted truths it must imply fewer observation statements and other statements which are believed to be false.
It must exceed other incompatible hypotheses about the same subject by so much, in characteristics 2 to 6, that there is little chance of an incompatible hypothesis, after further investigation, soon exceeding it in these respects.
McCullagh sums up, "if the scope and strength of an explanation are very great, so that it explains a large number and variety of facts, many more than any competing explanation, then it is likely to be true".
=== Statistical inference ===
McCullagh (1984) states this form of argument as follows:
There is probability (of the degree p1) that whatever is an A is a B.
It is probable (to the degree p2) that this is an A.
Therefore, (relative to these premises) it is probable (to the degree p1 × p2) that this is a B.
McCullagh gives this example:
In thousands of cases, the letters V.S.L.M. appearing at the end of a Latin inscription on a tombstone stand for Votum Solvit Libens Merito.
From all appearances the letters V.S.L.M. are on this tombstone at the end of a Latin inscription.
Therefore, these letters on this tombstone stand for Votum Solvit Libens Merito.
This is a syllogism in probabilistic form, making use of a generalization formed by induction from numerous examples (as the first premise).
=== Argument from analogy ===
The structure of the argument is as follows:
One thing (object, event, or state of affairs) has properties p1 . . . pn and pn + 1.
Another thing has properties p1 . . . pn.
So the latter has property pn + 1.
McCullagh says that an argument from analogy, if sound, is either a "covert statistical syllogism" or better expressed as an argument to the best explanation. It is a statistical syllogism when it is "established by a sufficient number and variety of instances of the generalization"; otherwise, the argument may be invalid because properties 1 through n are unrelated to property n + 1, unless property n + 1 is the best explanation of properties 1 through n. Analogy, therefore, is uncontroversial only when used to suggest hypotheses, not as a conclusive argument.
== Development ==
The development of historical methodology started in the ancient period. Herodotus, from the 5th century BC, has been acclaimed as the "father of history". However, his contemporary Thucydides is credited with having first approached history with a well-developed historical method in the History of the Peloponnesian War. Thucydides, unlike Herodotus, regarded history as the product of the choices and actions of humans, and looked at cause and effect, rather than the result of divine intervention (though Herodotus was not wholly committed to this idea himself). In his historical method, Thucydides emphasized chronology, a nominally neutral point of view, and that the human world was the result of human actions. Greek historians viewed history as cyclical, with events regularly recurring.
There was sophisticated use of historical method in ancient and medieval China. The groundwork for professional historiography in East Asia was established by court historian Sima Qian (145–90 BC), author of the Records of the Grand Historian (Shiji) and posthumously known as the Father of Chinese historiography. Saint Augustine was influential in Christian and Western thought at the beginning of the medieval period. Through the Medieval and Renaissance periods, history was often studied through a sacred or religious perspective. Around 1800, German philosopher and historian Georg Wilhelm Friedrich Hegel brought philosophy and a more secular approach in historical study.
In the preface to his book, the Muqaddimah (1377), the Arab historian and early sociologist, Ibn Khaldun, warned of 7 mistakes he thought historians committed. In this criticism, he approached the past as strange and in need of interpretation. The originality of Ibn Khaldun was to claim that the cultural difference of another age must govern the evaluation of relevant historical material, to distinguish the principles according to which it might be possible to attempt the evaluation, and to feel the need for experience, in addition to rational principles, in order to assess a culture of the past. Ibn Khaldun criticized "idle superstition and uncritical acceptance of historical data". He introduced a scientific method to the study of history, and referred to it as his "new science". His method laid the groundwork for the observation of the role of state, communication, propaganda and systematic bias in history, and so is sometimes considered to be the "father of historiography"
or the "father of the philosophy of history".
In the West, historians developed modern methods of historiography in the 17th and 18th centuries, especially in France and Germany. In 1851, Herbert Spencer summarized these methods:"From the successive strata of our historical deposits, they [historians] diligently gather all the highly colored fragments, pounce upon everything that is curious and sparkling and chuckle like children over their glittering acquisitions; meanwhile the rich veins of wisdom that ramify amidst this worthless debris, lie utterly neglected. Cumbrous volumes of rubbish are greedily accumulated, while those masses of rich ore, that should have been dug out, and from which golden truths might have been smelted, are left untaught and unsought."
By the "rich ore" Spencer meant scientific theory of history. Meanwhile, Henry Thomas Buckle expressed a dream of history becoming one day a science: "In regard to nature, events apparently the most irregular and capricious have been explained and have been shown to be in accordance with certain fixed and universal laws. This has been done because men of ability and, above all, men of patient, untiring thought have studied events with the view of discovering their regularity, and if human events were subject to a similar treatment, we have every right to expect similar results.
Contrary to Buckle's dream, the 19th-century historian with greatest influence on methods became Leopold von Ranke in Germany. He limited history to "what really happened" and by this directed the field further away from science. For Ranke, historical data should be collected carefully, examined objectively and put together with critical rigor. But these procedures "are merely the prerequisites and preliminaries of science. The heart of science is searching out order and regularity in the data being examined and in formulating generalizations or laws about them."
As Historians like Ranke and many who followed him have pursued it, no, history is not a science. Thus if Historians tell us that, given the manner in which he practices his craft, it cannot be considered a science, we must take him at his word. If he is not doing science, then, whatever else he is doing, he is not doing science. The traditional Historian is thus no scientist and history, as conventionally practiced, is not a science.
In the 20th century, academic historians focused less on epic nationalistic narratives, which often tended to glorify the nation or great men, to more objective and complex analyses of social and intellectual forces. A major trend of historical methodology in the 20th century was to treat history more as a social science rather than art, which traditionally had been the case. Leading advocates of history as a social science were a diverse collection of scholars which included Fernand Braudel and E. H. Carr. Many are noted for their multidisciplinary approach e.g. Braudel combined history with geography. Nevertheless, these multidisciplinary approaches failed to produce a theory of history. So far only one theory of history came from a professional historian. Whatever other theories of history exist, they were written by experts from other fields (for example, Marxian theory of history). The field of digital history has begun to address ways of using computer technology, to pose new questions to historical data and generate digital scholarship.
In opposition to the claims of history as a social science, historians such as Hugh Trevor-Roper argued the key to historians' work was the power of the imagination, and hence contended that history should be understood as art. French historians associated with the Annales school introduced quantitative history, using raw data to track the lives of typical individuals, and were prominent in the establishment of cultural history (cf. histoire des mentalités). Intellectual historians such as Herbert Butterfield have argued for the significance of ideas in history. American historians, motivated by the civil rights era, focused on formerly overlooked ethnic, racial, and socioeconomic groups. A genre of social history to emerge post-WWII was Alltagsgeschichte (History of Everyday Life). Scholars such as Ian Kershaw examined what everyday life was like for ordinary people in 20th-century Germany, especially in Nazi Germany.
The Marxist theory of historical materialism theorises that society is fundamentally determined by the material conditions at any given time – in other words, the relationships which people have with each other in order to fulfill basic needs such as feeding, clothing and housing themselves and their families. Overall, Marx and Engels claimed to have identified five successive stages of the development of these material conditions in Western Europe. Marxist historiography was once orthodoxy in the Soviet Union, but since the communism's collapse there, its influence has significantly reduced.
Marxist historians sought to validate Karl Marx's theories by analyzing history from a Marxist perspective. In response to the Marxist interpretation of history, historians such as François Furet have offered anti-Marxist interpretations of history. Feminist historians argued for the importance of studying the experience of women. Postmodernists have challenged the validity and need for the study of history on the basis all history is based on the personal interpretation of sources. Keith Windschuttle's 1994 book, The Killing of History defended the worth of history.
Today, most historians begin their research in archives, on either a physical or digital platform. They often propose an argument and use research to support it. John H. Arnold proposed that history is an argument, which creates the possibility of creating change. Digital information companies, such as Google, have sparked controversy over the role of internet censorship in information access.
== See also ==
Antiquarian
Archaeology
Archival research
Auxiliary sciences of history
Chinese whispers
Historical criticism
Historical significance
Historiography
List of history journals
Philosophy of history
Recorded history
Scholarly method
Scientific method
Source criticism
Unwitting testimony
== Footnotes ==
== References ==
Gilbert J. Garraghan, A Guide to Historical Method, Fordham University Press: New York (1946). ISBN 0-8371-7132-6
Louis Gottschalk, Understanding History: A Primer of Historical Method, Alfred A. Knopf: New York (1950). ISBN 0-394-30215-X.
Martha Howell and Walter Prevenier, From Reliable Sources: An Introduction to Historical Methods, Cornell University Press: Ithaca (2001). ISBN 0-8014-8560-6.
C. Behan McCullagh, Justifying Historical Descriptions, Cambridge University Press: New York (1984). ISBN 0-521-31830-0.
Presnell, J. L. (2019). The information-literate historian: a guide to research for history students (3rd ed.). Oxford University Press.
R. J. Shafer, A Guide to Historical Method, The Dorsey Press: Illinois (1974). ISBN 0-534-10825-3.
== External links ==
Introduction to Historical Method by Marc Comtois
Philosophy of History Archived 2005-09-05 at the Wayback Machine by Paul Newall
Federal Rules of Evidence in United States law | Wikipedia/Historical_method |
Languages of science are vehicular languages used by one or several scientific communities for international communication. According to science historian Michael Gordin, scientific languages are "either specific forms of a given language that are used in conducting science, or they are the set of distinct languages in which science is done." These two terms are different as one describes a distinct prose in a given language, while the other describes which languages are used in mainstream science.
Until the 19th century, classical languages such as Latin, Classical Arabic, Sanskrit, and Classical Chinese were commonly used across Afro-Eurasia for the purpose of international scientific communication. A combination of structural factors, the emergence of nation-states in Europe, the Industrial Revolution and the expansion of colonization entailed the global use of three European national languages: French, German and English. Yet new languages of science such as Russian or Italian had started to emerge by the end the 19th century, to the point that international scientific organizations started to promote the use of constructed languages like Esperanto as a non-national global standard.
After the First World War, English gradually outpaced French and German and became the leading language of science, but not the only international standard. Research in the Soviet Union rapidly expanded in the years following the Second World War, and access to Russian journals became a major policy issue in the United States, prompting the early development of machine translation. In the last decades of the 20th century, an increasing number of scientific publications used primarily English, in part due to the preeminence of English-speaking scientific infrastructures, indexes and metrics like the Science Citation Index. Local languages still remain largely relevant scientificly in major countries and world regions such as China, Latin America, and Indonesia. Disciplines and fields of study with a significant degree of public engagement such as social sciences, environmental studies, and medicine also have a maintained relevance of local languages.
The development of open science has revived the debate over linguistic diversity in science, as social and local impact has become an important objective of open science infrastructures and platforms. In 2019, 120 international research organizations co-signed the Helsinki Initiative on Multilingualism in Scholarly Communication and called for supporting multilingualism and the development of "infrastructure of scholarly communication in national languages". The 2021 Unesco Recommendation for Open Science includes "linguistic diversity" as one of the core features of open science, as it aims to "make multilingual scientific knowledge openly available, accessible and reusable for everyone." In 2022, the Council of the European Union officially supported "initiatives to promote multilingualism" in science, such as the Helsinki declaration.
== History ==
=== From classical languages to vernaculars ===
Until the 19th century, classical languages played an instrumental role in the diffusion of languages in Europe, Asia and North Africa.
In Europe, starting in the 12th century, Latin was the primary language of religion, law and administration until the Early Modern period. It became a language of science "through its encounter with Arabic"; during the Renaissance of the 12th century, a large corpus of Arabian scholarly texts was translated into Latin, in order for it to be available in the emerging network of European universities and centers of knowledge. In this process, the Latin language changed, and acquired the specific features of scholastic Latin, through numerous lexical and even syntactic borrowings from Greek and Arabic. The use of scientific Latin persisted long after the replacement of Latin by vernacular languages in most European administrations: "Latin's status as a language of science rested on the contrast it made with the use of the vernacular in other contexts" and created "a European community of learning" entirely distinct from the local communities where the scholars lived. Latin never was the sole language of science and education. Beyond local publications, vernaculars very early attained a status of international scientific languages, that could be expected to be understood and translated across Europe. In the mid-16th century, a significant amount of printed output in France was in Italian.
In the Indian and South Asian region, Sanskrit was a leading vehicular language for science. Sanskrit has been remodeled even more radically than Latin for the purpose of scientific communication as it shifted "toward ever more complex noun forms to encompass the kinds of abstractions demanded by scientific and mathematical thinking." Classical Chinese held a similarly prestigious position in East Asia, being largely adopted by scientific and Buddhist communities beyond the Chinese Empire, notably in Japan and Korea.
Classical languages declined throughout Eurasia during the 2nd millennium. Sanskrit was increasingly marginalized after the 13th century. Until the end of the 17th century, there was no clear trend of displacement of Latin in Europe by vernacular languages: while in the 16th century, medical books started to use French as well; this trend was reversed after 1597 and most medical literature in France remained only accessible in Latin until the 1680s. In 1670, as many books were printed in Latin as in German in the German states; in 1787, they accounted for no more than 10%. At this point, the decline became irreversible: since less and less European scholars were conversant with Latin, publications dwindled and there was less incentive to maintain linguistic training in Latin.
The emergence of scientific journals was both a symptom and cause of the declining use of a classical language. The first two modern scientific journals were published simultaneously in 1665: the Journal des Sçavans in France and the Philosophical Transactions of the Royal Society in England. They both used the local vernacular, which "made perfect historical sense" as both the Kingdom of France and the Kingdom of England were engaged in an active policy of linguistic promotion of the language standard.
=== French, English, German and the quest for an auxiliary language (1800–1920) ===
The gradual disuse of Latin opened an uneasy transition period as more and more works were only accessible in local languages. Many national European languages held the potential to become a language of science within a specific research field: some scholars "took measures to learn Swedish so they could follow the work of [the Swedish chemist] Bergman and his compatriots."
Language preferences and use across scientific communities were gradually consolidated into a triumvirate or triad of dominant languages of science: French, English and German. While each language would be expected to be understood for the purpose of international scientific communication, they also followed "different functional distributions evident in various scientific fields". French had been almost acknowledged as the international standard of European science in the late 18th century, and remained "essential" throughout the 19th century. German became a major scientific language within the 19th century as it "covered portions of the physical sciences, particularly physics and chemistry, plus mathematics and medicine." English was largely used by researchers and engineers, due to the seminal contribution of English technology to the Industrial Revolution.
In the years preceding the First World War, linguistic diversity of scientific publications increased significantly. The emergence of modern nationalities and early decolonization movements created new incentives to publish scientific knowledge in one's national language. Russian was one of the most successful developments of a new language of science. In the 1860s and 1870s, Russian researchers in chemistry and other physical sciences ceased to publish in German in favor of local periodicals, following a major work of adaptation and creation of names for scientific concepts or elements (such as chemical compounds). A controversy over the meaning of the periodic table of Dmitri Mendeleev contributed to the acknowledgement of original publications in Russian in the global scientific debate: the original version was deemed more authoritative than its first "imperfect" translation in German.
Linguistic diversity became framed as a structural problem that ultimately limited the spread of scientific knowledge. In 1924, the linguist Roland Grubb Kent underlined that scientific communication could be significantly disrupted in the near future by the use of as many as "twenty" languages of science:
Today with the recrudescence of certain minor linguistic units and the increased nationalistic spirit of certain larger ones, we face a time when scientific publications of value may appear in perhaps twenty languages [and] be facing an era in which important publications will appear in Finnish, Lithuanian, Hungarian, Serbian, Irish, Turkish, Hebrew, Arabic, Hindustani, Japanese, Chinese.
The definition of an auxiliary language for science became a major issue discussed in the emerging international scientific institutions. On January 17, 1901, the newly established International Association of Academies created a Delegation for the Adoption of an International Auxiliary Language "with support from 310 member organizations". The Delegation was tasked to find an auxiliary language that could be used for "scientific and philosophical exchanges" and could not be any "national language". In the context of increased nationalistic tensions any of the dominant languages of science would have appeared as a non-neutral choice. The Delegation had consequently a limited set of options that included the unlikely revival of a classical language like Latin or a new constructed language such as Volapük, Idiom Neutral or Esperanto.
Throughout the first part of the 20th century, Esperanto was seriously considered as a potential international language of science. As late as 1954, UNESCO passed a recommendation to promote the use of Esperanto for scientific communication. In contrast with Idiom Neutral, or the simplified version of Latin, Interlingua, Esperanto was not primarily conceived as a scientific language. Yet, by the early 1900s, it was by far the most successful constructed language, with a large international community as well as numerous dedicated publications. Starting in 1904, the Internacia Science Revuo aimed to adapt Esperanto to the specific needs of scientific communication. The development of a specialized technical vocabulary was a challenging task, as the extensive system of derivation of Esperanto made it complicated to import directly words commonly used in German, French or English scientific publications. In 1907, the Delegation for the Adoption of an International Auxiliary Language seemed close to retaining Esperanto as its preferred language. Significant criticism was nevertheless still addressed at a few remaining complexities of the language as well as its lack of scientific purpose and technical vocabulary. Unexpectedly, the Delegation supported a new variant of the Esperanto, Ido, which was submitted very late in the process by an unknown contributor. While it was framed as a compromise between the esperantist and the anti-esperantist factions, this decision ultimately disappointed all the proponents of an international medium for scientific communication and durably harmed the adoption of constructed languages in academic circles.
=== A transition period: English, new competitors and machine translation (1920–1965) ===
The two world wars had a lasting impact on scientific languages. A combination of political, economic and social factors durably weakened the triumvirate of the three main languages of science in 19th century and paved the way for the domination in English in the latter part of the 20th century. There is still ongoing debate as to whether the world wars accelerated a structural tendency toward English predominance or merely created the conditions for it. For Ulrich Ammon, "even without the World Wars the English language community would have gained economic and, consequently, scientific superiority and, thus, preference of its language for international scientific communication." In contrast, Michael Gordin underlines that until the 1960s the privileged status of English was far from settled.
The First World War had an immediate impact on the global use of German in academic settings. For nearly a decade after the First World War, German researchers were boycotted by international scientific events. The German scientific communities had been compromised by nationalistic propaganda in favor of German science during the war, as well as by the exploitation of scientific research for war crimes. German was no longer acknowledged as a global scientific language. While the boycott did not last, its effects were long-term. In 1919 the International Research Council was created to replace the International Association of Academies and used only French and English as working languages. In 1932, almost all (98.5%) of international scientific conferences admitted contributions in French, 83.5% in English and only 60% in German. In parallel, the focus of German periodicals and conferences had become increasingly local, and less and less frequently included research from non-Germanic countries. German never recovered its privileged status as a leading language of science in the United States, and due to the lack of alternatives beyond French, American education became "increasingly monoglot" and isolationist. Not affected by international boycott, the use of French reached "a plateau between the 1920s and 1940s": while it did not decline, neither did it profit from the marginalization of German, but instead decreased relative to the expansion of English.
The rise of totalitarianism in the 1930s reinforced the status of English as the leading scientific language. In absolute terms German publications retained some relevance, but German scientific research was structurally weakened by anti-Semitic and political purges, rejection of international collaborations and emigration. The German language was not boycotted again in international scientific conferences after the Second World War, as its use had quickly become marginal, even in Germany itself: even after the end of the occupied zone, English in the West and Russian in the East became major vehicular languages for higher education.
In the two decades following the Second World War, English had become the leading language of science. However, a large share of global research continued to be published in other languages, and language diversity even seemed to increase until the 1960s. Russian publications in numerous fields, especially chemistry and astronomy, had grown rapidly after the war: "in 1948, more than 33% of all technical data published in a foreign language now appeared in Russian." In 1962, Christopher Wharton Hanson still raised doubts about the future of English as the leading language in science, with Russian and Japanese rising as major languages of science and the new decolonized states seemingly poised to favor local languages:
It seems wise to assume that in the long run the number of significant contributions to scientific knowledge by different countries will be roughly proportional to their populations, and that except where populations are very small contributions will normally be published in native languages.
The expansion of Russian scientific publication became a source of recurring tensions in the United States during the decade of the cold war. Very few American researchers were able to read Russian which contrasted with a still widespread familiarity in the two oldest languages of science, French and German: "In a 1958 survey, 49% of American scientific and technical personnel claimed they could read at least one foreign language, yet only 1.2% could handle Russian." Science administrators and funders had recurring fears that they were not able to track efficiently the progress of academic research in the URSS. This ongoing anxiety became an overt crisis after the successful launch of Sputnik in 1958, as the decentralized American research system seemed for a time outpaced by the efficiency of Soviet planning.
Although the Sputnik crisis did not last long, it had far reaching consequences for linguistic practices in science: in particular, the development of machine translation. Research in this area emerged very precociously: automated translation appeared as a natural extension of the initial purpose of the first computers: code-breaking. Despite the initial reluctance of leading figures in computing like Norbert Wiener, several well-connected science administrators in the US, like Warren Weaver and Léon Dostert, set up a series of major conferences and experiments in the nascent field, out of a concern that "translation was vital to national security". On January 7, 1954, Dostert coordinated the Georgetown–IBM experiment, which aimed to demonstrate that the technique was sufficiently mature despite the significant shortcomings of the computing infrastructure of the time: some sentences from Russian scientific articles were automatically translated using a dictionary of 250 words and six basic syntax rules. It was not made clear at the time that the sentences had been purposely selected for their fitness for automated translation. At most Dostert argued that "scientific Russian" was easier to translate since it was more formulaic and less grammatically diverse than day-to-day Russian.
Machine translation became a major priority in Federal research funding in 1956 due to an emerging arms race with Soviet researchers. While the Georgetown–IBM experiment did not have a large impact at first in the United States, it was immediately noticed in the USSR. The first articles in the field appeared in 1955; and only one year later, a major conference was held attracting 340 representatives. In 1956, Léon Dostert secured a large funding with the support of the CIA and had enough resources to overcome the technical limitations of existing computing infrastructure: in 1957, automated translation from Russian to English could run on a vastly expanded dictionary of 24,000 words and rely on hundreds of predefined syntax rules. At this scale, automated translation remained costly as it relied on numerous computer operators using thousands of punch cards. Yet the quality of the output did not progress significantly: in 1964, the automated translation of the few sentences submitted during the Georgetown–IBM experiment yielded a much less readable output, as it was no longer possible to tweak the rules on a predefined corpus.
=== English as a global standard (1965 onwards) ===
During the 1960s and the 1970s, English was no longer a majority language of science but a scientific lingua franca. The transformation had more wide-ranging consequences than the substitution or two or three main language of science by one language: it marked "the transition from a triumvirate that valued, at least in a limited way, the expression of identity within science, to an overwhelming emphasis on communication and thus a single vehicular language." Ulrich Ammon characterizes English as an "asymmetrical lingua franca", as it is "the native tongue and the national language of the most influential segment of the global scientific community, but a foreign language for the rest of the world." This paradigm is usually connected with the globalization of American and English-speaking culture in the later part of the 20th century.
No specific event accounts for the entire shift although numerous transformations highlight an accelerated conversion to English science in the later part of the 1960s. On June 11, 1965, President Lyndon B. Johnson acted that the English language has become a lingua franca that opened "doors to scientific and technical knowledge" and whose promotion should be a "major policy" of the United States. In 1969, the most prestigious abstract collection in chemistry of the early 20th century, the German Chemisches Zentralblatt disappeared: this polyglot compilation in 36 languages could no longer compete with the English-focused Chemical abstract as more than 65% of publications in the field were in English. By 1982, the Compte-rendu of the Académie des Sciences admitted that "English is by now the international standard language of science and it could very nearly become its unique language" and is already the main "mean of communication" in European countries with a long-standing tradition of publication in the local language like Germany and Italy. In the European Union, the Bologna Declaration of 1999 "obliged universities throughout Europe and beyond to align their systems with that of the United Kingdom" and created strong incentives to publish academic results in English. From 1999 to 2014, the number of English-speaking course in European universities increased ten-fold.
Machine translation, which has been booming since 1954 thanks to Soviet-American competition, was immediately affected by the new paradigm. In 1964, the National Science Foundation underlined that "there is no emergency in the field of translation" and that translators were easily up to the task of making foreign research accessible. Funding stopped simultaneously in the United States and the Soviet Union and Machine Translation did not recover from this research "winter" until the 1980s and, by then, the translation of scientific publications was no longer the main incentive. Research in this area was still pursued in a few countries where bilingualism was an important political and cultural issue: in Canada, a METEO system was successfully set up to "translate weather forecasts from English into French".
English content became gradually prevalent in originally non-English journals, first as an additional language and then as the default language. In 1998, seven leading European journals published in their local languages (Acta Physica Hungarica, Anales de Física, Il Nuovo Cimento, Journal de Physique, Portugaliae Physica and Zeitschrift für Physik) merged and become the European Physical Journal, an international journal only accepting English submissions. The same process occurred repeatedly in less prestigious publications:
The pattern has become so routine as to be almost cliché: first, a periodical publishes only in a particular ethnic language (French, German, Italian); then, it permits publication in that language and also a foreign tongue, always including English but sometimes also others; finally, the journal excludes all other languages but English and becomes purely Anglophone.
Early scientific infrastructures have been a leading factor in the conversion to a single vehicular languages. Critical developments in applied scientific computing and information retrieval system occurred in the United States after the 1960s. The Sputnik crisis has been the main incentive, as it "turned the librarians’ problem of bibliographic control into a national information crisis." and favored ambitious research plans like SCITEL (an ultimately failed proposal to create a centrally planned system of electronic publication in the early 1960s), MEDLINE (for medicine journals) or NASA/RECON (for astronomics and engineering). In contrast with the decline of Machine Translation, scientific infrastructure and database became a profitable business in the 1970s. Even before the emergence of global network like the World Wide Web, "it was estimated in 1986 that fully 85% of the information available in worldwide networks was already in English."
The predominant use of English was not limited to the architecture of networks and infrastructures but affected the content as well. The Science Citation Index created by Eugene Garfield on the ruins of the SCITEL had a massive and lasting influence on the structure of global scientific publication in the last decades of the 20th century, as its most important metrics; the Journal Impact Factor, "ultimately came to provide the metric tool needed to structure a competitive market among journals." The Science Citation Index had a better coverage of English-speaking journals which yielded them a stronger Journal Impact Factor and created incentives to publish in English: "Publishing in English placed the lowest barriers toward making one’s work "detectable" to researchers." Due to the convenience of dealing with a monolingual corpus, Eugene Garfield called for acknowledging English as the only international language for science:
Since Current Contents has an international audience, one might say that the ideal publication would be multi-lingual, listing all titles in five languages -- one or more of which is read by most of our subscribers, including German, French, Russian and Japanese, as well as English. This is, of course, impractical since it would quadruple the size of Current Contents (…) the only reasonable solution is to publish as many contents pages in English as is economically and technically feasible. To do this we need the cooperation of publishers and authors.
== Current trends ==
=== English standardization ===
Nearly all the scientific publications indexed on the leading commercial academic search engines are in English. In 2022, this concerns 95.86% of the 28,142,849 references indexed on the Web of Science and 84.35% of the 20,600,733 references indexed on Scopus.
The lack of coverage of non-English languages creates a feedback loop as non-English publications can be held less valuable since they are not indexed in international rankings and fare poorly in evaluation metrics. As many as 75,000 articles, book titles and book reviews from Germany were excluded from Biological abstracts from 1970 to 1996. In 2009, at least 6555 journals were published in Spanish and Portuguese on a global scale and "only a small fraction are included in the Scopus and Web of Science indices."
Criteria for inclusion in commercial databases not only favor English journals but incentivize non-English journals to give up on their local journals. They "demand that articles be in English, have abstracts in English, or at least have their references in English". In 2012, the Web of Science was explicitly committed to the anglicization (and romanization) of published knowledge:
English is the universal language of science. For this reason, Thomson Reuters focuses on journals that publish full text in English, or at very least, bibliographic information in English. There are many journals covered in Web of Science that publish articles with bibliographic information in English and full text in another language. However, going forward, it is clear that the journals most important to the international research community will publish full text in English. This is especially true in the natural sciences. There are notable exceptions to this rule in the Arts & Humanities and in Social Sciences topics.
This commitment toward English science has a significant performative effect. Commercial databases "now wield on the international stage is considerable and works very much in favor of English" as they provide a wide range of indicators of research quality. They contributed "large-scale inequality, notably between Northern and Southern countries". While leading scientific publishers had initially, "failed to grasp the significance of electronic publishing," they have successfully pivoted to a "data analytics business" by the 2010s. Actors like Elsevier or Springer are increasingly able to control "all aspects of the research lifecycle, from submission to publication and beyond" Due to this vertical integration, commercial metrics are no longer restricted to journal article metadata but can include a wide range of individual and social data extracted among scientific communities.
National databases of scientific publications shows that the use English has continued to expand in the 2000s and the 2010s at the expense of local language. A comparison of seven national database in Europe from 2011 to 2014 shows that in "all countries, there was a growth in the proportion of English publications". In France, data from the Open Science Barometer shows that the share of publication in French has shrunk from 23% in 2013 to 12-16% by 2019–2020.
For Ulrich Ammon the predominance of English has created a hierarchy and a "central-peripheral dimension" within the global scientific publication landscape, that affects negatively the reception of research published in a non-English language. The unique use of English has discriminating effects on scholar who are not sufficiently conversant in the language: in a survey organized in Germany in 1991, 30% of researchers in all disciplines gave up on publication whenever English was the only option. In this context, the emergence of new scientific powers is no longer linked with the apparition of a new language science as it used to be the case until the 1960s. China has fast become a major player in international research, ranking second behind the United States in numerous rankings and disciplines. Yet, most of this research is English-speaking and abide to the linguistic norms set up by commercial indexes.
The dominant position of English has also been strengthened by the "lexical deficit" accumulated through the past decades by alternative language of sciences: after the 1960s "new terms were being coined in English at a much faster rate than they were being created in French."
=== Persistence of linguistic diversity ===
Several languages have kept a secondary status of international language of science, either due to the extent of the local scientific production or to their continued use as a vehicular language in specific contexts. This includes generally "Chinese, French, German, Italian, Japanese, Russian, and Spanish." Local languages have remained prevalent in major scientific countries: "most scientific publications are still published in Chinese in China".
Empirical studies of the use of languages in scientific publications have long been constrained by structural bias in the most readily accessible sources: commercial databases like the Web of Science. Unprecedented access to larger corpus not covered by global index showed that multilingualism remain non-negligible, although it remains little studied: by 2022 there are "few examples of analyses at scale" of multilingualism in science. In seven European countries with a limited international reach of the local language, one third of researchers in Social Sciences and the Humanities publish in two different languages or more: "research is international, but multilingual publishing keeps locally relevant research alive with the added potential for creating impact." Due to the discrepancy between the actual practices and their visibility, multilingualism has been described as a "hidden norm of academic publication".
Overall, the social sciences and the humanities have preserved more diverse linguistic practices: "while natural scientists of any linguistic background have largely shifted to English as their language of publication, social scientists and scholars of the humanities have not done so to the same extent." In these disciplines, the need for global communication is balanced by an implication in local culture: "the SSH are typically collaborating with, influencing and improving culture and society. To achieve this, their scholarly publishing is partly in the native languages." Yet, the specificity of the social science and the humanities has been increasingly reduced after 2000: by the 2010s, a large proportion of German and French articles in art and the humanities indexed in the Web of Science were in English. While German has been outpaced by English even in Germanic-speaking countries since the Second World War, it has also continued to be used marginally as a vehicular scientific language in specific disciplines or research fields (the Nischenfächer or "niche-disciplines"). Linguistic diversity is not specific to social sciences but this persistence may be invisibilized by the high prestige attached to international commercial databases: in the Earth sciences, "the proportion of English-language documents in the regional or national databases (KCI, RSCI, SciELO) was approximately 26%, whereas virtually all the documents (approximately 98%) in Scopus and WoS were in English."
Beyond the generic distinction between social sciences and natural sciences, there are finer-grained distribution of language practices. In 2018, a bibliometric analysis of the publications of eight European countries in social sciences and the humanities (SSH) highlighted that "patterns in the language and type of SSH publications are related not only to the norms, culture, and expectations of each SSH discipline but also to each country’s specific cultural and historic heritage." Use of English was more prevalent in Northern Europe than in Eastern Europe and publication in the local languages remain especially significant in Poland due to a large "‘local’ market of academic output". Local research policies may have a significant impact as preference for international commercial database like Scopus or the Web of Science may account for a steeper decline of publications in the local language in the Czech Republic, in comparison with Poland. Additional factors include the distribution of economic model within the journals: non-commercial publications have a much stronger "language diversity" than commercial publications.
Since the 2000s, the expansion of digital collections had contributed to a relative increase in linguistic diversity academic indexes and search engines. The Web of Science enhanced its regional coverage during the 2005-2010 period, which had the effect to "increase the number of non-English papers such as Spanish papers". In the Portuguese research communities, there have been a steep rise of Portuguese-language papers during the 2007-2018 period in commercial indexes which is both indicative of remaining "spaces of resilience and contestation of some hegemonic practices" and of a potential new paradigm of scientific publishing "steered towards plurilingual diversity". Multilingualism as a practice and competency has also increased: in 2022, 65% of early career researchers in Poland have published in two or more languages whereas only 54% of the older generations have done so.
In 2022, Bianca Kramer and Cameron Neylon have led a large scale analysis of the metadata available for 122 millions of Crossref objects indexed by a DOI. Overall, non-English publications make up for "less than 20%", although they can be under-estimated due to a lower adoption rate of DOIs or the use of local DOIs (like the Chinese National Knowledge Infrastructure). Yet, multilingualism seem to have improved through the past 20 years, with a significant growth of publication in Portuguese, Spanish and Indonesian.
=== Machine translation ===
Scientific publication has been the first major use case of machine translation with early experiments going back to 1954. Developments in this area were slowed after 1965, due to the increasing domination of English, the limitations of the computing infrastructure, and the shortcomings of the leading approach, rule-based machine translation. Rule-based methods favored by design translations between a few major languages (English, Russian, French, German...), as a "transfer module" had to be developed for "each pair of languages" which quickly led to a combinatory explosions whenever more languages were contemplated. After the 1980s, the field of Machine Translation was revived as it underwent a "full-scale paradigm shift": explicit rules were replaced by statistical and machine learning methods applied to large aligned corpus. By then, most of the demand stemmed non longer from scientific publication but from commercial translations such as technical and engineering manuals. A second paradigm shift occurred in the 2010s, with the development of deep learning methods, that can be partially trained on non-aligned corpus ("zero-shot translation"). Requiring little supervision inputs, deep learning models makes it possible to incorporate a wider diversity of languages, but also a wider diversity of linguistic contexts within one language. The results are significantly more accurate: after 2018, the automated translation of PubMed abstracts was deemed better than human translation for a few languages (like English to Portuguese). Scientific publications are a rather fitting use case for neural-network translation model since they work best "in restricted fields for which it has a lot of training data."
In 2021, there were "few in-depth studies on the efficiency of Machine Translation in social science and the humanities" as "most research in translation studies are focused on technical, commercial or law texts". Uses of machine translation are especially difficult to estimate and ascertain, as freely accessible tools like Google Translate have become ubiquitous: "There is an emerging yet rapidly increasing need for machine translation literacy among members of the scientific research and scholarly communication communities. Yet in spite of this, there are very few resources to help these community members acquire and teach this type of literacy."
In an academic setting, machine translation covers a variety of uses. Production of written translations remain constrained by a lack of accuracy and, consequently, of efficiency, as the post-editing of an imperfect translation needs to take less time than human translation. Automated translation of foreign language text in the context of literature survey or "information assimilation" is more widespread, as the quality requirements are generally lower and a global understanding of a text is sufficient. The impact of machine translation on linguistic diversity in science depends on these use:
If machine translation for assimilation purposes makes it possible, in principle, for researchers to publish in their own language and still reach a wide audience, then machine translation for dissemination purposes could be seen to favor the opposite and to support the use of a common language for research publication.
Increased use machine translation has created concerns of "uniform multilingualism". Research in the field has largely been focused on English and a few major European languages: "While we live in a multilingual word, this is paradoxically not taken into account by machine translation". English has frequently been used as a "pivotal" language and served as a hidden intermediary state for the translation of two non-English languages. Probabilistic methods tend to favor the most expected possible translation from the training corpus and to rule out more unusual alternatives: "A common argument against the statistical methods in translation is that when the algorithm suggests the most probable translation, it eliminates alternative options and makes the language of the text so produced conform to well-documented modes of expression." While deep learning models are able to deal with a wider diversity of language construct, they can still be limited by collection bias of the original corpus: "the translation of a word can be affected by the prevailing theories or paradigms in the corpus harvested to train the AI".
In its 2022 research assessment of open science, the Council of European Union welcomed the "promising developments that have recently emerged in the area of automatic translation" and supported a more widespread use of "semi-automatic translation of scholarly publications within Europe" due to its "major potential in terms of market creation".
== Open science and multilingualism ==
=== Open science infrastructures ===
The development of open science infrastructure or "community-controlled infrastructure" has become a major policy issue of the open science movement. In the 2010s expansion of commercial scientific infrastructure created a large acknowledgment of the fragility of open scholarly publishing and open archives. The concept of open science infrastructure emerged in 2015 with the publication of Principles for Open Scholarly Infrastructures. In November 2021, the UNESCO Recommendation acknowledged open science infrastructure as one of the four pillar of open science, along with open science knowledge, open engagement of societal actors and open dialog with other knowledge system and called for sustained investment and funding: "open science infrastructures are often the result of community-building efforts, which are crucial for their long-term sustainability and therefore should be not-for-profit and guarantee permanent and unrestricted access to all public to the largest extent possible." Examples of Open science infrastructure include indexes, publishing platforms, shared databases or computer grids.
Open infrastructures have supported linguistic diversity in science. The leading free software for scientific publishing, Open Journal Systems, is available in 50 languages and is widespread among non-commercial open access journals. A landscape study of SPARC in 2021 shows that European open science infrastructures "provide access to a range of language content of local and international significance." In 2019, leading open science infrastructure have endorsed the Helsinki Initiative on Multilingualism in Scholarly Communication and thus committed to "protect national infrastructures for publishing locally relevant research." Signatories include the DOAJ, DARIAH, LATINDEX, OpenEdition, OPERAS or SPARC Europe.
In contrast with commercial index, the Directory of Open Access Journals does not prescribe the use of English. Consequently, only half of the journals indexed are primarily published in English, which comes in stark contrast with the large prevalence of English in commercial indexes like Web of Science (> 95%). Six languages are represented by more than 500 journals: Spanish (2776 journals, or 19.3%), Portuguese (1917 journals), Indonesia (1329 journals), French (993 journals), Russian (733 journals) and Italian (529 journals). Most of the language diversity is due to non-commercial journals (or diamond open access): 25.7% of these publications accept contributions in Spanish vs. only 2.4% of APC-based journals. On the 2020-2022 period, "for English articles in DOAJ journals, 21% are in non-APC journals, but for articles in languages other than English, this percentage is a massive 86%."
Non-English open infrastructures have experimented a significant growth: in 2022, "national repositories and databases are growing everywhere (see the databases such as Latindex in Latin America, or the new repositories in Asia, China, Russia, India)". This development opens up new research opportunities for the study of multilingualism in a scientific context: it will become increasingly feasible to study " differences between locally published research in non-English speaking contexts and English-speaking international authors".
=== Multilingualism and social impact ===
Publication in open access platforms has created new incentives for publishing in a local language. In commercial indexes, non-English publications were penalized by the lack of international reception and had a significantly lower impact factor. Without a paywall, local language publication can find their own specific audience among a large non-academic public that may be less competent in English.
In the 2010s, quantitative studies have started to highlight the positive impact of local languages on the reuse of open access resources in varied national contexts such as Finland, Québec, Croatia or Mexico. A study of the Finnish platform Journal.fi shows that the audience of Finnish-speaking articles is significantly more diverse: "in case of the national language publications students (42%) are clearly the largest group, and besides researchers (25%), also private citizens (12%) and other experts (11%)". Comparatively, English-speaking publications attract mostly professional researchers. Due to the ease of access, open science platforms in a local language can also attain a more global reach. The French-Canadian journal consortium Érudit has mostly an international audience, with less than one third of the readers coming from Canada.
The development of a strong network of open science infrastructures in South America (such as Scielo or Redalyc) and the Iberian region has concurred to the resurgence of the Spanish and Portuguese language in international scientific communication: regional growth "may also be associated with the boom in open access publishing. Both Portuguese and Spanish (as well as Brazil and Spain) play important roles in open access publishing.
While multilingualism have been either neglected or even discriminated in commercial databases, it has been valued as a significant component of the social impact of open science platforms and infrastructure. In 2015, Juan Pablo Alperin introduced a systematic measure of social impact that highlighted the relevancy of scientific content for local communities : "By looking at a broad range of indicators of impact and reach, far beyond the typical measures of one article citing another, I argue, it is possible to gain a sense of the people that are using Latin American research, thereby opening the door for others to see the ways in which it has touched those individuals and communities. In this context, new indicators for linguistic diversity. Proposals include the PLOTE-index and the Linguistic Diversity Index. Yet, as of 2022, they have had "limited traction in the scholarly anglophone literature". Comprehensive indicators for the local impact of research remain largely non-existent: "many aspects of research cannot be measured quantitatively, especially its socio-cultural impact."
=== Policies in favor of multilingualism ===
A new scientific and policy debate over linguistic diversity emerged after 2015: "in recent years, policies for Responsible Research and Innovation (RRI) and Open Science call for increasing access to research, interaction between science and society and public understanding of science". It initially stemmed from a wider discussion over the evaluation of open science and the limitations of commercial metrics: in 2015, the Leiden Manifesto issued ten principles to "guide research evaluation" that included a call to "protect excellence in locally relevant research". Building up on empirical data showing the persistence of non-English research communities in Europe, Gunnar Sivertsen has in 2018 theorized the need for a balanced multilingualism: "to consider all the communication purposes in all different areas of research, and all the languages needed to fulfil these purposes, in a holistic manner without exclusions or priorities." In 2016, Sivertsen contributed to the "Norwegian model" of scientific evaluation by proposing a flat hierarchy between a few large international journals and a wide selection of journals that would not discriminate against local publications, and encouraged journals in social sciences and the humanities to favor Norwegian publications.
These local initiatives developed into a new international movement in favor of multilingualism. In 2019, 120 research organizations and several hundred individual researchers co-signed Helsinki Initiative on Multilingualism in Scholarly Communication. The declaration include three principles:
"Support dissemination of research results for the full benefit of the society", which implies that they should be available "in a variety of languages".
"Protect national infrastructures for publishing locally relevant research" through a specific support of the non-commercial/diamond model "make sure not for-profit journals and book publishers have both sufficient resources". Non-commercial journals are more likely to be published in a local language.
"Promote language diversity in research assessment, evaluation, and funding systems", in line with third recommendation of the Leiden Manifesto.
In the wake of the Helsinki Initiative, multilingualism has been increasingly associated to Open Science. This trend was accelerated in the context of the COVID pandemic, which "saw a widespread need for multilingual scholarly communication, not only between researchers, but to enable research to reach decision-makers, professionals and citizens". Multilingualism has also re-emerged as a topic of debate beyond the social sciences: in 2022, the Journal of Science Policy and Governance published a "Call to Diversify the Lingua Franca of Academic STEM Communities", that stressed that "cross-cultural solutions are necessary to prevent critical information from being missed by English-speaking researchers."
In November 2021, the UNESCO Recommendation for Open Science included multilingualism at the core of its definition of Open Science: "For the purpose of this Recommendation, open science is defined as an inclusive construct that combines various movements and practices aiming to make multilingual scientific knowledge openly available, accessible and reusable for everyone".
In the early 2020s, the European Union started to officially support language diversity in science, as a continuation of its general policies in favor of multilingualism. In December 2021, an important report of the European Commission on the future of scientific assessment in European countries still overlooked the issue of linguistic diversity: "Multilingualism is the most notable omission". In June 2022, the Council of the European Union included a detailed recommendation on "Development of multilingualism for European scholarly publications" in its research assessment of open science. The declaration acknowledges the "important role of multilingualism in the context of science communication with society" and welcomes "initiatives to promote multilingualism, such as the Helsinki initiative on multilingualism in scholarly communication." While the declaration is not constraining it invites the experiment with multilingualism "on a voluntary basis" and to assess the needs for further actions by the end of 2023.
== References ==
== Bibliography ==
=== Books & theses ===
Alperin, Juan Pablo (2015). The public impact of Latin America's approach to open access (Thesis). Stanford University.
Andriesse, Cornelis D. (2008-09-15). Dutch Messengers: A History of Science Publishing, 1930–1980. Leiden: Brill. ISBN 978-90-04-17084-1.
Behrens, Julia; Fischer, Lars; Minks, Karl-Heinz; Rösler, Lena (2010). Die internationale Positionierung der Geisteswissenschaften in Deutschland. Hannover: HIS:Projektbericht.{{cite book}}: CS1 maint: publisher location (link)
Bourne, Charles P.; Hahn, Trudi Bellardo (2003-08-01). A History of Online Information Services, 1963-1976. MIT Press. ISBN 978-0-262-26175-3.
Bowker, Lynne; CIro, Jairo Buitrago (2019-05-01). Machine Translation and Global Research: Towards Improved Machine Translation Literacy in the Scholarly Community. Emerald Group Publishing. ISBN 978-1-78756-721-4.
Gordin, Michael D. (2015-04-13). Scientific Babel: How Science Was Done Before and After Global English. University of Chicago Press. ISBN 978-0-226-00032-9.
Montgomery, Scott L. (2013-05-06). Does Science Need a Global Language?: English and the Future of Research. University of Chicago Press. ISBN 978-0-226-01004-5.
Moore, Samuel (2019-05-02). Common Struggles: Policy-based vs. scholar-led approaches to open access in the humanities (Thesis). Retrieved 2021-12-11.
Olechnicka, Agnieszka; Ploszaj, Adam; Celińska-Janowicz, Dorota (2018-10-08). The Geography of Scientific Collaboration. Routledge. ISBN 978-1-315-47192-1.
Poibeau, Thierry (2019-05-09). Babel 2.0: Où va la traduction automatique ?. Odile Jacob. ISBN 978-2-7381-4850-6.
Wächter, Bernd; Maiworm, Friedhelm (2014). English-taught Programmes in European Higher Education: The State of Play in 2014. Lemmens Medien GmbH. ISBN 978-3-86856-017-6.
Wouters, P. F. (1999). The citation culture (Thesis). Retrieved 2018-09-09.
=== Reports ===
Bosman, Jeroen; Frantsvåg, Jan Erik; Kramer, Bianca; Langlais, Pierre-Carl; Proudman, Vanessa (2021-03-09). OA Diamond Journals Study. Part 1: Findings (Report). doi:10.5281/zenodo.4558704.
Council of the European Union (2022-06-10). Research assessment and implementation of Open Science (PDF) (Report).
European Commission. Directorate General for Research and Innovation. (2019). Future of scholarly publishing and scholarly communication: report of the Expert Group to the European Commission (Report). LU: Publications Office. doi:10.2777/836532. ISBN 978-92-79-97238-6.
Ficarra, Victoria; Fosci, Mattia; Chiarelli, Andrea; Kramer, Bianca; Proudman, Vanessa (2020-10-30). Scoping the Open Science Infrastructure Landscape in Europe (Report). doi:10.5281/zenodo.4159838. Ficarra, Victoria; Chiarelli, Andrea (2020). "Open science, open access, open infrastructure, services, sustainability, funding, open standards, open content, good governance, open principles". Dataset: Scoping the Open Science Infrastructure Landscape in Europe (Dataset). doi:10.5281/zenodo.4153741.
Kramer, Bianca; Neylon, Cameron (2022-06-21). Language Diversity in Scholarly Publishing (Report). COKI. Retrieved 2022-06-28.
Ochsner, Michael; Kancewicz-Hoffman, Nina; Hołowiecki, Marek; Holm, Jon (April 2020). Overview of Peer Review Practices in the SSH (Report). European Network for Research Evaluation in the Social Sciences and Humanities. doi:10.6084/m9.figshare.12032589.v2. Retrieved 2020-09-24 – via figshare.
Recommendation on Open Science (Report). UNESCO. 2021-11-23. CL/4363.
=== Articles & chapters ===
"Rapport de l'Académie des sciences sur la langue française et le rayonnement de la science française" [Report from the Academy of Sciences on the French language and the influence of French science]. Comptes rendus des séances de l'Académie des Sciences [Reports of the sessions of the Academy of Sciences] (in French). 295: 131–146. 8 November 1982.
Ammon, Ulrich (2012-10-10). "Linguistic inequality and its effects on participation in scientific discourse and on global knowledge accumulation – With a closer look at the problems of the second-rank language communities". Applied Linguistics Review. 3 (2): 333–355. doi:10.1515/applirev-2012-0016. ISSN 1868-6311.
Anglaret, Anne-Sophie; Sofio, Séverine (2021-12-27). "Écrire en langues. Entre traduction automatique et hégémonie globish, le multilinguisme comme horizon réaliste pour les revues de sciences humaines et sociales". Biens Symboliques / Symbolic Goods. Revue de sciences sociales sur les arts, la culture et les idées. 9 (9). doi:10.4000/bssg.832. ISSN 2490-9424. S2CID 245925363. Retrieved 2022-01-17.
Aronova, Elena (September 2017). "Russian and the Making of World Languages during the Cold War". Isis. 108 (3): 643–650. doi:10.1086/694163. ISSN 0021-1753. S2CID 148831824.
Cameron-Pesant, Sarah (2018). "Usage et diffusion des revues savantes québécoises en sciences sociales et humaines : analyse des téléchargements de la plateforme Érudit". Recherches Sociographiques. 59 (3): 365–384. doi:10.7202/1058719ar. ISSN 0034-1282. Retrieved 2022-04-10.
Curry, Mary Jane; Lillis, Theresa (2022-04-07). "Multilingualism in academic writing for publication: Putting English in its place" (PDF). Language Teaching. 57: 87–100. doi:10.1017/S0261444822000040. ISSN 0261-4448. S2CID 248032636.
Dahler-Larsen, Peter (2018-07-01). "Making citations of publications in languages other than English visible: On the feasibility of a PLOTE-index". Research Evaluation. 27 (3): 212–221. doi:10.1093/reseval/rvy010. ISSN 0958-2029. Retrieved 2022-06-28.
Gao, Bin; Guo, Chunyue (2022-03-31). "Where to Publish: Chinese HSS Academics' Responses to 'Breaking SSCI Supremacy' Policies". Higher Education Policy. 36 (3): 478–496. doi:10.1057/s41307-022-00268-y. ISSN 1740-3863. S2CID 247913299.
Gordin, Michael D. (2017-09-19). "Introduction: Hegemonic Languages and Science". Isis. 108 (3): 606–611. doi:10.1086/694164. ISSN 0021-1753. S2CID 149105063.
Henry, Kaylee; Virk, Ranya; DeMarchi, Lindsay; Sears, Huei (2021-08-30). "A Call to Diversify the Lingua Franca of Academic STEM Communities". Journal of Science Policy & Governance. 18 (3). doi:10.38126/JSPG180303. ISSN 2372-2193.
Hicks, Diana; Wouters, Paul; Waltman, Ludo; de Rijcke, Sarah; Rafols, Ismael (April 2015). "Bibliometrics: The Leiden Manifesto for research metrics". Nature. 520 (7548): 429–431. Bibcode:2015Natur.520..429H. doi:10.1038/520429a. hdl:10261/132304. ISSN 1476-4687. PMID 25903611. S2CID 4462115. Retrieved 2022-01-19.
Hock, Hans Henrich (1983). Kachru, Braj B. (ed.). "Language-death phenomena in Sanskrit: grammatical evidence for attrition in contemporary spoken Sanskrit". Studies in the Linguistic Sciences. 13 (2).
Hutchins, John (2007). "Machine translation: a concise history". A Concise History. Computer Aided Translation: Theory and Practice. 13 (11): 21.
Irawan, Dasapta Erwin; Abraham, Juneman; Tennant, Jonathan Peter; Pourret, Olivier (2021-08-07). "The need for a new set of measures to assess the impact of research in earth sciences in Indonesia". European Science Editing. 47. e59032. doi:10.3897/ese.2021.e59032. ISSN 2518-3354.
Joseph, Heather (2018-09-05). "Securing community-controlled infrastructure: SPARC's plan of action | Joseph". College & Research Libraries News. 79 (8). doi:10.5860/crln.79.8.426. S2CID 116057034. Retrieved 2021-12-12.
Kaplan, Frederic (2014-08-01). "Linguistic Capitalism and Algorithmic Mediation". Representations. 127 (1): 57–63. doi:10.1525/rep.2014.127.1.57. ISSN 0734-6018. Retrieved 2022-04-08.
Kent, Roland G. (1924-06-20). "The Scientist and an International Language". Science. 59 (1538): 554–555. doi:10.1126/science.59.1538.554.b. PMID 17818586. S2CID 239785051.
Kulczycki, Emanuel; Engels, Tim C. E.; Pölönen, Janne (2022-04-12). "Multilingualism of social sciences". In Engels, Tim C. E.; Kulczycki, Emanuel (eds.). Handbook on Research Assessment in the Social Sciences. pp. 350–366. doi:10.4337/9781800372559.00031. hdl:10067/1875400151162165141. ISBN 978-1-80037-255-9.
Kulczycki, Emanuel; Engels, Tim C. E.; Pölönen, Janne; Bruun, Kasper; Dušková, Marta; Guns, Raf; Nowotniak, Robert; Petr, Michal; Sivertsen, Gunnar; Istenič Starčič, Andreja; Zuccala, Alesia (2018-07-01). "Publication patterns in the social sciences and humanities: evidence from eight European countries". Scientometrics. 116 (1): 463–486. doi:10.1007/s11192-018-2711-0. hdl:10067/1498050151162165141. ISSN 1588-2861. S2CID 4336325. Retrieved 2022-04-09.
Kulczycki, Emanuel; Guns, Raf; Pölönen, Janne; Engels, Tim C. E.; Rozkosz, Ewa A.; Zuccala, Alesia A.; Bruun, Kasper; Eskola, Olli; Starčič, Andreja Istenič; Petr, Michal; Sivertsen, Gunnar (2020). "Multilingual Publishing in the Social Sciences and Humanities: A Seven-Country European Study". Journal of the Association for Information Science and Technology. 71 (11): 1371–1385. doi:10.1002/asi.24336. ISSN 2330-1643. PMC 7687152. PMID 33288998.
Larivière, Vincent (2018). "Le français, langue seconde ? De l'évolution des lieux et langues de publication des chercheurs au Québec, en France et en Allemagne". Recherches Sociographiques. 59 (3): 339–363. doi:10.7202/1058718ar. hdl:1866/23374. ISSN 0034-1282. S2CID 191863500. Retrieved 2022-01-11.
Larsen, Peder Olesen; von Ins, Markus (September 2010). "The rate of growth in scientific publication and the decline in coverage provided by Science Citation Index". Scientometrics. 84 (3): 575–603. doi:10.1007/s11192-010-0202-z. ISSN 0138-9130. PMC 2909426. PMID 20700371.
Linkov, Václav; O’Doherty, Kieran; Choi, Eunsoo; Han, Gyuseog (2021-04-01). "Linguistic Diversity Index: A Scientometric Measure to Enhance the Relevance of Small and Minority Group Languages". SAGE Open. 11 (2). 21582440211009191. doi:10.1177/21582440211009191. ISSN 2158-2440.
Liu, Weishu (2017). "The changing role of non-English papers in scholarly communication: Evidence from Web of Science's three journal citation indexes". Learned Publishing. 30 (2): 115–123. doi:10.1002/leap.1089. ISSN 1741-4857. S2CID 7026937.
Luczaj, Kamil; Leonowicz-Bukala, Iwona; Kurek-Ochmanska, Olga (2022-04-01). "English as a lingua franca? The limits of everyday English-language communication in Polish academia". English for Specific Purposes. 66: 3–16. doi:10.1016/j.esp.2021.11.002. ISSN 0889-4906. S2CID 245558219.
Milia, Matias Federico; Giralt, Ariadna Nebot; Arvanitis, Rigas (2022-06-21). "Local emergence, global expansion: understanding the structural evolution of a bi-lingual national research landscape". Scientometrics. 127 (12): 7369–7395. doi:10.1007/s11192-022-04403-9. ISSN 1588-2861.
"Superpowered science: charting China's research rise". Nature. 593 (S4 – S5): S4 – S5. 2021-05-26. Bibcode:2021Natur.593S...4.. doi:10.1038/d41586-021-01403-2.
O'Neil, David (2018). "English as the lingua franca of international publishing". World Englishes. 37 (2): 146–165. doi:10.1111/weng.12293. ISSN 1467-971X.
Pölönen, Janne; Hammarfelt, Björn (August 2020). "Historical Bibliometrics Using Google Scholar: The Case of Roman Law, 1727–2016". Journal of Data and Information Science. 5 (3): 18–32. doi:10.2478/jdis-2020-0024. S2CID 211666815.
Pölönen, Janne; Syrjämäki, Sami; Nygård, Antti-Jussi; Hammarfelt, Björn (October 2021b). "Who are the users of national open access journals? The case of the Finnish Journal.fi platform". Learned Publishing. 34 (4): 585–592. doi:10.1002/leap.1405. ISSN 1741-4857. S2CID 236331208.
Ramati, Ido; Pinchevski, Amit (2018). "Uniform multilingualism: A media genealogy of Google Translate". New Media & Society. 20 (7): 2550–2565. doi:10.1177/1461444817726951. ISSN 1461-4448. S2CID 51882659.
Rocco, Goranka (2020). "The Status of German as a Lingua Franca in Written Scientific Communication: A Study on Language Policies in Linguistic Journals" (PDF). In Karpinska, Laura (ed.). Language for International Communication: Linking Interdisciplinary Perspectives. Vol. 3. University of Latvia Press. pp. 79–93. ISBN 978-9934-18-553-3. Retrieved 2022-01-12.
Sivertsen, Gunnar (2018). "Balanced multilingualism in science". BiD: Textos universitaris de biblioteconomia i documentació (40).
Soares, Felipe; Rebechi, Rozane; Stevenson, Mark (2020-06-15). "SciBabel: a system for crowd-sourced validation of automatic translations of scientific texts". Genomics & Informatics. 18 (2): –21. doi:10.5808/GI.2020.18.2.e21. ISSN 1598-866X. PMC 7362948. PMID 32634875.
"Délégation pour l'adoption d'une langue auxiliaire internationale" [Delegation for the adoption of an international auxiliary language]. Bulletin de la Société d'anthropologie de Lyon [Bulletin of the Anthropological Society of Lyon] (in French). 22: 10–13. 1903 – via Persée.
Solovova, Olga; Santos, Joana Vieira; Veríssimo, Joaquim (June 2018). "Publish in English or Perish in Portuguese: Struggles and Constraints on the Semiperiphery". Publications. 6 (2): 25. doi:10.3390/publications6020025. hdl:10316/79581.
Stojanovski, Jadranka; Petrak, Jelka; Macan, Bojan (2009). "The Croatian national open access journal platform". Learned Publishing. 22 (4): 263–273. doi:10.1087/20090402. ISSN 1741-4857. S2CID 32697476.
Younas, Ahtisham; Fàbregues, Sergi; Durante, Angela; Ali, Parveen (2022). "Providing English and native language quotes in qualitative research: A call to action". Nursing Open. 9 (1): 168–174. doi:10.1002/nop2.1115. ISSN 2054-1058. PMC 8685880. PMID 34725950.
Zhang, Lin; Sivertsen, Gunnar (2020-05-12). "The New Research Assessment Reform in China and Its Implementation". Scholarly Assessment Reports. 2 (1): 3. doi:10.29024/sar.15. hdl:11250/2733873. ISSN 2689-5870. Retrieved 2023-09-10.
=== Conferences ===
Shearer, Kathleen; Chan, Leslie; Kuchma, Iryna; Mounier, Pierre (2020-04-15). Fostering Bibliodiversity in Scholarly Communications: A Call for Action. Retrieved 2020-06-17.
Beigel, Fernanda (2022). Research evaluation in the southern road to open science (PDF). OSEC 2022. Paris.
=== Other articles ===
Garfield, Eugene (1967). "English – An international language for science?" (PDF). Current Contents.
Huttner-Koros, Adam (2015-08-21). "Why Science's Universal Language Is a Problem for Research". The Atlantic. Retrieved 2020-09-24.
van Weijen, Daphne (November 2012). "The Language of (Future) Scientific Communication". Research Trends. No. 31. Archived from the original on 2020-09-20. Retrieved 2020-09-24.
Gordin, Michael D. "How did science come to speak only English? – Michael D Gordin | Aeon Essays". Aeon. Retrieved 2020-09-24.
Taşkın, Zehra; Dogan, Guleda; Kulczycki, Emanuel; Zuccala, Alesia Ann (2020-06-18). "Science needs to inform the public. That can't be done solely in English". LSE COVID-19. Retrieved 2022-01-21.
Pölönen, Janne; Kulczycki, Emanuel; Mustajoki, Henriikka; Røeggen, Vidar (2021-12-07). "Multilingualism is integral to accessibility and should be part of European research assessment reform". Impact of Social Sciences. Retrieved 2022-01-20.
=== Declaration ===
Bundy, McGeorge. "Memorandum # 332, U.S. Government Policy on English Language Teaching Abroad, 6/11/1965" (June 11, 1965). National Security Files, Series: National Security Action Memorandums, Box: 6. LBJ Presidential Library.
Helsinki Initiative (2019). "Helsinki Initiative on Multilingualism in Scholarly Communication". Helsinki: Federation of Finnish Learned Societies, Committee for Public Information, Finnish Association for Scholarly Publishing, Universities Norway & European Network for Research Evaluation in the Social Sciences and the Humanities. doi:10.6084/m9.figshare.7887059. Retrieved 2020-09-24.
== External links ==
A Call to Diversify the Lingua Franca of Academic STEM Communities
AmeliCA Ciencia Abierta
GOAP: UNESCO's Global Open Access Portal, providing "status of open access to scientific information around the world."
Helsinki Initiative on Multilingualism in Scholarly Communication | Wikipedia/Languages_of_science |
Science journalism conveys reporting about science to the public. The field typically involves interactions between scientists, journalists and the public.
== Origins ==
Modern science journalism originated in weather and other natural history observations, as well as reports of new scientific findings, reported by almanacs and other news writing in the centuries following the advent of the printing press.
One early example dates back to Digdarshan (means showing the direction), which was an educational monthly magazine that started publication in 1818 from Srirampore, Bengal, India. Digdarshan carried articles on different aspects of science, such as plants, steam boat, etc. It was available in Bengali, Hindi and English languages.
In the U.S., Scientific American was founded in 1845, in another early example. One of the occasions an article was attributed to a 'scientific correspondent' was "A Gale in the Bay of Biscay" by William Crookes which appeared in The Times on 18 January 1871, page 7.
Thomas Henry Huxley (1825–1895) and John Tyndall (1820–1893) were scientists who were greatly involved in journalism and Peter Chalmers Mitchell (1864–1945) was Scientific Correspondent for The Times from 1918 to 1935.
However it was with James Crowther's appointment as the 'scientific correspondent' of The Manchester Guardian by C. P. Scott in 1928 that science journalism really took shape. Crowther related that Scott had declared that there was "no such thing" as science journalism, at which point Crowther replied that he intended to invent it. Scott was convinced and then employed him.
== Aims ==
Science values detail, precision, the impersonal, the technical, the lasting, facts, numbers and being right. Journalism values brevity, approximation, the personal, the colloquial, the immediate, stories, words and being right now. There are going to be tensions.
The aim of a science journalist is to render very detailed, specific, and often jargon-laden information produced by scientists into a form that non-scientists can understand and appreciate while still communicating the information accurately. One way science journalism can achieve that is to avoid an information deficit model of communication, which assumes a top-down, one-way direction of communicating information that limits an open dialogue between knowledge holders and the public. One such way of sparking an inclusive dialogue between science and society that leads to a broader uptake of post-high school science discoveries is science blogs. Science journalists face an increasing need to convey factually correct information through storytelling techniques in order to tap into both the rational and emotional side of their audiences, the latter of which to some extent ensuring that the information uptake persists.
Science journalists often have training in the scientific disciplines that they cover. Some have earned a degree in a scientific field before becoming journalists or exhibited talent in writing about science subjects. However, good preparation for interviews and even deceptively simple questions such as "What does this mean to the people on the street?" can often help a science journalist develop material that is useful for the intended audience.
== Status ==
With budget cuts at major newspapers and other media, there are fewer working science journalists employed by traditional print and broadcast media than before. Similarly, there are currently very few journalists in traditional media outlets that write multiple articles on emerging science, such as nanotechnology.
In 2011, there were 459 journalists who had written a newspaper article covering nanotechnology, of whom 7 wrote about the topic more than 25 times.
In January 2012, just a week after The Daily Climate reported that worldwide coverage of climate change continued a three-year slide in 2012 and that among the five largest US dailies, the New York Times published the most stories and had the biggest increase in coverage, that newspaper announced that it was dismantling its environmental desk and merging its journalists with other departments.
News coverage on science by traditional media outlets, such as newspapers, magazines, radio and news broadcasts is being replaced by online sources. In April 2012, the New York Times was awarded two Pulitzer Prizes for content published by Politico and The Huffington Post (now HuffPost) both online sources, a sign of the platform shift by the media outlet.
Science information continues to be widely available to the public online. The increase in access to scientific studies and findings causes science journalism to adapt. "In many countries the public's main source of information about science and technology is the mass media." Science journalists must compete for attention with other stories that are perceived as more entertaining. Science information cannot always be sensationalized to capture attention and the sheer amount of available information can cause important findings to be buried. The general public does not typically search for science information unless it is mentioned or discussed in mainstream media first. However, the mass media are the most important or only source of scientific information for people after completing their education.
A common misconception about public interest surrounds science journalism. Those who choose which news stories are important typically assume the public is not as interested in news written by a scientist and would rather receive news stories that are written by general reporters instead. The results of a study conducted comparing public interest between news stories written by scientists and stories written by reporters concluded there is no significant difference. The public was equally interested in news stories written by a reporter and a scientist. This is a positive finding for science journalism because it shows it is increasingly relevant and is relied upon by the public to make informed decisions. "The vast majority of non-specialists obtain almost all their knowledge about science from journalists, who serve as the primary gatekeepers for scientific information." Ethical and accurate reporting by science journalists is vital to keeping the public informed.
Science journalism is reported differently than traditional journalism. Conventionally, journalism is seen as more ethical if it is balanced reporting and includes information from both sides of an issue. Science journalism has moved to an authoritative type of reporting where they present information based on peer reviewed evidence and either ignore the conflicting side or point out their lack of evidence. Science journalism continues to adapt to a slow journalism method that is very time-consuming but contains higher quality information from peer-reviewed sources. They also practice sustainable journalism that focuses on solutions rather than only the problem. Presenting information from both sides of the issue can confuse readers on what the actual findings show. Balanced reporting can actually lead to unbalanced reporting because it gives attention to extreme minority views in the science community, implying that both sides have an equal number of supporters. It can give the false impression that an opposing minority viewpoint is valid.
For example, a 2019 survey of scientists' views on climate change yielded a 100% consensus that global warming is human-caused. However, articles like "Climate Change: A Scientist and Skeptic Exchange Viewpoints," published by Divided We Fall in 2018, may unintentionally foster doubt in readers, as this particular scientist "did not say, as the media and the political class has said, that the science is settled."
The public benefits from an authoritative reporting style in guiding them to make informed decisions about their lifestyle and health.
Tracking the remaining experienced science journalists is becoming increasingly difficult. For example, in Australia, the number of science journalists has decreased to abysmal numbers: "you need less than one hand to count them." Due to the rapidly decreasing number of science journalists, experiments on ways to improve science journalism are also rare. However, in one of the few experiments conducted with science journalists, when the remaining population of science journalists networked online, they produced more accurate articles than when in isolation. New communication environments provide essentially unlimited information on a large number of issues, which can be obtained anywhere and with relatively limited effort. The web also offers opportunities for citizens to connect with others through social media and other 2.0-type tools to make sense of this information.
"After a lot of hand wringing about the newspaper industry about six years ago, I take a more optimistic view these days," said Cristine Russell, president of the Council for the Advancement of Science Writing. "The world is online. Science writers today have the opportunity to communicate not just with their audience but globally".
Blog-based science reporting is filling in to some degree, but has problems of its own.
One of the main findings is about the controversy surrounding climate change and how the media affects people's opinions on this topic. Survey and experimental research have discovered connections between exposure to cable and talk show radio channels and views on global warming. However, early subject analyses noticed that U.S. media outlets over exaggerate the dispute that surrounds global warming actually existing. A majority of Americans view global warming as an outlying issue that will essentially affect future generations of individuals in other countries. This is a problem considering that they are getting most of their information from these media sources that are opinionated and not nearly as concerned with supplying facts to their viewers. Research found that after people finish their education, the media becomes the most significant, and for many individuals, the sole source of information regarding science, scientific findings and scientific processes. Many people fail to realize that information about science included from online sources is not always credible.
Since the 1980s, climate science and mass media have transformed into an increasingly politicized sphere. In the United States, Conservatives and Liberals understand global warming differently. Democrats often accept the evidence for global warming and think that it's caused by humans, while not many Republicans believe this. Democrats and liberals have higher and more steady trust in scientists, while conservative Republicans' trust in scientists has been declining. However, in the United Kingdom, mass media do not have nearly the impact on people's opinions as in the United States. They have a different attitude towards the environment which prompted them to approve the Kyoto Protocol, which works to reduce carbon dioxide emissions, while the U.S., the world's largest creator of carbon dioxide, has not done so.
The content of news stories regarding climate change are affected by journalistic norms including balance, impartiality, neutrality and objectivity. Balanced reporting, which involves giving equal time to each opposing side of a debate over an issue, has had a rather harmful impact on the media coverage of climate science.
=== Chocolate hoax ===
In 2015, John Bohannon produced a deliberately bad study to see how a low-quality open access publisher and the media would pick up their findings. He worked with a film-maker Peter Onneken who was making a film about junk science in the diet industry with fad diets becoming headline news despite terrible study design and almost no evidence. He invented a fake "diet institute" that lacks even a website, used the pen name "Johannes Bohannon" and fabricated a press release.
=== Criticism ===
Science journalists keep the public informed of scientific advancements and assess the appropriateness of scientific research. However, this work comes with a set of criticisms. Science journalists regularly come under criticism for misleading reporting of scientific stories. All three groups of scientists, journalists and the public often criticize science journalism for bias and inaccuracies. However, with the increasing collaborations online between science journalists there may be potential with removing inaccuracies.
The 2010 book Merchants of Doubt by historians of science Naomi Oreskes and Erik M. Conway argues that in topics like the global warming controversy, tobacco smoking, acid rain, DDT and ozone depletion, contrarian scientists have sought to "keep the controversy alive" in the public arena by demanding that reporters give false balance to the minority side. Very often, such as with climate change, this leaves the public with the impression that disagreement within the scientific community is much greater than it actually is. Science is based on experimental evidence and testing, and disputation is a normal activity.
Scholars have criticized science journalists for:
Uncritical reporting
Emphasizing frames of scientific progress and economic prospect
Not presenting a range of expert opinion
Having preferences toward positive messages
Reporting unrealistic timelines and engaging in the production of a "cycle of hype"
Science journalists can be seen as the gatekeepers of scientific information. Just like traditional journalists, science journalists are responsible for what truths reach the public.
Scientific information is often costly to access. This is counterproductive to the goals of science journalism. Open science, a movement for "free availability and usability of scholarly publications," seeks to counteract the accessibility issues of valuable scientific information. Freely accessible scientific journals will decrease the public's reliance on potentially biased popular media for scientific information.
Many science magazines, along with Newspapers like The New York Times and popular science shows like PBS Nova tailor their content to relatively highly educated audiences. Many universities and research institutions focus much of their media outreach efforts on coverage in such outlets. Some government departments require journalists to gain clearance to interview a scientist, and require that a press secretary listen in on phone conversations between government funded scientists and journalists.
Many pharmaceutical marketing representatives have come under fire for offering free meals to doctors in order to promote new drugs. Critics of science journalists have argued that they should disclose whether industry groups have paid for a journalist to travel, or has received free meals or other gifts.
Science journalism finds itself under a critical eye due to the fact that it combines the necessary tasks of a journalist along with the investigative process of a scientist.
=== Science journalist responsibility ===
Science journalists offer important contributions to the open science movement by using the Value Judgement Principle (VJP). Science journalists are responsible for "identifying and explaining major value judgments for members of the public." In other words, science journalists must make judgments such as what is good and bad (right and wrong). This is a very significant role because it helps "equip non-specialists to draw on scientific information and make decisions that accord with their own values". While scientific information is often portrayed in quantitative terms and can be interpreted by experts, the audience must ultimately decide how to feel about the information.
Most science journalists begin their careers as either a scientist or a journalist and transition to science communication.
One area in which science journalists seem to support varying sides of an issue is in risk communication. Science journalists may choose to highlight the amount of risk that studies have uncovered while others focus more on the benefits depending on audience and framing. Science journalism in contemporary risk societies leads to the institutionalisation of mediated scientific public spheres which exclusively discuss science and technology related issues. This also leads to the development of new professional relationship between scientists and journalists, which is mutually beneficial.
== Types ==
There are many different examples of science writing. A few examples include feature writing, risk communication, blogs, science books, scientific journals, science podcasts and science magazines.
== Notable science journalists ==
Natalie Angier, a science journalist for The New York Times
Isaac Asimov, American science writer
Philip Ball, English science writer
Jules Bergman, a science journalist for ABC News
Christopher Bird
David Bodanis, known for his microphotographic style
David Bradley (UK journalist)
William Broad, a science journalist for The New York Times
Deborah Byrd, of the Earth & Sky radio series
Peter Calamai, science journalist for the Toronto Star
Nigel Calder
Siri Carpenter
Marcus Chown
Wilson da Silva, editor and co-founder of Cosmos magazine
Claudia Dreifus
David Ewing Duncan
Gregg Easterbrook
Dan Fagin
Kitty Ferguson
Timothy Ferris, science writer, most often on astronomical topics
Albrecht Fölsing
Ben Goldacre
Gina Kolata, science journalist for The New York Times
Robert Krulwich
Robert Kunzig
Duncan Lunan
Katherine McAlpine
Bob McDonald, Canadian science journalist, host of Quirks & Quarks
Steve Mirsky, columnist for Scientific American
Chris Mooney, science journalist and author
Michelle Nijhuis
Dennis Overbye of The New York Times
Peter Hadfield, freelance journalist and ex-geologist, known for his YouTube channel 'Potholer54'
Michael Pollan
David Quammen, science, nature and travel writer
Mary Roach
Matt Ridley, science journalist and author, columnist at the Wall Street Journal
Kirsten Sanford
Rebecca Skloot
Meredith Small
John Timmer
Nicholas Wade, a science journalist for The New York Times
Robyn Williams
Carl Zimmer
Nagendra Vijay
== See also ==
== References ==
== External links ==
== Further reading ==
Brainard, Curtis (20 March 2009). "Nature's Artificial Divide". Columbia Journalism Review.
Yong, Ed (29 July 2010). "On the Origin of Science Writers". National Geographic Phenomena Blog. Archived from the original on 11 March 2021. | Wikipedia/Science_journalism |
The Linear Model of Innovation was an early model designed to understand the relationship of science and technology that begins with basic research that flows into applied research, development and diffusion
It posits scientific research as the basis of innovation which eventually leads to economic growth.
The model has been criticized by many scholars over decades of years. The majority of the criticisms pointed out its crudeness and limitations in capturing the sources, process, and effects of innovation. However, it has also been argued that the linear model was simply a creation by academics, debated heavily in academia, but was never believed in practice. The model is more fittingly used as a basis to understand more nuanced alternative models.
== Versions ==
Two versions of the linear model of innovation are often presented:
"technology push" model
"market pull" model
From the 1950s to the Mid-1960s, the industrial innovation process was generally perceived as a linear progression from scientific discovery, through technological development in firms, to the marketplace. The stages of the "Technology Push" model are:
Basic science→Design and engineering→Manufacturing→Marketing→Sales
From the Mid 1960s to the Early 1970s, emerges the second-generation Innovation model, referred to as the "market pull" model of innovation. According to this simple sequential model, the market was the source of new ideas for directing R&D, which had a reactive role in the process. The stages of the "market pull " model are:
Market need—Development—Manufacturing—Sales
The linear models of innovation supported numerous criticisms concerning the linearity of the models. These models ignore the many feedbacks and loops that occur between the different "stages" of the process. Shortcomings and failures that occur at various stages may lead to a reconsideration of earlier steps and this may result in an innovation. A history of the linear model of innovation may be found in Benoît Godin's The Linear Model of Innovation: The Historical Construction of an Analytical Framework. A critical look at the origin of the terminology and how it may have a dubious history can be found in David Edgerton's ‘The linear model’ did not exist: Reflections on the history and historiography of science and research in industry in the twentieth century.
== Current models ==
Current models of innovation derive from approaches such as Actor-Network Theory, Social shaping of technology and social learning, provide a much richer picture of the way innovation works. Current ideas in Open Innovation and User innovation derive from these later ideas.
In the 'Phase Gate Model', the product or services concept is frozen at an early stage to minimize risk. Through enterprise, the innovation process involves a series of sequential phases arranged in a manner that the preceding phase must be cleared before moving to the next phase. Therefore, a project must pass through a gate with the permission of the gatekeeper before moving to the next succeeding phase.
Criteria for passing through each gate is defined beforehand. The gatekeeper examines whether the stated objectives for the preceding phase have been properly met or not and whether desired development has taken place during the preceding phase or not.
== See also ==
Innovation
Technological change
Science and technology studies
== References ==
Rogers, Everett (2003). Diffusion of Innovations, 5th edition, Free Press. ISBN 0-7432-2209-1 | Wikipedia/Linear_model_of_innovation |
Hard science and soft science are colloquial terms used to compare scientific fields on the basis of perceived methodological rigor, exactitude, and objectivity. In general, the formal sciences and natural sciences are considered hard science, whereas the social sciences and other sciences are described as soft science.
Precise definitions vary, but features often cited as characteristic of hard science include producing testable predictions, performing controlled experiments, relying on quantifiable data and mathematical models, a high degree of accuracy and objectivity, higher levels of consensus, faster progression of the field, greater explanatory success, cumulativeness, replicability, and generally applying a purer form of the scientific method. A closely related idea (originating in the nineteenth century with Auguste Comte) is that scientific disciplines can be arranged into a hierarchy of hard to soft on the basis of factors such as rigor, "development", and whether they are basic or applied.
Philosophers and historians of science have questioned the relationship between these characteristics and perceived hardness or softness. The more "developed" hard sciences do not necessarily have a greater degree of consensus or selectivity in accepting new results. Commonly cited methodological differences are also not a reliable indicator. For example, social sciences such as psychology and sociology use mathematical models extensively, but are usually considered soft sciences. However, there are some measurable differences between hard and soft sciences. For example, hard sciences make more extensive use of graphs, and soft sciences are more prone to a rapid turnover of buzzwords.
The metaphor has been criticised for unduly stigmatizing soft sciences, creating an unwarranted imbalance in the public perception, funding, and recognition of different fields.
== History of the terms ==
The origin of the terms "hard science" and "soft science" is obscure. The earliest attested use of "hard science" is found in an 1858 issue of the Journal of the Society of Arts, but the idea of a hierarchy of the sciences can be found earlier, in the work of the French philosopher Auguste Comte (1798‒1857). He identified astronomy as the most general science, followed by physics, chemistry, biology, then sociology. This view was highly influential, and was intended to classify fields based on their degree of intellectual development and the complexity of their subject matter.
The modern distinction between hard and soft science is often attributed to a 1964 article published in Science by John R. Platt. He explored why he considered some scientific fields to be more productive than others, though he did not actually use the terms themselves. In 1967, sociologist of science Norman W. Storer specifically distinguished between the natural sciences as hard and the social sciences as soft. He defined hardness in terms of the degree to which a field uses mathematics and described a trend of scientific fields increasing in hardness over time, identifying features of increased hardness as including better integration and organization of knowledge, an improved ability to detect errors, and an increase in the difficulty of learning the subject.
== Empirical support ==
In the 1970s sociologist Stephen Cole conducted a number of empirical studies attempting to find evidence for a hierarchy of scientific disciplines, and was unable to find significant differences in terms of core of knowledge, degree of codification, or research material. Differences that he did find evidence for included a tendency for textbooks in soft sciences to rely on more recent work, while the material in textbooks from the hard sciences was more consistent over time. After he published in 1983, it has been suggested that Cole might have missed some relationships in the data because he studied individual measurements, without accounting for the way multiple measurements could trend in the same direction, and because not all the criteria that could indicate a discipline's scientific status were analysed.
In 1984, Cleveland performed a survey of 57 journals and found that natural science journals used many more graphs than journals in mathematics or social science, and that social science journals often presented large amounts of observational data in the absence of graphs. The amount of page area used for graphs ranged from 0% to 31%, and the variation was primarily due to the number of graphs included rather than their sizes. Further analyses by Smith in 2000, based on samples of graphs from journals in seven major scientific disciplines, found that the amount of graph usage correlated "almost perfectly" with hardness (r=0.97). They also suggested that the hierarchy applies to individual fields, and demonstrated the same result using ten subfields of psychology (r=0.93).
In a 2010 article, Fanelli proposed that we expect more positive outcomes in "softer" sciences because there are fewer constraints on researcher bias. They found that among research papers that tested a hypothesis, the frequency of positive results was predicted by the perceived hardness of the field. For example, the social sciences as a whole had a 2.3-fold increased odds of positive results compared to the physical sciences, with the biological sciences in between. They added that this supported the idea that the social sciences and natural sciences differ only in degree, as long as the social sciences follow the scientific approach.
In 2013, Fanelli tested whether the ability of researchers in a field to "achieve consensus and accumulate knowledge" increases with the hardness of the science, and sampled 29,000 papers from 12 disciplines using measurements that indicate the degree of scholarly consensus. Out of the three possibilities (hierarchy, hard/soft distinction, or no ordering), the results supported a hierarchy, with physical sciences performing the best followed by biological sciences and then social sciences. The results also held within disciplines, as well as when mathematics and the humanities were included.
== Criticism ==
Critics of the concept argue that soft sciences are implicitly considered to be less "legitimate" scientific fields, or simply not scientific at all. An editorial in Nature stated that social science findings are more likely to intersect with everyday experience and may be dismissed as "obvious or insignificant" as a result. Being labelled a soft science can affect the perceived value of a discipline to society and the amount of funding available to it. In the 1980s, mathematician Serge Lang successfully blocked influential political scientist Samuel P. Huntington's admission to the US National Academy of Sciences, describing Huntington's use of mathematics to quantify the relationship between factors such as "social frustration" (Lang asked Huntington if he possessed a "social-frustration meter") as "pseudoscience". During the late 2000s recessions, social science was disproportionately targeted for funding cuts compared to mathematics and natural science. Proposals were made for the United States' National Science Foundation to cease funding disciplines such as political science altogether. Both of these incidents prompted critical discussion of the distinction between hard and soft sciences.
The perception of hard vs soft science is influenced by gender bias with a higher proportion of women in a given field leading to a "soft" perception even within STEM fields. This perception of softness is accompanied by a devaluation of the field's worth.
== See also ==
Academic field
Demarcation problem
Exact sciences
Hard and soft science fiction
History of science
Methodological dualism
Non-science
Philosophy of social science
Positivism dispute
STEM fields
== Notes ==
== References == | Wikipedia/Hard_and_soft_science |
Heliocentrism (also known as the heliocentric model) is a superseded astronomical model in which the Earth and planets orbit around the Sun at the center of the universe. Historically, heliocentrism was opposed to geocentrism, which placed the Earth at the center. The notion that the Earth revolves around the Sun had been proposed as early as the 3rd century BC by Aristarchus of Samos, who had been influenced by a concept presented by Philolaus of Croton (c. 470 – 385 BC). In the 5th century BC the Greek philosophers Philolaus and Hicetas had the thought on different occasions that the Earth was spherical and revolving around a "mystical" central fire, and that this fire regulated the universe. In medieval Europe, however, Aristarchus' heliocentrism attracted little attention—possibly because of the loss of scientific works of the Hellenistic period.
It was not until the 16th century that a mathematical model of a heliocentric system was presented by the Renaissance mathematician, astronomer, and Catholic cleric, Nicolaus Copernicus, leading to the Copernican Revolution. In 1576, Thomas Digges published a modified Copernican system. His modifications are close to modern observations. In the following century, Johannes Kepler introduced elliptical orbits, and Galileo Galilei presented supporting observations made using a telescope.
With the observations of William Herschel, Friedrich Bessel, and other astronomers, it was realized that the Sun, while near the barycenter of the Solar System, was not central in the universe. Modern astronomy does not distinguish any center.
== Ancient and medieval astronomy ==
While the sphericity of the Earth was widely recognized in Greco-Roman astronomy from at least the 4th century BC, the Earth's daily rotation and yearly orbit around the Sun was never universally accepted until the Copernican Revolution.
While a moving Earth was proposed at least from the 4th century BC in Pythagoreanism, and a fully developed heliocentric model was developed by Aristarchus of Samos in the 3rd century BC, these ideas were not successful in replacing the view of a static spherical Earth, and from the 2nd century AD the predominant model, which would be inherited by medieval astronomy, was the geocentric model described in Ptolemy's Almagest.
The Ptolemaic system was a sophisticated astronomical system that managed to calculate the positions for the planets to a fair degree of accuracy. Ptolemy himself, in his Almagest, says that any model for describing the motions of the planets is merely a mathematical device, and since there is no actual way to know which is true, the simplest model that gets the right numbers should be used. However, he rejected the idea of a spinning Earth as absurd as he believed it would create huge winds. Within his model the distances of the Moon, Sun, planets and stars could be determined by treating orbits' celestial spheres as contiguous realities, which gave the stars' distance as less than 20 Astronomical Units, a regression, since Aristarchus of Samos's heliocentric scheme had centuries earlier necessarily placed the stars at least two orders of magnitude more distant.
Problems with Ptolemy's system were well recognized in medieval astronomy, and an increasing effort to criticize and improve it in the late medieval period eventually led to the Copernican heliocentrism developed in Renaissance astronomy.
=== Classical antiquity ===
==== Pythagoreans ====
The first non-geocentric model of the universe was proposed by the Pythagorean philosopher Philolaus (d. 390 BC), who taught that at the center of the universe was a "central fire", around which the Earth, Sun, Moon and planets revolved in uniform circular motion. This system postulated the existence of a Counter-Earth collinear with the Earth and central fire, with the same period of revolution around the central fire as the Earth. The Sun revolved around the central fire once a year, and the stars were stationary. The Earth maintained the same hidden face towards the central fire, rendering both it and the "Counter-Earth" invisible from Earth. The Pythagorean concept of uniform circular motion remained unchallenged for approximately the next 2000 years, and it was to the Pythagoreans that Copernicus referred to show that the notion of a moving Earth was neither new nor revolutionary. Kepler gave an alternative explanation of the Pythagoreans' "central fire" as the Sun, "as most sects purposely hid[e] their teachings".
Heraclides of Pontus (4th century BC) said that the rotation of the Earth explained the apparent daily motion of the celestial sphere. It used to be thought that he believed Mercury and Venus to revolve around the Sun, which in turn (along with the other planets) revolves around the Earth. Macrobius (AD 395—423) later described this as the "Egyptian System," stating that "it did not escape the skill of the Egyptians," though there is no other evidence it was known in ancient Egypt.
==== Aristarchus of Samos ====
The first person known to have proposed a heliocentric system was Aristarchus of Samos (c. 270 BC). Like his contemporary Eratosthenes, Aristarchus calculated the size of the Earth and measured the sizes and distances of the Sun and Moon. From his estimates, he concluded that the Sun was six to seven times wider than the Earth, and thought that the larger object would have the most attractive force.
His writings on the heliocentric system are lost, but some information about them is known from a brief description by his contemporary, Archimedes, and from scattered references by later writers. Archimedes' description of Aristarchus' theory is given in the former's book, The Sand Reckoner. The entire description comprises just three sentences, which Thomas Heath translates as follows:
You [King Gelon] are aware that "universe" is the name given by most astronomers to the sphere, the centre of which is the centre of the earth, while its radius is equal to the straight line between the centre of the sun and the centre of the earth. This is the common account (τά γραφόμενα), as you have heard from astronomers. But Aristarchus brought out a book consisting of certain hypotheses, wherein it appears, as a consequence of the assumptions made, that the universe is many times greater than the "universe" just mentioned. His hypotheses are that the fixed stars and the sun remain unmoved, that the earth revolves about the sun on the circumference of a circle, the sun lying in the middle of the orbit, and that the sphere of the fixed stars, situated about the same centre as the sun, is so great that the circle in which he supposes the earth to revolve bears such a proportion to the distance of the fixed stars as the centre of the sphere bears to its surface.
Aristarchus presumably took the stars to be very far away because he was aware that their parallax would otherwise be observed over the course of a year. The stars are in fact so far away that stellar parallax only became detectable when sufficiently powerful telescopes had been developed in the 1830s.
No references to Aristarchus' heliocentrism are known in any other writings from before the common era. The earliest of the handful of other ancient references occur in two passages from the writings of Plutarch. These mention one detail not stated explicitly in Archimedes' account—namely, that Aristarchus' theory had the Earth rotating on an axis. The first of these reference occurs in Concerning the Face Which Appears in the Orb of the Moon:
Only do not, my good fellow, enter an action against me for impiety in the style of Cleanthes, who thought it was the duty of Greeks to indict Aristarchus of Samos on the charge of impiety for putting in motion the Hearth of the Universe, this being the effect of his attempt to save the phenomena by supposing the heaven to remain at rest and the earth to revolve in an oblique circle, while it rotates, at the same time, about its own axis.
Only scattered fragments of Cleanthes' writings have survived in quotations by other writers, but in Lives and Opinions of Eminent Philosophers, Diogenes Laërtius lists A reply to Aristarchus (Πρὸς Ἀρίσταρχον) as one of Cleanthes' works, and some scholars have suggested that this might have been where Cleanthes had accused Aristarchus of impiety.
The second of the references by Plutarch is in his Platonic Questions:
Did Plato put the earth in motion, as he did the sun, the moon, and the five planets, which he called the instruments of time on account of their turnings, and was it necessary to conceive that the earth "which is globed about the axis stretched from pole to pole through the whole universe" was not represented as being held together and at rest, but as turning and revolving (στρεφομένην καὶ ἀνειλουμένην), as Aristarchus and Seleucus afterwards maintained that it did, the former stating this as only a hypothesis (ὑποτιθέμενος μόνον), the latter as a definite opinion (καὶ ἀποφαινόμενος)?
The remaining references to Aristarchus' heliocentrism are extremely brief, and provide no more information beyond what can be gleaned from those already cited. Ones which mention Aristarchus explicitly by name occur in Aëtius' Opinions of the Philosophers, Sextus Empiricus' Against the Mathematicians, and an anonymous scholiast to Aristotle. Another passage in Aëtius' Opinions of the Philosophers reports that Seleucus the astronomer had affirmed the Earth's motion, but does not mention Aristarchus.
==== Seleucus of Seleucia ====
Since Plutarch mentions the "followers of Aristarchus" in passing, it is likely that there were other astronomers in the Classical period who also espoused heliocentrism, but whose work was lost. The only other astronomer from antiquity known by name who is known to have supported Aristarchus' heliocentric model was Seleucus of Seleucia (b. 190 BC), a Hellenistic astronomer who flourished a century after Aristarchus in the Seleucid Empire. Seleucus was a proponent of the heliocentric system of Aristarchus. Seleucus may have proved the heliocentric theory by determining the constants of a geometric model for the heliocentric theory and developing methods to compute planetary positions using this model. He may have used early trigonometric methods that were available in his time, as he was a contemporary of Hipparchus. A fragment of a work by Seleucus has survived in Arabic translation, which was referred to by Rhazes (b. 865).
Alternatively, his explanation may have involved the phenomenon of tides, which he supposedly theorized to be caused by the attraction to the Moon and by the revolution of the Earth around the Earth and Moon's center of mass.
==== Late antiquity ====
There were occasional speculations about heliocentrism in Europe before Copernicus. In Roman Carthage, the pagan Martianus Capella (5th century AD) expressed the opinion that the planets Venus and Mercury did not go about the Earth but instead circled the Sun. Capella's model was discussed in the Early Middle Ages by various anonymous 9th-century commentators and Copernicus mentions him as an influence on his own work. Also Macrobius (420 CE) described a heliocentric model.
=== Ancient India ===
Aryabhata (476–550), in his magnum opus Aryabhatiya (499), propounded a planetary model in which the Earth was taken to be spinning on its axis and the periods of the planets were given with respect to the Sun. His immediate commentators, such as Lalla, and other later authors, rejected his innovative view about the turning Earth. It has been argued that Aryabhatta's calculations were based on an underlying heliocentric model, in which the planets orbit the Sun, although this has also been rebutted. The general consensus is that a synodic anomaly (depending on the position of the Sun) does not imply a physically heliocentric orbit (such corrections being also present in late Babylonian astronomical texts), and that Aryabhata's system was not explicitly heliocentric. He also made many astronomical calculations, such as the times of the solar and lunar eclipses, and the instantaneous motion of the Moon. Early followers of Aryabhata's model included Varahamihira, Brahmagupta, and Bhaskara II.
=== Medieval Islamic world ===
For a time, Muslim astronomers accepted the Ptolemaic system and the geocentric model, which were used by al-Battani to show that the distance between the Sun and the Earth varies. In the 10th century, al-Sijzi accepted that the Earth rotates around its axis. According to later astronomer al-Biruni, al-Sijzi invented an astrolabe called al-zūraqī based on a belief held by some of his contemporaries that the apparent motion of the stars was due to the Earth's movement, and not that of the firmament. Islamic astronomers began to criticize the Ptolemaic model, including Ibn al-Haytham in his Al-Shukūk 'alā Baṭalamiyūs ("Doubts Concerning Ptolemy", c. 1028), who found contradictions in Ptolemy's model, but al-Haytham remained committed to a geocentric model.
Al-Biruni discussed the possibility of whether the Earth rotated about its own axis and orbited the Sun, but in his Masudic Canon (1031), he expressed his faith in a geocentric and stationary Earth. He was aware that if the Earth rotated on its axis, it would be consistent with his astronomical observations, but considered it a problem of natural philosophy rather than one of mathematics.
In the 12th century, non-heliocentric alternatives to the Ptolemaic system were developed by some Islamic astronomers, such as Nur ad-Din al-Bitruji, who considered the Ptolemaic model mathematical, and not physical. His system spread throughout most of Europe in the 13th century, with debates and refutations of his ideas continued to the 16th century.
The Maragha school of astronomy in Ilkhanid-era Persia further developed "non-Ptolemaic" planetary models involving Earth's rotation. Notable astronomers of this school are Al-Urdi (d. 1266) Al-Katibi (d. 1277), and Al-Tusi (d. 1274).
The arguments and evidence used resemble those used by Copernicus to support the Earth's motion.
The criticism of Ptolemy as developed by Averroes and by the Maragha school explicitly address the Earth's rotation but it did not arrive at explicit heliocentrism.
The observations of the Maragha school were further improved at the Timurid-era Samarkand observatory under Qushji (1403–1474).
=== Medieval India ===
In India, Nilakantha Somayaji (1444–1544), in his Aryabhatiyabhasya, a commentary on Aryabhata's Aryabhatiya, developed a computational system for a geo-heliocentric planetary model, in which the planets orbit the Sun, which in turn orbits the Earth, similar to the system later proposed by Tycho Brahe. In the Tantrasamgraha (1501), Somayaji further revised his planetary system, which was mathematically more accurate at predicting the heliocentric orbits of the interior planets than both the Tychonic and Copernican models, but did not propose any specific models of the universe. Nilakantha's planetary system also incorporated the Earth's rotation on its axis. Most astronomers of the Kerala school of astronomy and mathematics seem to have accepted his planetary model.
== Renaissance-era astronomy ==
=== Medieval period ===
Martianus Capella (5th century CE) expressed the opinion that the planets Venus and Mercury did not go about the Earth but instead circled the Sun. Capella's model was discussed in the Early Middle Ages by various anonymous 9th-century commentators and Copernicus mentions him as an influence on his own work. Macrobius (420 CE) described a heliocentric model. John Scotus Eriugena(815-877 CE) proposed a model reminiscent of that from Tycho Brahe.
In the 14th century, bishop Nicole Oresme discussed the possibility that the Earth rotated on its axis, while Cardinal Nicholas of Cusa in his Learned Ignorance asked whether there was any reason to assert that the Sun (or any other point) was the center of the universe. In parallel to a mystical definition of God, Cusa wrote that "Thus the fabric of the world (machina mundi) will quasi have its center everywhere and circumference nowhere," recalling Hermes Trismegistus.
Some historians maintain that the thought of the Maragheh observatory, in particular the mathematical devices known as the Urdi lemma and the Tusi couple, influenced Renaissance-era European astronomy, and thus was indirectly received by Renaissance-era European astronomy and thus by Copernicus.
Copernicus used such devices in the same planetary models as found in Arabic sources. The exact replacement of the equant by two epicycles used by Copernicus in the Commentariolus was found in an earlier work by Ibn al-Shatir (d. c. 1375) of Damascus. Copernicus' lunar and Mercury models are also identical to Ibn al-Shatir's.
While the influence of the criticism of Ptolemy by Averroes on Renaissance thought is clear and explicit, the claim of direct influence of the
Maragha school, postulated by Otto E. Neugebauer in 1957, remains an open question. Since the Tusi couple was used by Copernicus in his reformulation of mathematical astronomy, there is a growing consensus that he became aware of this idea in some way. One possible route of transmission may have been through Byzantine science, which translated some of al-Tusi's works from Arabic into Byzantine Greek. Several Byzantine Greek manuscripts containing the Tusi couple are still extant in Italy. The Mathematics Genealogy Project suggests that there is a "genealogy" of Nasir al-Dīn al-Ṭūsī → Shams al‐Dīn al‐Bukhārī → Gregory Chioniades → Manuel Bryennios → Theodore Metochites → Gregory Palamas → Nilos Kabasilas → Demetrios Kydones → Gemistos Plethon → Basilios Bessarion → Johannes Regiomontanus → Domenico Maria Novara da Ferrara → Nicolaus (Mikołaj Kopernik) Copernicus. Leonardo da Vinci (1452–1519) wrote "Il sole non si move." ("The Sun does not move.") and he was a student of a student of Bessarion according to the Mathematics Genealogy Project. It has been suggested that the idea of the Tusi couple may have arrived in Europe leaving few manuscript traces, since it could have occurred without the translation of any Arabic text into Latin.
Other scholars have argued that Copernicus could well have developed these ideas independently of the late Islamic tradition. Copernicus explicitly references several astronomers of the "Islamic Golden Age" (10th to 12th centuries) in De Revolutionibus: Albategnius (Al-Battani), Averroes (Ibn Rushd), Thebit (Thabit Ibn Qurra), Arzachel (Al-Zarqali), and Alpetragius (Al-Bitruji), but he does not show awareness of the existence of any of the later astronomers of the Maragha school.
It has been argued that Copernicus could have independently discovered the Tusi couple or took the idea from Proclus's Commentary on the First Book of Euclid, which Copernicus cited. Another possible source for Copernicus' knowledge of this mathematical device is the Questiones de Spera of Nicole Oresme, who described how a reciprocating linear motion of a celestial body could be produced by a combination of circular motions similar to those proposed by al-Tusi.
The state of knowledge on planetary theory received by Copernicus is summarized in Georg von Peuerbach's Theoricae Novae Planetarum (printed in 1472 by Regiomontanus). By 1470, the accuracy of observations by the Vienna school of astronomy, of which Peuerbach and Regiomontanus were members, was high enough to make the eventual development of heliocentrism inevitable, and indeed it is possible that Regiomontanus did arrive at an explicit theory of heliocentrism before his death in 1476, some 30 years before Copernicus.
=== Copernican heliocentrism ===
Nicolaus Copernicus in his De revolutionibus orbium coelestium ("On the revolution of heavenly spheres", first printed in 1543 in Nuremberg), presented a discussion of a heliocentric model of the universe in much the same way as Ptolemy in the 2nd century had presented his geocentric model in his Almagest. Copernicus discussed the philosophical implications of his proposed system, elaborated it in geometrical detail, used selected astronomical observations to derive the parameters of his model, and wrote astronomical tables which enabled one to compute the past and future positions of the stars and planets. In doing so, Copernicus moved heliocentrism from philosophical speculation to predictive geometrical astronomy. In reality, Copernicus' system did not predict the planets' positions any better than the Ptolemaic system. This theory resolved the issue of planetary retrograde motion by arguing that such motion was only perceived and apparent, rather than real: it was a parallax effect, as an object that one is passing seems to move backwards against the horizon. This issue was also resolved in the geocentric Tychonic system; the latter, however, while eliminating the major epicycles, retained as a physical reality the irregular back-and-forth motion of the planets, which Kepler characterized as a "pretzel".
Copernicus cited Aristarchus in an early (unpublished) manuscript of De Revolutionibus (which still survives), stating: "Philolaus believed in the mobility of the earth, and some even say that Aristarchus of Samos was of that opinion." However, in the published version he restricts himself to noting that in works by Cicero he had found an account of the theories of Hicetas and that Plutarch had provided him with an account of the Pythagoreans, Heraclides Ponticus, Philolaus, and Ecphantus. These authors had proposed a moving Earth, which did not, however, revolve around a central sun.
== Reception in Early Modern Europe ==
=== Circulation of Commentariolus (published before 1515) ===
The first information about the heliocentric views of Nicolaus Copernicus was circulated in manuscript completed some time before May 1, 1514. In 1533, Johann Albrecht Widmannstetter delivered in Rome a series of lectures outlining Copernicus' theory. The lectures were heard with interest by Pope Clement VII and several Catholic cardinals.
In 1539, Martin Luther purportedly said:
"There is talk of a new astrologer who wants to prove that the earth moves and goes around instead of the sky, the sun, the moon, just as if somebody were moving in a carriage or ship might hold that he was sitting still and at rest while the earth and the trees walked and moved. But that is how things are nowadays: when a man wishes to be clever he must … invent something special, and the way he does it must needs be the best! The fool wants to turn the whole art of astronomy upside-down. However, as Holy Scripture tells us, so did Joshua bid the sun to stand still and not the earth."
This was reported in the context of a conversation at the dinner table and not a formal statement of faith. Melanchthon, however, opposed the doctrine over a period of years.
=== Publication of De Revolutionibus (1543) ===
Nicolaus Copernicus published the definitive statement of his system in De Revolutionibus in 1543. Copernicus began to write it in 1506 and finished it in 1530, but did not publish it until the year of his death. Although he was in good standing with the Church and had dedicated the book to Pope Paul III, the published form contained an unsigned preface by Osiander defending the system and arguing that it was useful for computation even if its hypotheses were not necessarily true. Possibly because of that preface, the work of Copernicus inspired very little debate on whether it might be heretical during the next 60 years. There was an early suggestion among Dominicans that the teaching of heliocentrism should be banned, but nothing came of it at the time.
Some years after the publication of De Revolutionibus John Calvin preached a sermon in which he denounced those who "pervert the order of nature" by saying that "the sun does not move and that it is the earth that revolves and that it turns".
=== Tycho Brahe's geo-heliocentric system (c. 1587) ===
Prior to the publication of De Revolutionibus, the most widely accepted system had been proposed by Ptolemy, in which the Earth was the center of the universe and all celestial bodies orbited it. Tycho Brahe, arguably the most accomplished astronomer of his time, advocated against Copernicus' heliocentric system and for an alternative to the Ptolemaic geocentric system: a geo-heliocentric system now known as the Tychonic system in which the Sun and Moon orbit the Earth, Mercury and Venus orbit the Sun inside the Sun's orbit of the Earth, and Mars, Jupiter and Saturn orbit the Sun outside the Sun's orbit of the Earth.
Tycho appreciated the Copernican system, but objected to the idea of a moving Earth on the basis of physics, astronomy, and religion. The Aristotelian physics of the time (modern Newtonian physics was still a century away) offered no physical explanation for the motion of a massive body like Earth, whereas it could easily explain the motion of heavenly bodies by postulating that they were made of a different sort substance called aether that moved naturally. So Tycho said that the Copernican system "...expertly and completely circumvents all that is superfluous or discordant in the system of Ptolemy. On no point does it offend the principle of mathematics. Yet it ascribes to the Earth, that hulking, lazy body, unfit for motion, a motion as quick as that of the aethereal torches, and a triple motion at that." Likewise, Tycho took issue with the vast distances to the stars that Aristarchus and Copernicus had assumed in order to explain the lack of any visible parallax. Tycho had measured the apparent sizes of stars (now known to be illusory), and used geometry to calculate that in order to both have those apparent sizes and be as far away as heliocentrism required, stars would have to be huge (much larger than the sun; the size of Earth's orbit or larger). Regarding this Tycho wrote, "Deduce these things geometrically if you like, and you will see how many absurdities (not to mention others) accompany this assumption [of the motion of the earth] by inference." He also cited the Copernican system's "opposition to the authority of Sacred Scripture in more than one place" as a reason why one might wish to reject it, and observed that his own geo-heliocentric alternative "offended neither the principles of physics nor Holy Scripture."
The Jesuits astronomers in Rome were at first unreceptive to Tycho's system; the most prominent, Clavius, commented that Tycho was "confusing all of astronomy, because he wants to have Mars lower than the Sun." However, after the advent of the telescope showed problems with some geocentric models (by demonstrating that Venus circles the Sun, for example), the Tychonic system and variations on that system became popular among geocentrists, and the Jesuit astronomer Giovanni Battista Riccioli would continue Tycho's use of physics, stellar astronomy (now with a telescope), and religion to argue against heliocentrism and for Tycho's system well into the seventeenth century.
=== Giordano Bruno ===
During Giordano Bruno's lifetime, he is the only known person to defend Copernicus' heliocentrism. In 1584, Bruno published two dialogues (La Cena de le Ceneri and De l'infinito universo et mondi) in which he argued against the planetary spheres (Christoph Rothmann did the same in 1586 as did Tycho Brahe in 1587) and affirmed the Copernican principle.
In particular, to support the Copernican view and oppose the objection according to which the motion of the Earth would be perceived by means of the motion of winds, clouds etc., in La Cena de le Ceneri Bruno anticipates some of the arguments of Galilei on the relativity principle. Note that he also uses the example now known as Galileo's ship.
=== Johannes Kepler ===
Using measurements made at Tycho's observatory, Johannes Kepler developed his laws of planetary motion between 1609 and 1619. In Astronomia nova (1609), Kepler made a diagram of the movement of Mars in relation to Earth if Earth were at the center of its orbit, which shows that Mars' orbit would be completely imperfect and never follow along the same path. To solve the apparent derivation of Mars' orbit from a perfect circle, Kepler derived both a mathematical definition and, independently, a matching ellipse around the Sun to explain the motion of the red planet.
Between 1617 and 1621, Kepler developed a heliocentric model of the Solar System in Epitome astronomiae Copernicanae, in which all the planets have elliptical orbits. This provided significantly increased accuracy in predicting the position of the planets. Kepler's ideas were not immediately accepted, and Galileo for example ignored them. In 1621, Epitome astronomia Copernicanae was placed on the Catholic Church's index of prohibited books despite Kepler being a Protestant.
=== Galileo Galilei and 1616 ban against Copernicanism ===
Galileo was able to look at the night sky with the newly invented telescope. He published his observations that Jupiter is orbited by moons and that the Sun rotates in his Sidereus Nuncius (1610) and Letters on Sunspots (1613), respectively. Around this time, he also announced that Venus exhibits a full range of phases (satisfying an argument that had been made against Copernicus). As the Jesuit astronomers confirmed Galileo's observations, the Jesuits moved away from the Ptolemaic model and toward Tycho's teachings.
In his 1615 "Letter to the Grand Duchess Christina", Galileo defended heliocentrism, and claimed it was not contrary to Holy Scripture. He took Augustine's position on Scripture: not to take every passage literally when the scripture in question is in a Bible book of poetry and songs, not a book of instructions or history. The writers of the Scripture wrote from the perspective of the terrestrial world, and from that vantage point the Sun does rise and set. In fact, it is the Earth's rotation which gives the impression of the Sun in motion across the sky.
In February 1615, prominent Dominicans including Thomaso Caccini and Niccolò Lorini brought Galileo's writings on heliocentrism to the attention of the Inquisition, because they appeared to violate Holy Scripture and the decrees of the Council of Trent. Cardinal and Inquisitor Robert Bellarmine was called upon to adjudicate, and wrote in April that treating heliocentrism as a real phenomenon would be "a very dangerous thing," irritating philosophers and theologians, and harming "the Holy Faith by rendering Holy Scripture as false."
In January 1616, Msgr. Francesco Ingoli addressed an essay to Galileo disputing the Copernican system. Galileo later stated that he believed this essay to have been instrumental in the ban against Copernicanism that followed in February. According to Maurice Finocchiaro, Ingoli had probably been commissioned by the Inquisition to write an expert opinion on the controversy, and the essay provided the "chief direct basis" for the ban. The essay focused on eighteen physical and mathematical arguments against heliocentrism. It borrowed primarily from the arguments of Tycho Brahe, and it notedly mentioned the problem that heliocentrism requires the stars to be much larger than the Sun. Ingoli wrote that the great distance to the stars in the heliocentric theory "clearly proves ... the fixed stars to be of such size, as they may surpass or equal the size of the orbit circle of the Earth itself." Ingoli included four theological arguments in the essay, but suggested to Galileo that he focus on the physical and mathematical arguments. Galileo did not write a response to Ingoli until 1624.
In February 1616, the Inquisition assembled a committee of theologians, known as qualifiers, who delivered their unanimous report condemning heliocentrism as "foolish and absurd in philosophy, and formally heretical since it explicitly contradicts in many places the sense of Holy Scripture." The Inquisition also determined that the Earth's motion "receives the same judgement in philosophy and ... in regard to theological truth it is at least erroneous in faith." Bellarmine personally ordered Galileo
...to abstain completely from teaching or defending this doctrine and opinion or from discussing it... to abandon completely... the opinion that the sun stands still at the center of the world and the earth moves, and henceforth not to hold, teach, or defend it in any way whatever, either orally or in writing.
In March 1616, after the Inquisition's injunction against Galileo, the papal Master of the Sacred Palace, Congregation of the Index, and the Pope banned all books and letters advocating the Copernican system, which they called "the false Pythagorean doctrine, altogether contrary to Holy Scripture." In 1618, the Holy Office recommended that a modified version of Copernicus' De Revolutionibus be allowed for use in calendric calculations, though the original publication remained forbidden until 1758.
Pope Urban VIII encouraged Galileo to publish the pros and cons of heliocentrism. Galileo's response, Dialogue concerning the two chief world systems (1632), clearly advocated heliocentrism, despite his declaration in the preface that,
I will endeavour to show that all experiments that can be made upon the Earth are insufficient means to conclude for its mobility but are indifferently applicable to the Earth, movable or immovable...
and his straightforward statement,
I might very rationally put it in dispute, whether there be any such centre in nature, or no; being that neither you nor any one else hath ever proved, whether the World be finite and figurate, or else infinite and interminate; yet nevertheless granting you, for the present, that it is finite, and of a terminate Spherical Figure, and that thereupon it hath its centre...
Some ecclesiastics also interpreted the book as characterizing the Pope as a simpleton, since his viewpoint in the dialogue was advocated by the character Simplicio. Urban VIII became hostile to Galileo and he was again summoned to Rome. Galileo's trial in 1633 involved making fine distinctions between "teaching" and "holding and defending as true". For advancing heliocentric theory Galileo was forced to recant Copernicanism and was put under house arrest for the last few years of his life. According to J. L. Heilbron, informed contemporaries of Galileo's "appreciated that the reference to heresy in connection with Galileo or Copernicus had no general or theological significance."
In 1664, Pope Alexander VII published his Index Librorum Prohibitorum Alexandri VII Pontificis Maximi jussu editus (Index of Prohibited Books, published by order of Alexander VII, P.M.) which included all previous condemnations of heliocentric books.
=== Age of Reason ===
René Descartes' first cosmological treatise, written between 1629 and 1633 and titled The World, included a heliocentric model, but Descartes abandoned it in the light of Galileo's treatment. In his Principles of Philosophy (1644), Descartes introduced a mechanical model in which planets do not move relative to their immediate atmosphere, but are constituted around space-matter vortices in curved space; these rotate due to centrifugal force and the resulting centripetal pressure. The Galileo affair did little overall to slow the spread of heliocentrism across Europe, as Kepler's Epitome of Copernican Astronomy became increasingly influential in the coming decades. By 1686, the model was well enough established that the general public was reading about it in Conversations on the Plurality of Worlds, published in France by Bernard le Bovier de Fontenelle and translated into English and other languages in the coming years. It has been called "one of the first great popularizations of science."
In 1687, Isaac Newton published Philosophiæ Naturalis Principia Mathematica, which provided an explanation for Kepler's laws in terms of universal gravitation and what came to be known as Newton's laws of motion. This placed heliocentrism on a firm theoretical foundation, although Newton's heliocentrism was of a somewhat modern kind. Already in the mid-1680s he recognized the "deviation of the Sun" from the center of gravity of the Solar System. For Newton it was not precisely the center of the Sun or any other body that could be considered at rest, but "the common centre of gravity of the Earth, the Sun and all the Planets is to be esteem'd the Centre of the World", and this center of gravity "either is at rest or moves uniformly forward in a right line". Newton adopted the "at rest" alternative in view of common consent that the center, wherever it was, was at rest.
Meanwhile, the Catholic Church remained opposed to heliocentrism as a literal description, but this did not by any means imply opposition to all astronomy; indeed, it needed observational data to maintain its calendar. In support of this effort it allowed the cathedrals themselves to be used as solar observatories called meridiane; i.e., they were turned into "reverse sundials", or gigantic pinhole cameras, where the Sun's image was projected from a hole in a window in the cathedral's lantern onto a meridian line.
In the mid-18th century the Church's opposition began to fade. An annotated copy of Newton's Principia was published in 1742 by Fathers le Seur and Jacquier of the Franciscan Minims, two Catholic mathematicians, with a preface stating that the author's work assumed heliocentrism and could not be explained without the theory. In 1758 the Catholic Church dropped the general prohibition of books advocating heliocentrism from the Index of Forbidden Books. The Observatory of the Roman College was established by Pope Clement XIV in 1774 (nationalized in 1878, but re-founded by Pope Leo XIII as the Vatican Observatory in 1891). In spite of dropping its active resistance to heliocentrism, the Catholic Church did not lift the prohibition of uncensored versions of Copernicus' De Revolutionibus or Galileo's Dialogue. The affair was revived in 1820, when the Master of the Sacred Palace (the Catholic Church's chief censor), Filippo Anfossi, refused to license a book by a Catholic canon, Giuseppe Settele, because it openly treated heliocentrism as a physical fact. Settele appealed to pope Pius VII. After the matter had been reconsidered by the Congregation of the Index and the Holy Office, Anfossi's decision was overturned. Pius VII approved a decree in 1822 by the Sacred Congregation of the Inquisition to allow the printing of heliocentric books in Rome. Copernicus' De Revolutionibus and Galileo's Dialogue were then subsequently omitted from the next edition of the Index when it appeared in 1835.
Three apparent proofs of the heliocentric hypothesis were provided in 1727 by James Bradley, in 1838 by Friedrich Wilhelm Bessel, and in 1851 by Léon Foucault. Bradley discovered the stellar aberration, proving the relative motion of the Earth. Bessel proved that the parallax of a star was greater than zero by measuring the parallax of 0.314 arcseconds of a star named 61 Cygni. In the same year Friedrich Georg Wilhelm Struve and Thomas Henderson measured the parallaxes of other stars, Vega and Alpha Centauri. Experiments like those of Foucault were performed by V. Viviani in 1661 in Florence and by Bartolini in 1833 in Rimini.
== Reception in Judaism ==
Already in the Talmud, Greek philosophy and science under the general name "Greek wisdom" were considered dangerous. They were put under ban then and later for some periods.
The first Jewish scholar to describe the Copernican system, albeit without mentioning Copernicus by name, was Maharal of Prague, in his book "Be'er ha-Golah" (1593). Maharal makes an argument of radical skepticism, arguing that no scientific theory can be reliable, which he illustrates by the new-fangled theory of heliocentrism upsetting even the most fundamental views on the cosmos.
Copernicus is mentioned in the books of David Gans (1541–1613), who worked with Brahe and Kepler. Gans wrote two books on astronomy in Hebrew: a short one, "Magen David" (1612), and a full one, "Nehmad veNaim" (published only in 1743). He described objectively three systems: those of Ptolemy, Copernicus and Brahe, without taking sides.
Joseph Solomon Delmedigo (1591–1655) in his "Elim" (1629) says that the arguments of Copernicus are so strong, that only an imbecile will not accept them. Delmedigo studied at Padua and was acquainted with Galileo.
An actual controversy on the Copernican model within Judaism arises only in the early 18th century. Most authors in this period had accepted Copernican heliocentrism, with opposition from David Nieto and Tobias Cohn, who argued against heliocentrism on the grounds it contradicted scripture. Nieto merely rejected the new system on those grounds without much passion, whereas Cohn went so far as to call Copernicus "a first-born of Satan", though he also acknowledged that he would have found it difficult to proffer one particular objection based on a passage from the Talmud.
In the 19th century, two students of the Hatam Sofer wrote books that were given approbations by him even though one supported heliocentrism and the other geocentrism. One, a commentary on Genesis titled Yafe’ah le-Ketz written by R. Israel David Schlesinger resisted a heliocentric model and supported geocentrism. The other, Mei Menuchot written by R. Eliezer Lipmann Neusatz encouraged acceptance of the heliocentric model and other modern scientific thinking.
Since the 20th century most Jews have not questioned the science of heliocentrism. Exceptions include Shlomo Benizri and R. M.M. Schneerson of Chabad who argued that the question of heliocentrism vs. geocentrism is obsolete because of the relativity of motion. Schneerson's followers in Chabad continue to deny the heliocentric model.
== Modern science ==
=== William Herschel's heliocentrism ===
In 1783, amateur astronomer William Herschel attempted to determine the shape of the universe by examining stars through his handmade telescopes. Herschel was the first to propose a model of the universe based on observation and measurement. At that time, the dominant assumption in cosmology was that the Milky Way was the entire universe, an assumption that has since been proven wrong with observations. Herschel concluded that it was in the shape of a disk, but assumed that the Sun was in the center of the disk, making the model heliocentric.
Seeing that the stars belonging to the Milky Way appeared to encircle the Earth, Herschel carefully counted stars of given apparent magnitudes, and after finding the numbers were the same in all directions, concluded Earth must be close to the center of the Milky Way. However, there were two flaws in Herschel's methodology: magnitude is not a reliable index to the distance of stars, and some of the areas that he mistook for empty space were actually dark, obscuring nebulae that blocked his view toward the center of the Milky Way.
The Herschel model remained relatively unchallenged for the next hundred years, with minor refinements. Jacobus Kapteyn introduced motion, density, and luminosity to Herschel's star counts, which still implied a near-central location of the Sun.
=== Replacement with galactocentrism and acentrism ===
Already in the early 19th century, Thomas Wright and Immanuel Kant speculated that fuzzy patches of light called nebulae were actually distant "island universes" consisting of many stellar systems. The shape of the Milky Way galaxy was expected to resemble such "islands universes."
However, "scientific arguments were marshalled against such a possibility," and this view was rejected by almost all scientists until the early 20th century, with Harlow Shapley's work on globular clusters and Edwin Hubble's measurements in 1924. After Shapley and Hubble showed that the Sun is not the center of the universe, cosmology moved on from heliocentrism to galactocentrism, which states that the Milky Way is the center of the universe.
Hubble's observations of redshift in light from distant galaxies indicated that the universe was expanding and acentric. As a result, soon after galactocentrism was formulated, it was abandoned in favor of the Big Bang model of the acentric expanding universe. Further assumptions, such as the Copernican principle, the cosmological principle, dark energy, and dark matter, eventually lead to the current model of cosmology, Lambda-CDM.
=== Special relativity and the "center" ===
The concept of an absolute velocity, including being "at rest" as a particular case, is ruled out by the principle of relativity, also eliminating any obvious "center" of the universe as a natural origin of coordinates. Even if the discussion is limited to the Solar System, the Sun is not at the geometric center of any planet's orbit, but rather approximately at one focus of the elliptical orbit. Furthermore, to the extent that a planet's mass cannot be neglected in comparison to the Sun's mass, the center of gravity of the Solar System is displaced slightly away from the center of the Sun. (The masses of the planets, mostly Jupiter, amount to 0.14% of that of the Sun.) Therefore, a hypothetical astronomer on an extrasolar planet would observe a small "wobble" in the Sun's motion.
=== Modern use of geocentric and heliocentric ===
In modern calculations, the terms "geocentric" and "heliocentric" are often used to refer to reference frames. In such systems the origin in the center of mass of the Earth, of the Earth–Moon system, of the Sun, of the Sun plus the major planets, or of the entire Solar System, can be selected. Right ascension and declination are examples of geocentric coordinates, used in Earth-based observations, while the heliocentric latitude and longitude are used for orbital calculations. This leads to such terms as "heliocentric velocity" and "heliocentric angular momentum". In this heliocentric picture, any planet of the Solar System can be used as a source of mechanical energy because it moves relatively to the Sun. A smaller body (either artificial or natural) may gain heliocentric velocity due to gravity assist – this effect can change the body's mechanical energy in heliocentric reference frame (although it will not changed in the planetary one). However, such selection of "geocentric" or "heliocentric" frames is merely a matter of computation. It does not have philosophical implications and does not constitute a distinct physical or scientific model. From the point of view of general relativity, inertial reference frames do not exist at all, and any practical reference frame is only an approximation to the actual space-time, which can have higher or lower precision. Some forms of Mach's principle consider the frame at rest with respect to the distant masses in the universe to have special properties.
== See also ==
Copernican principle
Copernican Revolution (metaphor)
== Notes ==
== References ==
=== Citations ===
=== Sources ===
== External links ==
"Does Heliocentrism Mean That the Sun is Stationary?". Scienceray. Archived from the original on August 16, 2013. Retrieved November 27, 2018.
The Heliocentric Pantheon: An Interview with Walter Murch
The Heliocentric Model and Kepler's Laws of Planetary Motion on YouTube - The development of the Heliocentric model with the contributions of Nicolaus Copernicus, Giordano Bruno, Tycho Brahe, Galileo Galilei and Johannes Kepler | Wikipedia/Heliocentric_model |
The Commonwealth Scientific and Industrial Research Organisation (CSIRO) is an Australian Government agency that is responsible for scientific research and its commercial and industrial applications.
CSIRO works with leading organisations around the world. From its headquarters in Canberra, CSIRO maintains more than 50 sites across Australia as well as in France and the United States, employing over 6,500 people.
Federally funded scientific research in Australia began in 1916 with the creation of the Advisory Council of Science and Industry. However, the council struggled due to insufficient funding. In 1926, research efforts were revitalised with the establishment of the Council for Scientific and Industrial Research (CSIR), which strengthened national science leadership and increased research funding. CSIR grew rapidly, achieving significant early successes. In 1949, legislative changes led to the renaming of the organisation as Commonwealth Scientific and Industrial Research Organisation (CSIRO).
Notable developments by CSIRO have included the invention of atomic absorption spectroscopy, essential components of the early Wi-Fi technology, development of the first commercially successful polymer banknote, the invention of the insect repellent Aerogard and the introduction of a series of biological controls into Australia, such as the introduction of myxomatosis and rabbit calicivirus for the control of rabbit populations.
== Structure ==
CSIRO is governed by a board appointed by the Australian Government, currently chaired by Ming Long AM. There are eight directors inclusive of the chief executive, presently Doug Hilton, who are responsible for management of the organisation.
== Research and focus areas ==
CSIRO is structured into Research Business Units, National Facilities and Collections, and Services.
=== Research Business Units ===
As at 2023, CSIRO's research areas are identified as "Impact science" and organised into the following Business Units:
Agriculture and Food
Health and Biosecurity
Data61
Energy
Manufacturing
Mineral Resources
Space and Astronomy
Environment (being the amalgamation of the former Land and Water and Oceans & Atmosphere BUs)
=== National facilities and collections ===
==== National facilities ====
CSIRO manages national research facilities and scientific infrastructure on behalf of the nation to assist with the delivery of research. The national facilities and specialised laboratories are available to both international and Australian users from industry and research. As at 2019, the following National Facilities are listed:
Australian Centre for Disease Preparedness (ACDP)
Australia Telescope National Facility – radio telescopes included in the Facility include the Australia Telescope Compact Array, the Parkes Observatory, Mopra Observatory and the Australian Square Kilometre Array Pathfinder
Canberra Deep Space Communication Complex
Energy Centre and National Solar Energy Centre
Marine National Facility (R.V. "Investigator")
New Norcia ground station
NovaSAR-1 satellite
Pawsey Supercomputing Centre
==== Collections ====
CSIRO manages a number of collections of animal and plant specimens that contribute to national and international biological knowledge. The National Collections contribute to taxonomic, genetic, agricultural and ecological research. As at 2019, CSIRO's Collections are listed as the following:
Australian National Algae Culture Collection
The Atlas of Living Australia
Australian Tree Seed Centre
Australian National Fish Collection
Australian National Insect Collection
Australian National Herbarium
Australian National Soil Archive (managed through A&F)
Australian National Wildlife Collection
Cape Grim Air Archive
=== Services ===
In 2019, CSIRO Services are itemised as follows:
Materials and infrastructure services
Agricultural and environmental analysis
Environmental services
Biological, food and medical science services
Australian Animal Health Laboratory services
Other services are noted as including education, publishing, infrastructure technologies, Small and Medium Enterprise engagement and CSIRO Futures.
== History ==
=== Evolution of the organisation ===
A precursor to CSIRO, the Advisory Council of Science and Industry, was established in 1916 on the initiative of prime minister Billy Hughes. However, the advisory council struggled with insufficient funding during the First World War. In 1920 the council was renamed the Commonwealth Institute of Science and Industry, and was led by George Handley Knibbs (1921–26), but continued to struggle financially.
Implementing the 1923 Imperial Conference's call for colonies to broaden their economic base, in 1926 the Australian Parliament modified the principal Act (the Institute of Science and Industry Act 1920) for national scientific research by passing the Science and Industry Research Act 1926. The same conference led to the creation of the Department of Scientific and Industrial Research in New Zealand.
The new Act replaced the institute with the Council for Scientific and Industrial Research (CSIR). With encouragement from prime minister Stanley Bruce, strengthened national science leadership and increased research funding, CSIR grew rapidly and achieved significant early successes. The council was structured to represent the federal structure of government in Australia, and had state-level committees and a central council. In addition to an improved structure, CSIR benefited from strong bureaucratic management under George Julius, David Rivett, and Arnold Richardson. Research focused on primary and secondary industries. Early in its existence, CSIR established divisions studying animal health and animal nutrition. After the Great Depression, research was extended into manufacturing and other secondary industries.
In 1949 the Act was changed again, and the entity name amended to the Commonwealth Scientific and Industrial Research Organisation. The amendment enlarged and reconstituted the organisation and its administrative structure. Under Ian Clunies Ross as chairman, CSIRO pursued new areas such as radio astronomy and industrial chemistry. CSIRO still operates under the provisions of the 1949 Act in a wide range of scientific inquiry.
Participation by women in CSIRO research was severely limited by the Australian government policy, in place until 1966, forcing women public servants out of their jobs when they married. Even unmarried women were considered a poor investment because they might eventually marry. Single women such as Helen Newton Turner nevertheless made major contributions.
Since 1949, CSIRO has expanded its activities to almost every field of primary, secondary and tertiary industry, including the environment, human nutrition, conservation, urban and rural planning, and water. It works with leading organisations around the world and maintains more than 50 sites across Australia and in France, Chile and the United States of America, employing about 5500 people.
In 2016 CSIRO launched its "Innovation Catalyst" Strategy which focused on solving Australia's Innovation Dilemma, it generated $10,000,000,000 more social, economic, and environmental value than any prior strategy, and trained 3,500 researchers from across 32 Universities on the process of innovation, and became the first Australian entity of any kind to reach the Thomson Reuters Global Top 25 Innovators.
In March 2025, research from Pollster DemosAU identified the CSIRO as Australia's second most trusted national institution, behind the Bureau of Meteorology.
=== Achievements ===
National Research "Flagships" launched in 2003, expanded 2007 to $250,000,000 in research funding
Sues Global Chip makers over WiFi Patent infringement 2005, wins $205,000,000 in 2009, and $105,000,000 by 2016
Dr Cathy Foley becomes CSIRO's first Chief Scientist in 2018, then Australia's Chief Scientist in 2021
CSIRO becomes first Australian entity to reach the Thomson Reuters Global Top 25 Innovators, beating NASA in 2018
Health Business Unit is created in 2016, enables scale up and, in partnership with CSL, mass production of Australia's only COVID vaccine in 2020, and invests $450,000,000 to create Australian Center for Disease Preparedness
CSIRO makes first acquisition, NICTA creating Australia's largest Digital and AI group
"ON" becomes Australia's first National Science Accelerator, training 3,500 university researchers across 33 institutions, and beating the prestigious US iCorps program by 2018, with 300% higher financial outcomes, diversity, and innovation ecosystem penetration
Female leadership doubles by 2020, bringing CSIRO into the Sage "green" zone for gender equity for first time in 100y
CSIRO marches in Sydney Gay & Lesbian Mardi Gras for first time, CEO joins
Main Sequence Ventures is created in 2017 as first Venture Capital fund inside government, becomes $1,000,000,000 top-quartile global fund
By 2023 "Innovation Catalyst" strategy creates $10,000,000,000 more value than any prior strategy, and $400,000,000 per year greater investment in science
CSIRO wins Roy Morgan Most Trusted Brand for first time in 2022
CSIRO achieves first emissions reduction in 100y, reaching 83% of Net Zero by 2022
=== Inventions ===
Notable inventions and breakthroughs by CSIRO include:
A4 DSP chip
Aerogard, insect repellent
Atomic absorption spectroscopy
Biological control of Salvinia
Development of Linola (a flax variety with low alpha-linolenic acid content) with a longer life used as a stockfeed
Distance measuring equipment (DME) used for aviation navigation
Gene shears
Interscan Microwave landing system, a microwave approach and landing system for aircraft
Use of myxomatosis and calicivirus to control rabbit numbers
Parkes Radio Telescope
The permanent pleat for fabrics
Plasma sintering
Polymer banknote
Production of metals from their halides
Relenza flu drug
Sirosmelt lance
"Softly" woollens detergent
Phase-contrast X-ray imaging
Method to use titanium in 3D printing
UltraBattery
Essential components of Wi-Fi technology
Zebedee - Mobile Handheld 3D Lidar Mapping technology
=== Historic research ===
CSIRO had a pioneering role in the scientific discovery of the universe through radio "eyes". A team led by Paul Wild built and operated (from 1948) the world's first solar radiospectrograph, and from 1967 the 3-kilometre-diameter (1.9 mi) radioheliograph at Culgoora in New South Wales. For three decades, the Division of Radiophysics had a world-leading role in solar research, attracting prominent solar physicists from around the world.
CSIRO owned the first computer in Australia, CSIRAC, built as part of a project began in the Sydney Radiophysics Laboratory in 1947. The CSIR Mk 1 ran its first program in 1949, the fifth electronic computer in the world. It was over 1,000 times faster than the mechanical calculators available at the time. It was decommissioned in 1955 and recommissioned in Melbourne as CSIRAC in 1956 as a general purpose computing machine used by over 700 projects until 1964. The CSIRAC is the only surviving first-generation computer in the world.
Between 1965 and 1985, George Bornemissza of CSIRO's Division of Entomology founded and led the Australian Dung Beetle Project. Bornemissza, upon settling in Australia from Hungary in 1951, noticed that the pastureland was covered in dry cattle dung pads which did not seem to be recycled into the soil and caused areas of rank pasture which were unpalatable to the cattle. He proposed that the reason for this was that native Australian dung beetles, which had co-evolved alongside the marsupials (which produce dung very different in its composition from cattle), were not adapted to utilise cattle dung for their nutrition and breeding since cattle had only relatively recently been introduced to the continent in the 1880s. The Australian Dung Beetle Project sought, therefore, to introduce species of dung beetle from South Africa and Europe (which had co-evolved alongside bovids) in order to improve the fertility and quality of cattle pastures. Twenty-three species were successfully introduced throughout the duration of the project and also had the effect of reducing the pestilent bush fly population by 90%.
=== Domain name ===
CSIRO was the first Australian organisation to start using the Internet and was able to register the second-level domain csiro.au (as opposed to csiro.org.au or csiro.com.au). Guidelines were introduced in 1996 to regulate the use of the .au domain.
== Governance and management ==
When CSIR was formed in 1926, it was led initially by an executive committee of three people, two of whom were designated as the chairman and the chief executive. Since then the roles and responsibilities of the chair and chief executive have changed many times. From 1927 to 1986 the head of CSIR (and from 1949, CSIRO) was the chairman, who was responsible for the management of the organisation, supported by the chief executive. From 1 July 1959 to 4 December 1986 CSIRO had no chief executive; the chairman undertook both functions.
In 1986, when the Australian Government changed the structure of CSIRO to include a board of non-executive members plus the chief executive to lead CSIRO, the roles changed. The chief executive is now responsible for management of the organisation in accordance with the strategy, plans and policies approved by the CSIRO Board which, led by the chair of the board, is responsible to the Australian Government for the overall strategy, governance and performance of CSIRO.
As with its governance structure, the priorities and structure of CSIRO, and the teams and facilities that implement its research, have changed as Australia's scientific challenges have evolved.
Numerous CSIRO scientists have gone onto distinguished careers in the university sector. Several have been appointed to the role of Vice-Chancellor/President. They include: Sir George Currie (UNZ 1952–62, Western Australia 1945–52), Paul Wellings CBE (Wollongong 2012–21, Lancaster 2002–12), Michael Barber AO (Flinders 2008–14), Mark Smith CBE (Southampton 2019–ff, Lancaster 2012–19), Annabelle Duncan (UNE 2014–19), Attila Brungs (UNSW 2021–ff, UTS 2014–21), Alex Zelinsky AO (Newcastle (2018–ff), Andrew Parfitt (UTS 2021–ff), Chris Moran (UNE 2023–ff).
=== Chairs ===
=== Chief executives ===
== Controversies ==
=== Total Wellbeing Diet ===
In 2005 the CSIRO gained worldwide attention, including some criticism, for promoting a high-protein, low-carbohydrate diet of their own creation called Total Wellbeing Diet. The CSIRO published the diet in a book which sold over half a million copies in Australia and over 100,000 overseas. The diet was criticised in an editorial by Nature for giving scientific credence to a "fashionable" diet sponsored by meat and dairy industries.
=== 802.11 patent ===
In the early 1990s, CSIRO radio astronomy scientists John O'Sullivan, Graham Daniels, Terence Percival, Diethelm Ostry and John Deane undertook research directed to finding a way to make wireless networks work as fast as wired networks within confined spaces such as office buildings. The technique they developed, involving a particular combination of forward error correction, frequency-domain interleaving, and multi-carrier modulation, became the subject of U.S. patent 5,487,069, which was granted on 23 January 1996.
In 1997 Macquarie University professor David Skellern and his colleague Neil Weste established the company Radiata, Inc., which took a nonexclusive licence to the CSIRO patent for the purpose of developing commercially viable integrated circuit devices implementing the patented technology.
During this period, the IEEE 802.11 Working Group was developing the 802.11a wireless LAN standard. CSIRO did not participate directly in the standards process, however David Skellern was an active participant as secretary of the Working Group, and representative of Radiata. In 1998 it became apparent that the CSIRO patent would be pertinent to the standard. In response to a request from Victor Hayes of Lucent Technologies, who was chair of the 802.11 Working Group, CSIRO confirmed its commitment to make non-exclusive licenses available to implementers of the standard on reasonable and non-discriminatory terms.
In 1999, Cisco Systems, Inc. and Broadcom Corporation each invested A$4 million in Radiata, representing an 11% stake for each investor and valuing the company at around A$36 million. In September 2000, Radiata demonstrated a chip set complying with the recently finalised IEEE 802.11a Wi-Fi standard, and capable of handling transmission rates of up to 54 Mbit/s, at a major international exhibition.
In November 2000, Cisco acquired Radiata in exchange for US$295 million in Cisco common stock with the intention of incorporating the Radiata Baseband Processor and Radio chips into its Aironet family of wireless LAN products. Cisco subsequently took a large write-down on the Radiata acquisition, following the 2001 telecoms crash, and in 2004 it shut down its internal development of wireless chipsets based on the Radiata technology in order to focus on software development and emerging new technologies.
Controversy over the CSIRO patent arose in 2006 after the organisation won an injunction against Buffalo Technology in an infringement suit filed in Federal Court in the Eastern District of Texas. The injunction was subsequently suspended on appeal, with the Court of Appeals for the Federal Circuit finding that the judge in Texas should have allowed a trial to proceed on Buffalo's challenge to the validity of the CSIRO patent. In 2007, CSIRO declined to provide an assurance to the IEEE that it would not sue companies which refused to take a license for use in 802.11n-compliant devices, while at the same time continuing to defend legal challenges to the validity of the patent brought by Intel, Dell, Microsoft, Hewlett-Packard and Netgear.
In April 2009, Hewlett-Packard broke ranks with the rest of the industry becoming the first to reach a settlement of its dispute with CSIRO. This agreement was followed quickly by settlements with Microsoft, Fujitsu and Asus and then Dell, Intel, Nintendo, Toshiba, Netgear, Buffalo, D-Link, Belkin, SMC, Accton, and 3Com.
The controversy grew after CSIRO sued US carriers AT&T, Verizon and T-Mobile in 2010, with the organisation being accused of being "Australia's biggest patent troll", a wrathful "patent bully", and of imposing a "WiFi tax" on American innovation.
Further fuel was added to the controversy after a settlement with the carriers, worth around $229 million, was announced in March 2012. Encouraged in part by an announcement by the Australian Minister for Tertiary Education, Skills Science and Research, Senator Chris Evans, an article in Ars Technica portrayed CSIRO as a shadowy organisation responsible for US consumers being compelled to make "a multimillion dollar donation" on the basis of a questionable patent claiming "decades old" technology. The resulting debate became so heated that the author was compelled to follow up with a defence of the original article. An alternative view was also published on The Register, challenging a number of the assertions made in the Ars Technica piece.
Total income to CSIRO from the patent is currently estimated at nearly $430 million. On 14 June 2012, the CSIRO inventors received the European Patent Office (EPO) European Inventor Award (EIA), in the category of "Non-European Countries".
=== Genetically modified wheat trials ===
On 14 July 2011, Greenpeace activists vandalised a crop of GM wheat, circumventing the scientific trials being undertaken. Greenpeace was forced to pay reparations to CSIRO of $280,000 for the criminal damage, and were accused by the sentencing judge, Justice Hilary Penfold, of cynically using junior members of the organisation with good standing to avoid custodial sentences, while the offenders were given 9-month suspended sentences.
Following the attack Greenpeace criticised CSIRO for a close relationship with industry that had led to an increase in genetically modified crops, even though a core aim of CSIRO is Cooperative Research "working hand in hand with industry [to] build partnerships and engage with industry to generate impact".
=== Climate change censorship: Clive Spash ===
On 25 November 2009, a debate was held in the Australian Senate concerning the alleged involvement of the CSIRO and the Labor government in censorship. The debate was called for by opposition parties after evidence came to light that a paper critical of carbon emissions trading was being suppressed. At the time, the Labor government was trying to get such a scheme through the Senate. After the debate, the Science Minister, Kim Carr, was forced to release the paper, but when doing so in the Senate he also delivered a letter from the CEO of the CSIRO, Megan Clark, which attacked the report's author and threatened him with unspecified punishment. The author of the paper, Clive Spash, was cited in the press as having been bullied and harassed, and later gave a radio interview about this. In the midst of the affair, CSIRO management had considered releasing the paper with edits that Nature reported would be "tiny". Spash claimed the changes actually demanded amounted to censorship and resigned. He later posted on his website a document detailing the text that CSIRO management demanded be deleted; by itself, this document forms a coherent set of statements criticising emissions trading without any additional wording needed. In subsequent Senate Estimates hearings during 2010, Senator Carr and Clark went on record claiming the paper was originally stopped from publication solely due to its low quality not meeting CSIRO standards. At the time of its attempted suppression, the paper had been accepted for publication in an academic journal, New Political Economy, which in 2010 had been ranked by the Australian Research Council as an 'A class' publication. In an ABC radio interview, Spash called for a Senate enquiry into the affair and the role played by senior management and the Science Minister. After these events, the Sydney Morning Herald reported that "Questions are being raised about the closeness of BHP Billiton and the CSIRO under its chief executive, Megan Clark". After his resignation, an unedited version of the paper was released by Spash as a discussion paper, and later published as an academic journal article.
=== CSIRO–Novartis–DataTrace scandal ===
On 11 April 2013, the Sydney Morning Herald ran a story on how CSIRO had "duped" the Swiss-based pharmaceutical giant Novartis into purchasing an anti-counterfeit technology for its vials of injectable Voltaren. The invention was marketed by a small Australian company called DataTrace DNA as a method of identifying fake vials, on the basis that a unique tracer code developed by CSIRO was embedded in the product. However, the code sold to Novartis for more than A$2M was apparently not unique, and was based on a "cheap tracer ... bought in bulk from a Chinese distributor". Novartis was contractually bound not to reverse-engineer the tracer to verify its uniqueness. The Sydney Morning Herald report alleges that this was done with the knowledge of key CSIRO personnel.
CSIRO has since conducted a full review of the allegations and found no evidence to support them.
=== Alleged bullying, harassment and victimisation ===
Around 2008–2012, CSIRO fell under the spotlight for allegedly exhibiting a culture of workplace bullying and harassment. Former CSIRO employees started to surface with experiences of workplace bullying and other unreasonable behaviour by current and former CSIRO staff members. CSIRO took the allegations seriously and responded to the articles on a number of occasions.
The shadow minister for innovation, industry, science and research, Sophie Mirabella, wrote to the government requesting it establish an inquiry. Mirabella said she is aware of as many as 100 cases of alleged workplace harassment. On 20 July 2012 Comcare issued CSIRO with an Improvement Notice with regard to handling and management of workplace misconduct/code of conduct type investigations and allegations. On 24 June 2013 Mirabella advised the Australian House of Representatives that in relation to the worker's compensation claim for psychological injuries of ex-CSIRO employee, Martin Williams, which was vigorously defended by Comcare on the advice of the CSIRO, that CSIRO officers had provided false testimony on no less than 128 occasions under oath when the matter went before the Administrative Appeals Tribunal. Mirabella stated, "even in establishing the framework for this inquiry it is obvious there's an inappropriate 'hands on' approach by CSIRO."
In response to the allegations Clark commissioned Dennis Pearce, who is assisted by an investigation team from HWL Ebsworth Lawyers, to conduct an independent investigation into allegations of workplace bullying and other unreasonable behaviour. Mirabella continued to question the independence of the investigation. The first stage of the investigation published its findings at the end of July 2013, and the final stage was scheduled to be complete by February 2014. Post the Pearce Report, CSIRO overhauled its relevant policies and put in place training and whistleblower procedures to address the situation.
=== CSIRO and climate change ===
In 2013, the Abbott government cuts $25,000,000 from CSIRO's annual budget, and in 2014 CEO Megan Clarke makes "almost a quarter of CSIRO's scientists redundant"
In 2014, Minister Greg Hunt created NESP, diverting $21,000,000 per year of CSIRO climate funding to competitive Universities
In 2015, Dr Larry Marshall becomes CEO and shifts CSIRO's purpose to solving national challenges with science, launches “Innovation Catalyst Strategy”
In August 2015, the CSIRO discontinued its annual July and August survey, conducted over the previous five years, polling to create a long-term view of how Australians viewed global warming and their support for action. In the previous 2013 poll, 86 per cent agreed with the statement that climate change was occurring and only 7.6 per cent disagreed.
In 2016, Funding cuts of 2014 force 70 redundancies in climate science, Marshall says the argument about climate change is settled so its time to find a solution, compares emotion of debate to religion.
In "an open letter to the Australian Government and CSIRO", 2,800 of the leading climate scientists from 60 countries say the announcement of cuts to the CSIRO's Oceans and Atmosphere research program has alarmed the global climate research community. They say the decision shows a lack of insight and a misunderstanding of the importance of the depth and significance of Australian contributions to global and regional climate research.
Climate lobby, Greens & Labor launch intense political campaign against Marshall – terminating the “failed Marshall plan” and “reversing the cuts and "sacking Marshall" become a focus of Labor's 2016 election campaign.
Labor loses election, value of CSIRO doubles, Marshall becomes longest serving CEO in CSIRO's history.
In 2018, CSIRO creates 1st Net Zero plan for Australia, and demonstrates it by taking all 55 sites across Australia 80% of way to net zero, and doubling value of CSIRO at same time.
The CSIRO has been the target of successive funding cuts under the Morrison government, starting with cuts targeting climate science research initiated by Tony Abbott.
=== Trademark dispute with Cisco ===
In 2015, Cisco Systems filed a trademark infringement lawsuit against CSIRO, claiming that the colours and style of CSIRO's logo were too similar to Cisco's. An Australian court ruled in CSIRO's favor and ordered Cisco to pay CSIRO's court costs.
== See also ==
Australia Telescope National Facility
Australian Animal Health Laboratory
Australian Bird and Bat Banding Scheme
Australian Dung Beetle Project
Australian Space Research Institute
Backing Australia's Ability
Biosecurity in Australia
Cooperative Research Centres
Council for Scientific and Industrial Research – Ghana
Council of Scientific and Industrial Research, India
Council for Scientific and Industrial Research, South Africa
CSIRO Oceans and Atmosphere
CSIRO Publishing
Defence Science and Technology Group
Fraunhofer Society, Germany
George Bornemissza
Goyder Institute for Water Research, a research collaboration with universities and SA government
Parkes Observatory
Peter Rathjen
SINTEF, Norway
Susan Wijffels
Netherlands Organisation for Applied Scientific Research
Waste management in Australia
Yingjie Jay Guo
== Notes ==
== References ==
== External links ==
Official website
CSIRO US website
CSIROpedia Official CSIRO history site
Commonwealth of Australia. Commonwealth Scientific and Industrial Research Organisation (CSIRO). (1949–) National Library of Australia, Trove, People and Organisation record for CSIRO
Commonwealth of Australia. Council for Scientific and Industrial Research (CSIR). (1926–1949) National Library of Australia, Trove, People and Organisation record for CSIR
Australian e-Health Research Centre (AeHRC)
Centre for Liveability Real Estate
Issues
"United States Appellate Court Rules in Buffalo's Favor in Ongoing U.S. Patent Litigation". Buffalo Tech. 24 September 2008. Archived from the original on 12 October 2008. Wi-Fi technology relating to the transmission of wireless signals
"Victims of Bullying, Harassment, and Victimisation in the CSIRO". 2011. | Wikipedia/Commonwealth_Scientific_and_Industrial_Research_Organisation |
Junk science is spurious or fraudulent scientific data, research, or analysis. The concept is often invoked in political and legal contexts where facts and scientific results have a great amount of weight in making a determination. It usually conveys a pejorative connotation that the research has been untowardly driven by political, ideological, financial, or otherwise unscientific motives.
The concept was popularized in the 1990s in relation to expert testimony in civil litigation. More recently, invoking the concept has been a tactic to criticize research on the harmful environmental or public health effects of corporate activities, and occasionally in response to such criticism.
In some contexts, junk science is counterposed to the "sound science" or "solid science" that favors one's own point of view. Junk science has been criticized for undermining public trust in real science.: 110–111 Junk science is not the same as pseudoscience.
== Definition ==
Junk science has been defined as:
"science done to establish a preconceived notion—not to test the notion, which is what proper science tries to do, but to establish it regardless of whether or not it would hold up to real testing."
"opinion posing as empirical evidence, or through evidence of questionable warrant, based on inadequate scientific methodology."
"methodologically sloppy research conducted to advance some extrascientific agenda or to prevail in litigation."
== Motivations ==
Junk science happens for different reasons: researchers believing that their ideas are correct before proper analysis (a sort of scientific self-delusion or drinking the Kool-Aid), researchers biased with their study designs, and/or a "plain old lack of ethics". Being overly attached to one's own ideas can cause research to veer from ordinary junk science (e.g., designing an experiment that is expected to produce the desired results) into scientific fraud (e.g., lying about the results) and pseudoscience (e.g., claiming that the unfavorable results actually proved the idea correct).
Junk science can occur when the perpetrator has something to gain from arriving at the desired conclusion. It can often happen in the testimony of expert witnesses in legal proceedings, and especially in the self-serving advertising of products and services. These situations may encourage researchers to make sweeping or overstated claims based on limited evidence.
== History ==
The phrase junk science appears to have been in use prior to 1985. A 1985 United States Department of Justice report by the Tort Policy Working Group noted:
The use of such invalid scientific evidence (commonly referred to as 'junk science') has resulted in findings of causation which simply cannot be justified or understood from the standpoint of the current state of credible scientific or medical knowledge.
In 1989, the climate scientist Jerry Mahlman (Director of the Geophysical Fluid Dynamics Laboratory) characterized the theory that global warming was due to solar variation (presented in Scientific Perspectives on the Greenhouse Problem by Frederick Seitz et al.) as "noisy junk science."
Peter W. Huber popularized the term with respect to litigation in his 1991 book Galileo's Revenge: Junk Science in the Courtroom. The book has been cited in over 100 legal textbooks and references; as a consequence, some sources cite Huber as the first to coin the term. By 1997, the term had entered the legal lexicon as seen in an opinion by Supreme Court of the United States Justice John Paul Stevens:
An example of 'junk science' that should be excluded under the Daubert standard as too unreliable would be the testimony of a phrenologist who would purport to prove a defendant's future dangerousness based on the contours of the defendant's skull. Lower courts have subsequently set guidelines for identifying junk science, such as the 2005 opinion of United States Court of Appeals for the Seventh Circuit Judge Frank H. Easterbrook:
Positive reports about magnetic water treatment are not replicable; this plus the lack of a physical explanation for any effects are hallmarks of junk science.
As the subtitle of Huber's book, Junk Science in the Courtroom, suggests, his emphasis was on the use or misuse of expert testimony in civil litigation. One prominent example cited in the book was litigation over casual contact in the spread of AIDS. A California school district sought to prevent a young boy with AIDS, Ryan Thomas, from attending kindergarten. The school district produced an expert witness, Steven Armentrout, who testified that a possibility existed that AIDS could be transmitted to schoolmates through yet undiscovered "vectors". However, five experts testified on behalf of Thomas that AIDS is not transmitted through casual contact, and the court affirmed the "solid science" (as Huber called it) and rejected Armentrout's argument.
In 1999, Paul Ehrlich and others advocated public policies to improve the dissemination of valid environmental scientific knowledge and discourage junk science:
The Intergovernmental Panel on Climate Change reports offer an antidote to junk science by articulating the current consensus on the prospects for climate change, by outlining the extent of the uncertainties, and by describing the potential benefits and costs of policies to address climate change.
In a 2003 study about changes in environmental activism regarding the Crown of the Continent Ecosystem, Pedynowski noted that junk science can undermine the credibility of science over a much broader scale because misrepresentation by special interests casts doubt on more defensible claims and undermines the credibility of all research.
In his 2006 book Junk Science, Dan Agin emphasized two main causes of junk science: fraud, and ignorance. In the first case, Agin discussed falsified results in the development of organic transistors:
As far as understanding junk science is concerned, the important aspect is that both Bell Laboratories and the international physics community were fooled until someone noticed that noise records published by Jan Hendrik Schön in several papers were identical—which means physically impossible.
In the second case, he cites an example that demonstrates ignorance of statistical principles in the lay press:
Since no such proof is possible [that genetically modified food is harmless], the article in The New York Times was what is called a "bad rap" against the U.S. Department of Agriculture—a bad rap based on a junk-science belief that it's possible to prove a null hypothesis.
Agin asks the reader to step back from the rhetoric, as "how things are labeled does not make a science junk science." In its place, he offers that junk science is ultimately motivated by the desire to hide undesirable truths from the public.
The rise of open source (free to read) journals has resulted in economic pressure on academic publishers to publish junk science. Even when the journal is peer-reviewed, the authors, rather than the readers, become the customer and the source of funding for the journal, so the publisher is incentivized to publish as many papers as possible, including those that are methodologically unsound.
== Misuse in public relations ==
John Stauber and Sheldon Rampton of PR Watch say the concept of junk science has come to be invoked in attempts to dismiss scientific findings that stand in the way of short-term corporate profits. In their book Trust Us, We're Experts (2001), they write that industries have launched multimillion-dollar campaigns to position certain theories as junk science in the popular mind, often failing to employ the scientific method themselves. For example, the tobacco industry has described research demonstrating the harmful effects of smoking and second-hand smoke as junk science, through the vehicle of various astroturf groups.
Theories more favorable to corporate activities are portrayed in words as "sound science". Past examples where "sound science" was used include the research into the toxicity of Alar, which was heavily criticized by antiregulatory advocates, and Herbert Needleman's research into low dose lead poisoning. Needleman was accused of fraud and personally attacked.
Fox News commentator Steven Milloy often denigrates credible scientific research on topics like global warming, ozone depletion, and passive smoking as "junk science". The credibility of Milloy's website junkscience.com was questioned by Paul D. Thacker, a writer for The New Republic, in the wake of evidence that Milloy had received funding from Philip Morris, RJR Tobacco, and ExxonMobil. Thacker also noted that Milloy was receiving almost $100,000 a year in consulting fees from Philip Morris while he criticized the evidence regarding the hazards of second-hand smoke as junk science. Following the publication of this article, the Cato Institute, which had hosted the junkscience.com site, ceased its association with the site and removed Milloy from its list of adjunct scholars.
Tobacco industry documents reveal that Philip Morris executives conceived of the "Whitecoat Project" in the 1980s as a response to emerging scientific data on the harmfulness of second-hand smoke. The goal of the Whitecoat Project, as conceived by Philip Morris and other tobacco companies, was to use ostensibly independent "scientific consultants" to spread doubt in the public mind about scientific data through invoking concepts like junk science. According to epidemiologist David Michaels, Assistant Secretary of Energy for Environment, Safety, and Health in the Clinton Administration, the tobacco industry invented the "sound science" movement in the 1980s as part of their campaign against the regulation of second-hand smoke.
David Michaels has argued that, since the U.S. Supreme Court ruling in Daubert v. Merrell Dow Pharmaceuticals, Inc., lay judges have become "gatekeepers" of scientific testimony and, as a result, respected scientists have sometimes been unable to provide testimony so that corporate defendants are "increasingly emboldened" to accuse adversaries of practicing junk science.
== Notable cases ==
American psychologist Paul Cameron has been designated by the Southern Poverty Law Center (SPLC) as an anti-gay extremist and a purveyor of "junk science". Cameron's research has been heavily criticized for unscientific methods and distortions which attempt to link homosexuality with pedophilia. In one instance, Cameron claimed that lesbians are 300 times more likely to get into car accidents. The SPLC states his work has been continually cited in some sections of the media despite being discredited. Cameron was expelled from the American Psychological Association in 1983.
== Combatting junk science ==
In 1995, the Union of Concerned Scientists launched the Sound Science Initiative, a national network of scientists committed to debunking junk science through media outreach, lobbying, and developing joint strategies to participate in town meetings or public hearings. In its newsletter on Science and Technology in Congress, the American Association for the Advancement of Science also recognized the need for increased understanding between scientists and lawmakers: "Although most individuals would agree that sound science is preferable to junk science, fewer recognize what makes a scientific study 'good' or 'bad'." The American Dietetic Association, criticizing marketing claims made for food products, has created a list of "Ten Red Flags of Junk Science".
== See also ==
== References ==
== Further reading ==
Agin, Dan (2006). Junk Science – How Politicians, Corporations, and Other Hucksters Betray Us. St. Martin's Griffin. ISBN 978-0312374808. Archived from the original on 2023-11-04. Retrieved 2016-10-18.
Huber, Peter W. (1993). Galileo's Revenge: Junk Science in the Courtroom. Basic Books. ISBN 978-0465026241.
Mooney, Chris (2005). The Republican War on Science. Basic Books. ISBN 978-0465046751.
Kiss Sarnoff, Susan (2001). Sanctified Snake Oil: The Effect of Junk Science on Public Policy. Bloomsbury Academic. ISBN 978-0275968458.
== External links ==
Project on Scientific Knowledge and Public Policy(SKAPP) DefendingScience.org
Michaels, David (June 2005). "Doubt is Their Product". Scientific American. 292 (6): 96–101. Bibcode:2005SciAm.292f..96M. doi:10.1038/scientificamerican0605-96. PMID 15934658. Archived from the original on 2007-09-27. Retrieved 2008-06-03.
Baba, Annamaria; Cook, Daniel M.; McGarity, Thomas O.; Bero, Lisa A. (July 2005). "Legislating 'Sound Science': The Role of the Tobacco Industry". American Journal of Public Health. 95 (1): 20–27. doi:10.2105/AJPH.2004.050963. hdl:10.2105/AJPH.2004.050963. PMID 16030333. Archived from the original on 2008-05-10. Retrieved 2008-06-03.
Michaels, David; Monforton, Celeste (July 2005). "Manufacturing Uncertainty: Contested Science and the Protection of the Public's Health & Environment". American Journal of Public Health. 95 (1): 39–48. CiteSeerX 10.1.1.620.6171. doi:10.2105/AJPH.2004.043059. PMID 16030337. Archived from the original on 2008-05-10. Retrieved 2008-06-03.
Yach, Derek; Aguinaga Bialous, Stella (November 2001). "Junking Science to Promote Tobacco". American Journal of Public Health. 91 (11): 1745–1748. doi:10.2105/ajph.91.11.1745. PMC 1446867. PMID 11684592.
Thacker, Paul D. (May 11, 2005). "The Junkman Climbs to the Top". Environmental Science & Technology. Archived from the original on June 20, 2005. Retrieved August 7, 2017.
Baloney Detection Kit on YouTube (10 questions we should ask when encountering a pseudoscience claim) | Wikipedia/Junk_science |
Public awareness of science (PAS) is everything relating to the awareness, attitudes, behaviors, opinions, and activities that comprise the relations between the general public or lay society as a whole to scientific knowledge and organization. This concept is also known as public understanding of science (PUS), or more recently, public engagement with science and technology (PEST). It is a comparatively new approach to the task of exploring the multitude of relations and linkages science, technology, and innovation have among the general public. While early work in the discipline focused on increasing or augmenting the public's knowledge of scientific topics, in line with the information deficit model of science communication, the deficit model has largely been abandoned by science communication researchers. Instead, there is an increasing emphasis on understanding how the public chooses to use scientific knowledge and on the development of interfaces to mediate between expert and lay understandings of an issue. Newer frameworks of communicating science include the dialogue and the participation models. The dialogue model aims to create spaces for conversations between scientists and non-scientists to occur while the participation model aims to include non-scientists in the process of science.
== Major themes ==
The area integrates a series of fields and themes such as:
Citizen science
Consumer education
Fixed and mobile science exhibits
Media and science (medialisation of science)
Public controversies over science and technology
Public tours of research and development (R&D) parks, manufacturing companies, etc.
Science and art
Science communication in the mass media, Internet, radio, films and television programs
Science education for adults
Science fairs in schools and social groups
Science festivals
Science in popular culture
Science in text books and classrooms
Science museums, aquaria, planetaria, zoological parks, botanical gardens, etc.
Science social movements
Important lines of research are how to raise public awareness and public understanding of science and technology. Also, learning how the public feels and knows about science generally as well as individual subjects, such as genetic engineering, or bioethics. Research by Matthew Nisbet highlights several challenges in science communication, including the paradox that scientific success can create either trust or distrust in experts in different populations and that attitudes of trust are shaped by mostly socioeconomic rather than religious or ideological differences. A 2020 survey by the Pew Research Center found varying levels of trust in science by country, political leanings, and other factors.
== Bodmer report ==
The publication of the Royal Society's' report The Public Understanding of Science (or Bodmer Report) in 1985 is widely held to be the birth of the Public Understanding of Science movement in Britain. The report led to the founding of the Committee on the Public Understanding of Science and a cultural change in the attitude of scientists to outreach activities.
== Models of engagement ==
=== Contextualist model ===
In the 1990s, a new perspective emerged in the field with the classic study of Cumbrian Sheep Farmers' interaction with the Nuclear scientists in England. Brian Wynne demonstrated how the experts were ignorant or disinterested in taking into account the lay knowledge of the sheep farmers while conducting field experiments on the impact of the Chernobyl nuclear fallout on the sheep in the region. Because of this shortcoming from the side of the scientists, local farmers lost their trust in them. The experts were unaware of the local environmental conditions and the behaviour of sheep and this has eventually led to the failure of their experimental models. Following this study, scholars have studies similar micro-sociological contexts of expert-lay interaction and proposed that the context of knowledge communication is important to understand public engagement with science. Instead of large scale public opinion surveys, researchers proposed studies informed by sociology of scientific knowledge (SSK). The contextualist model focuses on the social impediments in the bidirectional flow of scientific knowledge between experts and laypersons/communities.
=== Deliberative model ===
Scholars like Sheila Jasanoff have advanced the debate around public engagement with science by leveraging the theory of deliberative democracy to analyze the public deliberation of and participation in science through various institutional forms. Proponents of greater public deliberation argue it is a basic condition for decision making in democratic societies, even on science and technology issues. There are also attempts to develop more inclusive participatory models of technological governance in the form of consensus conferences, citizen juries, extended peer reviews, and deliberative mapping.
=== Civic science model ===
Some scholars have identified a new era of "post-normal science" (PNS) in which many scientific discoveries carry high stakes if risks are estimated incorrectly within a broader social context that has a high degree of uncertainty. This PNS era requires a new approach to public engagement efforts and requires a reevaluation of the underlying assumptions of "public engagement", especially with emerging science and technology issues, like CRISPR gene editing, that have the potential to become "wicked problems". These "wicked" issues often require regulatory and policy decisions that have no single correct solution and often involve numerous interest groups – none of whom are clearly positioned to decide and resolve the problem. Policy and regulatory decisions around these scientific issues are inherently political and must balance trade-offs between the scientific research, perceptions of risk, societal needs, and ethical values. While scientists can provide factual answers to research questions and mathematical estimates of risk, many considerations surrounding these wicked science and technology issues have no factual answer. The unidirectional deficit model of simply educating the public on theses issues is insufficient to address these complex questions, and some scholars have proposed scientists adopt a culture of civic science: "broad public engagement with issues that arise at the many intersections between science and society." An emphasis is placed on developing an iterative engagement model that actively seeks to incorporate groups who stand to be adversely effected by a new technology and conducting this engagement away from universities so that it can be done on the public's terms with the public's terms. Other scholars have emphasized that this model of public engagement requires that the public be able to influence science, not merely be engaged by it, up to the point of being able to say "no" to research that does not align with the broader public's values. Under the civic science model, there are five key lessons for scientists committed to public engagement:
Establish why you want to engage with the public and clearly identify your goals.
Seek out and engage with a broad, diverse range of groups and perspectives and center engagement on listening to these groups.
Work cooperatively with groups to establish common definitions to avoid the perception that researchers are being disingenuous by relying on semantic differences between expert and lay interpretations of vocabulary to ensure the public "supports" their position.
Working to tilt public debates in favor of the priorities and values of researchers will not lead to consistent "best" decisions because wicked science and technology problems will have different considerations and perspectives depending on the application and cultural context.
Meaningfully engage as early as possible; engagement must begin early enough in the research process that the public's views can shape both the research and implementation of findings
== Public understanding of science ==
Social scientists use various metrics to measure public understanding of science, including:
=== Factual knowledge ===
The key assumptions is that the more individual pieces of information a person is able to retrieve, the more that person is considered to have learned.
Examples of measurement:
Recognition: Answering a specific question by selecting the correct answer out a list
Cued recall: Answering a specific question without a list of choices
Free recall: After exposure to information, the study participant produces a list of as much of the information as they can remember
=== Self-reported knowledge, perceived knowledge, or perceived familiarity ===
The key assumption is that emphasizes the value of knowledge of one's knowledge.
Examples of measurement:
Scaled survey responses to questions such as, "How well informed you would say you are about this topic?", this can be also used to assess perceived knowledge before and after events
=== Structural knowledge ===
The nature of connections among different pieces of information in memory.
The key assumption is that the use of elaboration increases the likelihood of remembering information.
Examples of measurement:
Asking study participants to assess relationships among concepts. For example, participants free recall concepts onto the first row and column of a matrix, then indicate whether the concepts are related to each other by placing an "X" in the cell if they are not. Participants then rank the remaining open cells by their relatedness from 1 (only very weakly) to 7 (very strongly related).
Study participants answer questions designed to measure elaboration involved in a task, such as, "I tried to relate the ideas I read about to my own past experiences."
=== Trust and credibility ===
People may trust science or scientists to different degrees, or may find specific scientists or specific research to be more or less credible. These factors can be related to how science can be used to advance knowledge, and may also be related to how science is communicated.
Examples of measurement:
The 21-item Trust in Science and Scientists Inventory, which measures agreement/disagreement with statements like, "We can trust scientists to share their discoveries even if we don't like their findings."
Scientist-specific measures of agreement, such as "I would trust scientific information if I knew it came from this author."
=== Mixed use of measures ===
While some studies purport that factual and perceived knowledge can be viewed as the same construct, a 2012 study investigating public knowledge of nanotechnology supports separating their use in communications research, as they "do not reflect the same underlying knowledge structures". Correlations between them were found to be low and they were not predicted by the same factors. For example different types of science media use, television versus online, predicted different constructs.
Factual knowledge has been shown to be empirically distinct from structural knowledge.
== Project example ==
Government and private-led campaigns and events, such as Dana Foundation's "Brain Awareness Week", are becoming a strong focus of programmes which try to promote public awareness of science.
The UK PAWS Foundation dramatically went as far as establishing a Drama Fund with the BBC in 1994. The purpose was to encourage and support the creation of new drama for television, drawing on the world of science and technology.
The Vega Science Trust was set up in 1994 to promote science through the media of television and the internet with the aim of giving scientists a platform from which to communicate to the general public.
The Simonyi Professorship for the Public Understanding of Science chair at The University of Oxford was established in 1995 for the ethologist Richard Dawkins by an endowment from Charles Simonyi. Mathematician Marcus du Sautoy has held the chair since Dawkins' retirement in 2008. Similar professorships have since been created at other British universities. Professorships in the field have been held by well-known academics including Richard Fortey and Kathy Sykes at the University of Bristol, Brian Cox at Manchester University, Tanya Byron at Edge Hill University, Jim Al-Khalili at the University of Surrey, and Alice Roberts at the University of Birmingham.
== See also ==
== References ==
== Further reading ==
Bensaude-vincent, Bernadette (2001). "A Genealogy of the Increasing Gap between Science and the Public". Public Understanding of Science. 10 (1): 99–113. doi:10.1088/0963-6625/10/1/307.
Bijker, Wiebe E., Bal, Roland and Hendriks, Ruud. 2009. The Paradox of Scientific Authority: The Role of Scientific Advice in Democracies. Cambridge and London: The MIT Press.
Bucchi, Massimiano (1996). "When Scientists Turn to the Public: Alternative Routes in Science Communication". Public Understanding of Science. 5 (4): 375–394. doi:10.1088/0963-6625/5/4/005. S2CID 143374883.
Dash, Biswanath (2014a). "Public Understanding of Cyclone Warning in India: Can Wind be Predicted?". Public Understanding of Science. 24 (8): 970–987. doi:10.1177/0963662514553203. PMID 25313142. S2CID 22226217.
Davenport, Sally and Leitch, Shirley. 2005. "Agoras, Ancient and Modern, and a Framework for Science-Society Debate", Science and Public Policy 32(2), April, pp. 137–153.
Dryzek, John S. 2000. Deliberative Democracy and Beyond: Liberals, Critics, Contestations. New York and Oxford: Oxford University Press.
Felt, Ulrike; Fochler, Maximilian (2010). "Machineries for Making Publics: Inscribing and De-scribing Publics in Public Engagement". Minerva. 48 (3): 219–239. doi:10.1007/s11024-010-9155-x. S2CID 144227502.
Fischer, Frank. 2005. Citizens, Experts, and the Environment. Durham: Duke University Press.
Gregory, Jane & Miller, Steve (1998); Science in Public: Communication, Culture & Credibility (Cambridge, Massachusetts USA: Perseus Publishing)
Hess, David J (2011). "To Tell the Truth: On Scientific Counter Publics". Public Understanding of Science. 20 (5): 627–641. doi:10.1177/0963662509359988. S2CID 145627603.
Hilgartner, Stephen (1990). "The Dominant View of Popularisation: Conceptual Problems, Political Uses". Social Studies of Science. 20 (3): 519–539. doi:10.1177/030631290020003006. S2CID 144068473.
Irwin, Alan and Wynne, Brian. (eds.) 1996. Misunderstanding Science? The Public Reconstruction of Science and Technology. Cambridge: Cambridge University Press.
Irwin, Alan. 1995. Citizen Science: A Study of People, Expertise and Sustainable Development. London and New York: Routledge.
Jasanoff, Sheila (2003c). "Technologies of Humility: Citizen Participation in Governing Science". Minerva. 41 (3): 223–244. doi:10.1023/A:1025557512320. S2CID 14370392.
Jasanoff, Sheila. 2005. Designs on Nature: Science and Democracy in Europe and the United States. Princeton and Oxford: Princeton University Press.
Leach, Melissa, Scoones, Ian and Wynne, Brian. (eds.) 2005. Science and Citizens: Globalisation and the Challenge of Engagement. London and New York: Zed Books.
Public Understanding of Science, specialist journal.
Shapin, Steven. 1990. 'Science and the Public' in R.C. Olby et al. (eds). Companion to the History of Modern Science. London and New York: Routledge. Pp. 990–1007.
The Royal Academy of Science's 2006 "Factors affecting science communication: a survey of scientists and engineers" report.
Southwell, Brian G. (2013). "Social Networks and Popular Understanding of Science and Health". Baltimore, MD: Johns Hopkins University Press.
Southwell, Brian G.; Torres, Alicia (2006). "Connecting interpersonal and mass communication: Science news exposure, perceived ability to understand science, and conversation". Communication Monographs. 73 (3): 334–350. doi:10.1080/03637750600889518. S2CID 143644528.
Varughese, Shiju Sam (2012). "Where are the missing masses? The Quasi-publics and Non-publics of Technoscience". Minerva. 50 (2): 239–254. doi:10.1007/s11024-012-9197-3. S2CID 144319733.
Varughese, Shiju Sam (2017). Contested Knowledge: Science, Media, and Democracy in Kerala. Oxford University Press. doi:10.1093/acprof:oso/9780199469123.001.0001. ISBN 9780199469123.
== External links ==
Science.gov
Vega Science Trust | Wikipedia/Public_awareness_of_science |
Public science is a term for research that is conducted amongst, or includes, the public. Two traditions of public science have emerged, one based on participatory action research and another based on science outreach.
== Participatory action research ==
The participatory action research approach seeks to develop a critical framework for making systematic inquiry and analysis a public enterprise. It is committed to valuing knowledges that have been historically marginalized and delegitimized (i.e., youth, prisoner, immigrant, farmer) alongside traditionally recognized knowledges (i.e., scholarly). Through the formation of research collectives, it aims to share the various knowledges and resources held by its individual members so members can participate as equally as possible. The choice of appropriate research questions, design, methods and analysis as well as useful research products are decided collectively. Institutions for this form of public science include the Public Science Project. Examples of public science projects in the participatory action research tradition include the Morris Justice Project.
== Science outreach ==
The science outreach approach has some similarities to citizen science but typically describes projects that are conducted outdoors or in another type of public or accessible space such as a public park, metro stop, library, university campus, etc. Similar to public art, it includes aspects of collaboration, community support and involvement, and site specificity.
Public science efforts in the science outreach tradition include Science on the Buses, in which city buses in many major European Union cities were decorated with large informational science posters in November 2002. Likewise, a project in Toronto placed "advertisements" with science facts on buses in Toronto during July 2009.
Science City was a public science initiative that ran from June 1994 through May 1995. Created by staff and consultants from the New York Hall of Science, Science City was an outdoor exhibition that utilized the street, fences, buildings and other public structures in New York City to attract the "non-museum-going" public to the science in everyday life. The exhibition asked questions such as "Why is it warmer in the city?", "What pulses under the street?" and "What's under the sidewalk?" to help increase public awareness about the science and technology that runs invisibly underneath modern urban life.
Science Cafés, founded by the public science pioneer Duncan Dallas, are public science events that initiate a discussion on a science topic in pubs or cafes, usually with a local researcher in attendance to answer questions and present information.
Science festivals can also be grouped into this category of public science efforts, with modern incarnations of festivals including a range of learner-centered activities and events conducted in public spaces.
Public science initiatives often attempt to reach new audiences (particularly, non-experts who might not actively seek out science), in addition to existing science outreach audiences, by hosting events in alternative informal learning environments. By definition, such public science projects are outside the walls of the science centre or science museum, where the main focus of the particular space is not typically science outreach.
An example of a specific public science initiative in astronomy is From Earth to the Universe (FETTU), a project of the International Year of Astronomy 2009 (IYA2009). FETTU displayed large-scale images of astronomical objects with contextual information and supplementary materials and activities in non-traditional and mostly public locations such as parks, airports, art festivals, and shopping malls. By 2011, FETTU had been exhibited at about 1000 sites worldwide, with 50 sites in the United States. One result from FETTU demonstrated a trend towards more non-self-selective audiences for science communications in these public spaces.
== References ==
== External links ==
Public Science Project
International Year of Astronomy 2009
From Earth to the Universe
From Earth to the Solar System
Voyage to the Solar System
USA Science and Engineering Festival
World Science Festival
San Diego Science Festival | Wikipedia/Public_science |
Metascience (also known as meta-research) is the use of scientific methodology to study science itself. Metascience seeks to increase the quality of scientific research while reducing inefficiency. It is also known as "research on research" and "the science of science", as it uses research methods to study how research is done and find where improvements can be made. Metascience concerns itself with all fields of research and has been described as "a bird's eye view of science". In the words of John Ioannidis, "Science is the best thing that has happened to human beings ... but we can do it better."
In 1966, an early meta-research paper examined the statistical methods of 295 papers published in ten high-profile medical journals. It found that "in almost 73% of the reports read ... conclusions were drawn when the justification for these conclusions was invalid." Meta-research in the following decades found many methodological flaws, inefficiencies, and poor practices in research across numerous scientific fields. Many scientific studies could not be reproduced, particularly in medicine and the soft sciences. The term "replication crisis" was coined in the early 2010s as part of a growing awareness of the problem.
Measures have been implemented to address the issues revealed by metascience. These measures include the pre-registration of scientific studies and clinical trials as well as the founding of organizations such as CONSORT and the EQUATOR Network that issue guidelines for methodology and reporting. There are continuing efforts to reduce the misuse of statistics, to eliminate perverse incentives from academia, to improve the peer review process, to systematically collect data about the scholarly publication system, to combat bias in scientific literature, and to increase the overall quality and efficiency of the scientific process. As such, metascience is a big part of methods underlying the Open Science Movement.
== History ==
In 1966, an early meta-research paper examined the statistical methods of 295 papers published in ten high-profile medical journals. It found that, "in almost 73% of the reports read ... conclusions were drawn when the justification for these conclusions was invalid." A paper in 1976 called for funding for meta-research: "Because the very nature of research on research, particularly if it is prospective, requires long periods of time, we recommend that independent, highly competent groups be established with ample, long term support to conduct and support retrospective and prospective research on the nature of scientific discovery". In 2005, John Ioannidis published a paper titled "Why Most Published Research Findings Are False", which argued that a majority of papers in the medical field produce conclusions that are wrong. The paper went on to become the most downloaded paper in the Public Library of Science and is considered foundational to the field of metascience. In a related study with Jeremy Howick and Despina Koletsi, Ioannidis showed that only a minority of medical interventions are supported by 'high quality' evidence according to The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Later meta-research identified widespread difficulty in replicating results in many scientific fields, including psychology and medicine. This problem was termed "the replication crisis". Metascience has grown as a reaction to the replication crisis and to concerns about waste in research.
Many prominent publishers are interested in meta-research and in improving the quality of their publications. Top journals such as Science, The Lancet, and Nature, provide ongoing coverage of meta-research and problems with reproducibility. In 2012 PLOS ONE launched a Reproducibility Initiative. In 2015 Biomed Central introduced a minimum-standards-of-reporting checklist to four titles.
The first international conference in the broad area of meta-research was the Research Waste/EQUATOR conference held in Edinburgh in 2015; the first international conference on peer review was the Peer Review Congress held in 1989. In 2016, Research Integrity and Peer Review was launched. The journal's opening editorial called for "research that will increase our understanding and suggest potential solutions to issues related to peer review, study reporting, and research and publication ethics".
== Fields and topics of meta-research ==
Metascience can be categorized into five major areas of interest: Methods, Reporting, Reproducibility, Evaluation, and Incentives. These correspond, respectively, with how to perform, communicate, verify, evaluate, and reward research.
=== Methods ===
Metascience seeks to identify poor research practices, including biases in research, poor study design, abuse of statistics, and to find methods to reduce these practices. Meta-research has identified numerous biases in scientific literature. Of particular note is the widespread misuse of p-values and abuse of statistical significance.
==== Scientific data science ====
Scientific data science is the use of data science to analyse research papers. It encompasses both qualitative and quantitative methods. Research in scientific data science includes fraud detection and citation network analysis.
==== Journalology ====
Journalology, also known as publication science, is the scholarly study of all aspects of the academic publishing process. The field seeks to improve the quality of scholarly research by implementing evidence-based practices in academic publishing. The term "journalology" was coined by Stephen Lock, the former editor-in-chief of The BMJ. The first Peer Review Congress, held in 1989 in Chicago, Illinois, is considered a pivotal moment in the founding of journalology as a distinct field. The field of journalology has been influential in pushing for study pre-registration in science, particularly in clinical trials. Clinical-trial registration is now expected in most countries.
=== Reporting ===
Meta-research has identified poor practices in reporting, explaining, disseminating and popularizing research, particularly within the social and health sciences. Poor reporting makes it difficult to accurately interpret the results of scientific studies, to replicate studies, and to identify biases and conflicts of interest in the authors. Solutions include the implementation of reporting standards, and greater transparency in scientific studies (including better requirements for disclosure of conflicts of interest). There is an attempt to standardize reporting of data and methodology through the creation of guidelines by reporting agencies such as CONSORT and the larger EQUATOR Network.
=== Reproducibility ===
The replication crisis is an ongoing methodological crisis in which it has been found that many scientific studies are difficult or impossible to replicate. While the crisis has its roots in the meta-research of the mid- to late 20th century, the phrase "replication crisis" was not coined until the early 2010s as part of a growing awareness of the problem. The replication crisis has been closely studied in psychology (especially social psychology) and medicine, including cancer research. Replication is an essential part of the scientific process, and the widespread failure of replication puts into question the reliability of affected fields.
Moreover, replication of research (or failure to replicate) is considered less influential than original research, and is less likely to be published in many fields. This discourages the reporting of, and even attempts to replicate, studies.
=== Evaluation and incentives ===
Metascience seeks to create a scientific foundation for peer review. Meta-research evaluates peer review systems including pre-publication peer review, post-publication peer review, and open peer review. It also seeks to develop better research funding criteria.
Metascience seeks to promote better research through better incentive systems. This includes studying the accuracy, effectiveness, costs, and benefits of different approaches to ranking and evaluating research and those who perform it. Critics argue that perverse incentives have created a publish-or-perish environment in academia which promotes the production of junk science, low quality research, and false positives. According to Brian Nosek, "The problem that we face is that the incentive system is focused almost entirely on getting research published, rather than on getting research right." Proponents of reform seek to structure the incentive system to favor higher-quality results. For example, by quality being judged on the basis of narrative expert evaluations ("rather than [only or mainly] indices"), institutional evaluation criteria, guaranteeing of transparency, and professional standards.
==== Contributorship ====
Studies proposed machine-readable standards and (a taxonomy of) badges for science publication management systems that hones in on contributorship – who has contributed what and how much of the research labor – rather that using traditional concept of plain authorship – who was involved in any way creation of a publication. A study pointed out one of the problems associated with the ongoing neglect of contribution nuanciation – it found that "the number of publications has ceased to be a good metric as a result of longer author lists, shorter papers, and surging publication numbers".
==== Assessment factors ====
Factors other than a submission's merits can substantially influence peer reviewers' evaluations. Such factors may however also be important such as the use of track-records about the veracity of a researchers' prior publications and its alignment with public interests. Nevertheless, evaluation systems – include those of peer-review – may substantially lack mechanisms and criteria that are oriented or well-performingly oriented towards merit, real-world positive impact, progress and public usefulness rather than analytical indicators such as number of citations or altmetrics even when such can be used as partial indicators of such ends. Rethinking of the academic reward structure "to offer more formal recognition for intermediate products, such as data" could have positive impacts and reduce data withholding.
==== Recognition of training ====
A commentary noted that academic rankings don't consider where (country and institute) the respective researchers were trained.
==== Scientometrics ====
Scientometrics concerns itself with measuring bibliographic data in scientific publications. Major research issues include the measurement of the impact of research papers and academic journals, the understanding of scientific citations, and the use of such measurements in policy and management contexts. Studies suggest that "metrics used to measure academic success, such as the number of publications, citation number, and impact factor, have not changed for decades" and have to some degrees "ceased" to be good measures, leading to issues such as "overproduction, unnecessary fragmentations, overselling, predatory journals (pay and publish), clever plagiarism, and deliberate obfuscation of scientific results so as to sell and oversell".
Novel tools in this area include systems to quantify how much the cited-node informs the citing-node. This can be used to convert unweighted citation networks to a weighted one and then for importance assessment, deriving "impact metrics for the various entities involved, like the publications, authors etc" as well as, among other tools, for search engine- and recommendation systems.
==== Science governance ====
Science funding and science governance can also be explored and informed by metascience.
===== Incentives =====
Various interventions such as prioritization can be important. For instance, the concept of differential technological development refers to deliberately developing technologies – e.g. control-, safety- and policy-technologies versus risky biotechnologies – at different precautionary paces to decrease risks, mainly global catastrophic risk, by influencing the sequence in which technologies are developed. Relying only on the established form of legislation and incentives to ensure the right outcomes may not be adequate as these may often be too slow or inappropriate.
Other incentives to govern science and related processes, including via metascience-based reforms, may include ensuring accountability to the public (in terms of e.g. accessibility of, especially publicly-funded, research or of it addressing various research topics of public interest in serious manners), increasing the qualified productive scientific workforce, improving the efficiency of science to improve problem-solving in general, and facilitating that unambiguous societal needs based on solid scientific evidence – such as about human physiology – are adequately prioritized and addressed. Such interventions, incentives and intervention-designs can be subjects of metascience.
===== Science funding and awards =====
Scientific awards are one category of science incentives. Metascience can explore existing and hypothetical systems of science awards. For instance, it found that work honored by Nobel Prizes clustered in only a few scientific fields with only 36/71 having received at least one Nobel Prize. Of the 114/849 domains science could be divided into their DC2 and DC3 classification systems, five were shown to comprise over half of the Nobel Prizes awarded between 1995 and 2017 (particle physics [14%], cell biology [12.1%], atomic physics [10.9%], neuroscience [10.1%], molecular chemistry [5.3%]).
A study found that delegation of responsibility by policy-makers – a centralized authority-based top-down approach – for knowledge production and appropriate funding to science with science subsequently somehow delivering "reliable and useful knowledge to society" is too simple.
Measurements show that allocation of bio-medical resources can be more strongly correlated to previous allocations and research than to burden of diseases.
A study suggests that "[i]f peer review is maintained as the primary mechanism of arbitration in the competitive selection of research reports and funding, then the scientific community needs to make sure it is not arbitrary".
Studies indicate there to is a need to "reconsider how we measure success" (see #Factors of success and progress).
Funding data
Funding information from grant databases and funding acknowledgment sections can be sources of data for scientometrics studies, e.g. for investigating or recognition of the impact of funding entities on the development of science and technology.
===== Research questions and coordination =====
===== Risk governance =====
=== Science communication and public use ===
It has been argued that "science has two fundamental attributes that underpin its value as a global public good: that knowledge claims and the evidence on which they are based are made openly available to scrutiny, and that the results of scientific research are communicated promptly and efficiently". Metascientific research is exploring topics of science communication such as media coverage of science, science journalism and online communication of results by science educators and scientists. A study found that the "main incentive academics are offered for using social media is amplification" and that it should be "moving towards an institutional culture that focuses more on how these [or such] platforms can facilitate real engagement with research". Science communication may also involve the communication of societal needs, concerns and requests to scientists.
==== Alternative metrics tools ====
Alternative metrics tools can be used not only for help in assessment (performance and impact) and findability, but also aggregate many of the public discussions about a scientific paper in social media such as reddit, citations on Wikipedia, and reports about the study in the news media which can then in turn be analyzed in metascience or provided and used by related tools. In terms of assessment and findability, altmetrics rate publications' performance or impact by the interactions they receive through social media or other online platforms, which can for example be used for sorting recent studies by measured impact, including before other studies are citing them. The specific procedures of established altmetrics are not transparent and the used algorithms can not be customized or altered by the user as open source software can. A study has described various limitations of altmetrics and points "toward avenues for continued research and development". They are also limited in their use as a primary tool for researchers to find received constructive feedback. (see above)
==== Societal implications and applications ====
It has been suggested that it may benefit science if "intellectual exchange—particularly regarding the societal implications and applications of science and technology—are better appreciated and incentivized in the future".
==== Knowledge integration ====
Primary studies "without context, comparison or summary are ultimately of limited value" and various types of research syntheses and summaries integrate primary studies. Progress in key social-ecological challenges of the global environmental agenda is "hampered by a lack of integration and synthesis of existing scientific evidence", with a "fast-increasing volume of data", compartmentalized information and generally unmet evidence synthesis challenges. According to Khalil, researchers are facing the problem of too many papers – e.g. in March 2014 more than 8,000 papers were submitted to arXiv – and to "keep up with the huge amount of literature, researchers use reference manager software, they make summaries and notes, and they rely on review papers to provide an overview of a particular topic". He notes that review papers are usually (only)" for topics in which many papers were written already, and they can get outdated quickly" and suggests "wiki-review papers" that get continuously updated with new studies on a topic and summarize many studies' results and suggest future research. A study suggests that if a scientific publication is being cited in a Wikipedia article this could potentially be considered as an indicator of some form of impact for this publication, for example as this may, over time, indicate that the reference has contributed to a high-level of summary of the given topic.
==== Science journalism ====
Science journalists play an important role in the scientific ecosystem and in science communication to the public and need to "know how to use, relevant information when deciding whether to trust a research finding, and whether and how to report on it", vetting the findings that get transmitted to the public.
=== Science education ===
Some studies investigate science education, e.g. the teaching about selected scientific controversies and historical discovery process of major scientific conclusions, and common scientific misconceptions. Education can also be a topic more generally such as how to improve the quality of scientific outputs and reduce the time needed before scientific work or how to enlarge and retain various scientific workforces.
==== Science misconceptions and anti-science attitudes ====
Many students have misconceptions about what science is and how it works. Anti-science attitudes and beliefs are also a subject of research. Hotez suggests antiscience "has emerged as a dominant and highly lethal force, and one that threatens global security", and that there is a need for "new infrastructure" that mitigates it.
=== Evolution of sciences ===
==== Scientific practice ====
Metascience can investigate how scientific processes evolve over time. A study found that teams are growing in size, "increasing by an average of 17% per decade". (see labor advantage below)
It was found that prevalent forms of non-open access publication and prices charged for many conventional journals – even for publicly funded papers – are unwarranted, unnecessary – or suboptimal – and detrimental barriers to scientific progress. Open access can save considerable amounts of financial resources, which could be used otherwise, and level the playing field for researchers in developing countries. There are substantial expenses for subscriptions, gaining access to specific studies, and for article processing charges. Paywall: The Business of Scholarship is a documentary on such issues.
Another topic are the established styles of scientific communication (e.g. long text-form studies and reviews) and the scientific publishing practices – there are concerns about a "glacial pace" of conventional publishing. The use of preprint-servers to publish study-drafts early is increasing and open peer review, new tools to screen studies, and improved matching of submitted manuscripts to reviewers are among the proposals to speed up publication.
==== Science overall and intrafield developments ====
Studies have various kinds of metadata which can be utilized, complemented and made accessible in useful ways. OpenAlex is a free online index of over 200 million scientific documents that integrates and provides metadata such as sources, citations, author information, scientific fields and research topics. Its API and open source website can be used for metascience, scientometrics and novel tools that query this semantic web of papers. Another project under development, Scholia, uses metadata of scientific publications for various visualizations and aggregation features such as providing a simple user interface summarizing literature about a specific feature of the SARS-CoV-2 virus using Wikidata's "main subject" property.
===== Subject-level resolutions =====
Beyond metadata explicitly assigned to studies by humans, natural language processing and AI can be used to assign research publications to topics – one study investigating the impact of science awards used such to associate a paper's text (not just keywords) with the linguistic content of Wikipedia's scientific topics pages ("pages are created and updated by scientists and users through crowdsourcing"), creating meaningful and plausible classifications of high-fidelity scientific topics for further analysis or navigability.
===== Growth or stagnation of science overall =====
Metascience research is investigating the growth of science overall, using e.g. data on the number of publications in bibliographic databases. A study found segments with different growth rates appear related to phases of "economic (e.g., industrialization)" – money is considered as necessary input to the science system – "and/or political developments (e.g., Second World War)". It also confirmed a recent exponential growth in the volume of scientific literature and calculated an average doubling period of 17.3 years.
However, others have pointed out that is difficult to measure scientific progress in meaningful ways, partly because it's hard to accurately evaluate how important any given scientific discovery is. A variety of perspectives of the trajectories of science overall (impact, number of major discoveries, etc) have been described in books and articles, including that science is becoming harder (per dollar or hour spent), that if science "slowing today, it is because science has remained too focused on established fields", that papers and patents are increasingly less likely to be "disruptive" in terms of breaking with the past as measured by the "CD index", and that there is a great stagnation – possibly as part of a larger trend – whereby e.g. "things haven't changed nearly as much since the 1970s" when excluding the computer and the Internet.
Better understanding of potential slowdowns according to some measures could be a major opportunity to improve humanity's future. For example, emphasis on citations in the measurement of scientific productivity, information overloads, reliance on a narrower set of existing knowledge (which may include narrow specialization and related contemporary practices) based on three "use of previous knowledge"-indicators, and risk-avoidant funding structures may have "toward incremental science and away from exploratory projects that are more likely to fail". The study that introduced the "CD index" suggests the overall number of papers has risen while the total of "highly disruptive" papers as measured by the index hasn't (notably, the 1998 discovery of the accelerating expansion of the universe has a CD index of 0). Their results also suggest scientists and inventors "may be struggling to keep up with the pace of knowledge expansion".
Various ways of measuring "novelty" of studies, novelty metrics, have been proposed to balance a potential anti-novelty bias – such as textual analysis or measuring whether it makes first-time-ever combinations of referenced journals, taking into account the difficulty. Other approaches include pro-actively funding risky projects. (see above)
=== Topic mapping ===
Science maps could show main interrelated topics within a certain scientific domain, their change over time, and their key actors (researchers, institutions, journals). They may help find factors determine the emergence of new scientific fields and the development of interdisciplinary areas and could be relevant for science policy purposes. (see above) Theories of scientific change could guide "the exploration and interpretation of visualized intellectual structures and dynamic patterns". The maps can show the intellectual, social or conceptual structure of a research field. Beyond visual maps, expert survey-based studies and similar approaches could identify understudied or neglected societally important areas, topic-level problems (such as stigma or dogma), or potential misprioritizations. Examples of such are studies about policy in relation to public health and the social science of climate change mitigation where it has been estimated that only 0.12% of all funding for climate-related research is spent on such despite the most urgent puzzle at the current juncture being working out how to mitigate climate change, whereas the natural science of climate change is already well established.
There are also studies that map a scientific field or a topic such as the study of the use of research evidence in policy and practice, partly using surveys.
=== Controversies, current debates and disagreement ===
Some research is investigating scientific controversy or controversies, and may identify currently ongoing major debates (e.g. open questions), and disagreement between scientists or studies. One study suggests the level of disagreement was highest in the social sciences and humanities (0.61%), followed by biomedical and health sciences (0.41%), life and earth sciences (0.29%); physical sciences and engineering (0.15%), and mathematics and computer science (0.06%). Such research may also show, where the disagreements are, especially if they cluster, including visually such as with cluster diagrams.
=== Challenges of interpretation of pooled results ===
Studies about a specific research question or research topic are often reviewed in the form of higher-level overviews in which results from various studies are integrated, compared, critically analyzed and interpreted. Examples of such works are scientific reviews and meta-analyses. These and related practices face various challenges and are a subject of metascience.
Various issues with included or available studies such as, for example, heterogeneity of methods used may lead to faulty conclusions of the meta-analysis.
=== Knowledge integration and living documents ===
Various problems require swift integration of new and existing science-based knowledge. Especially setting where there are a large number of loosely related projects and initiatives benefit from a common ground or "commons".
Evidence synthesis can be applied to important and, notably, both relatively urgent and certain global challenges: "climate change, energy transitions, biodiversity loss, antimicrobial resistance, poverty eradication and so on". It was suggested that a better system would keep summaries of research evidence up to date via living systematic reviews – e.g. as living documents. While the number of scientific papers and data (or information and online knowledge) has risen substantially, the number of published academic systematic reviews has risen from "around 6,000 in 2011 to more than 45,000 in 2021". An evidence-based approach is important for progress in science, policy, medical and other practices. For example, meta-analyses can quantify what is known and identify what is not yet known and place "truly innovative and highly interdisciplinary ideas" into the context of established knowledge which may enhance their impact. (see above)
=== Factors of success and progress ===
It has been hypothesized that a deeper understanding of factors behind successful science could "enhance prospects of science as a whole to more effectively address societal problems".
==== Novel ideas and disruptive scholarship ====
Two metascientists reported that "structures fostering disruptive scholarship and focusing attention on novel ideas" could be important as in a growing scientific field citation flows disproportionately consolidate to already well-cited papers, possibly slowing and inhibiting canonical progress. A study concluded that to enhance impact of truly innovative and highly interdisciplinary novel ideas, they should be placed in the context of established knowledge.
==== Mentorship, partnerships and social factors ====
Other researchers reported that the most successful – in terms of "likelihood of prizewinning, National Academy of Science (NAS) induction, or superstardom" – protégés studied under mentors who published research for which they were conferred a prize after the protégés' mentorship. Studying original topics rather than these mentors' research-topics was also positively associated with success. Highly productive partnerships are also a topic of research – e.g. "super-ties" of frequent co-authorship of two individuals who can complement skills, likely also the result of other factors such as mutual trust, conviction, commitment and fun.
==== Study of successful scientists and processes, general skills and activities ====
The emergence or origin of ideas by successful scientists is also a topic of research, for example reviewing existing ideas on how Mendel made his discoveries, – or more generally, the process of discovery by scientists. Science is a "multifaceted process of appropriation, copying, extending, or combining ideas and inventions" [and other types of knowledge or information], and not an isolated process. There are also few studies investigating scientists' habits, common modes of thinking, reading habits, use of information sources, digital literacy skills, and workflows.
==== Labor advantage ====
A study theorized that in many disciplines, larger scientific productivity or success by elite universities can be explained by their larger pool of available funded laborers. The study found that university prestige was only associated with higher productivity for faculty with group members, not for faculty publishing alone or the group members themselves. This is presented as evidence that the outsize productivity of elite researchers is not from a more rigorous selection of talent by top universities, but from labor advantages accrued through greater access to funding and the attraction of prestige to graduate and postdoctoral researchers.
==== Ultimate impacts ====
Success in science (as indicated in tenure review processes) is often measured in terms of metrics like citations, not in terms of the eventual or potential impact on lives and society, which awards (see above) sometimes do. Problems with such metrics are roughly outlined elsewhere in this article and include that reviews replace citations to primary studies. There are also proposals for changes to the academic incentives systems that increase the recognition of societal impact in the research process.
==== Progress studies ====
A proposed field of "Progress Studies" could investigate how scientists (or funders or evaluators of scientists) should be acting, "figuring out interventions" and study progress itself. The field was explicitly proposed in a 2019 essay and described as an applied science that prescribes action.
==== As and for acceleration of progress ====
A study suggests that improving the way science is done could accelerate the rate of scientific discovery and its applications which could be useful for finding urgent solutions to humanity's problems, improve humanity's conditions, and enhance understanding of nature. Metascientific studies can seek to identify aspects of science that need improvement, and develop ways to improve them. If science is accepted as the fundamental engine of economic growth and social progress, this could raise "the question of what we – as a society – can do to accelerate science, and to direct science toward solving society's most important problems." However, one of the authors clarified that a one-size-fits-all approach is not thought to be right answer – for example, in funding, DARPA models, curiosity-driven methods, allowing "a single reviewer to champion a project even if his or her peers do not agree", and various other approaches all have their uses. Nevertheless, evaluation of them can help build knowledge of what works or works best.
== Reforms ==
Meta-research identifying flaws in scientific practice has inspired reforms in science. These reforms seek to address and fix problems in scientific practice which lead to low-quality or inefficient research.
A 2015 study lists "fragmented" efforts in meta-research.
=== Pre-registration ===
The practice of registering a scientific study before it is conducted is called pre-registration. It arose as a means to address the replication crisis. Pregistration requires the submission of a registered report, which is then accepted for publication or rejected by a journal based on theoretical justification, experimental design, and the proposed statistical analysis. Pre-registration of studies serves to prevent publication bias (e.g. not publishing negative results), reduce data dredging, and increase replicability.
=== Reporting standards ===
Studies showing poor consistency and quality of reporting have demonstrated the need for reporting standards and guidelines in science, which has led to the rise of organisations that produce such standards, such as CONSORT (Consolidated Standards of Reporting Trials) and the EQUATOR Network.
The EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Network is an international initiative aimed at promoting transparent and accurate reporting of health research studies to enhance the value and reliability of medical research literature. The EQUATOR Network was established with the goals of raising awareness of the importance of good reporting of research, assisting in the development, dissemination and implementation of reporting guidelines for different types of study designs, monitoring the status of the quality of reporting of research studies in the health sciences literature, and conducting research relating to issues that impact the quality of reporting of health research studies. The Network acts as an "umbrella" organisation, bringing together developers of reporting guidelines, medical journal editors and peer reviewers, research funding bodies, and other key stakeholders with a mutual interest in improving the quality of research publications and research itself.
== Applications ==
=== Information and communications technologies ===
Metascience is used in the creation and improvement of technical systems (ICTs) and standards of science evaluation, incentivation, communication, commissioning, funding, regulation, production, management, use and publication. Such can be called "applied metascience" and may seek to explore ways to increase quantity, quality and positive impact of research. One example for such is the development of alternative metrics.
==== Study screening and feedback ====
Various websites or tools also identify inappropriate studies and/or enable feedback such as PubPeer, Cochrane's Risk of Bias Tool and RetractionWatch. Medical and academic disputes are as ancient as antiquity and a study calls for research into "constructive and obsessive criticism" and into policies to "help strengthen social media into a vibrant forum for discussion, and not merely an arena for gladiator matches". Feedback to studies can be found via altmetrics which is often integrated at the website of the study – most often as an embedded Altmetrics badge – but may often be incomplete, such as only showing social media discussions that link to the study directly but not those that link to news reports about the study. (see above)
==== Tools used, modified, extended or investigated ====
Tools may get developed with metaresearch or can be used or investigated by such. Notable examples may include:
Search engines like Google Scholar are used to find studies and the notification service Google Alerts enables notifications for new studies matching specified search terms. Scholarly communication infrastructure includes search databases.
Shadow library Sci-hub is a topic of metascience
Personal knowledge management systems for research-, knowledge- and task management, such as saving information in organized ways with multi-document text editors for future use Such systems could be described as part of, along with e.g. Web browser (tabs-addons etc) and search software, "mind-machine partnerships" that could be investigated by metascience for how they could improve science.
Scholia – efforts to open scholarly publication metadata and use it via Wikidata. (see above)
Various software enables common metascientific practices such as bibliometric analysis.
==== Development ====
According to a study "a simple way to check how often studies have been repeated, and whether or not the original findings are confirmed" is needed due to reproducibility issues in science. A study suggests a tool for screening studies for early warning signs for research fraud.
=== Medicine ===
Clinical research in medicine is often of low quality, and many studies cannot be replicated. An estimated 85% of research funding is wasted. Additionally, the presence of bias affects research quality. The pharmaceutical industry exerts substantial influence on the design and execution of medical research. Conflicts of interest are common among authors of medical literature and among editors of medical journals. While almost all medical journals require their authors to disclose conflicts of interest, editors are not required to do so. Financial conflicts of interest have been linked to higher rates of positive study results. In antidepressant trials, pharmaceutical sponsorship is the best predictor of trial outcome.
Blinding is another focus of meta-research, as error caused by poor blinding is a source of experimental bias. Blinding is not well reported in medical literature, and widespread misunderstanding of the subject has resulted in poor implementation of blinding in clinical trials. Furthermore, failure of blinding is rarely measured or reported. Research showing the failure of blinding in antidepressant trials has led some scientists to argue that antidepressants are no better than placebo. In light of meta-research showing failures of blinding, CONSORT standards recommend that all clinical trials assess and report the quality of blinding.
Studies have shown that systematic reviews of existing research evidence are sub-optimally used in planning a new research or summarizing the results. Cumulative meta-analyses of studies evaluating the effectiveness of medical interventions have shown that many clinical trials could have been avoided if a systematic review of existing evidence was done prior to conducting a new trial. For example, Lau et al. analyzed 33 clinical trials (involving 36974 patients) evaluating the effectiveness of intravenous streptokinase for acute myocardial infarction. Their cumulative meta-analysis demonstrated that 25 of 33 trials could have been avoided if a systematic review was conducted prior to conducting a new trial. In other words, randomizing 34542 patients was potentially unnecessary. One study analyzed 1523 clinical trials included in 227 meta-analyses and concluded that "less than one quarter of relevant prior studies" were cited. They also confirmed earlier findings that most clinical trial reports do not present systematic review to justify the research or summarize the results.
Many treatments used in modern medicine have been proven to be ineffective, or even harmful. A 2007 study by John Ioannidis found that it took an average of ten years for the medical community to stop referencing popular practices after their efficacy was unequivocally disproven.
=== Psychology ===
Metascience has revealed significant problems in psychological research. The field suffers from high bias, low reproducibility, and widespread misuse of statistics. The replication crisis affects psychology more strongly than any other field; as many as two-thirds of highly publicized findings may be impossible to replicate. Meta-research finds that 80-95% of psychological studies support their initial hypotheses, which strongly implies the existence of publication bias.
The replication crisis has led to renewed efforts to re-test important findings. In response to concerns about publication bias and p-hacking, more than 140 psychology journals have adopted result-blind peer review, in which studies are pre-registered and published without regard for their outcome. An analysis of these reforms estimated that 61 percent of result-blind studies produce null results, in contrast with 5 to 20 percent in earlier research. This analysis shows that result-blind peer review substantially reduces publication bias.
Psychologists routinely confuse statistical significance with practical importance, enthusiastically reporting great certainty in unimportant facts. Some psychologists have responded with an increased use of effect size statistics, rather than sole reliance on the p values.
=== Physics ===
Richard Feynman noted that estimates of physical constants were closer to published values than would be expected by chance. This was believed to be the result of confirmation bias: results that agreed with existing literature were more likely to be believed, and therefore published. Physicists now implement blinding to prevent this kind of bias.
=== Computer Science ===
Web measurement studies are essential for understanding the workings of the modern Web, particularly in the fields of security and privacy. However, these studies often require custom-built or modified crawling setups, leading to a plethora of analysis tools for similar tasks. In a paper by Nurullah Demir et al., the authors surveyed 117 recent research papers to derive best practices for Web-based measurement studies and establish criteria for reproducibility and replicability. They found that experimental setups and other critical information for reproducing and replicating results are often missing. In a large-scale Web measurement study on 4.5 million pages with 24 different measurement setups, the authors demonstrated the impact of slight differences in experimental setups on the overall results, emphasizing the need for accurate and comprehensive documentation.
== Organizations and institutes ==
There are several organizations and universities across the globe which work on meta-research – these include the Meta-Research Innovation Center at Berlin, the Meta-Research Innovation Center at Stanford, the Meta-Research Center at Tilburg University, the Meta-research & Evidence Synthesis Unit, The George Institute for Global Health at India and Center for Open Science. Organizations that develop tools for metascience include OurResearch, Center for Scientific Integrity and altmetrics companies. There is an annual Metascience Conference hosted by the Association for Interdisciplinary Meta-Research and Open Science (AIMOS) and biannual conference hosted by the Centre for Open Science.
== See also ==
== References ==
== Further reading ==
Bonett, D.G. (2021). Design and analysis of replication studies. Organizational Research Methods, 24, 513-529. https://doi.org/10.1177/1094428120911088
Lydia Denworth, "A Significant Problem: Standard scientific methods are under fire. Will anything change?", Scientific American, vol. 321, no. 4 (October 2019), pp. 62–67.
"The use of p values for nearly a century [since 1925] to determine statistical significance of experimental results has contributed to an illusion of certainty and [to] reproducibility crises in many scientific fields. There is growing determination to reform statistical analysis... Some [researchers] suggest changing statistical methods, whereas others would do away with a threshold for defining "significant" results." (p. 63.)
Harris, Richard (2017). Rigor Mortis: How Sloppy Science Creates Worthless Cures, Crushes Hopes, and Wastes Billions. Basic Books. ISBN 978-0465097913.
Fortunato, Santo; Bergstrom, Carl T.; et al. (2 March 2018). "Science of science". Science. 359 (6379): eaao0185. doi:10.1126/science.aao0185. PMC 5949209. PMID 29496846.
== External links ==
=== Journals ===
Minerva: A Journal of Science, Learning and Policy
Research Integrity and Peer Review
Research Policy
Science and Public Policy
=== Conferences ===
Annual Metascience Conference | Wikipedia/Metascience |
Neo-colonial research or neo-colonial science, frequently described as helicopter research, parachute science or research, parasitic research, or safari study, is when researchers from wealthier countries go to a developing country, collect information, travel back to their country, analyze the data and samples, and publish the results with no or little involvement of local researchers. A 2003 study by the Hungarian Academy of Sciences found that 70% of articles in a random sample of publications about least-developed countries did not include a local research co-author.
Frequently, during this kind of research, the local colleagues might be used to provide logistics support as fixers but are not engaged for their expertise or given credit for their participation in the research. Scientific publications resulting from parachute science frequently only contribute to the career of the scientists from rich countries, thus limiting the development of local science capacity (such as funded research centers) and the careers of local scientists. This form of "colonial" science has reverberations of 19th century scientific practices of treating non-Western participants as "others" in order to advance colonialism—and critics call for the end of these extractivist practices in order to decolonize knowledge.
This kind of research approach reduces the quality of research because international researchers may not ask the right questions or draw connections to local issues. The result of this approach is that local communities are unable to leverage the research to their own advantage. Ultimately, especially for fields dealing with global issues like conservation biology which rely on local communities to implement solutions, neo-colonial science prevents institutionalization of the findings in local communities in order to address issues being studied by scientists.
== Effects ==
The use of helicopter research has also led to a stigma of research within minority groups; some going so far as to deny research within their communities. Such safari studies lead to long-term negative effects for the scientific community and researchers, as distrust develops within peripheral communities.
=== Donor robbery ===
Funds for research in developing countries are often provided by bilateral and international academic and research programmes for sustainable development. Through 'donor robbery' a large proportion of such international funds may end up in the wealthier countries via consultancy fees, laboratory costs in rich universities, overhead or purchase of expensive equipment, hiring expatriates and running "enclave" research institutes, depending on international conglomerates.
=== Use of open data ===
The current tendency of freely availing research datasets may lead to exploitation of, and rapid publication of results based on data pertaining to developing countries by rich and well-equipped research institutes, without any further involvement and/or benefit to local communities; similarly to the historical open access to tropical forests that has led to the disappropriation ("Global Pillage") of plant genetic resources from developing countries.
=== Professional discourse ===
In certain fields of research, such as global public health, both the journals and professionals creating the field have defined much of their work under colonial structures and assumptions. This in turn prevents participation in the field from early in the process, even before authorship or credit is given during the publishing representation of editorial boards of journals publishing in environmental sciences and public health, with a vast majority of editors based in high-income countries despite the global scope of the journals' fields.
== Mitigation ==
Some journals and publishers are implementing policies that should mitigate the impact of parachute science. One of the conditions for publication set by the journal Global Health Action is that, "Articles reporting research involving primary data collection will normally include researchers and institutions from the countries concerned as authors, and include in-country ethical approval." Similarly The Lancet Global Health placed restriction encouraged submissions to review their practices for including local participants. Similarly in 2021, PLOS announced a policy that required changes in reporting for researchers working in other countries.
A number of research communities are putting protocols in place for indigenous health information. In the US, the Cherokee Nation established a specific Institutional Review Board, aiming at ensuring the protection of the rights and welfare of tribal members involved in research projects. The Cherokee Nation IRB does not allow helicopter research. The Human Heredity and Health in Africa (H3Africa) Initiative launched guidelines for working with genetic information from the continent in 2018.
An Ethiopian soil scientist, Mitiku Haile, suggests that such "free riding" should be "condemned by all partners and, if found, should be brought to the attention of the scientific community and the international and national funding agencies".
Also in Africa, since the outbreak of the coronavirus pandemic in 2020, travel restrictions on international scholars tend to local scientists stepping up to lead research.
== Examples by field ==
Examples of neo-colonial approaches to science include:
In the medical world: "A popular term for a clinical or epidemiologic research project conducted by foreign scientists who use local contacts to gain access to a population group and obtain samples"
In anthropology, particularly when related to peripheral ethnic groups: "Any investigation within the community in which a researcher collects data, leaves to disseminate it, and never again has contact with the tribe."
In geosciences, a 2020 study found that 30% of studies about Africa contained an African author. (See also: Ubirajara jubatus.)
When scientists from a central, dominant ethnic or sociological group conduct research in areas where minority groups are living (often peripheral areas), there is also a risk for helicopter research, though it may not appear directly from the academic affiliation of the researchers. For instance, within the United States, it has been used primarily in the study of Native Americans.
=== Climate change ===
An analysis of research money from 1990 to 2020 for climate change, found that 78% of research money for research on Climate change in Africa, was spent in European and North American institutions and more was spent for former British colonies than other countries. This in turn both prevents local researchers from doing groundbreaking work, because they don't have the funding for experimental activities and reduces investment in local researchers ideas and in topics important to the Global South, such as climate change adaptation.
=== Soil science ===
Soil scientists have qualified helicopter research as a perpetuation of "colonial" science. Typically researchers from rich countries would come to establish soil profile pits or collect soil and peat samples, which is often more easily done in poor countries given the availability of cheap labour and goodwill of villagers to dig a pit on their land against small payment. The profile will be described and samples taken with the help of local people, possibly also university staff. In case of helicopter research, the outcomes are then published such as discovery in tropical peatlands, sometimes in high-level journals without the involvement of local colleagues. "Overall, helicopter research tends to produce academic papers that further the career of scientists from developed countries, but provide little practical outcomes for nations where the studies are conducted, nor develop the careers of their local scientists."
=== Coral Reef research ===
A 2021 study in Current Biology quantified the amount of parachute research happening in coral reef studies and found such approaches to be the norm.
== Examples by region ==
=== Europe ===
The 2015 description of Tetrapodophis was performed by three European scientists. When the Brazilan newspaper Estadão – Brazil being the country where the fossil hails from – questioned lead researcher David M. Martill, he replied "It should be fossils for all. No countries existed when the animals were fossilized. [..] what difference would it make [partnering with Brazilian scientists]? I mean, do you want me also to have a black person on the team for ethnicity reasons, and a cripple and a woman, and maybe a homosexual too, just for a bit of all round balance? [..] Now I don't work in Brazil. But I still work on Brazilian fossils. There are hundreds of them in museums all over Europe, America and in Japan."
=== Central Africa ===
A 2009 study found that Europeans participated in 77% of regionally co-authored papers in Central African countries. Even though local authors are credited with the work, they aren't always given participatory roles in the final production of the research itself—instead playing roles in fieldwork.
=== Indonesia ===
In April 2018, a publication about Indonesia's Bajau people received great attention. These "sea nomads" had a genetic adaptation resulting in large spleens that supply additional oxygenated red blood cells. A month later this publication was criticised by Indonesian scientists. Their article in Science questioned the ethics of scientists from the United States and Denmark who took DNA samples of the Bajau people and analyzed them, without much involvement of Bajau or other Indonesian people.
== See also ==
== References == | Wikipedia/Neo-colonial_science |
The relationship between religion and science involves discussions that interconnect the study of the natural world, history, philosophy, and theology. Even though the ancient and medieval worlds did not have conceptions resembling the modern understandings of "science" or of "religion", certain elements of modern ideas on the subject recur throughout history. The pair-structured phrases "religion and science" and "science and religion" first emerged in the literature during the 19th century. This coincided with the refining of "science" (from the studies of "natural philosophy") and of "religion" as distinct concepts in the preceding few centuries—partly due to professionalization of the sciences, the Protestant Reformation, colonization, and globalization. Since then the relationship between science and religion has been characterized in terms of "conflict", "harmony", "complexity", and "mutual independence", among others.
Both science and religion are complex social and cultural endeavors that may vary across cultures and change over time. Most scientific and technical innovations until the scientific revolution were achieved by societies organized by religious traditions. Ancient pagan, Islamic, and Christian scholars pioneered individual elements of the scientific method. Roger Bacon, often credited with formalizing the scientific method, was a Franciscan friar and medieval Christians who studied nature emphasized natural explanations. Confucian thought, whether religious or non-religious in nature, has held different views of science over time. Many 21st-century Buddhists view science as complementary to their beliefs, although the philosophical integrity of such Buddhist modernism has been challenged. While the classification of the material world by the ancient Indians and Greeks into air, earth, fire, and water was more metaphysical, and figures like Anaxagoras questioned certain popular views of Greek divinities, medieval Middle Eastern scholars empirically classified materials.
Events in Europe such as the Galileo affair of the early 17th century, associated with the scientific revolution and the Age of Enlightenment, led scholars such as John William Draper to postulate (c. 1874) a conflict thesis, suggesting that religion and science have been in conflict methodologically, factually and politically throughout history. Some contemporary philosophers and scientists, such as Richard Dawkins, Lawrence Krauss, Peter Atkins, and Donald Prothero subscribe to this thesis; however, historians such as Stephen Shapin state "it is a very long time since these attitudes have been held by historians of science."
Many scientists, philosophers, and theologians throughout history, from Augustine of Hippo to Thomas Aquinas to Francisco Ayala, Kenneth R. Miller, and Francis Collins, have seen compatibility or interdependence between religion and science. Biologist Stephen Jay Gould regarded religion and science as "non-overlapping magisteria", addressing fundamentally separate forms of knowledge and aspects of life. Some historians of science and mathematicians, including John Lennox, Thomas Berry, and Brian Swimme, propose an interconnection between science and religion, while others such as Ian Barbour believe there are even parallels. Public acceptance of scientific facts may sometimes be influenced by religious beliefs such as in the United States, where some reject the concept of evolution by natural selection, especially regarding Human beings. Nevertheless, the American National Academy of Sciences has written that "the evidence for evolution can be fully compatible with religious faith",
a view endorsed by many religious denominations.
== History ==
=== Concepts of science and religion ===
The concepts of "science" and "religion" are a recent invention: "religion" emerged in the 17th century in the midst of colonization, globalization and as a consequence of the Protestant reformation. "Science" emerged in the 19th century in the midst of attempts to narrowly define those who studied nature. Originally what is now known as "science" was pioneered as "natural philosophy".
It was in the 19th century that the terms "Buddhism", "Hinduism", "Taoism", "Confucianism" and "World Religions" first emerged. In the ancient and medieval world, the etymological Latin roots of both science (scientia) and religion (religio) were understood as inner qualities of the individual or virtues, never as doctrines, practices, or actual sources of knowledge.
The 19th century also experienced the concept of "science" receiving its modern shape with new titles emerging such as "biology" and "biologist", "physics", and "physicist", among other technical fields and titles; institutions and communities were founded, and unprecedented applications to and interactions with other aspects of society and culture occurred. The term scientist was coined by the naturalist-theologian William Whewell in 1834 and it was applied to those who sought knowledge and understanding of nature. From the ancient world, starting with Aristotle, to the 19th century, the practice of studying nature was commonly referred to as "natural philosophy". Isaac Newton's book Philosophiae Naturalis Principia Mathematica (1687), whose title translates to "Mathematical Principles of Natural Philosophy", reflects the then-current use of the words "natural philosophy", akin to "systematic study of nature". Even in the 19th century, a treatise by Lord Kelvin and Peter Guthrie Tait's, which helped define much of modern physics, was titled Treatise on Natural Philosophy (1867).
It was in the 17th century that the concept of "religion" received its modern shape despite the fact that ancient texts like the Bible, the Quran, and other texts did not have a concept of religion in the original languages and neither did the people or the cultures in which these texts were written. In the 19th century, Max Müller noted that what is called ancient religion today, would have been called "law" in antiquity. For example, there is no precise equivalent of "religion" in Hebrew, and Judaism does not distinguish clearly between religious, national, racial, or ethnic identities. The Sanskrit word "dharma", sometimes translated as "religion", also means law or duty. Throughout classical India, the study of law consisted of concepts such as penance through piety and ceremonial as well as practical traditions. Medieval Japan at first had a similar union between "imperial law" and universal or "Buddha law", but these later became independent sources of power. Throughout its long history, Japan had no concept of "religion" since there was no corresponding Japanese word, nor anything close to its meaning, but when American warships appeared off the coast of Japan in 1853 and forced the Japanese government to sign treaties demanding, among other things, freedom of religion, the country had to contend with this Western idea.
=== Middle Ages and Renaissance ===
The development of sciences (especially natural philosophy) in Western Europe during the Middle Ages, has a considerable foundation in the works of the Arabs who translated Greek and Latin compositions. The works of Aristotle played a major role in the institutionalization, systematization, and expansion of reason. Christianity accepted reason within the ambit of faith. In Christendom, ideas articulated via divine revelation were assumed to be true, and thus via the law of non-contradiction, it was maintained that the natural world must accord with this revealed truth. Any apparent contradiction would indicate either a misunderstanding of the natural world or a misunderstanding of revelation. The prominent scholastic Thomas Aquinas writes in the Summa Theologica concerning apparent contradictions:
"In discussing questions of this kind two rules are to observed, as Augustine teaches (Gen. ad lit. i, 18). The first is, to hold the truth of Scripture without wavering. The second is that since Holy Scripture can be explained in a multiplicity of senses, one should adhere to a particular explanation, only in such measure as to be ready to abandon it, if it be proved with certainty to be false; lest Holy Scripture be exposed to the ridicule of unbelievers, and obstacles be placed to their believing." (Summa 1a, 68, 1)
where the referenced text from Augustine of Hippo reads:
"In matters that are obscure and far beyond our vision, even in such as we may find treated in Holy Scripture, different interpretations are sometimes possible without prejudice to the faith we have received. In such a case, we should not rush in headlong and so firmly take our stand on one side that, if further progress in the search of truth justly undermines this position, we too fall with it. That would be to battle not for the teaching of Holy Scripture but for our own, wishing its teaching to conform to ours, whereas we ought to wish ours to conform to that of Sacred Scripture." (Gen. ad lit. i, 18)
In medieval universities, the faculty for natural philosophy and theology were separate, and discussions pertaining to theological issues were often not allowed to be undertaken by the faculty of philosophy. Natural philosophy, as taught in the arts faculties of the universities, was seen as an essential area of study in its own right and was considered necessary for almost every area of study. It was an independent field, separated from theology, and enjoyed a good deal of intellectual freedom as long as it was restricted to the natural world. In general, there was religious support for natural science by the late Middle Ages and a recognition that it was an important element of learning.
The extent to which medieval science led directly to the new philosophy of the scientific revolution remains a subject for debate, but it certainly had a significant influence.
The Middle Ages laid ground for the developments that took place in science, during the Renaissance which immediately succeeded it. By 1630, ancient authority from classical literature and philosophy, as well as their necessity, started eroding, although scientists were still expected to be fluent in Latin, the international language of Europe's intellectuals. With the sheer success of science and the steady advance of rationalism, the individual scientist gained prestige. Along with the inventions of this period, especially the printing press by Johannes Gutenberg, allowing for the dissemination of the Bible in vernacular languages. This allowed more people to read and learn from the scripture, leading to the Evangelical movement. The people who spread this message concentrated more on individual agency rather than the structures of the Church.
==== Medieval Contributors ====
Some medieval contributors to science included: Boethius (c. 477–524), John Philoponus (c. 490–570), Bede the Venerable (c. 672–735), Alcuin of York (c. 735–804), Leo the Mathematician (c. 790–869), Gerbert of Aurillac (c. 946–1003), Constantine the African (c. 1020–1087), Adelard of Bath (c. 1080–1152), Robert Grosseteste (c. 1168–1253), St. Albert the Great (c. 1200–1280), Roger Bacon (c. 1214–1294), William of Ockham (c. 1287–1347), Jean Burdian (c. 1301–1358), Thomas Bradwardine (1300–1349), Nicole Oresme (c. 1320–1382), Nicholas of Cusa (c. 1401–1464).
=== Modern period ===
In the 17th century, founders of the Royal Society largely held conventional and orthodox religious views, and a number of them were prominent Churchmen. While theological issues that had the potential to be divisive were typically excluded from formal discussions of the early Society, many of its fellows nonetheless believed that their scientific activities provided support for traditional religious belief. Clerical involvement in the Royal Society remained high until the mid-nineteenth century when science became more professionalized.
Albert Einstein supported the compatibility of some interpretations of religion with science. In "Science, Philosophy and Religion, A Symposium" published by the Conference on Science, Philosophy and Religion in Their Relation to the Democratic Way of Life, Inc., New York in 1941, Einstein stated:
Accordingly, a religious person is devout in the sense that he has no doubt of the significance and loftiness of those superpersonal objects and goals which neither require nor are capable of rational foundation. They exist with the same necessity and matter-of-factness as he himself. In this sense religion is the age-old endeavor of mankind to become clearly and completely conscious of these values and goals and constantly to strengthen and extend their effect. If one conceives of religion and science according to these definitions then a conflict between them appears impossible. For science can only ascertain what is, but not what should be, and outside of its domain value judgments of all kinds remain necessary. Religion, on the other hand, deals only with evaluations of human thought and action: it cannot justifiably speak of facts and relationships between facts. According to this interpretation the well-known conflicts between religion and science in the past must all be ascribed to a misapprehension of the situation which has been described.
Einstein thus expresses views of ethical non-naturalism (contrasted to ethical naturalism).
Prominent modern scientists who are atheists include evolutionary biologist Richard Dawkins and Nobel Prize–winning physicist Steven Weinberg. Prominent scientists advocating religious belief include Nobel Prize–winning physicist and United Church of Christ member Charles Townes, evangelical Christian and past head of the Human Genome Project Francis Collins, and climatologist John T. Houghton.
== Perspectives ==
The kinds of interactions that might arise between science and religion have been categorized by theologian, Anglican priest, and physicist John Polkinghorne: (1) conflict between the disciplines, (2) independence of the disciplines, (3) dialogue between the disciplines where they overlap and (4) integration of both into one field.
This typology is similar to ones used by theologians Ian Barbour and John Haught. More typologies that categorize this relationship can be found among the works of other science and religion scholars such as theologian and biochemist Arthur Peacocke.
=== Incompatibility ===
According to Guillermo Paz-y-Miño-C and Avelina Espinosa, the historical conflict between evolution and religion is intrinsic to the incompatibility between scientific rationalism/empiricism and the belief in supernatural causation/faith. According to evolutionary biologist Jerry Coyne, views on evolution and levels of religiosity in some countries, along with the existence of books explaining reconciliation between evolution and religion, indicate that people have trouble in believing both at the same time, thus implying incompatibility. According to physical chemist Peter Atkins, "whereas religion scorns the power of human comprehension, science respects it." Planetary scientist Carolyn Porco describes a hope that "the confrontation between science and formal religion will come to an end when the role played by science in the lives of all people is the same played by religion today."
Geologist and paleontologist Donald Prothero has stated that religion is the reason "questions about evolution, the age of the earth, cosmology, and human evolution nearly always cause Americans to flunk science literacy tests compared to other nations." However, Jon Miller, who studies science literacy across nations, states that Americans in general are slightly more scientifically literate than Europeans and the Japanese.
According to cosmologist and astrophysicist Lawrence Krauss, compatibility or incompatibility is a theological concern, not a scientific concern. In Lisa Randall's view, questions of incompatibility or otherwise are not answerable, since by accepting revelations one is abandoning rules of logic which are needed to identify if there are indeed contradictions between holding certain beliefs. Daniel Dennett holds that incompatibility exists because religion is not problematic to a certain point before it collapses into a number of excuses for keeping certain beliefs, in light of evolutionary implications.
According to theoretical physicist Steven Weinberg, teaching cosmology and evolution to students should decrease their self-importance in the universe, as well as their religiosity. Evolutionary developmental biologist PZ Myers' view is that all scientists should be atheists, and that science should never accommodate any religious beliefs. Physicist Sean M. Carroll claims that since religion makes claims that are supernatural, both science and religion are incompatible.
Evolutionary biologist Richard Dawkins is openly hostile to religion because he believes it actively debauches the scientific enterprise and education involving science. According to Dawkins, religion "subverts science and saps the intellect". He believes that when science teachers attempt to expound on evolution, there is hostility aimed towards them by parents who are skeptical because they believe it conflicts with their own religious beliefs, and that even in some textbooks have had the word 'evolution' systematically removed. He has worked to argue the negative effects that he believes religion has on education of science.
According to Renny Thomas' study on Indian scientists, atheistic scientists in India called themselves atheists even while accepting that their lifestyle is very much a part of tradition and religion. Thus, they differ from Western atheists in that for them following the lifestyle of a religion is not antithetical to atheism.
==== Criticism ====
Others such as Francis Collins, George F. R. Ellis, Kenneth R. Miller, Katharine Hayhoe, George Coyne and Simon Conway Morris argue for compatibility since they do not agree that science is incompatible with religion and vice versa. They argue that science provides many opportunities to look for and find God in nature and to reflect on their beliefs. According to Kenneth Miller, he disagrees with Jerry Coyne's assessment and argues that since significant portions of scientists are religious and the proportion of Americans believing in evolution is much higher, it implies that both are indeed compatible. Elsewhere, Miller has argued that when scientists make claims on science and theism or atheism, they are not arguing scientifically at all and are stepping beyond the scope of science into discourses of meaning and purpose. What he finds particularly odd and unjustified is in how atheists often come to invoke scientific authority on their non-scientific philosophical conclusions like there being no point or no meaning to the universe as the only viable option when the scientific method and science never have had any way of addressing questions of meaning or God in the first place. Furthermore, he notes that since evolution made the brain and since the brain can handle both religion and science, there is no natural incompatibility between the concepts at the biological level.
Karl Giberson argues that when discussing compatibility, some scientific intellectuals often ignore the viewpoints of intellectual leaders in theology and instead argue against less informed masses, thereby, defining religion by non-intellectuals and slanting the debate unjustly. He argues that leaders in science sometimes trump older scientific baggage and that leaders in theology do the same, so once theological intellectuals are taken into account, people who represent extreme positions like Ken Ham and Eugenie Scott will become irrelevant. Cynthia Tolman notes that religion does not have a method per se partly because religions emerge through time from diverse cultures, but when it comes to Christian theology and ultimate truths, she notes that people often rely on scripture, tradition, reason, and experience to test and gauge what they experience and what they should believe.
==== Conflict thesis ====
The conflict thesis, which holds that religion and science have been in conflict continuously throughout history, was popularized in the 19th century by John William Draper's and Andrew Dickson White's accounts. It was in the 19th century that relationship between science and religion became an actual formal topic of discourse, while before this no one had pitted science against religion or vice versa, though occasional complex interactions had been expressed before the 19th century. Most contemporary historians of science now reject the conflict thesis in its original form and no longer support it. Instead, it has been superseded by subsequent historical research which has resulted in a more nuanced understanding. Historian of science, Gary Ferngren, has stated: "Although popular images of controversy continue to exemplify the supposed hostility of Christianity to new scientific theories, studies have shown that Christianity has often nurtured and encouraged scientific endeavour, while at other times the two have co-existed without either tension or attempts at harmonization. If Galileo and the Scopes trial come to mind as examples of conflict, they were the exceptions rather than the rule."
Most historians today have moved away from a conflict model, which is based mainly on two historical episodes (Galileo and Darwin), toward compatibility theses (either the integration thesis or non-overlapping magisteria) or toward a "complexity" model, because religious figures were on both sides of each dispute and there was no overall aim by any party involved to discredit religion.
An often cited example of conflict, that has been clarified by historical research in the 20th century, was the Galileo affair, whereby interpretations of the Bible were used to attack ideas by Copernicus on heliocentrism. By 1616 Galileo went to Rome to try to persuade Catholic Church authorities not to ban Copernicus' ideas. In the end, a decree of the Congregation of the Index was issued, declaring that the ideas that the Sun stood still and that the Earth moved were "false" and "altogether contrary to Holy Scripture", and suspending Copernicus's De Revolutionibus until it could be corrected. Galileo was found "vehemently suspect of heresy", namely of having held the opinions that the Sun lies motionless at the center of the universe, that the Earth is not at its centre and moves. He was required to "abjure, curse and detest" those opinions. However, before all this, Pope Urban VIII had personally asked Galileo to give arguments for and against heliocentrism in a book, and to be careful not to advocate heliocentrism as physically proven since the scientific consensus at the time was that the evidence for heliocentrism was very weak. The Church had merely sided with the scientific consensus of the time. Pope Urban VIII asked that his own views on the matter be included in Galileo's book. Only the latter was fulfilled by Galileo. Whether unknowingly or deliberately, Simplicio, the defender of the Aristotelian/Ptolemaic geocentric view in Dialogue Concerning the Two Chief World Systems, was often portrayed as an unlearned fool who lacked mathematical training. Although the preface of his book claims that the character is named after a famous Aristotelian philosopher (Simplicius in Latin, Simplicio in Italian), the name "Simplicio" in Italian also has the connotation of "simpleton". Unfortunately for his relationship with the Pope, Galileo put the words of Urban VIII into the mouth of Simplicio. Most historians agree Galileo did not act out of malice and felt blindsided by the reaction to his book. However, the Pope did not take the suspected public ridicule lightly, nor the physical Copernican advocacy. Galileo had alienated one of his biggest and most powerful supporters, the Pope, and was called to Rome to defend his writings.
The actual evidences that finally proved heliocentrism came centuries after Galileo: the stellar aberration of light by James Bradley in the 18th century, the orbital motions of binary stars by William Herschel in the 19th century, the accurate measurement of the stellar parallax in the 19th century, and Newtonian mechanics in the 17th century. According to physicist Christopher Graney, Galileo's own observations did not actually support the Copernican view, but were more consistent with Tycho Brahe's hybrid model where that Earth did not move and everything else circled around it and the Sun.
British philosopher A. C. Grayling, still believes there is competition between science and religions in areas related to the origin of the universe, the nature of human beings and the possibility of miracles.
=== Independence ===
A modern view, described by Stephen Jay Gould as "non-overlapping magisteria" (NOMA), is that science and religion deal with fundamentally separate aspects of human experience and so, when each stays within its own domain, they co-exist peacefully. While Gould spoke of independence from the perspective of science, W. T. Stace viewed independence from the perspective of the philosophy of religion. Stace felt that science and religion, when each is viewed in its own domain, are both consistent and complete. They originate from different perceptions of reality, as Arnold O. Benz points out, but meet each other, for example, in the feeling of amazement and in ethics.
The USA's National Academy of Sciences supports the view that science and religion are independent.
Science and religion are based on different aspects of human experience. In science, explanations must be based on evidence drawn from examining the natural world. Scientifically based observations or experiments that conflict with an explanation eventually must lead to modification or even abandonment of that explanation. Religious faith, in contrast, does not depend on empirical evidence, is not necessarily modified in the face of conflicting evidence, and typically involves supernatural forces or entities. Because they are not a part of nature, supernatural entities cannot be investigated by science. In this sense, science and religion are separate and address aspects of human understanding in different ways. Attempts to put science and religion against each other create controversy where none needs to exist.
According to Archbishop John Habgood, both science and religion represent distinct ways of approaching experience and these differences are sources of debate. He views science as descriptive and religion as prescriptive. He stated that if science and mathematics concentrate on what the world ought to be, in the way that religion does, it may lead to improperly ascribing properties to the natural world as happened among the followers of Pythagoras in the sixth century B.C. In contrast, proponents of a normative moral science take issue with the idea that science has no way of guiding "oughts". Habgood also stated that he believed that the reverse situation, where religion attempts to be descriptive, can also lead to inappropriately assigning properties to the natural world. A notable example is the now defunct belief in the Ptolemaic (geocentric) planetary model that held sway until changes in scientific and religious thinking were brought about by Galileo and proponents of his views.
In the view of the Lubavitcher rabbi Menachem Mendel Schneerson, non-Euclidean geometry such as Lobachevsky's hyperbolic geometry and Riemann's elliptic geometry proved that Euclid's axioms, such as, "there is only one straight line between two points", are in fact arbitrary. Therefore, science, which relies on arbitrary axioms, can never refute Torah, which is absolute truth.
==== Parallels in method ====
According to Ian Barbour, Thomas S. Kuhn asserted that science is made up of paradigms that arise from cultural traditions, which is similar to the secular perspective on religion.
Michael Polanyi asserted that it is merely a commitment to universality that protects against subjectivity and has nothing at all to do with personal detachment as found in many conceptions of the scientific method. Polanyi further asserted that all knowledge is personal and therefore the scientist must be performing a very personal if not necessarily subjective role when doing science. Polanyi added that the scientist often merely follows intuitions of "intellectual beauty, symmetry, and 'empirical agreement'". Polanyi held that science requires moral commitments similar to those found in religion.
Two physicists, Charles A. Coulson and Harold K. Schilling, both claimed that "the methods of science and religion have much in common." Schilling asserted that both fields—science and religion—have "a threefold structure—of experience, theoretical interpretation, and practical application." Coulson asserted that science, like religion, "advances by creative imagination" and not by "mere collecting of facts," while stating that religion should and does "involve critical reflection on experience not unlike that which goes on in science." Religious language and scientific language also show parallels (cf. rhetoric of science).
=== Dialogue ===
The religion and science community consists of those scholars who involve themselves with what has been called the "religion-and-science dialogue" or the "religion-and-science field." The community belongs to neither the scientific nor the religious community, but is said to be a third overlapping community of interested and involved scientists, priests, clergymen, theologians and engaged non-professionals. Institutions interested in the intersection between science and religion include the Center for Theology and the Natural Sciences, the Institute on Religion in an Age of Science, the Ian Ramsey Centre, and the Faraday Institute. Journals addressing the relationship between science and religion include Theology and Science and Zygon. Eugenie Scott has written that the "science and religion" movement is, overall, composed mainly of theists who have a healthy respect for science and may be beneficial to the public understanding of science. She contends that the "Christian scholarship" movement is not a problem for science, but that the "Theistic science" movement, which proposes abandoning methodological materialism, does cause problems in understanding of the nature of science. The Gifford Lectures were established in 1885 to further the discussion between "natural theology" and the scientific community. This annual series continues and has included William James, John Dewey, Carl Sagan, and many other professors from various fields.
The modern dialogue between religion and science is rooted in Ian Barbour's 1966 book Issues in Science and Religion. Since that time it has grown into a serious academic field, with academic chairs in the subject area, and two dedicated academic journals, Zygon and Theology and Science. Articles are also sometimes found in mainstream science journals such as American Journal of Physics
and Science.
Philosopher Alvin Plantinga has argued that there is superficial conflict but deep concord between science and religion, and that there is deep conflict between science and naturalism. Plantinga, in his book Where the Conflict Really Lies: Science, Religion, and Naturalism, heavily contests the linkage of naturalism with science, as conceived by Richard Dawkins, Daniel Dennett and like-minded thinkers; while Daniel Dennett thinks that Plantinga stretches science to an unacceptable extent. Philosopher Maarten Boudry, in reviewing the book, has commented that he resorts to creationism and fails to "stave off the conflict between theism and evolution." Cognitive scientist Justin L. Barrett, by contrast, reviews the same book and writes that "those most needing to hear Plantinga's message may fail to give it a fair hearing for rhetorical rather than analytical reasons."
=== Integration ===
As a general view, this holds that while interactions are complex between influences of science, theology, politics, social, and economic concerns, the productive engagements between science and religion throughout history should be duly stressed as the norm.
Scientific and theological perspectives often coexist peacefully. Christians and some non-Christian religions have historically integrated well with scientific ideas, as in the ancient Egyptian technological mastery applied to monotheistic ends, the scientific advances made by Muslim scholars during the Ottoman Empire and mathematics under Hinduism and Buddhism. Even many 19th-century Christian communities welcomed scientists who claimed that science was not at all concerned with discovering the ultimate nature of reality. According to Lawrence M. Principe, the Johns Hopkins University Drew Professor of the Humanities, from a historical perspective this points out that much of the current-day clashes occur between limited extremists—both religious and scientistic fundamentalists—over a very few topics, and that the movement of ideas back and forth between scientific and theological thought has been more usual. To Principe, this perspective would point to the fundamentally common respect for written learning in religious traditions of rabbinical literature, Christian theology, and the Islamic Golden Age, including a Transmission of the Classics from Greek to Islamic to Christian traditions which helped spark the Renaissance. Religions have also given key participation in development of modern universities and libraries; centers of learning & scholarship were coincident with religious institutions—whether pagan, Muslim, or Christian.
== Individual religions ==
=== Baháʼí Faith ===
A fundamental principle of the Baháʼí Faith is the harmony of religion and science. Baháʼí scripture asserts that true science and true religion can never be in conflict. `Abdu'l-Bahá, the son of the founder of the religion, stated that religion without science is superstition and that science without religion is materialism. He also admonished that true religion must conform to the conclusions of science.
=== Buddhism ===
Buddhism and science have been regarded as compatible by numerous authors. Some philosophic and psychological teachings found in Buddhism share points in common with modern Western scientific and philosophic thought. For example, Buddhism encourages the impartial investigation of nature (an activity referred to as Dhamma-Vicaya in the Pali Canon)—the principal object of study being oneself. Buddhism and science both show a strong emphasis on causality. However, Buddhism does not focus on materialism.
Tenzin Gyatso, the 14th Dalai Lama, mentions that empirical scientific evidence supersedes the traditional teachings of Buddhism when the two are in conflict. In his book The Universe in a Single Atom he wrote, "My confidence in venturing into science lies in my basic belief that as in science, so in Buddhism, understanding the nature of reality is pursued by means of critical investigation." He also stated, "If scientific analysis were conclusively to demonstrate certain claims in Buddhism to be false," he says, "then we must accept the findings of science and abandon those claims."
=== Christianity ===
Among early Christian teachers, Tertullian (c. 160–220) held a generally negative opinion of Greek philosophy, while Origen (c. 185–254) regarded it much more favorably and required his students to read nearly every work available to them.
Earlier attempts at reconciliation of Christianity with Newtonian mechanics appear quite different from later attempts at reconciliation with the newer scientific ideas of evolution or relativity. Many early interpretations of evolution polarized themselves around a struggle for existence. These ideas were significantly countered by later findings of universal patterns of biological cooperation. According to John Habgood, the universe seems to be a mix of good and evil, beauty and pain, and that suffering may somehow be part of the process of creation. Habgood holds that Christians should not be surprised that suffering may be used creatively by God, given their faith in the symbol of the Cross.
Robert John Russell has examined consonance and dissonance between modern physics, evolutionary biology, and Christian theology.
Christian philosophers Augustine of Hippo (354–430) and Thomas Aquinas (1225–1274) held that scriptures can have multiple interpretations on certain areas where the matters were far beyond their reach, therefore one should leave room for future findings to shed light on the meanings. The "Handmaiden" tradition, which saw secular studies of the universe as a very important and helpful part of arriving at a better understanding of scripture, was adopted throughout Christian history from early on. Also the sense that God created the world as a self operating system is what motivated many Christians throughout the Middle Ages to investigate nature.
Modern historians of science such as J.L. Heilbron, Alistair Cameron Crombie, David Lindberg, Edward Grant, Thomas Goldstein, and Ted Davis have reviewed the popular notion that medieval Christianity was a negative influence in the development of civilization and science. In their views, not only did the monks save and cultivate the remnants of ancient civilization during the barbarian invasions, but the medieval church promoted learning and science through its sponsorship of many universities which, under its leadership, grew rapidly in Europe in the 11th and 12th centuries. Saint Thomas Aquinas, the Church's "model theologian", not only argued that reason is in harmony with faith, he even recognized that reason can contribute to understanding revelation, and so encouraged intellectual development. He was not unlike other medieval theologians who sought out reason in the effort to defend his faith. Some modern scholars, such as Stanley Jaki, have claimed that Christianity with its particular worldview, was a crucial factor for the emergence of modern science.
David C. Lindberg states that the widespread popular belief that the Middle Ages was a time of ignorance and superstition due to the Christian church is a "caricature". According to Lindberg, while there are some portions of the classical tradition which suggest this view, these were exceptional cases. It was common to tolerate and encourage critical thinking about the nature of the world. The relation between Christianity and science is complex and cannot be simplified to either harmony or conflict, according to Lindberg. Lindberg reports that "the late medieval scholar rarely experienced the coercive power of the church and would have regarded himself as free (particularly in the natural sciences) to follow reason and observation wherever they led. There was no warfare between science and the church." Ted Peters in Encyclopedia of Religion writes that although there is some truth in the "Galileo's condemnation" story but through exaggerations, it has now become "a modern myth perpetuated by those wishing to see warfare between science and religion who were allegedly persecuted by an atavistic and dogma-bound ecclesiastical authority". In 1992, the Catholic Church's seeming vindication of Galileo attracted much comment in the media.
A degree of concord between science and religion can be seen in religious belief and empirical science. The belief that God created the world and therefore humans, can lead to the view that he arranged for humans to know the world. This is underwritten by the doctrine of imago dei. In the words of Thomas Aquinas, "Since human beings are said to be in the image of God in virtue of their having a nature that includes an intellect, such a nature is most in the image of God in virtue of being most able to imitate God".
During the Enlightenment, a period "characterized by dramatic revolutions in science" and the rise of Protestant challenges to the authority of the Catholic Church via individual liberty, the authority of Christian scriptures became strongly challenged. As science advanced, acceptance of a literal version of the Bible became "increasingly untenable" and some in that period presented ways of interpreting scripture according to its spirit on its authority and truth.
After the Black Death in Europe, there occurred a generalized decrease in faith in the Catholic Church. The "Natural Sciences" during the Medieval Era focused largely on scientific arguments. The Copernicans, who were generally a small group of privately sponsored individuals, who were deemed Heretics by the Church in some instances. Copernicus and his work challenged the view held by the Catholic Church and the common scientific view at the time, yet according to scholar J. L. Heilbron, the Roman Catholic Church sometimes provided financial support to the Copernicans. In doing so, the Church did support and promote scientific research when the goals in question were in alignment with those of the faith, so long as the findings were in line with the rhetoric of the Church. A case example is the Catholic need for an accurate calendar. Calendar reform was a touchy subject: civilians doubted the accuracy of the mathematics and were upset that the process unfairly selected curators of the reform. The Roman Catholic Church needed a precise date for the Easter Sabbath, and thus the Church was highly supportive of calendar reform. The need for the correct date of Easter was also the impetus of cathedral construction. Cathedrals essentially functioned as massive scale sun dials and, in some cases, camera obscuras. They were efficient scientific devices because they rose high enough for their naves to determine the summer and winter solstices. Heilbron contends that as far back as the twelfth century, the Roman Catholic Church was funding scientific discovery and the recovery of ancient Greek scientific texts. However, the Copernican revolution challenged the view held the Catholic Church and placed the Sun at the center of the Solar System.
==== Perspectives on evolution ====
In recent history, the theory of evolution has been at the center of some controversy between Christianity and science. Christians who accept a literal interpretation of the biblical account of creation find incompatibility between Darwinian evolution and their interpretation of the Christian faith. Creation science or scientific creationism is a branch of creationism that attempts to provide scientific support for a literal reading of the Genesis creation narrative in the Book of Genesis and attempts to disprove generally accepted scientific facts, theories and scientific paradigms about the geological history of the Earth, cosmology of the early universe,
the chemical origins of life and biological evolution. It began in the 1960s as a fundamentalist Christian effort in the United States to prove Biblical inerrancy and falsify the scientific evidence for evolution. It has since developed a sizable religious following in the United States, with creation science ministries branching worldwide. In 1925, The State of Tennessee passed the Butler Act, which prohibited the teaching of the theory of evolution in all schools in the state. Later that year, a similar law was passed in Mississippi, and likewise, Arkansas in 1927. In 1968, these "anti-monkey" laws were struck down by the Supreme Court of the United States as unconstitutional, "because they established a religious doctrine violating both the First and Fourth Amendments to the Constitution."
Most scientists have rejected creation science for several reasons, including that its claims do not refer to natural causes and cannot be tested. In 1987, the United States Supreme Court ruled that creationism is religion, not science, and cannot be advocated in public school classrooms. In 2018, the Orlando Sentinel reported that "Some private schools in Florida that rely on public funding teach students" Creationism.
Theistic evolution attempts to reconcile Christian beliefs and science by accepting the scientific understanding of the age of the Earth and the process of evolution. It includes a range of beliefs, including views described as evolutionary creationism, which accepts some findings of modern science but also upholds classical religious teachings about God and creation in Christian context.
==== Roman Catholicism ====
While refined and clarified over the centuries, the Roman Catholic position on the relationship between science and religion is one of harmony, and has maintained the teaching of natural law as set forth by Thomas Aquinas. For example, regarding scientific study such as that of evolution, the church's unofficial position is an example of theistic evolution, stating that faith and scientific findings regarding human evolution are not in conflict, though humans are regarded as a special creation, and that the existence of God is required to explain both monogenism and the spiritual component of human origins. Catholic schools have included all manners of scientific study in their curriculum for many centuries.
Galileo once stated that "The intention of the Holy Spirit is to teach us how to go to heaven, not how the heavens go." In 1981, Pope John Paul II, then leader of the Roman Catholic Church, spoke of the relationship this way: "The Bible itself speaks to us of the origin of the universe and its make-up, not in order to provide us with a scientific treatise, but in order to state the correct relationships of man with God and with the universe. Sacred Scripture wishes simply to declare that the world was created by God, and in order to teach this truth it expresses itself in the terms of the cosmology in use at the time of the writer".
Pope Francis, in his encyclical letter Laudato si', affirms his opinion that "science and religion, with their distinctive approaches to understanding reality, can
enter into an intense dialogue fruitful for both".
==== Influence of a biblical worldview on early modern science ====
According to Andrew Dickson White's A History of the Warfare of Science with Theology in Christendom from the 19th century, a biblical world view affected negatively the progress of science through time. Dickinson also argues that immediately following the Reformation matters were even worse. The interpretations of Scripture by Luther and Calvin became as sacred to their followers as the Scripture itself. For instance, when Georg Calixtus ventured, in interpreting the Psalms, to question the accepted belief that "the waters above the heavens" were contained in a vast receptacle upheld by a solid vault, he was bitterly denounced as heretical. Today, much of the scholarship in which the conflict thesis was originally based is considered to be inaccurate. For instance, the claim that early Christians rejected scientific findings by the Greco-Romans is false, since the "handmaiden" view of secular studies was seen to shed light on theology. This view was widely adapted throughout the early medieval period and afterwards by theologians (such as Augustine) and ultimately resulted in fostering interest in knowledge about nature through time. Also, the claim that people of the Middle Ages widely believed that the Earth was flat was first propagated in the same period that originated the conflict thesis and is still very common in popular culture. Modern scholars regard this claim as mistaken, as the contemporary historians of science David C. Lindberg and Ronald L. Numbers write: "there was scarcely a Christian scholar of the Middle Ages who did not acknowledge [earth's] sphericity and even know its approximate circumference." From the fall of Rome to the time of Columbus, all major scholars and many vernacular writers interested in the physical shape of the earth held a spherical view with the exception of Lactantius and Cosmas.
H. Floris Cohen argued for a biblical Protestant, but not excluding Catholicism, influence on the early development of modern science. He presented Dutch historian R. Hooykaas' argument that a biblical world-view holds all the necessary antidotes for the hubris of Greek rationalism: a respect for manual labour, leading to more experimentation and empiricism, and a supreme God that left nature open to emulation and manipulation. It supports the idea early modern science rose due to a combination of Greek and biblical thought.
Oxford historian Peter Harrison is another who has argued that a biblical worldview was significant for the development of modern science. Harrison contends that Protestant approaches to the book of scripture had significant, if largely unintended, consequences for the interpretation of the book of nature. Harrison has also suggested that literal readings of the Genesis narratives of the Creation and Fall motivated and legitimated scientific activity in seventeenth-century England. For many of its seventeenth-century practitioners, science was imagined to be a means of restoring a human dominion over nature that had been lost as a consequence of the Fall.
Historian and professor of religion Eugene M. Klaaren holds that "a belief in divine creation" was central to an emergence of science in seventeenth-century England. The philosopher Michael Foster has published analytical philosophy connecting Christian doctrines of creation with empiricism. Historian William B. Ashworth has argued against the historical notion of distinctive mind-sets and the idea of Catholic and Protestant sciences. Historians James R. Jacob and Margaret C. Jacob have argued for a linkage between seventeenth-century Anglican intellectual transformations and influential English scientists (e.g., Robert Boyle and Isaac Newton). John Dillenberger and Christopher B. Kaiser have written theological surveys, which also cover additional interactions occurring in the 18th, 19th, and 20th centuries. Philosopher of Religion, Richard Jones, has written a philosophical critique of the "dependency thesis" which assumes that modern science emerged from Christian sources and doctrines. Though he acknowledges that modern science emerged in a religious framework, that Christianity greatly elevated the importance of science by sanctioning and religiously legitimizing it in the medieval period, and that Christianity created a favorable social context for it to grow; he argues that direct Christian beliefs or doctrines were not primary sources of scientific pursuits by natural philosophers, nor was Christianity, in and of itself, exclusively or directly necessary in developing or practicing modern science.
Oxford University historian and theologian John Hedley Brooke wrote that "when natural philosophers referred to laws of nature, they were not glibly choosing that metaphor. Laws were the result of legislation by an intelligent deity. Thus the philosopher René Descartes (1596–1650) insisted that he was discovering the "laws that God has put into nature." Later Newton would declare that the regulation of the solar system presupposed the "counsel and dominion of an intelligent and powerful Being." Historian Ronald L. Numbers stated that this thesis "received a boost" from mathematician and philosopher Alfred North Whitehead's Science and the Modern World (1925). Numbers has also argued, "Despite the manifest shortcomings of the claim that Christianity gave birth to science—most glaringly, it ignores or minimizes the contributions of ancient Greeks and medieval Muslims—it too, refuses to succumb to the death it deserves." The sociologist Rodney Stark of Baylor University, argued in contrast that "Christian theology was essential for the rise of science."
Protestantism had an important influence on science. According to the Merton Thesis there was a positive correlation between the rise of Puritanism and Protestant Pietism on the one hand and early experimental science on the other. The Merton Thesis has two separate parts: Firstly, it presents a theory that science changes due to an accumulation of observations and improvement in experimental techniques and methodology; secondly, it puts forward the argument that the popularity of science in 17th-century England and the religious demography of the Royal Society (English scientists of that time were predominantly Puritans or other Protestants) can be explained by a correlation between Protestantism and the scientific values. In his theory, Robert K. Merton focused on English Puritanism and German Pietism as having been responsible for the development of the scientific revolution of the 17th and 18th centuries. Merton explained that the connection between religious affiliation and interest in science was the result of a significant synergy between the ascetic Protestant values and those of modern science. Protestant values encouraged scientific research by allowing science to study God's influence on the world and thus providing a religious justification for scientific research.
Some scholars have noted a direct tie between "particular aspects of traditional Christianity" and the rise of science. Other scholars and historians attribute Christianity to having contributed to the rise of the Scientific Revolution.
==== Reconciliation in Britain in the early 20th century ====
In Reconciling Science and Religion: The Debate in Early-twentieth-century Britain, historian of biology Peter J. Bowler argues that in contrast to the conflicts between science and religion in the U.S. in the 1920s (most famously the Scopes Trial), during this period Great Britain experienced a concerted effort at reconciliation, championed by intellectually conservative scientists, supported by liberal theologians but opposed by younger scientists and secularists and conservative Christians. These attempts at reconciliation fell apart in the 1930s due to increased social tensions, moves towards neo-orthodox theology and the acceptance of the modern evolutionary synthesis.
In the 20th century, several ecumenical organizations promoting a harmony between science and Christianity were founded, most notably the American Scientific Affiliation, The Biologos Foundation, Christians in Science, The Society of Ordained Scientists, and The Veritas Forum.
=== Confucianism and traditional Chinese religion ===
The historical process of Confucianism has largely been antipathic towards scientific discovery. However the religio-philosophical system itself is more neutral on the subject than such an analysis might suggest. In his writings On Heaven, Xunzi espoused a proto-scientific world view. However, during the Han Synthesis the more anti-empirical Mencius was favored and combined with Daoist skepticism regarding the nature of reality. Likewise, during the medieval period, Zhu Xi argued against technical investigation and specialization proposed by Chen Liang. After contact with the West, scholars such as Wang Fuzhi would rely on Buddhist/Daoist skepticism to denounce all science as a subjective pursuit limited by humanity's fundamental ignorance of the true nature of the world.
The Jesuits from Europe taught Western math and science to the Chinese bureaucrats in hopes of religious conversion. This process saw several challenges of both European and Chinese spiritual and scientific beliefs. The keynote text of Chinese scientific philosophy, The Book of Changes (or Yi Jing) was initially mocked and disregarded by the Westerners. In return, Confucian scholars Dai Zhen and Ji Yun found the concept of phantoms laughable and ridiculous. The Book of Changes outlined orthodoxy cosmology in the Qing, including yin and yang and the five cosmic phases. Sometimes the missionary exploits proved dangerous for the Westerners. Jesuit missionaries and scholars Ferdinand Vervbiest and Adam Schall were punished after using scientific methods to determine the exact time of the 1664 eclipse. However, the European mission eastward did not only cause conflict. Joachim Bouvet, a theologian who held equal respect for both the Bible and the Book of Changes, was productive in his mission of spreading the Christian faith.
After the May Fourth Movement, attempts to modernize Confucianism and reconcile it with scientific understanding were attempted by many scholars including Feng Youlan and Xiong Shili. Given the close relationship that Confucianism shares with Buddhism, many of the same arguments used to reconcile Buddhism with science also readily translate to Confucianism. However, modern scholars have also attempted to define the relationship between science and Confucianism on Confucianism's own terms and the results have usually led to the conclusion that Confucianism and science are fundamentally compatible.
=== Hinduism ===
In Hinduism, the dividing line between objective sciences and spiritual knowledge (adhyatma vidya) is a linguistic paradox. Hindu scholastic activities and ancient Indian scientific advancements were so interconnected that many Hindu scriptures are also ancient scientific manuals and vice versa. In 1835, English was made the primary language for teaching in higher education in India, exposing Hindu scholars to Western secular ideas; this started a renaissance regarding religious and philosophical thought. Hindu sages maintained that logical argument and rational proof using Nyaya is the way to obtain correct knowledge. The scientific level of understanding focuses on how things work and from where they originate, while Hinduism strives to understand the ultimate purposes for the existence of living things. To obtain and broaden the knowledge of the world for spiritual perfection, many refer to the Bhāgavata for guidance because it draws upon a scientific and theological dialogue. Hinduism offers methods to correct and transform itself in course of time. For instance, Hindu views on the development of life include a range of viewpoints in regards to evolution, creationism, and the origin of life within the traditions of Hinduism. For instance, it has been suggested that Wallace-Darwininan evolutionary thought was a part of Hindu thought centuries before modern times. The Shankara and the Sāmkhya did not have a problem with the theory of evolution, but instead, argued about the existence of God and what happened after death. These two distinct groups argued among each other's philosophies because of their texts, not the idea of evolution. With the publication of Darwin's On the Origin of Species, many Hindus were eager to connect their scriptures to Darwinism, finding similarities between Brahma's creation, Vishnu's incarnations, and evolution theories.
Samkhya, the oldest school of Hindu philosophy prescribes a particular method to analyze knowledge. According to Samkhya, all knowledge is possible through three means of valid knowledge –
Pratyakṣa or Dṛṣṭam – direct sense perception,
Anumāna – logical inference and
Śabda or Āptavacana – verbal testimony.
Nyaya, the Hindu school of logic, accepts all these 3 means and in addition accepts one more – Upamāna (comparison).
The accounts of the emergence of life within the universe vary in description, but classically the deity called Brahma, from a Trimurti of three deities also including Vishnu and Shiva, is described as performing the act of 'creation', or more specifically of 'propagating life within the universe' with the other two deities being responsible for 'preservation' and 'destruction' (of the universe) respectively. In this respect some Hindu schools do not treat the scriptural creation myth literally and often the creation stories themselves do not go into specific detail, thus leaving open the possibility of incorporating at least some theories in support of evolution. Some Hindus find support for, or foreshadowing of evolutionary ideas in scriptures, namely the Vedas.
The incarnations of Vishnu (Dashavatara) is almost identical to the scientific explanation of the sequence of biological evolution of man and animals. The sequence of avatars starts from an aquatic organism (Matsya), to an amphibian (Kurma), to a land-animal (Varaha), to a humanoid (Narasimha), to a dwarf human (Vamana), to 5 forms of well developed human beings (Parashurama, Rama, Balarama/Buddha, Krishna, Kalki) who showcase an increasing form of complexity (Axe-man, King, Plougher/Sage, wise Statesman, mighty Warrior). In fact, many Hindu gods are represented with features of animals as well as those of humans, leading many Hindus to easily accept evolutionary links between animals and humans. In India, the home country of Hindus, educated Hindus widely accept the theory of biological evolution. In a survey of 909 people, 77% of respondents in India agreed with Charles Darwin's Theory of Evolution, and 85 per cent of God-believing people said they believe in evolution as well.
As per Vedas, another explanation for the creation is based on the five elements: earth, water, fire, air and aether.
The Hindu religion traces its beginnings to the Vedas. Everything that is established in the Hindu faith such as the gods and goddesses, doctrines, chants, spiritual insights, etc. flow from the poetry of Vedic hymns. The Vedas offer an honor to the sun and moon, water and wind, and to the order in Nature that is universal. This naturalism is the beginning of what further becomes the connection between Hinduism and science.
=== Islam ===
From an Islamic standpoint, science, the study of nature, is considered to be linked to the concept of Tawhid (the Oneness of God), as are all other branches of knowledge. In Islam, nature is not seen as a separate entity, but rather as an integral part of Islam's holistic outlook on God, humanity, and the world. The Islamic view of science and nature is continuous with that of religion and God. This link implies a sacred aspect to the pursuit of scientific knowledge by Muslims, as nature itself is viewed in the Qur'an as a compilation of signs pointing to the Divine. It was with this understanding that science was studied and understood in Islamic civilizations, specifically during the eighth to sixteenth centuries, prior to the colonization of the Muslim world. Robert Briffault, in The Making of Humanity, asserts that the very existence of science, as it is understood in the modern sense, is rooted in the scientific thought and knowledge that emerged in Islamic civilizations during this time. Ibn al-Haytham, an Arab Muslim, was an early proponent of the concept that a hypothesis must be proved by experiments based on confirmable procedures or mathematical evidence—hence understanding the scientific method 200 years before Renaissance scientists. Ibn al-Haytham described his theology:
I constantly sought knowledge and truth, and it became my belief that for gaining access to the effulgence and closeness to God, there is no better way than that of searching for truth and knowledge.
With the decline of Islamic Civilizations in the late Middle Ages and the rise of Europe, the Islamic scientific tradition shifted into a new period. Institutions that had existed for centuries in the Muslim world looked to the new scientific institutions of European powers. This changed the practice of science in the Muslim world, as Islamic scientists had to confront the western approach to scientific learning, which was based on a different philosophy of nature. From the time of this initial upheaval of the Islamic scientific tradition to the present day, Muslim scientists and scholars have developed a spectrum of viewpoints on the place of scientific learning within the context of Islam, none of which are universally accepted or practiced. However, most maintain the view that the acquisition of knowledge and scientific pursuit in general is not in disaccord with Islamic thought and religious belief.
During the thirteenth century, the Caliphate system in the Islamic Empire fell, and scientific discovery thrived. The Islamic Civilization has a long history of scientific advancement; and their theological practices catalyzed a great deal of scientific discovery. In fact, it was due to necessities of Muslim worship and their vast empire that much science and philosophy was created. People needed to know in which direction they needed to pray toward to face Mecca. Many historians through time have asserted that all modern science originates from ancient Greek scholarship; but scholars like Martin Bernal have claimed that most ancient Greek scholarship relied heavily on the work of scholars from ancient Egypt and the Levant. Ancient Egypt was the foundational site of the Hermetic School, which believed that the sun represented an invisible God. Amongst other things, Islamic civilization was key because it documented and recorded Greek scholarship.
==== Ahmadiyya ====
The Ahmadiyya movement emphasize that "there is no contradiction between Islam and science". For example, Ahmadi Muslims universally accept in principle the process of evolution, albeit divinely guided, and actively promote it. Over the course of several decades the movement has issued various publications in support of the scientific concepts behind the process of evolution, and frequently engages in promoting how religious scriptures, such as the Qur'an, supports the concept. For general purposes, the second Khalifa of the community, Mirza Basheer-ud-Din Mahmood Ahmad says:
The Holy Quran directs attention towards science, time and again, rather than evoking prejudice against it. The Quran has never advised against studying science, lest the reader should become a non-believer; because it has no such fear or concern. The Holy Quran is not worried that if people will learn the laws of nature its spell will break. The Quran has not prevented people from science, rather it states, "Say, 'Reflect on what is happening in the heavens and the earth.'" (Al Younus)
=== Jainism ===
==== Biology ====
Jainism classifies life into two main divisions those who are static by nature (sthavar) and those who are mobile (trasa).
Jain texts describes life in plant long before Jagdish Chandra Bose proved that plants have life. In the Jain philosophy the plant lives are termed as 'Vanaspatikaya'.
==== Jainism and non-creationism ====
Jain theory of causality holds that a cause and its effect are always identical in nature and an immaterial entity like a creator God cannot be the cause of a material entity like the universe. According to Jain belief, it is not possible to create matter out of nothing.[a] The universe and its constituents– soul, matter, space, time, and natural laws have always existed (a static universe, similar to that proposed by the steady state cosmological model).
== Surveys on scientists and the general public ==
=== Scientists ===
Between 1901 and 2000, 654 Nobel prize laureates belonged to 28 different religions. Most (65%) have identified Christianity in its various forms as their religious preference. Specifically on the science-related prizes, Christians have won a total of 73% of all the Chemistry, 65% in Physics, 62% in Medicine, and 54% in all Economics awards. Jews have won 17% of the prizes in Chemistry, 26% in Medicine, and 23% in Physics. Atheists, Agnostics, and Freethinkers have won 7% of the prizes in Chemistry, 9% in Medicine, and 5% in Physics. Muslims have won 13 prizes (three were in scientific categories).
According to scholar Benjamin Beit-Hallahmi, between 1901–2001, about 57% of laureates in scientific fields were Christians, and 26% were of Jewish descent (including Jewish atheists).
==== Global ====
According to a global study on scientists, a significant portion of scientists around the world have religious identities, beliefs, and practices overall. Furthermore, the majority of scientists do not believe there is inherent conflict in being religious and a scientist and stated that "the conflict perspective on science and religion is an invention of the West" since such a view is not prevalent among most of scientists around the world. Instead of seeing religion and science as 'always in conflict' they rather view it through the lenses of various cultural dimensions to the relations between religion and science.
==== Europe ====
According to a study from 2023 "30–39% of Western-European researchers identify with “some religious affiliation”. "30–37% of scientists identify as non-believers or atheists, and an additional 10–28% as agnostic (with wide geographical differences)".
==== United States ====
In 1916, 1,000 leading American scientists were randomly chosen from American Men of Science and 42% believed God existed, 42% disbelieved, and 17% had doubts/did not know; however, when the study was replicated 80 years later using American Men and Women of Science in 1996, the results were very much the same with 39% believing God exists, 45% disbelieved, and 15% had doubts/did not know. In the same 1996 survey, for scientists in the fields of biology, mathematics, and physics/astronomy, belief in a god that is "in intellectual and affective communication with humankind" was most popular among mathematicians (about 45%) and least popular among physicists (about 22%).
In terms of belief in God among elite scientists, such as "great scientists" in the "American Men of Science" or members of the National Academies of Science; 53% disbelieved, 21% were agnostic, and 28% believed in 1914; 68% disbelieved, 17% were agnostic, and 15% believed in 1933; and 72% disbelieved, 21% were agnostic, and 7% believed in 1998. However Eugenie Scott argued that there are methodological issues in the study, including ambiguity in the questions such using a personal definition of God instead of broader definitions of God. A study with simplified wording to include impersonal or non-interventionist ideas of God concluded that 40% of "prominent scientists" in the US believe in a god.
Others have also observed some methodological issues which impacted the results.
A survey conducted between 2005 and 2007 by Elaine Howard Ecklund of University at Buffalo, The State University of New York of 1,646 natural and social science professors at 21 US research universities found that, in terms of belief in God or a higher power, more than 60% expressed either disbelief or agnosticism and more than 30% expressed belief. More specifically, nearly 34% answered "I do not believe in God" and about 30% answered "I do not know if there is a God and there is no way to find out." In the same study, 28% said they believed in God and 8% believed in a higher power that was not God. Ecklund stated that scientists were often able to consider themselves spiritual without religion or belief in god. Ecklund and Scheitle concluded, from their study, that the individuals from non-religious backgrounds disproportionately had self-selected into scientific professions and that the assumption that becoming a scientist necessarily leads to loss of religion is untenable since the study did not strongly support the idea that scientists had dropped religious identities due to their scientific training. Instead, factors such as upbringing, age, and family size were significant influences on religious identification since those who had religious upbringing were more likely to be religious and those who had a non-religious upbringing were more likely to not be religious. The authors also found little difference in religiosity between social and natural scientists.
In terms of perceptions, most social and natural scientists from 21 American universities did not perceive conflict between science and religion, while 37% did. However, in the study, scientists who had experienced limited exposure to religion tended to perceive conflict. In the same study they found that nearly one in five atheist scientists who are parents (17%) are part of religious congregations and have attended a religious service more than once in the past year. Some of the reasons for doing so are their scientific identity (wishing to expose their children to all sources of knowledge so they can make up their own minds), spousal influence, and desire for community.
A 2009 report by the Pew Research Center found that members of the American Association for the Advancement of Science (AAAS) were "much less religious than the general public," with 51% believing in some form of deity or higher power. Specifically, 33% of those polled believe in God, 18% believe in a universal spirit or higher power, and 41% did not believe in either God or a higher power. 48% say they have a religious affiliation, equal to the number who say they are not affiliated with any religious tradition. 17% were atheists, 11% were agnostics, 20% were nothing in particular, 8% were Jewish, 10% were Catholic, 16% were Protestant, 4% were Evangelical, 10% were other religion. The survey also found younger scientists to be "substantially more likely than their older counterparts to say they believe in God". Among the surveyed fields, chemists were the most likely to say they believe in God.
Elaine Ecklund conducted a study from 2011 to 2014 involving the general US population, including rank and file scientists, in collaboration with the AAAS. The study noted that 76% of the scientists identified with a religious tradition. 85% of evangelical scientists had no doubts about the existence of God, compared to 35% of the whole scientific population. In terms of religion and science, 85% of evangelical scientists saw no conflict (73% collaboration, 12% independence), while 75% of the whole scientific population saw no conflict (40% collaboration, 35% independence).
Religious beliefs of US professors were examined using a nationally representative sample of more than 1,400 professors. They found that in the social sciences: 23% did not believe in God, 16% did not know if God existed, 43% believed God existed, and 16% believed in a higher power. Out of the natural sciences: 20% did not believe in God, 33% did not know if God existed, 44% believed God existed, and 4% believed in a higher power. Overall, out of the whole study: 10% were atheists, 13% were agnostic, 19% believe in a higher power, 4% believe in God some of the time, 17% had doubts but believed in God, 35% believed in God and had no doubts.
In 2005, Farr Curlin, a University of Chicago Instructor in Medicine and a member of the MacLean Center for Clinical Medical Ethics, noted in a study that doctors tend to be science-minded religious people. He helped author a study that "found that 76 percent of doctors believe in God and 59 percent believe in some sort of afterlife." Furthermore, "90 percent of doctors in the United States attend religious services at least occasionally, compared to 81 percent of all adults." He reasoned, "The responsibility to care for those who are suffering and the rewards of helping those in need resonate throughout most religious traditions.". A study from 2017 showed 65% of physicians believe in God.
==== Other or multiple countries ====
According to the Study of Secularism in Society and Culture's report on 1,100 scientists in India: 66% are Hindu, 14% did not report a religion, 10% are atheist/no religion, 3% are Muslim, 3% are Christian, 4% are Buddhist, Sikh or other. 39% have a belief in a god, 6% have belief in a god sometimes, 30% do not believe in a god but believe in a higher power, 13% do not know if there is a god, and 12% do not believe in a god. 49% believe in the efficacy of prayer, 90% strongly agree or somewhat agree with approving degrees in Ayurvedic medicine. Furthermore, the term "secularism" is understood to have diverse and simultaneous meanings among Indian scientists: 93% believe it to be tolerance of religions and philosophies, 83% see it as involving separation of church and state, 53% see it as not identifying with religious traditions, 40% see it as absence of religious beliefs, and 20% see it as atheism. Accordingly, 75% of Indian scientists had a "secular" outlook in terms of being tolerant of other religions.
According to the Religion Among Scientists in International Context (RASIC) study on 1,581 scientists from the United Kingdom and 1,763 scientists from India, along with 200 interviews: 65% of U.K. scientists identified as nonreligious and only 6% of Indian scientists identify as nonreligious, 12% of scientists in the U.K. attend religious services on a regular basis and 32% of scientists in India do. In terms of the Indian scientists, 73% of scientists responded that there are basic truths in many religions, 27% said they believe in God and 38% expressed belief in a higher power of some kind. In terms of perceptions of conflict between science and religion, less than half of both U.K. scientists (38%) and Indian scientists (18%) perceived conflict between religion and science.
According to Elaine Ecklund's research on 1,293 atheist scientists from the US and UK, a majority of atheist scientists came from a nonreligious upbringing and never had a religious affiliation. Also, fewer than half of the atheist scientists who were exposed to religion in their youth said science played a role in them becoming an atheist.
=== General public ===
Global studies which have pooled data on religion and science from 1981 to 2001, have noted that countries with greater faith in science also often have stronger religious beliefs, while less religious countries have more skepticism of the impact of science and technology.
Other research cites the National Science Foundation's finding that America has more favorable public attitudes towards science than Europe, Russia, and Japan despite differences in levels of religiosity in these cultures.
Other cross-national studies have found no correlations supporting the contention that religiosity undermines interest in science topics or activities among the general populations globally.
Cross-cultural studies indicate that people tend to use both natural and supernatural explanations for explaining numerous things about the world such as illness, death, and origins. In other words, they do not think of natural and supernatural explanations as antagonistic or dichotomous, but instead see them as coexisting and complementary. The reconciliation of natural and supernatural explanations is normal and pervasive from a psychological standpoint across cultures.
==== Europe ====
A study conducted on adolescents from Christian schools in Northern Ireland, noted a positive relationship between attitudes towards Christianity and science once attitudes towards scientism and creationism were accounted for.
A study on people from Sweden concludes that though the Swedes are among the most non-religious, paranormal beliefs are prevalent among both the young and adult populations. This is likely due to a loss of confidence in institutions such as the Church and Science.
Concerning specific topics like creationism, it is not an exclusively American phenomenon. A poll on adult Europeans revealed that 40% believed in naturalistic evolution, 21% in theistic evolution, 20% in special creation, and 19% are undecided; with the highest concentrations of young earth creationists in Switzerland (21%), Austria (20%), Germany (18%). Other countries such as Netherlands, Britain, and Australia have experienced growth in such views as well.
==== United States ====
According to a 2015 Pew Research Center Study on the public perceptions on science, people's perceptions on conflict with science have more to do with their perceptions of other people's beliefs than their own personal beliefs. For instance, the majority of people with a religious affiliation (68%) saw no conflict between their own personal religious beliefs and science while the majority of those without a religious affiliation (76%) perceived science and religion to be in conflict. The study noted that people who are not affiliated with any religion, also known as "religiously unaffiliated", often have supernatural beliefs and spiritual practices despite them not being affiliated with any religion and also that "just one-in-six religiously unaffiliated adults (16%) say their own religious beliefs conflict with science." Furthermore, the study observed, "The share of all adults who perceive a conflict between science and their own religious beliefs has declined somewhat in recent years, from 36% in 2009 to 30% in 2014. Among those who are affiliated with a religion, the share of people who say there is a conflict between science and their personal religious beliefs dropped from 41% to 34% during this period."
In a 2024 Pew research center report, only 35% of "nones" (atheist, agnostics, and nothing in particular on religious affiliation); believe that the natural world is all there is, while the majority of nones (63%) believe there are spiritual things beyond the world; and the majority of nones (56%) also believe there are some things that science cannot explain.
The 2013 MIT Survey on Science, Religion and Origins examined the views of religious people in America on origins science topics like evolution, the Big Bang, and perceptions of conflicts between science and religion. It found that a large majority of religious people see no conflict between science and religion and only 11% of religious people belong to religions openly rejecting evolution. The fact that the gap between personal and official beliefs of their religions is so large suggests that part of the problem, might be defused by people learning more about their own religious doctrine and the science it endorses, thereby bridging this belief gap. The study concluded that "mainstream religion and mainstream science are neither attacking one another nor perceiving a conflict." Furthermore, they note that this conciliatory view is shared by most leading science organizations such as the American Association for the Advancement of Science (AAAS).
A study was made in collaboration with the AAAS collecting data on the general public from 2011 to 2014, with the focus on evangelicals and evangelical scientists. Even though evangelicals make up only 26% of the US population, the study found that nearly 70 percent of all evangelical Christians do not view science and religion as being in conflict with each other (48% saw them as complementary and 21% saw them as independent) while 73% of the general US population saw no conflict either.
According to Elaine Ecklund's 2018 study, the majority of religious groups see religion and science in collaboration or independent of each other, while the majority of groups without religion see science and religion in conflict.
Other lines of research on perceptions of science among the American public conclude that most religious groups see no general epistemological conflict with science and they have no differences with nonreligious groups in the propensity of seeking out scientific knowledge, although there may be subtle epistemic or moral conflicts when scientists make counterclaims to religious tenets. Findings from the Pew Center note similar findings and also note that the majority of Americans (80–90%) show strong support for scientific research, agree that science makes society and individual's lives better, and 8 in 10 Americans would be happy if their children were to become scientists. Even strict creationists tend to have very favorable views on science.
According to a 2007 poll by the Pew Forum, "while large majorities of Americans respect science and scientists, they are not always willing to accept scientific findings that squarely contradict their religious beliefs." The Pew Forum states that specific factual disagreements are "not common today", though 40% to 50% of Americans do not accept the evolution of humans and other living things, with the "strongest opposition" coming from evangelical Christians at 65% saying life did not evolve. 51% of the population believes humans and other living things evolved: 26% through natural selection only, 21% somehow guided, 4% do not know. In the U.S., biological evolution is the only concrete example of conflict where a significant portion of the American public denies scientific consensus for religious reasons. In terms of advanced industrialized nations, the United States is the most religious.
A 2009 study from the Pew Research Center on Americans perceptions of science, showed a broad consensus that most Americans, including most religious Americans, hold scientific research and scientists themselves in high regard. The study showed that 84% of Americans say they view science as having a mostly positive impact on society. Among those who attend religious services at least once a week, the number is roughly the same at 80%. Furthermore, 70% of U.S. adults think scientists contribute "a lot" to society.
A 2011 study on a national sample of US college students examined whether these students viewed the science / religion relationship as reflecting primarily conflict, collaboration, or independence. The study concluded that the majority of undergraduates in both the natural and social sciences do not see conflict between science and religion. Another finding in the study was that it is more likely for students to move away from a conflict perspective to an independence or collaboration perspective than towards a conflict view.
In the US, people who had no religious affiliation were no more likely than the religious population to have New Age beliefs and practices.
== See also ==
== References ==
== Sources ==
== Further reading ==
== External links == | Wikipedia/Relationship_between_religion_and_science |
Hippocrates of Kos (; Ancient Greek: Ἱπποκράτης ὁ Κῷος, romanized: Hippokrátēs ho Kôios; c. 460 – c. 370 BC), also known as Hippocrates II, was a Greek physician and philosopher of the classical period who is considered one of the most outstanding figures in the history of medicine. He is traditionally referred to as the "Father of Medicine" in recognition of his lasting contributions to the field, such as the use of prognosis and clinical observation, the systematic categorization of diseases, and the (however misguided) formulation of humoral theory. His studies set out the basic ideas of modern-day specialties, including surgery, urology, neurology, acute medicine and orthopedics. The Hippocratic school of medicine revolutionized ancient Greek medicine, establishing it as a discipline distinct from other fields with which it had traditionally been associated (theurgy and philosophy), thus establishing medicine as a profession.
However, the achievements of the writers of the Hippocratic Corpus, the practitioners of Hippocratic medicine, and the actions of Hippocrates himself were often conflated; thus very little is known about what Hippocrates actually thought, wrote, and did. Hippocrates is commonly portrayed as the paragon of the ancient physician and credited with coining the Hippocratic Oath, which is still relevant and in use today. He is also credited with greatly advancing the systematic study of clinical medicine, summing up the medical knowledge of previous schools, and prescribing practices for physicians through the Hippocratic Corpus and other works.
== Biography ==
Historians agree that Hippocrates was born around the year 460 BC on the Greek island of Kos; other biographical information, however, is likely to be untrue.
Soranus of Ephesus, a 2nd-century Greek physician, was Hippocrates's first biographer and is the source of most personal information about him. Later biographies are in the Suda of the 10th century AD, and in the works of John Tzetzes, which date from the 12th century AD. Hippocrates is mentioned in passing in the writings of two contemporaries: in Plato's dialogues Protagoras and Phaedrus, and in Aristotle's Politics, all of which date from the 4th century BC.
Soranus wrote that Hippocrates's father was Heraclides, a physician, and his mother was Praxitela, daughter of Tizane. The two sons of Hippocrates, Thessalus and Draco, and his son-in-law, Polybus, were his students. According to Galen, a later physician, Polybus was Hippocrates's true successor, while Thessalus and Draco each had a son named Hippocrates (Hippocrates III and IV).
Soranus said that Hippocrates learned medicine from his father and grandfather (Hippocrates I), and studied other subjects with Democritus and Gorgias. Hippocrates was probably trained at the asklepieion of Kos, and took lessons from the Thracian physician Herodicus of Selymbria. Plato mentions Hippocrates in two of his dialogues: in Protagoras, Plato describes Hippocrates as "Hippocrates of Kos, the Asclepiad"; while in Phaedrus, Plato suggests that "Hippocrates the Asclepiad" thought that a complete knowledge of the nature of the body was necessary for medicine. Hippocrates taught and practiced medicine throughout his life, traveling at least as far as Thessaly, Thrace, and the Sea of Marmara. Several different accounts of his death exist. He died, probably in Larissa, at the age of 83, 85 or 90, though some say he lived to be well over 100.
== Hippocratic theory ==
It is thus with regard to the disease called Sacred: it appears to me to be nowise more divine nor more sacred than other diseases, but has a natural cause from the originates like other affections. Men regard its nature and cause as divine from ignorance and wonder...
Hippocrates is credited as the first person to believe that diseases were caused naturally, not because of superstition and gods. He was acknowledged by the disciples of Pythagoras for allying philosophy and medicine. He separated the discipline of medicine from religion, believing and arguing that disease was not a punishment inflicted by the gods but rather the product of environmental factors, diet, and living habits. There is not a single mention of a mystical illness in the entirety of the Hippocratic Corpus. However, Hippocrates did hold many convictions that were based on incorrect anatomy and physiology, such as Humorism.
Ancient Greek schools of medicine were split into the Knidian and Koan on how to deal with disease. The Knidian school of medicine focused on diagnosis. Medicine at the time of Hippocrates knew almost nothing of human anatomy and physiology because of the Greek taboo forbidding the dissection of humans. The Knidian school consequently failed to distinguish when one disease caused many possible series of symptoms. The Hippocratic school or Koan school achieved greater success by applying general diagnoses and passive treatments. Its focus was on patient care and prognosis, not diagnosis. It could effectively treat diseases and allowed for a great development in clinical practice.
Hippocratic medicine and its philosophy are far removed from modern medicine, in which the physician focuses on specific diagnosis and specialized treatment, both of which were espoused by the Knidian school. This shift in medical thought since Hippocrates's day has generated serious criticism of their denunciations; for example, the French doctor M. S. Houdart called the Hippocratic treatment a "meditation upon death".
If you want to learn about the health of a population, look at the air they breathe, the water they drink, and the places where they live.
Analogies have been drawn between Thucydides' historical method and the Hippocratic method, in particular the notion of "human nature" as a way of explaining foreseeable repetitions for future usefulness, for other times or for other cases.
=== Crisis ===
An important concept in Hippocratic medicine was that of a crisis, a point in the progression of disease at which either the illness would begin to triumph and the patient would succumb to death, or the opposite would occur and natural processes would make the patient recover. After a crisis, a relapse might follow, and then another deciding crisis. According to this doctrine, crises tend to occur on critical days, which were supposed to be a fixed time after the contraction of a disease. If a crisis occurred on a day far from a critical day, a relapse might be expected. Galen believed that this idea originated with Hippocrates, though it is possible that it predated him.
Hippocratic medicine was humble and passive. The therapeutic approach was based on "the healing power of nature" (Latin: vis medicatrix naturae). According to this doctrine, the body contains within itself the power to re-balance the four humours and heal itself (physis). Hippocratic therapy focused on simply easing this natural process. To this end, Hippocrates believed "rest and immobilization [were] of capital importance". In general, the Hippocratic medicine was very kind to the patient; treatment was gentle, and emphasized keeping the patient clean and sterile. For example, only clean water or wine were ever used on wounds, though "dry" treatment was preferable. Soothing balms were sometimes employed.
Hippocrates was reluctant to administer drugs and engage in specialized treatment that might prove to be wrongly chosen; generalized therapy followed a generalized diagnosis. Some of the generalized treatments he prescribed are fasting and the consumption of a mix of honey and vinegar. Hippocrates once said that "to eat when you are sick, is to feed your sickness". However, potent drugs were used on certain occasions. This passive approach was very successful in treating relatively simple ailments such as broken bones, which required traction to stretch the skeletal system and relieve pressure on the injured area. The Hippocratic bench and other devices were used to this end.
In Hippocrates's time it was thought that fever was a disease in and of itself. Hippocrates treated patients with fever by starving them out, believing that 'starving' the fever was a way to neutralize the disease. He may therefore have been the originator of the idea "Feed a cold, starve a fever".
One of the strengths of Hippocratic medicine was its emphasis on prognosis. At Hippocrates's time, medicinal therapy was quite immature, and often the best thing that physicians could do was to evaluate an illness and predict its likely progression based upon data collected in detailed case histories.
=== Professionalism ===
Hippocratic medicine was notable for its strict professionalism, discipline, and rigorous practice. The Hippocratic work On the Physician recommends that physicians always be well-kempt, honest, calm, understanding, and serious. The Hippocratic physician paid careful attention to all aspects of his practice: he followed detailed specifications for "lighting, personnel, instruments, positioning of the patient, and techniques of bandaging and splinting" in the ancient operating room. He even kept his fingernails to a precise length.
The Hippocratic school gave importance to the clinical doctrines of observation and documentation. These doctrines dictate that physicians record their findings and their medicinal methods in a very clear and objective manner, so that these records may be passed down and employed by other physicians. Hippocrates made careful, regular note of many symptoms including complexion, pulse, fever, pains, movement, and excretions. He is said to have measured a patient's pulse when taking a case history to discover whether the patient was lying. Hippocrates extended clinical observations into family history and environment. "To him medicine owes the art of clinical inspection and observation."
== Direct contributions to medicine ==
Hippocrates and his followers were the first to describe many diseases and medical conditions. He is given credit for the first description of clubbing of the fingers, an important diagnostic sign in chronic lung disease, lung cancer and cyanotic heart disease. For this reason, clubbed fingers are sometimes referred to as "Hippocratic fingers". Hippocrates was also the first physician to describe Hippocratic face in Prognosis. Shakespeare famously alludes to this description when writing of Falstaff's death in Act II, Scene iii. of Henry V.
Hippocrates began to categorize illnesses as acute, chronic, endemic and epidemic, and use terms such as, "exacerbation, relapse, resolution, crisis, paroxysm, peak, and convalescence." Another of Hippocrates's major contributions may be found in his descriptions of the symptomatology, physical findings, surgical treatment and prognosis of thoracic empyema, i.e. suppuration of the lining of the chest cavity. His teachings remain relevant to present-day students of pulmonary medicine and surgery. Hippocrates was the first documented chest surgeon and his findings and techniques, while crude, such as the use of lead pipes to drain chest wall abscess, are still valid.
The Hippocratic school of medicine described well the ailments of the human rectum and the treatment thereof, despite the school's poor theory of medicine. Hemorrhoids, for instance, though believed to be caused by an excess of bile and phlegm, were treated by Hippocratic physicians in relatively advanced ways. Cautery and excision are described in the Hippocratic Corpus, in addition to the preferred methods: ligating the hemorrhoids and drying them with a hot iron. Other treatments such as applying various salves are suggested as well. Today, "treatment [for hemorrhoids] still includes burning, strangling, and excising." Also, some of the fundamental concepts of proctoscopy outlined in the Corpus are still in use. For example, the uses of the rectal speculum, a common medical device, are discussed in the Hippocratic Corpus. This constitutes the earliest recorded reference to endoscopy. Hippocrates often used lifestyle modifications such as diet and exercise to treat diseases such as diabetes, what is today called lifestyle medicine.
Hippocrates helped establish several areas that would become specialized, contributing to them with his studies, those including surgery, urology, neurology, acute medicine and orthopedics. In neurology, he analyzed conditions such as hemiplegia, paraplegia, apoplexy, and epilepsy, the latter of which his studies contributed to the diminishing of its origin as a divine, and rather a common brain disorder. He laid the foundation of surgery with his studies, as his works described differing surgical techniques of general surgery, urology, orthopedics, and neurosurgery. He also used antiseptic techniques such as cleaning the surgical field with boiled water, salt, seawater, and natural perfumes. He also noted that a surgeon should have an organized medical bag of instruments. In urology, in studied urine in relation to acute and chronic diseases, and noted that stone formation is due to the quality of drinking water and to inflammation of the bladder neck, which is still true in modern urology.
Two popular but likely misquoted attributions to Hippocrates are "Let food be your medicine, and medicine be your food" and "Walking is man's best medicine". Both appear to be misquotations, and their exact origins remain unknown.
In 2017, researchers claimed that, while conducting restorations on the Saint Catherine's Monastery in South Sinai, they found a manuscript which contains a medical recipe of Hippocrates. The manuscript also contains three recipes with pictures of herbs that were created by an anonymous scribe.
== Hippocratic Corpus ==
The Hippocratic Corpus (Latin: Corpus Hippocraticum) is a collection of around seventy early medical works collected in Alexandrian Greece. It is written in Ionic Greek. The question of whether Hippocrates himself was the author of any of the treatises in the corpus has not been conclusively answered, but modern debate revolves around only a few of the treatises seen as potentially authored by him. Because of the variety of subjects, writing styles and apparent date of construction, the Hippocratic Corpus could not have been written by one person (Ermerins numbers the authors at nineteen). The corpus came to be known by his name because of his fame; possibly all medical works were classified under 'Hippocrates' by a librarian in Alexandria. The volumes were probably produced by his students and followers.
The Hippocratic Corpus contains textbooks, lectures, research, notes and philosophical essays on various subjects in medicine, in no particular order. These works were written for different audiences, both specialists and laymen, and were sometimes written from opposing viewpoints; significant contradictions can be found between works in the Corpus. Among the treatises of the Corpus are The Hippocratic Oath; The Book of Prognostics; On Regimen in Acute Diseases; Aphorisms; On Airs, Waters and Places; Instruments of Reduction; On The Sacred Disease; etc.
=== Hippocratic Oath ===
The Hippocratic Oath, a seminal document on the ethics of medical practice, was attributed to Hippocrates in antiquity although new information shows it may have been written after his death. This is probably the most famous document of the Hippocratic Corpus. Recently, the authenticity of the document's author has come under scrutiny. While the Oath is rarely used in its original form today, it serves as a foundation for other, similar oaths and laws that define good medical practice and morals. Such derivatives are regularly taken by modern medical graduates about to enter medical practice.
== Legacy ==
Although Hippocrates neither founded the school of medicine named after him, nor wrote most of the treatises attributed to him, he is traditionally regarded as the "Father of Medicine". His contributions revolutionized the practice of medicine; but after his death the advancement stalled. So revered was Hippocrates that his teachings were largely taken as too great to be improved upon and no significant advancements of his methods were made for a long time. The centuries after Hippocrates's death were marked as much by retrograde movement as by further advancement. For instance, "after the Hippocratic period, the practice of taking clinical case-histories died out," according to Fielding Garrison.
After Hippocrates, another significant physician was Galen, a Greek who lived from AD 129 to AD 200. Galen perpetuated the tradition of Hippocratic medicine, making some advancements, but also some regressions. In the Middle Ages, the Islamic world adopted Hippocratic methods and developed new medical technologies. After the European Renaissance, Hippocratic methods were revived in western Europe and even further expanded in the 19th century. Notable among those who employed Hippocrates's rigorous clinical techniques were Thomas Sydenham, William Heberden, Jean-Martin Charcot and William Osler. Henri Huchard, a French physician, said that these revivals make up "the whole history of internal medicine."
=== Image ===
According to Aristotle's testimony, Hippocrates was known as "The Great Hippocrates". Concerning his disposition, Hippocrates was first portrayed as a "kind, dignified, old country doctor" and later as "stern and forbidding". He is certainly considered wise, of very great intellect and especially as very practical. Francis Adams describes him as "strictly the physician of experience and common sense."
His image as the wise, old doctor is reinforced by busts of him, which wear large beards on a wrinkled face. Many physicians of the time wore their hair in the style of Jove and Asklepius. Accordingly, the busts of Hippocrates that have been found could be only altered versions of portraits of these deities. Hippocrates and the beliefs that he embodied are considered medical ideals. Fielding Garrison, an authority on medical history, stated, "He is, above all, the exemplar of that flexible, critical, well-poised attitude of mind, ever on the lookout for sources of error, which is the very essence of the scientific spirit." "His figure... stands for all time as that of the ideal physician," according to A Short History of Medicine, inspiring the medical profession since his death.
=== Legends ===
The Travels of Sir John Mandeville reports (incorrectly) that Hippocrates was the ruler of the islands of "Kos and Lango" [sic], and recounts a legend about Hippocrates's daughter. She was transformed into a hundred-foot long dragon by the goddess Diana, and is the "lady of the manor" of an old castle. She emerges three times a year, and will be turned back into a woman if a knight kisses her, making the knight into her consort and ruler of the islands. Various knights try, but flee when they see the hideous dragon; they die soon thereafter. This is a version of the legend of Melusine.
== Namesakes ==
Some clinical symptoms and signs have been named after Hippocrates as he is believed to be the first person to describe them. Hippocratic face is the change produced in the countenance by death, or long sickness, excessive evacuations, excessive hunger, and the like. Clubbing, a deformity of the fingers and fingernails, is also known as Hippocratic fingers. Hippocratic succussion is the internal splashing noise of hydropneumothorax or pyopneumothorax. Hippocratic bench (a device which uses tension to aid in setting bones) and Hippocratic cap-shaped bandage are two devices named after Hippocrates. Hippocratic Corpus and Hippocratic Oath are also his namesakes. Risus sardonicus, a sustained spasming of the face muscles may also be termed the Hippocratic Smile. The most severe form of hair loss and baldness is called the Hippocratic form.
In the modern age, a lunar crater has been named Hippocrates. The Hippocratic Museum, a museum on the Greek island of Kos is dedicated to him. The Hippocrates Project is a program of the New York University Medical Center to enhance education through use of technology. Project Hippocrates (an acronym of "High Performance Computing for Robot-Assisted Surgery") is an effort of the Carnegie Mellon School of Computer Science and Shadyside Medical Center, "to develop advanced planning, simulation, and execution technologies for the next generation of computer-assisted surgical robots." Both the Canadian Hippocratic Registry and American Hippocratic Registry are organizations of physicians who uphold the principles of the original Hippocratic Oath as inviolable through changing social times.
== Genealogy ==
Hippocrates's legendary genealogy traces his paternal heritage directly to Asklepius and his maternal ancestry to Heracles. According to Tzetzes's Chiliades, the ahnentafel of Hippocrates II is:
1. Hippocrates II.
2. Heraclides
4. Hippocrates I.
8. Gnosidicus
16. Nebrus
32. Sostratus III.
64. Theodorus II.
128. Sostratus, II.
256. Thedorus
512. Cleomyttades
1024. Crisamis
2048. Dardanus
4096. Sostratus
8192. Hippolochus
16384. Podalirius
32768. Asklepius
== See also ==
Hippocrates Prize for Poetry and Medicine
== Notes ==
== References ==
== Further reading ==
== External links ==
Greek Wikisource has original text related to this article: Hippocrates
Works by Hippocrates at the Corpus Medicorum Graecorum
The Harvard Classics Volume 38 with "The Oath of Hippocrates", project gutenberg
Hippocrates collection, full works in English, at One More Library
Works by Hippocrates at LibriVox (public domain audiobooks)
Hippocrates entry in the Internet Encyclopedia of Philosophy
First printed editions of the Hippocratic Collection at the Bibliothèque Interuniversitaire de Médecine of Paris (BIUM) studies and digitized texts by the BIUM (Bibliothèque interuniversitaire de médecine et d'odontologie, Paris) see its digital library Medic@.
List of works by Hippocrates Archived 2021-10-29 at the Wayback Machine, with digitized editions, manuscripts and translations.
Works by Hippocrates at the Biodiversity Heritage Library | Wikipedia/Hippocrates |
Functional contextualism is a modern philosophy of science rooted in philosophical pragmatism and contextualism. It is most actively developed in behavioral science in general and the field of behavior analysis and contextual behavioral science in particular (see the entry for the Association for Contextual Behavioral Science). Functional contextualism serves as the basis of a theory of language known as relational frame theory and its most prominent application, acceptance and commitment therapy. It is an extension and contextualistic interpretation of B.F. Skinner's radical behaviorism first delineated by Steven C. Hayes which emphasizes the importance of predicting and influencing psychological events (including thoughts, feelings, and behaviors) with precision, scope, and depth, by focusing on manipulable variables in their context.
== Contextualism ==
The form of contextualism from which functional contextualism emerged is the one described by the philosopher Stephen C. Pepper in his book World Hypotheses: A Study in Evidence. In this work, Pepper noted that philosophical systems tend to cluster around a few distinct "world hypotheses" or "world views". Each world view is characterized by a distinctive underlying root metaphor and truth criterion. Root metaphors are based on seemingly well-understood, common-sense, everyday objects or ideas, and serve as the basic analogy by which an analyst attempts to understand the world. A world view's root metaphor roughly corresponds to its ontological assumptions, or views about the nature of being or existence (e.g., whether the universe is deterministic or not). Truth criteria are inextricably linked to their root metaphors, and provide the basis for evaluating the validity of analyses. A world view's truth criterion roughly corresponds to its epistemological assumptions, or views about the nature of knowledge and truth (e.g., whether it is discovered or constructed).
The root metaphor of contextualism is the "act in context", whereby any event is interpreted as an ongoing act inseparable from its current and historical context. The truth criterion of contextualism is often dubbed "successful working", whereby the truth and meaning of an idea lies in its function or utility, not in how well it is said to mirror reality. In contextualism, an analysis is said to be true or valid insofar it as it leads to effective action, or achievement of some goal. Contextualism is Pepper's term for the philosophical pragmatism developed by Charles Sanders Peirce, William James, John Dewey, and others.
== Varieties of contextualism ==
Analytic goals are vitally important to the contextualistic world view. This is because the analytic tools of contextualism—its root metaphor and truth criterion—both hinge on the purpose of the analysis, and neither can be mounted effectively without a clearly specified analytic goal. The pragmatic truth criterion of "successful working" is rendered meaningless in an analysis without an explicit goal because "success" can only be measured in relation to the achievement of some objective.
Likewise, the root metaphor of the "act-in-context" is rendered meaningless in an analysis without an explicit goal because there would be no basis on which to restrict the analysis to a subset of the infinite expanse of the act's historical and environmental context. Without a clear analytic goal, the contextualist could analyze the endless context of an act in perpetuity, without ever knowing when the analysis was complete or good enough to be deemed "true" or "useful". It is very difficult for a contextualist without an explicit goal to construct or share knowledge.
Contextualists can, and do, adopt different analytic goals, and the many different varieties of contextualism can be distinguished by their goals. Based on their overarching analytic goals, contextualistic theories can be divided into two general categories: "descriptive contextualism" and "functional contextualism".
=== Descriptive contextualism ===
Descriptive contextualists seek to understand the complexity and richness of a whole event through a personal and aesthetic appreciation of its participants and features. This approach reveals a strong adherence to the root metaphor of contextualism and can be likened to the enterprise of history, in which stories of the past are constructed in an attempt to understand whole events. The knowledge constructed by the descriptive contextualist is personal, ephemeral, specific, and spatiotemporally restricted. Like a historical narrative, it is knowledge that reflects an in-depth personal understanding of a particular event that occurred (or is occurring) at a particular time and place. Most forms of contextualism, including social constructionism, dramaturgy, hermeneutics, and narrative approaches, are instances of descriptive contextualism.
=== Functional contextualism ===
Functional contextualists, on the other hand, seek to predict and influence events using empirically based concepts and rules. This approach reveals a strong adherence to contextualism's extremely practical truth criterion and can be likened to the enterprise of science or engineering, in which general rules and principles are used to predict and control events. Rules or theories that do not contribute to the achievement of one's practical goals are ignored or rejected. Knowledge constructed by the functional contextualist is general, abstract, and spatiotemporally unrestricted. Like a scientific principle, it is knowledge that is likely to be applicable to all (or many) similar such events, regardless of time or place.
== References == | Wikipedia/Functional_contextualism |
This list of life sciences comprises the branches of science that involve the scientific study of life – such as microorganisms, plants, and animals including human beings. This science is one of the two major branches of natural science, the other being physical science, which is concerned with non-living matter. Biology is the overall natural science that studies life, with the other life sciences as its sub-disciplines.
Some life sciences focus on a specific type of organism. For example, zoology is the study of animals, while botany is the study of plants. Other life sciences focus on aspects common to all or many life forms, such as anatomy and genetics. Some focus on the micro-scale (e.g. molecular biology, biochemistry) other on larger scales (e.g. cytology, immunology, ethology, pharmacy, ecology). Another major branch of life sciences involves understanding the mind – neuroscience. Life sciences discoveries are helpful in improving the quality and standard of life and have applications in health, agriculture, medicine, and the pharmaceutical and food science industries. For example, it has provided information on certain diseases which has overall aided in the understanding of human health.
== Basic life science branches ==
Biology – scientific study of life
Anatomy – study of form and function, in plants, animals, and other organisms
Histology – the study of tissues
Neuroscience – the study of the nervous system
Astrobiology – the study of the formation and presence of life in the universe
Biotechnology – study of combination of both the living organism and technology
Biochemistry – the study of the chemical reactions required for life to exist and function, usually focused on the cellular level
Quantum biology – the study of quantum phenomena in organisms
Bioinformatics – developing of methods or software tools for storing, retrieving, organizing and analyzing biological data to generate useful biological knowledge
Biophysics – study of biological processes by applying the theories and methods that have been traditionally used in the physical sciences
Biomechanics – the study of the mechanics of living beings
Botany – study of plants
Agrostology – the study of grasses and grass-like species
Phycology – the study of algae
Cell biology (cytology) – study of the cell as a complete unit, and the molecular and chemical interactions that occur within a living cell
Developmental biology – the study of the processes through which an organism forms, from zygote to full structure
Ecology – study of the interactions of living organisms with one another and with the non-living elements of their environment
Enzymology – study of enzymes
Evolutionary biology – study of the origin and descent of species over time
Evolutionary developmental biology – the study of the evolution of development including its molecular control
Genetics – the study of genes and heredity
Immunology – the study of the immune system
Marine biology – the study of ocean organisms
Biological oceanography – the study of life in the oceans and their interaction with the environment
Microbiology – the study of microscopic organisms (microorganisms) and their interactions with other living organisms
Aerobiology – study of the movement and transportation of microorganisms in the air
Bacteriology – study of bacteria
Virology – study of viruses and virus-like agents
Molecular biology – the study of biology and biological functions at the molecular level, some cross over with biochemistry, genetics, and microbiology
Structural biology – a branch of molecular biology, biochemistry, and biophysics concerned with the molecular structure of biological macro-molecules
Mycology – the study of fungi
Paleontology – the study of prehistoric organisms
Parasitology – the study of parasites, their hosts, and the relationship between them
Pathology – study of the causes and effects of disease or injury
Human biology – the biological study of human beings
Pharmacology – study of drug action
Biological (or physical) anthropology – the study of humans, non-human primates, and hominids
Biolinguistics – the study of the biology and evolution of language
Physiology – the study of the functioning of living organisms and the organs and parts of living organisms
Population biology – the study of groups of conspecific organisms
Population dynamics – the study of short-term and long-term changes in the size and age composition of populations, and the biological and environmental processes influencing those changes. Population dynamics deals with the way populations are affected by birth and death rates, and by immigration and emigration, and studies topics such as ageing populations or population decline.
Synthetic biology – the design and construction of new biological entities such as enzymes, genetic circuits and cells, or the redesign of existing biological systems
Systems biology – the study of the integration and dependencies of various components within a biological system, with particular focus upon the role of metabolic pathways and cell-signaling strategies in physiology
Theoretical biology – use of abstractions and mathematical models to study biological phenomena
Toxicology – the study of poisons
Zoology – the study of (generally non-human) animals
Ethology – the study of animal behavior
== Applied life science branches and derived concepts ==
Agriculture – science and practice of cultivating plants and livestock
Agronomy – science of cultivating plants for resources
Biocomputers – systems of biologically derived molecules, such as DNA and proteins, are used to perform computational calculations involving storing, retrieving, and processing data. The development of biological computing has been made possible by the expanding new science of nanobiotechnology.
Biocontrol – bioeffector-method of controlling pests (including insects, mites, weeds and plant diseases) using other living organisms.
Bioengineering – study of biology through the means of engineering with an emphasis on applied knowledge and especially related to biotechnology
Bioelectronics – field at the convergence of electronics and biological sciences. The electrical state of biological matter significantly affects its structure and function, compare for instance the membrane potential, the signal transduction by neurons, the isoelectric point (IEP) and so on. Micro- and nano-electronic components and devices have increasingly been combined with biological systems like medical implants, biosensors, lab-on-a-chip devices etc. causing the emergence of this new scientific field.
Biomaterials – any matter, surface, or construct that interacts with biological systems. As a science, biomaterials is about fifty years old. The study of biomaterials is called biomaterials science. It has experienced steady and strong growth over its history, with many companies investing large amounts of money into the development of new products. Biomaterials science encompasses elements of medicine, biology, chemistry, tissue engineering and materials science.
Biomedical science – healthcare science, also known as biomedical science, is a set of applied sciences applying portions of natural science or formal science, or both, to develop knowledge, interventions, or technology of use in healthcare or public health. Such disciplines as medical microbiology, clinical virology, clinical epidemiology, genetic epidemiology and pathophysiology are medical sciences.
Biomonitoring – measurement of the body burden of toxic chemical compounds, elements, or their metabolites, in biological substances. Often, these measurements are done in blood and urine.
Biopolymer – polymers produced by living organisms; in other words, they are polymeric biomolecules. Since they are polymers, biopolymers contain monomeric units that are covalently bonded to form larger structures. There are three main classes of biopolymers, classified according to the monomeric units used and the structure of the biopolymer formed: polynucleotides (RNA and DNA), which are long polymers composed of 13 or more nucleotide monomers; polypeptides, which are short polymers of amino acids; and polysaccharides, which are often linear bonded polymeric carbohydrate structures.
Biotechnology – manipulation of living matter, including genetic modification and synthetic biology
Conservation biology – the management of nature and of Earth's biodiversity with the aim of protecting species, their habitats, and ecosystems from excessive rates of extinction and the erosion of biotic interactions. It is an interdisciplinary subject drawing on natural and social sciences, and the practice of natural resource management.
Environmental health – multidisciplinary field concerned with environmental epidemiology, toxicology, and exposure science.
Fermentation technology – study of use of microorganisms for industrial manufacturing of various products like vitamins, amino acids, antibiotics, beer, wine, etc.
Food science – applied science devoted to the study of food. Activities of food scientists include the development of new food products, design of processes to produce and conserve these foods, choice of packaging materials, shelf-life studies, study of the effects of food on the human body, sensory evaluation of products using panels or potential consumers, as well as microbiological, physical (texture and rheology) and chemical testing.
Genomics – application of recombinant DNA, DNA sequencing methods, and bioinformatics to sequence, assemble, and analyze the function and structure of genomes (the complete set of DNA within a single cell of an organism). The field includes efforts to determine the entire DNA sequence of organisms and fine-scale genetic mapping. The field also includes studies of intragenomic phenomena such as heterosis, epistasis, pleiotropy and other interactions between loci and alleles within the genome. In contrast, the investigation of the roles and functions of single genes is a primary focus of molecular biology or genetics and is a common topic of modern medical and biological research. Research of single genes does not fall into the definition of genomics unless the aim of this genetic, pathway, and functional information analysis is to elucidate its effect on, place in, and response to the entire genome's networks.
Health sciences – sciences which focus on health, or health care, as core parts of their subject matter. These two subject matters relate to multiple academic disciplines, both STEM disciplines, as well as emerging patient safety disciplines (such as social care research), and are both relevant to current health science knowledge.
Medical devices – A medical device is an instrument, apparatus, implant, in vitro reagent, or similar or related article that is used to diagnose, prevent, or treat disease or other conditions, and does not achieve its purposes through chemical action within or on the body (which would make it a drug). Whereas medicinal products (also called pharmaceuticals) achieve their principal action by pharmacological, metabolic or immunological means, medical devices act by other means like physical, mechanical, or thermal means.
Medical imaging – the technique and process used to create images of the human body (or parts and function thereof) for clinical or physiological research purposes
Immunotherapy – the "treatment of disease by inducing, enhancing, or suppressing an immune response". Immunotherapies designed to elicit or amplify an immune response are classified as activation immunotherapies, while immunotherapies that reduce or suppress are classified as suppression immunotherapies.
Kinesiology – scientific study of human movement. Kinesiology, also known as human kinetics, addresses physiological, mechanical, and psychological mechanisms. Applications of kinesiology to human health include: biomechanics and orthopedics; strength and conditioning; sport psychology; methods of rehabilitation, such as physical and occupational therapy; and sport and exercise. Individuals who have earned degrees in kinesiology can work in research, the fitness industry, clinical settings, and in industrial environments. Studies of human and animal motion include measures from motion tracking systems, electrophysiology of muscle and brain activity, various methods for monitoring physiological function, and other behavioral and cognitive research techniques.
Optogenetics – a neuromodulation technique employed in neuroscience that uses a combination of techniques from optics and genetics to control and monitor the activities of individual neurons in living tissue—even within freely-moving animals—and to precisely measure the effects of those manipulations in real-time. The key reagents used in optogenetics are light-sensitive proteins. Spatially-precise neuronal control is achieved using optogenetic actuators like channelrhodopsin, halorhodopsin, and archaerhodopsin, while temporally-precise recordings can be made with the help of optogenetic sensors like Clomeleon, Mermaid, and SuperClomeleon.
Pharmacogenomics – field of science and technology that analyses how genetic makeup affects an individual's response to drugs. Pharmacogenomics (a portmanteau of pharmacology and genomics) deals with the influence of genetic variation on drug response in patients by correlating gene expression or single-nucleotide polymorphisms with a drug's efficacy or toxicity.
Pharmacology – branch of medicine and biology concerned with the study of drug action, where a drug can be broadly defined as any human-made, natural, or endogenous (within the body) molecule which exerts a biochemical and/or physiological effect on the cell, tissue, organ, or organism. More specifically, it is the study of the interactions that occur between a living organism and chemicals that affect normal or abnormal biochemical function. If substances have medicinal properties, they are considered pharmaceuticals.
Proteomics – the large-scale study of proteins, particularly their structures and functions. Proteins are vital parts of living organisms, as they are the main components of the physiological metabolic pathways of cells. The proteome is the entire set of proteins, produced or modified by an organism or system. This varies with time and distinct requirements, or stresses, that a cell or organism undergoes.
== See also ==
Outline of biology
Divisions of pharmacology
Control theory
== References ==
== Further reading ==
Magner, Lois N. (2002). A history of the life sciences (Rev. and expanded 3rd ed.). New York: M. Dekker. ISBN 0824708245. | Wikipedia/Life_science |
Science in classical antiquity encompasses inquiries into the workings of the world or universe aimed at both practical goals (e.g., establishing a reliable calendar or determining how to cure a variety of illnesses) as well as more abstract investigations belonging to natural philosophy. Classical antiquity is traditionally defined as the period between the 8th century BC (beginning of Archaic Greece) and the 6th century AD (after which there was medieval science). It is typically limited geographically to the Greco-Roman West, Mediterranean basin, and Ancient Near East, thus excluding traditions of science in the ancient world in regions such as China and the Indian subcontinent.
Ideas regarding nature that were theorized during classical antiquity were not limited to science but included myths as well as religion. Those who are now considered as the first scientists may have thought of themselves as natural philosophers, as practitioners of a skilled profession (e.g., physicians), or as followers of a religious tradition (e.g., temple healers). Some of the more widely known figures active in this period include Hippocrates, Aristotle, Euclid, Archimedes, Hipparchus, Galen, and Ptolemy. Their contributions and commentaries spread throughout the Eastern, Islamic, and Latin worlds and contributed to the birth of modern science. Their works covered many different categories including mathematics, cosmology, medicine, and physics.
== Classical Greece ==
=== Knowledge of causes ===
This subject inquires into the nature of things first began out of practical concerns among the ancient Greeks. For instance, an attempt to establish a calendar is first exemplified by the Works and Days of the Greek poet Hesiod, who lived around 700 BC. Hesiod's calendar was meant to regulate seasonal activities by the seasonal appearances and disappearances of the stars, as well as by the phases of the Moon, which were held to be propitious or ominous. Around 450 BC we begin to see compilations of the seasonal appearances and disappearances of the stars in texts known as parapegmata, which were used to regulate the civil calendars of the Greek city-states on the basis of astronomical observations.
Medicine is another area where practically oriented investigations of nature took place during this period. Greek medicine was not the province of a single trained profession and there was no accepted method of qualification of licensing. Physicians in the Hippocratic tradition, temple healers associated with the cult of Asclepius, herb collectors, drug sellers, midwives, and gymnastic trainers all claimed to be qualified as healers in specific contexts and competed actively for patients. This rivalry among these competing traditions contributed to an active public debate about the causes and proper treatment of disease, and about the general methodological approaches of their rivals.
An example of the search for causal explanations is found in the Hippocratic text On the Sacred Disease, which deals with the nature of epilepsy. In it, the author attacks his rivals (temple healers) for their ignorance in attributing epilepsy to divine wrath, and for their love of gain. Although the author insists that epilepsy has a natural cause, when it comes to explain what that cause is and what the proper treatment would be, the explanation is as short on specific evidence and the treatment as vague as that of his rivals. Nonetheless, observations of natural phenomena continued to be compiled in an effort to determine their causes, as for instance in the works of Aristotle and Theophrastus, who wrote extensively on animals and plants. Theophrastus also produced the first systematic attempt to classify minerals and rocks, a summary of which is found in Pliny's Natural History.
The legacy of Greek science in this era included substantial advances in factual knowledge due to empirical research (e.g., in zoology, botany, mineralogy, and astronomy), an awareness of the importance of certain scientific problems (e.g., the problem of change and its causes), and a recognition of the methodological significance of establishing criteria for truth (e.g., applying mathematics to natural phenomena), despite the lack of universal consensus in any of these areas.
=== Pre-Socratic philosophy ===
==== Materialist philosophers ====
The earliest Greek philosophers, known as the pre-Socratics, were materialists who provided alternative answers to the same question found in the myths of their neighbors: "How did the ordered cosmos in which we live come to be?" Although the question is much the same, their answers and their attitude towards the answers is markedly different. As reported by such later writers as Aristotle, their explanations tended to center on the material source of things.
Thales of Miletus (624–546 BC) considered that all things came to be from and find their sustenance in water. Anaximander (610–546 BC) then suggested that things could not come from a specific substance like water, but rather from something he called the "boundless". Exactly what he meant is uncertain but it has been suggested that it was boundless in its quantity, so that creation would not fail; in its qualities, so that it would not be overpowered by its contrary; in time, as it has no beginning or end; and in space, as it encompasses all things. Anaximenes (585–525 BC) returned to a concrete material substance, air, which could be altered by rarefaction and condensation. He adduced common observations (the wine stealer) to demonstrate that air was a substance and a simple experiment (breathing on one's hand) to show that it could be altered by rarefaction and condensation.
Heraclitus of Ephesus (about 535–475 BC), then maintained that change, rather than any substance was fundamental, although the element fire seemed to play a central role in this process. Finally, Empedocles of Acragas (490–430 BC), seems to have combined the views of his predecessors, asserting that there are four elements (Earth, Water, Air and Fire) which produce change by mixing and separating under the influence of two opposing "forces" that he called Love and Strife.
All these theories imply that matter is a continuous substance. Two Greek philosophers, Leucippus (first half of the 5th century BC) and Democritus came up with the notion that there were two real entities: atoms, which were small indivisible particles of matter, and the void, which was the empty space in which matter was located. Although all the explanations from Thales to Democritus involve matter, what is more important is the fact that these rival explanations suggest an ongoing process of debate in which alternate theories were put forth and criticized.
Xenophanes of Colophon prefigured paleontology and geology as he thought that periodically the earth and sea mix and turn all to mud, citing several fossils of sea creatures that he had seen.
==== Pythagorean philosophy ====
The materialist explanations of the origins of the cosmos were attempts at answering the question of how an organized universe came to be; however, the idea of a random assemblage of elements (e.g., fire or water) producing an ordered universe without the existence of some ordering principle remained problematic to some.
One answer to this problem was advanced by the followers of Pythagoras (c. 582–507 BC), who saw number as the fundamental unchanging entity underlying all the structure of the universe. Although it is difficult to separate fact from legend, it appears that some Pythagoreans believed matter to be made up of ordered arrangements of points according to geometrical principles: triangles, squares, rectangles, or other figures. Other Pythagoreans saw the universe arranged on the basis of numbers, ratios, and proportions, much like musical scales. Philolaus, for instance, held that there were ten heavenly bodies because the sum of 1 + 2 + 3 + 4 gives the perfect number 10. Thus, the Pythagoreans were some of the first to apply mathematical principles to explain the rational basis of an orderly universe—an idea that was to have immense consequences in the development of scientific thought.
==== Hippocrates and the Hippocratic Corpus ====
According to tradition, the physician Hippocrates of Kos (460–370 BC) is considered the "father of medicine" because he was the first to make use of prognosis and clinical observation, to categorize diseases, and to formulate the ideas behind humoral theory. However, most of the Hippocratic Corpus—a collection of medical theories, practices, and diagnoses—was often attributed to Hippocrates with very little justification, thus making it difficult to know what Hippocrates actually thought, wrote, and did.
Despite their wide variability in terms of style and method, the writings of the Hippocratic Corpus had a significant influence on the medical practice of Islamic and Western medicine for more than a thousand years.
=== Schools of philosophy ===
==== The Academy ====
The first institution of higher learning in Ancient Greece was founded by Plato (c. 427 – c. 347 BC), an Athenian who—perhaps under Pythagorean influence—appears to have identified the ordering principle of the universe as one based on number and geometry. A later account has it that Plato had inscribed at the entrance to the Academy the words "Let no man ignorant of geometry enter." Although the story is most likely a myth, it nonetheless testifies to Plato's interest in mathematics, which is alluded to in several of his dialogues.
Plato's philosophy maintained that all material things are imperfect reflections of eternal unchanging ideas, just as all mathematical diagrams are reflections of eternal unchanging mathematical truths. Since Plato believed that material things had an inferior kind of reality, he considered that demonstrative knowledge cannot be achieved by looking at the imperfect material world. Truth is to be found through rational argumentation, analogous to the demonstrations of mathematicians. For instance, Plato recommended that astronomy be studied in terms of abstract geometrical models rather than empirical observations, and proposed that leaders be trained in mathematics in preparation for philosophy.
Aristotle (384–322 BC) studied at the Academy and nonetheless disagreed with Plato in several important respects. While he agreed that truth must be eternal and unchanging, Aristotle maintained that the world is knowable through experience and that we come to know the truth by what we perceive with our senses. For him, directly observable things are real; ideas (or as he called them, forms) only exist as they express themselves in matter, such as in living things, or in the mind of an observer or artisan.
Aristotle's theory of reality led to a different approach to science. Unlike Plato, Aristotle emphasized observation of the material entities which embody the forms. He also played down (but did not negate) the importance of mathematics in the study of nature. The process of change took precedence over Plato's focus on eternal unchanging ideas in Aristotle's philosophy. Finally, he reduced the importance of Plato's forms to one of four causal factors.
Aristotle thus distinguished between four causes:
the matter of which a thing was made (the material cause).
the form into which it was made (the formal cause; similar to Plato's ideas).
the agent who made the thing (the moving or efficient cause).
the purpose for which the thing was made (the final cause).
Aristotle insisted that scientific knowledge (Ancient Greek: ἐπιστήμη, Latin: scientia) is knowledge of necessary causes. He and his followers would not accept mere description or prediction as science. Most characteristic of Aristotle's causes is his final cause, the purpose for which a thing is made. He came to this insight through his biological researches, such as those of marine animals at Lesbos, in which he noted that the organs of animals serve a particular function:
The absence of chance and the serving of ends are found in the works of nature especially. And the end for the sake of which a thing has been constructed or has come to be belongs to what is beautiful.
==== The Lyceum ====
After Plato's death, Aristotle left the Academy and traveled widely before returning to Athens to found a school adjacent to the Lyceum. As one of the most prolific natural philosophers of Antiquity, Aristotle wrote and lecture on many topics of scientific interest, including biology, meteorology, psychology, logic, and physics. He developed a comprehensive physical theory that was a variation of the classical theory of the elements (earth, water, fire, air, and aether). In his theory, the light elements (fire and air) have a natural tendency to move away from the center of the universe while the heavy elements (earth and water) have a natural tendency to move toward the center of the universe, thereby forming a spherical Earth. Since the celestial bodies (i.e., the planets and stars) were seen to move in circles, he concluded that they must be made of a fifth element, which he called aether.
Aristotle used intuitive ideas to justify his reasoning and could point to the falling stone, rising flames, or pouring water to illustrate his theory. His laws of motion emphasized the common observation that friction was an omnipresent phenomenon: that any body in motion would, unless acted upon, come to rest. He also proposed that heavier objects fall faster, and that voids were impossible.
Aristotle's successor at the Lyceum was Theophrastus, who wrote valuable books describing plant and animal life. His works are regarded as the first to put botany and zoology on a systematic footing. Theophrastus' work on mineralogy provided descriptions of ores and minerals known to the world at that time, making some shrewd observations of their properties. For example, he made the first known reference to the phenomenon that the mineral tourmaline attracts straws and bits of wood when heated, now known to be caused by pyroelectricity. Pliny the Elder makes clear references to his use of the work in his Natural History, while updating and making much new information available on minerals himself. From both these early texts was to emerge the science of mineralogy, and ultimately geology. Both authors describe the sources of the minerals they discuss in the various mines exploited in their time, so their works should be regarded not just as early scientific texts, but also important for the history of engineering and the history of technology.
Other notable peripatetics include Strato, who was a tutor in the court of the Ptolemies and who devoted time to physical research, Eudemus, who edited Aristotle's works and wrote the first books on the history of science, and Demetrius of Phalerum, who governed Athens for a time and later may have helped establish the Library of Alexandria.
== Hellenistic age ==
The military campaigns of Alexander the Great spread Greek thought to Egypt, Asia Minor, Persia, up to the Indus River. The resulting migration of many Greek speaking populations across these territories provided the impetus for the foundation of several seats of learning, such as those in Alexandria, Antioch, and Pergamum.
Hellenistic science differed from Greek science in at least two respects: first, it benefited from the cross-fertilization of Greek ideas with those that had developed in other non-Hellenic civilizations; secondly, to some extent, it was supported by royal patrons in the kingdoms founded by Alexander's successors. The city of Alexandria, in particular, became a major center of scientific research in the 3rd century BC. Two institutions established there during the reigns of Ptolemy I Soter (367–282 BC) and Ptolemy II Philadelphus (309–246 BC) were the Library and the Museum. Unlike Plato's Academy and Aristotle's Lyceum, these institutions were officially supported by the Ptolemies, although the extent of patronage could be precarious depending on the policies of the current ruler.
Hellenistic scholars often employed the principles developed in earlier Greek thought in their scientific investigations, such as the application of mathematics to phenomena or the deliberate collection of empirical data. The assessment of Hellenistic science, however, varies widely. At one extreme is the view of English classical scholar Cornford, who believed that "all the most important and original work was done in the three centuries from 600 to 300 BC". At the other end is the view of Italian physicist and mathematician Lucio Russo, who claims that the scientific method was actually born in the 3rd century BC, only to be largely forgotten during the Roman period and not revived again until the Renaissance.
=== Technology ===
A good example of the level of achievement in astronomical knowledge and engineering during the Hellenistic age can be seen in the Antikythera mechanism (150–100 BC). It is a 37-gear mechanical computer which calculated the motions of the Sun, Moon, and possibly the other five planets known to the ancients. The Antikythera mechanism included lunar and solar eclipses predicted on the basis of astronomical periods believed to have been learned from the Babylonians. The device may have been part of an ancient Greek tradition of complex mechanical technology that was later, at least in part, transmitted to the Byzantine and Islamic worlds, where mechanical devices which were complex, albeit simpler than the Antikythera mechanism, were built during the Middle Ages. Fragments of a geared calendar attached to a sundial, from the fifth or sixth century Byzantine Empire, have been found; the calendar may have been used to assist in telling time. A geared calendar similar to the Byzantine device was described by the scientist al-Biruni around 1000, and a surviving 13th-century astrolabe also contains a similar clockwork device.
=== Medicine ===
An important school of medicine was formed in Alexandria from the late 4th century to the 2nd century BC. Beginning with Ptolemy I Soter, medical officials were allowed to cut open and examine cadavers for the purposes of learning how human bodies operated. The first use of human bodies for anatomical research occurred in the work of Herophilos (335–280 BC) and Erasistratus (c. 304 – c. 250 BC), who gained permission to perform live dissections, or vivisections, on condemned criminals in Alexandria under the auspices of the Ptolemaic dynasty.
Herophilos developed a body of anatomical knowledge much more informed by the actual structure of the human body than previous works had been. He also reversed the longstanding notion made by Aristotle that the heart was the "seat of intelligence", arguing for the brain instead. Herophilos also wrote on the distinction between veins and arteries, and made many other accurate observations about the structure of the human body, especially the nervous system. Erasistratus differentiated between the function of the sensory and motor nerves, and linked them to the brain. He is credited with one of the first in-depth descriptions of the cerebrum and cerebellum. For their contributions, Herophilos is often called the "father of anatomy", while Erasistratus is regarded by some as the "founder of physiology".
=== Mathematics ===
Greek mathematics in the Hellenistic period reached a level of sophistication not matched for several centuries afterward, as much of the work represented by scholars active at this time was of a very advanced level. There is also evidence of combining mathematical knowledge with high levels of technical expertise, as found for instance in the construction of massive building projects (e.g., the Syracusia), or in Eratosthenes' (276–195 BC) measurement of the distance between the Sun and the Earth and the size of the Earth.
Although few in number, Hellenistic mathematicians actively communicated with each other; publication consisted of passing and copying someone's work among colleagues. Among the most recognizable is the work of Euclid (325–265 BC), who presumably authored a series of books known as the Elements, a canon of geometry and elementary number theory for many centuries. Euclid's Elements served as the main textbook for the teaching of theoretical mathematics until the early 20th century.
Archimedes (287–212 BC), a Sicilian Greek, wrote about a dozen treatises where he communicated many remarkable results, such as the sum of an infinite geometric series in Quadrature of the Parabola, an approximation to the value π in Measurement of the Circle, and a nomenclature to express very large numbers in the Sand Reckoner.
The most characteristic product of Greek mathematics may be the theory of conic sections, which was largely developed in the Hellenistic period, primarily by Apollonius (262–190 BC). The methods used made no explicit use of algebra, nor trigonometry, the latter appearing around the time of Hipparchus (190–120 BC).
=== Astronomy ===
Advances in mathematical astronomy also took place during the Hellenistic age. Aristarchus of Samos (310–230 BC) was an ancient Greek astronomer and mathematician who presented the first known heliocentric model that placed the Sun at the center of the known universe, with the Earth revolving around the Sun once a year and rotating about its axis once a day. Aristarchus also estimated the sizes of the Sun and Moon as compared to Earth's size, and the distances to the Sun and Moon. His heliocentric model did not find many adherents in antiquity but did influence some early modern astronomers, such as Nicolaus Copernicus, who was aware of the heliocentric theory of Aristarchus.
In the 2nd century BC, Hipparchus discovered precession, calculated the size and distance of the Moon and invented the earliest known astronomical devices such as the astrolabe. Hipparchus also created a comprehensive catalog of 1020 stars, and most of the constellations of the northern hemisphere derive from Greek astronomy. It has recently been claimed that a celestial globe based on Hipparchus's star catalog sits atop the broad shoulders of a large 2nd-century Roman statue known as the Farnese Atlas.
== Roman era ==
Science during the Roman Empire was concerned with systematizing knowledge gained in the preceding Hellenistic age and the knowledge from the vast areas the Romans had conquered. It was largely the work of authors active in this period that would be passed on uninterrupted to later civilizations.
Even though science continued under Roman rule, Latin texts were mainly compilations drawing on earlier Greek work. Advanced scientific research and teaching continued to be carried on in Greek. Such Greek and Hellenistic works as survived were preserved and developed later in the Byzantine Empire and then in the Islamic world. Late Roman attempts to translate Greek writings into Latin had limited success (e.g., Boethius), and direct knowledge of most ancient Greek texts only reached western Europe from the 12th century onwards.
=== Pliny ===
Pliny the Elder published the Naturalis Historia in 77 AD, one of the most extensive compilations of the natural world which survived into the Middle Ages. Pliny did not simply list materials and objects but also recorded explanations of phenomena. Thus he is the first to correctly describe the origin of amber as being the fossilized resin of pine trees. He makes the inference from the observation of trapped insects within some amber samples.
Pliny's work is divided neatly into the organic world of plants and animals, and the realm of inorganic matter, although there are frequent digressions in each section. He is especially interested in not just describing the occurrence of plants, animals and insects, but also their exploitation (or abuse) by man. The description of metals and minerals is particularly detailed, and valuable as being the most extensive compilation still available from the ancient world. Although much of the work was compiled by judicious use of written sources, Pliny gives an eyewitness account of gold mining in Spain, where he was stationed as an officer. Pliny is especially significant because he provides full bibliographic details of the earlier authors and their works he uses and consults. Because his encyclopaedia survived the Dark Ages, we know of these lost works, even if the texts themselves have disappeared. The book was one of the first to be printed in 1489, and became a standard reference work for Renaissance scholars, as well as an inspiration for the development of a scientific and rational approach to the world.
=== Hero ===
Hero of Alexandria was a Greco-Egyptian mathematician and engineer who is often considered to be the greatest experimenter of antiquity. Among his most famous inventions was a windwheel, constituting the earliest instance of wind harnessing on land, and a well-recognized description of a steam-powered device called an aeolipile, which was the first-recorded steam engine.
=== Galen ===
The greatest medical practitioner and philosopher of this era was Galen, active in the 2nd century AD. Around 100 of his works survive—the most for any ancient Greek author—and fill 22 volumes of modern text. Galen was born in the ancient Greek city of Pergamon (now in Turkey), the son of a successful architect who gave him a liberal education. Galen was instructed in all major philosophical schools (Platonism, Aristotelianism, Stoicism and Epicureanism) until his father, moved by a dream of Asclepius, decided he should study medicine. After his father's death, Galen traveled widely searching for the best doctors in Smyrna, Corinth, and finally Alexandria.
Galen compiled much of the knowledge obtained by his predecessors, and furthered the inquiry into the function of organs by performing dissections and vivisections on Barbary apes, oxen, pigs, and other animals. In 158 AD, Galen served as chief physician to the gladiators in his native Pergamon, and was able to study all kinds of wounds without performing any actual human dissection. It was through his experiments, however, that Galen was able to overturn many long-held beliefs, such as the theory that the arteries contained air which carried it to all parts of the body from the heart and the lungs. This belief was based originally on the arteries of dead animals, which appeared to be empty. Galen was able to demonstrate that living arteries contain blood, but his error, which became the established medical orthodoxy for centuries, was to assume that the blood goes back and forth from the heart in an ebb-and-flow motion.
Anatomy was a prominent part of Galen's medical education and was a major source of interest throughout his life. He wrote two great anatomical works, On anatomical procedure and On the uses of the parts of the body of man. The information in these tracts became the foundation of authority for all medical writers and physicians for the next 1300 years until they were challenged by Vesalius and Harvey in the 16th century.
=== Ptolemy ===
Claudius Ptolemy (c. 100–170 AD), living in or around Alexandria, carried out a scientific program centered on the writing of about a dozen books on astronomy, astrology, cartography, harmonics, and optics. Despite their severe style and high technicality, a great deal of them have survived, in some cases the sole remnants of their kind of writing from antiquity. Two major themes that run through Ptolemy's works are mathematical modelling of physical phenomena and methods of visual representation of physical reality.
Ptolemy's research program involved a combination of theoretical analysis with empirical considerations seen, for instance, in his systematized study of astronomy. Ptolemy's Mathēmatikē Syntaxis (Ancient Greek: Μαθηματικὴ Σύνταξις), better known as the Almagest, sought to improve on the work of his predecessors by building astronomy not only upon a secure mathematical basis but also by demonstrating the relationship between astronomical observations and the resulting astronomical theory. In his Planetary Hypotheses, Ptolemy describes in detail physical representations of his mathematical models found in the Almagest, presumably for didactic purposes. Likewise, the Geography was concerned with the drawing of accurate maps using astronomical information, at least in principle. Apart from astronomy, both the Harmonics and the Optics contain (in addition to mathematical analyses of sound and sight, respectively) instructions on how to construct and use experimental instruments to corroborate theory.
In retrospect, it is apparent that Ptolemy adjusted some reported measurements to fit his (incorrect) assumption that the angle of refraction is proportional to the angle of incidence.
Ptolemy's thoroughness and his preoccupation with ease of data presentation (for example, in his widespread use of tables) virtually guaranteed that earlier work on these subjects be neglected or considered obsolete, to the extent that almost nothing remains of the works Ptolemy often refers. His astronomical work in particular defined the method and subject matter of future research for centuries, and the Ptolemaic system became the dominant model for the motions of the heavens until the seventeenth century.
== See also ==
Forensics in antiquity
Protoscience
Roman technology
Obsolete scientific theories
== Notes ==
== References == | Wikipedia/Science_in_classical_antiquity |
Science advanced dramatically during the 20th century. There were new and radical developments in the physical, life and human sciences, building on the progress made in the 19th century.
The development of post-Newtonian theories in physics, such as special relativity, general relativity, and quantum mechanics led to the development of nuclear weapons. New models of the structure of the atom led to developments in theories of chemistry and the development of new materials such as nylon and plastics. Advances in biology led to large increases in food production, as well as the elimination of diseases such as polio.
A massive amount of new technologies were developed in the 20th century. Technologies such as electricity, the incandescent light bulb, the automobile and the phonography, first developed at the end of the 19th century, were perfected and universally deployed. The first airplane flight occurred in 1903, and by the end of the century large airplanes such as the Boeing 777 and Airbus A330 flew thousands of miles in a matter of hours. The development of the television and computers caused massive changes in the dissemination of information.
== Astronomy and spaceflight ==
A much better understanding of the evolution of the universe was achieved, its age (about 13.8 billion years) was determined, and the Big Bang theory on its origin was proposed and generally accepted.
The age of the Solar System, including Earth, was determined, and it turned out to be much older than believed earlier: more than 4 billion years, rather than the 20 million years suggested by Lord Kelvin in 1862.
The planets of the Solar System and their moons were closely observed via numerous space probes. Pluto was discovered in 1930 on the edge of the Solar System, although in the early 21st century, it was reclassified as a dwarf planet (planetoid) instead of a planet proper, leaving eight planets.
No trace of life was discovered on any of the other planets in the Solar System, although it remained undetermined whether some forms of primitive life might exist, or might have existed, somewhere. Extrasolar planets were observed for the first time.
In 1969, Apollo 11 was launched towards the Moon and Neil Armstrong and Buzz Aldrin became the first persons from Earth to walk on another celestial body.
That same year, Soviet astronomer Victor Safronov published his book Evolution of the protoplanetary cloud and formation of the Earth and the planets. In this book, almost all major problems of the planetary formation process were formulated and some of them solved. Safronov's ideas were further developed in the works of George Wetherill, who discovered runaway accretion.
The Space Race between the United States and the Soviet Union gave a peaceful outlet to the political and military tensions of the Cold War, leading to the first human spaceflight with the Soviet Union's Vostok 1 mission in 1961, and man's first landing on another world—the Moon—with America's Apollo 11 mission in 1969. Later, the first space station was launched by the Soviet space program. The United States developed the first (and to date only) reusable spacecraft system with the Space Shuttle program, first launched in 1981. As the century ended, a permanent human presence in space was being founded with the ongoing construction of the International Space Station.
In addition to human spaceflight, uncrewed space probes became a practical and relatively inexpensive form of exploration. The first orbiting space probe, Sputnik 1, was launched by the Soviet Union in 1957. Over time, a massive system of artificial satellites was placed into orbit around Earth. These satellites greatly advanced navigation, communications, military intelligence, geology, climate, and numerous other fields. Also, by the end of the 20th century, uncrewed probes had visited the Moon, Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, and various asteroids and comets. The Hubble Space Telescope, launched in 1990, greatly expanded the understanding of the Universe and brought brilliant images to TV and computer screens around the world.
== Biology and medicine ==
Genetics was unanimously accepted and significantly developed. The structure of DNA was determined in 1953 by James Watson, Francis Crick, Rosalind Franklin and Maurice Wilkins, following by developing techniques which allow to read DNA sequences and culminating in starting the Human Genome Project (not finished in the 20th century) and cloning the first mammal in 1996.
The role of sexual reproduction in evolution was understood, and bacterial conjugation was discovered.
The convergence of various sciences for the formulation of the modern evolutionary synthesis (produced between 1936 and 1947), providing a widely accepted account of evolution.
Placebo-controlled, randomized, blinded clinical trials became a powerful tool for testing new medicines.
Antibiotics drastically reduced mortality from bacterial diseases and their prevalence.
A vaccine was developed for polio, ending a worldwide epidemic. Effective vaccines were also developed for a number of other serious infectious diseases, including influenza, diphtheria, pertussis (whooping cough), tetanus, measles, mumps, rubella (German measles), chickenpox, hepatitis A, and hepatitis B.
Epidemiology and vaccination led to the eradication of the smallpox virus in humans.
X-rays became powerful diagnostic tool for wide spectrum of diseases, from bone fractures to cancer. In the 1960s, computerized tomography was invented. Other important diagnostic tools developed were sonography and magnetic resonance imaging.
Development of vitamins virtually eliminated scurvy and other vitamin-deficiency diseases from industrialized societies.
New psychiatric drugs were developed. These include antipsychotics for treating hallucinations and delusions, and antidepressants for treating depression.
The role of tobacco smoking in the causation of cancer and other diseases was proven during the 1950s (see British Doctors Study).
New methods for cancer treatment, including chemotherapy, radiation therapy, and immunotherapy, were developed. As a result, cancer could often be cured or placed in remission.
The development of blood typing and blood banking made blood transfusion safe and widely available.
The invention and development of immunosuppressive drugs and tissue typing made organ and tissue transplantation a clinical reality.
New methods for heart surgery were developed, including pacemakers and artificial hearts.
Cocaine/crack and heroin were found to be dangerous addictive drugs, and their wide usage had been outlawed; mind-altering drugs such as LSD and MDMA were discovered and later outlawed. In many countries, a war on drugs caused prices to soar 10–20 times higher, leading to profitable black market drug dealing, and in some countries (e.g. the United States) to prison inmate sentences being 80% related to drug use by the 1990s.
Contraceptive drugs were developed, which reduced population growth rates in industrialized countries, as well as decreased the taboo of premarital sex throughout many western countries.
The development of medical insulin during the 1920s helped raise the life expectancy of diabetics to three times of what it had been earlier.
Vaccines, hygiene and clean water improved health and decreased mortality rates, especially among infants and the young.
=== Notable diseases ===
An influenza pandemic, Spanish Flu, killed anywhere from 20 to 100 million people between 1918 and 1919.
A new viral disease, called the Human Immunodeficiency Virus, or HIV, arose in Africa and subsequently killed millions of people throughout the world. HIV leads to a syndrome called Acquired Immunodeficiency Syndrome, or AIDS. Treatments for HIV remained inaccessible to many people living with AIDS and HIV in developing countries, and a cure has yet to be discovered.
Because of increased life spans, the prevalence of cancer, Alzheimer's disease, Parkinson's disease, and other diseases of old age increased slightly.
Sedentary lifestyles, due to labour-saving devices and technology, along with the increase in home entertainment and technology such as television, video games, and the internet contributed to an "epidemic" of obesity, at first in the rich countries, but by the end of the 20th century spreading to the developing world.
== Chemistry ==
In 1903, Mikhail Tsvet invented chromatography, an important analytic technique. In 1904, Hantaro Nagaoka proposed an early nuclear model of the atom, where electrons orbit a dense massive nucleus. In 1905, Fritz Haber and Carl Bosch developed the Haber process for making ammonia, a milestone in industrial chemistry with deep consequences in agriculture. The Haber process, or Haber-Bosch process, combined nitrogen and hydrogen to form ammonia in industrial quantities for production of fertilizer and munitions. The food production for half the world's current population depends on this method for producing fertilizer. Haber, along with Max Born, proposed the Born–Haber cycle as a method for evaluating the lattice energy of an ionic solid. Haber has also been described as the "father of chemical warfare" for his work developing and deploying chlorine and other poisonous gases during World War I.
In 1905, Albert Einstein explained Brownian motion in a way that definitively proved atomic theory. Leo Baekeland invented bakelite, one of the first commercially successful plastics. In 1909, American physicist Robert Andrews Millikan – who had studied in Europe under Walther Nernst and Max Planck – measured the charge of individual electrons with unprecedented accuracy through the oil drop experiment, in which he measured the electric charges on tiny falling water (and later oil) droplets. His study established that any particular droplet's electrical charge is a multiple of a definite, fundamental value – the electron's charge – and thus a confirmation that all electrons have the same charge and mass. Beginning in 1912, he spent several years investigating and finally proving Albert Einstein's proposed linear relationship between energy and frequency, and providing the first direct photoelectric support for the Planck constant. In 1923 Millikan was awarded the Nobel Prize for Physics.
In 1909, S. P. L. Sørensen invented the pH concept and develops methods for measuring acidity. In 1911, Antonius Van den Broek proposed the idea that the elements on the periodic table are more properly organized by positive nuclear charge rather than atomic weight. In 1911, the first Solvay Conference was held in Brussels, bringing together most of the most prominent scientists of the day. In 1912, William Henry Bragg and William Lawrence Bragg proposed Bragg's law and established the field of X-ray crystallography, an important tool for elucidating the crystal structure of substances. In 1912, Peter Debye develops the concept of molecular dipole to describe asymmetric charge distribution in some molecules.
In 1913, Niels Bohr, a Danish physicist, introduced the concepts of quantum mechanics to atomic structure by proposing what is now known as the Bohr model of the atom, where electrons exist only in strictly defined circular orbits around the nucleus similar to rungs on a ladder. The Bohr Model is a planetary model in which the negatively charged electrons orbit a small, positively charged nucleus similar to the planets orbiting the Sun (except that the orbits are not planar) – the gravitational force of the solar system is mathematically akin to the attractive Coulomb (electrical) force between the positively charged nucleus and the negatively charged electrons.
In 1913, Henry Moseley, working from Van den Broek's earlier idea, introduces concept of atomic number to fix inadequacies of Mendeleev's periodic table, which had been based on atomic weight. The peak of Frederick Soddy's career in radiochemistry was in 1913 with his formulation of the concept of isotopes, which stated that certain elements exist in two or more forms which have different atomic weights but which are indistinguishable chemically. He is remembered for proving the existence of isotopes of certain radioactive elements, and is also credited, along with others, with the discovery of the element protactinium in 1917. In 1913, J. J. Thomson expanded on the work of Wien by showing that charged subatomic particles can be separated by their mass-to-charge ratio, a technique known as mass spectrometry.
In 1916, Gilbert N. Lewis published his seminal article "The Atom of the Molecule", which suggested that a chemical bond is a pair of electrons shared by two atoms. Lewis's model equated the classical chemical bond with the sharing of a pair of electrons between the two bonded atoms. Lewis introduced the "electron dot diagrams" in this paper to symbolize the electronic structures of atoms and molecules. Now known as Lewis structures, they are discussed in virtually every introductory chemistry book. Lewis in 1923 developed the electron pair theory of acids and base: Lewis redefined an acid as any atom or molecule with an incomplete octet that was thus capable of accepting electrons from another atom; bases were, of course, electron donors. His theory is known as the concept of Lewis acids and bases. In 1923, G. N. Lewis and Merle Randall published Thermodynamics and the Free Energy of Chemical Substances, first modern treatise on chemical thermodynamics.
The 1920s saw a rapid adoption and application of Lewis's model of the electron-pair bond in the fields of organic and coordination chemistry. In organic chemistry, this was primarily due to the efforts of the British chemists Arthur Lapworth, Robert Robinson, Thomas Lowry, and Christopher Ingold; while in coordination chemistry, Lewis's bonding model was promoted through the efforts of the American chemist Maurice Huggins and the British chemist Nevil Sidgwick.
=== Quantum chemistry ===
Some view the birth of quantum chemistry in the discovery of the Schrödinger equation and its application to the hydrogen atom in 1926. However, the 1927 article of Walter Heitler and Fritz London is often recognised as the first milestone in the history of quantum chemistry. This is the first application of quantum mechanics to the diatomic hydrogen molecule, and thus to the phenomenon of the chemical bond. In the following years much progress was accomplished by Edward Teller, Robert S. Mulliken, Max Born, J. Robert Oppenheimer, Linus Pauling, Erich Hückel, Douglas Hartree, Vladimir Aleksandrovich Fock, to cite a few.
Still, skepticism remained as to the general power of quantum mechanics applied to complex chemical systems. The situation around 1930 is described by Paul Dirac:
The underlying physical laws necessary for the mathematical theory of a large part of physics and the whole of chemistry are thus completely known, and the difficulty is only that the exact application of these laws leads to equations much too complicated to be soluble. It therefore becomes desirable that approximate practical methods of applying quantum mechanics should be developed, which can lead to an explanation of the main features of complex atomic systems without too much computation.
Hence the quantum mechanical methods developed in the 1930s and 1940s are often referred to as theoretical molecular or atomic physics to underline the fact that they were more the application of quantum mechanics to chemistry and spectroscopy than answers to chemically relevant questions. In 1951, a milestone article in quantum chemistry is the seminal paper of Clemens C. J. Roothaan on Roothaan equations. It opened the avenue to the solution of the self-consistent field equations for small molecules like hydrogen or nitrogen. Those computations were performed with the help of tables of integrals which were computed on the most advanced computers of the time.
In the 1940s many physicists turned from molecular or atomic physics to nuclear physics (like J. Robert Oppenheimer or Edward Teller). Glenn T. Seaborg was an American nuclear chemist best known for his work on isolating and identifying transuranium elements (those heavier than uranium). He shared the 1951 Nobel Prize for Chemistry with Edwin Mattison McMillan for their independent discoveries of transuranium elements. Seaborgium was named in his honour, making him one of three people, along Albert Einstein and Yuri Oganessian, for whom a chemical element was named during his lifetime.
=== Molecular biology and biochemistry ===
By the mid 20th century, in principle, the integration of physics and chemistry was extensive, with chemical properties explained as the result of the electronic structure of the atom; Linus Pauling's book on The Nature of the Chemical Bond used the principles of quantum mechanics to deduce bond angles in ever-more complicated molecules. However, though some principles deduced from quantum mechanics were able to predict qualitatively some chemical features for biologically relevant molecules, they were, till the end of the 20th century, more a collection of rules, observations, and recipes than rigorous ab initio quantitative methods.
This heuristic approach triumphed in 1953 when James Watson and Francis Crick deduced the double helical structure of DNA by constructing models constrained by and informed by the knowledge of the chemistry of the constituent parts and the X-ray diffraction patterns obtained by Rosalind Franklin. This discovery lead to an explosion of research into the biochemistry of life.
In the same year, the Miller–Urey experiment, conducted by Stanley Miller and Harold Urey demonstrated that basic constituents of protein, simple amino acids, could themselves be built up from simpler molecules in a simulation of primordial processes on Earth. Though many questions remain about the true nature of the origin of life, this was the first attempt by chemists to study hypothetical processes in the laboratory under controlled conditions.
In 1983 Kary Mullis devised a method for the in-vitro amplification of DNA, known as the polymerase chain reaction (PCR), which revolutionized the chemical processes used in the laboratory to manipulate it. PCR could be used to synthesize specific pieces of DNA and made possible the sequencing of DNA of organisms, which culminated in the huge human genome project.
An important piece in the double helix puzzle was solved by one of Pauling's students Matthew Meselson and Frank Stahl, the result of their collaboration (Meselson–Stahl experiment) has been called as "the most beautiful experiment in biology".
They used a centrifugation technique that sorted molecules according to differences in weight. Because nitrogen atoms are a component of DNA, they were labelled and therefore tracked in replication in bacteria.
=== Late 20th century ===
In 1970, John Pople developed the Gaussian program greatly easing computational chemistry calculations. In 1971, Yves Chauvin offered an explanation of the reaction mechanism of olefin metathesis reactions. In 1975, Karl Barry Sharpless and his group discovered a stereoselective oxidation reactions including Sharpless epoxidation, Sharpless asymmetric dihydroxylation, and Sharpless oxyamination.
In 1985, Harold Kroto, Robert Curl and Richard Smalley discovered fullerenes, a class of large carbon molecules superficially resembling the geodesic dome designed by architect R. Buckminster Fuller. In 1991, Sumio Iijima used electron microscopy to discover a type of cylindrical fullerene known as a carbon nanotube, though earlier work had been done in the field as early as 1951. This material is an important component in the field of nanotechnology. In 1994, Robert A. Holton and his group achieved the first total synthesis of Taxol. In 1995, Eric Cornell and Carl Wieman produced the first Bose–Einstein condensate, a substance that displays quantum mechanical properties on the macroscopic scale.
== Earth science ==
In 1912 Alfred Wegener proposed the theory of Continental Drift. This theory suggests that the shapes of continents and matching coastline geology between some continents indicates they were joined in the past and formed a single landmass known as Pangaea; thereafter they separated and drifted like rafts over the ocean floor, currently reaching their present position. Additionally, the theory of continental drift offered a possible explanation as to the formation of mountains; Plate Tectonics built on the theory of continental drift.
Unfortunately, Wegener provided no convincing mechanism for this drift, and his ideas were not generally accepted during his lifetime. Arthur Homes accepted Wegener's theory and provided a mechanism: mantle convection, to cause the continents to move. However, it was not until after the Second World War that new evidence started to accumulate that supported continental drift. There followed a period of 20 extremely exciting years where the Theory of Continental Drift developed from being believed by a few to being the cornerstone of modern Geology. Beginning in 1947 research found new evidence about the ocean floor, and in 1960 Bruce C. Heezen published the concept of mid-ocean ridges. Soon after this, Robert S. Dietz and Harry H. Hess proposed that the oceanic crust forms as the seafloor spreads apart along mid-ocean ridges in seafloor spreading. This was seen as confirmation of mantle convection and so the major stumbling block to the theory was removed. Geophysical evidence suggested lateral motion of continents and that oceanic crust is younger than continental crust. This geophysical evidence also spurred the hypothesis of paleomagnetism, the record of the orientation of the Earth's magnetic field recorded in magnetic minerals. British geophysicist S. K. Runcorn suggested the concept of paleomagnetism from his finding that the continents had moved relative to the Earth's magnetic poles. Tuzo Wilson, who was a promoter of the sea floor spreading hypothesis and continental drift from the very beginning, added the concept of transform faults to the model, completing the classes of fault types necessary to make the mobility of the plates on the globe function. A symposium on continental drift was held at the Royal Society of London in 1965 must be regarded as the official start of the acceptance of plate tectonics by the scientific community. The abstracts from the symposium are issued as Blacket, Bullard, Runcorn;1965.In this symposium, Edward Bullard and co-workers showed with a computer calculation how the continents along both sides of the Atlantic would best fit to close the ocean, which became known as the famous "Bullard's Fit". By the late 1960s the weight of the evidence available saw Continental Drift as the generally accepted theory.
Other theories of the causes of climate change fared no better. The principal advances were in observational paleoclimatology, as scientists in various fields of geology worked out methods to reveal ancient climates. Wilmot H. Bradley found that annual varves of clay laid down in lake beds showed climate cycles. Andrew Ellicott Douglass saw strong indications of climate change in tree rings. Noting that the rings were thinner in dry years, he reported climate effects from solar variations, particularly in connection with the 17th-century dearth of sunspots (the Maunder Minimum) noticed previously by William Herschel and others. Other scientists, however, found good reason to doubt that tree rings could reveal anything beyond random regional variations. The value of tree rings for climate study was not solidly established until the 1960s.
Through the 1930s the most persistent advocate of a solar-climate connection was astrophysicist Charles Greeley Abbot. By the early 1920s, he had concluded that the solar "constant" was misnamed: his observations showed large variations, which he connected with sunspots passing across the face of the Sun. He and a few others pursued the topic into the 1960s, convinced that sunspot variations were a main cause of climate change. Other scientists were skeptical. Nevertheless, attempts to connect the solar cycle with climate cycles were popular in the 1920s and 1930s. Respected scientists announced correlations that they insisted were reliable enough to make predictions. Sooner or later, every prediction failed, and the subject fell into disrepute.
Meanwhile Milutin Milankovitch, building on James Croll's theory, improved the tedious calculations of the varying distances and angles of the Sun's radiation as the Sun and Moon gradually perturbed the Earth's orbit. Some observations of varves (layers seen in the mud covering the bottom of lakes) matched the prediction of a Milankovitch cycle lasting about 21,000 years. However, most geologists dismissed the astronomical theory. For they could not fit Milankovitch's timing to the accepted sequence, which had only four ice ages, all of them much longer than 22,000 years.
In 1938 Guy Stewart Callendar attempted to revive Arrhenius's greenhouse-effect theory. Callendar presented evidence that both temperature and the CO2 level in the atmosphere had been rising over the past half-century, and he argued that newer spectroscopic measurements showed that the gas was effective in absorbing infrared in the atmosphere. Nevertheless, most scientific opinion continued to dispute or ignore the theory.
Another clue to the nature of climate change came in the mid-1960s from analysis of deep-sea cores by Cesare Emiliani and analysis of ancient corals by Wallace Broecker and collaborators. Rather than four long ice ages, they found a large number of shorter ones in a regular sequence. It appeared that the timing of ice ages was set by the small orbital shifts of the Milankovitch cycles. While the matter remained controversial, some began to suggest that the climate system is sensitive to small changes and can readily be flipped from a stable state into a different one.
Scientists meanwhile began using computers to develop more sophisticated versions of Arrhenius's calculations. In 1967, taking advantage of the ability of digital computers to integrate absorption curves numerically, Syukuro Manabe and Richard Wetherald made the first detailed calculation of the greenhouse effect incorporating convection (the "Manabe-Wetherald one-dimensional radiative-convective model"). They found that, in the absence of unknown feedbacks such as changes in clouds, a doubling of carbon dioxide from the current level would result in approximately 2 °C increase in global temperature.
By the 1960s, aerosol pollution ("smog") had become a serious local problem in many cities, and some scientists began to consider whether the cooling effect of particulate pollution could affect global temperatures. Scientists were unsure whether the cooling effect of particulate pollution or warming effect of greenhouse gas emissions would predominate, but regardless, began to suspect that human emissions could be disruptive to climate in the 21st century if not sooner. In his 1968 book The Population Bomb, Paul R. Ehrlich wrote, "the greenhouse effect is being enhanced now by the greatly increased level of carbon dioxide... [this] is being countered by low-level clouds generated by contrails, dust, and other contaminants ... At the moment we cannot predict what the overall climatic results will be of our using the atmosphere as a garbage dump."
A 1968 study by the Stanford Research Institute for the American Petroleum Institute noted:
If the earth's temperature increases significantly, a number of events might be expected to occur, including the melting of the Antarctic ice cap, a rise in sea levels, warming of the oceans, and an increase in photosynthesis. [..] Revelle makes the point that man is now engaged in a vast geophysical experiment with his environment, the earth. Significant temperature changes are almost certain to occur by the year 2000 and these could bring about climatic changes.
In 1969, NATO was the first candidate to deal with climate change on an international level. It was planned then to establish a hub of research and initiatives of the organization in the civil area, dealing with environmental topics as acid rain and the greenhouse effect. The suggestion of US President Richard Nixon was not very successful with the administration of German Chancellor Kurt Georg Kiesinger. But the topics and the preparation work done on the NATO proposal by the German authorities gained international momentum, (see e.g. the Stockholm United Nations Conference on the Human Environment 1970) as the government of Willy Brandt started to apply them on the civil sphere instead.
Also in 1969, Mikhail Budyko published a theory on the ice-albedo feedback, a foundational element of what is today known as Arctic amplification. The same year a similar model was published by William D. Sellers. Both studies attracted significant attention, since they hinted at the possibility for a runaway positive feedback within the global climate system.
In the early 1970s, evidence that aerosols were increasing worldwide encouraged Reid Bryson and some others to warn of the possibility of severe cooling. Meanwhile, the new evidence that the timing of ice ages was set by predictable orbital cycles suggested that the climate would gradually cool, over thousands of years. For the century ahead, however, a survey of the scientific literature from 1965 to 1979 found 7 articles predicting cooling and 44 predicting warming (many other articles on climate made no prediction); the warming articles were cited much more often in subsequent scientific literature. Several scientific panels from this time period concluded that more research was needed to determine whether warming or cooling was likely, indicating that the trend in the scientific literature had not yet become a consensus.
John Sawyer published the study Man-made Carbon Dioxide and the "Greenhouse" Effect in 1972. He summarized the knowledge of the science at the time, the anthropogenic attribution of the carbon dioxide greenhouse gas, distribution and exponential rise, findings which still hold today. Additionally he accurately predicted the rate of global warming for the period between 1972 and 2000.
The increase of 25% CO2 expected by the end of the century therefore corresponds to an increase of 0.6°C in the world temperature – an amount somewhat greater than the climatic variation of recent centuries. – John Sawyer, 1972
The mainstream news media at the time exaggerated the warnings of the minority who expected imminent cooling. For example, in 1975, Newsweek magazine published a story that warned of "ominous signs that the Earth's weather patterns have begun to change." The article continued by stating that evidence of global cooling was so strong that meteorologists were having "a hard time keeping up with it." On 23 October 2006, Newsweek issued an update stating that it had been "spectacularly wrong about the near-term future".
In the first two "Reports for the Club of Rome" in 1972 and 1974, the anthropogenic climate changes by CO2 increase as well as by waste heat were mentioned. About the latter John Holdren wrote in a study cited in the 1st report, "... that global thermal pollution is hardly our most immediate environmental threat. It could prove to be the most inexorable, however, if we are fortunate enough to evade all the rest." Simple global-scale estimates that recently have been actualized and confirmed by more refined model calculations show noticeable contributions from waste heat to global warming after the year 2100, if its growth rates are not strongly reduced (below the averaged 2% p.a. which occurred since 1973).
Evidence for warming accumulated. By 1975, Manabe and Wetherald had developed a three-dimensional Global climate model that gave a roughly accurate representation of the current climate. Doubling CO2 in the model's atmosphere gave a roughly 2 °C rise in global temperature. Several other kinds of computer models gave similar results: it was impossible to make a model that gave something resembling the actual climate and not have the temperature rise when the CO2 concentration was increased.
The 1979 World Climate Conference (12 to 23 February) of the World Meteorological Organization concluded "it appears plausible that an increased amount of carbon dioxide in the atmosphere can contribute to a gradual warming of the lower atmosphere, especially at higher latitudes....It is possible that some effects on a regional and global scale may be detectable before the end of this century and become significant before the middle of the next century."
In July 1979 the United States National Research Council published a report,
concluding (in part):
When it is assumed that the CO2 content of the atmosphere is doubled and statistical thermal equilibrium is achieved, the more realistic of the modeling efforts predict a global surface warming of between 2 °C and 3.5 °C, with greater increases at high latitudes.
... we have tried but have been unable to find any overlooked or underestimated physical effects that could reduce the currently estimated global warmings due to a doubling of atmospheric CO2 to negligible proportions or reverse them altogether.
By the early 1980s, the slight cooling trend from 1945 to 1975 had stopped. Aerosol pollution had decreased in many areas due to environmental legislation and changes in fuel use, and it became clear that the cooling effect from aerosols was not going to increase substantially while carbon dioxide levels were progressively increasing.
Hansen and others published the 1981 study Climate impact of increasing atmospheric carbon dioxide, and noted: It is shown that the anthropogenic carbon dioxide warming should emerge from the noise level of natural climate variability by the end of the century, and there is a high probability of warming in the 1980s. Potential effects on climate in the 21st century include the creation of drought-prone regions in North America and central Asia as part of a shifting of climatic zones, erosion of the West Antarctic ice sheet with a consequent worldwide rise in sea level, and opening of the fabled Northwest Passage.
In 1982, Greenland ice cores drilled by Hans Oeschger, Willi Dansgaard, and collaborators revealed dramatic temperature oscillations in the space of a century in the distant past. The most prominent of the changes in their record corresponded to the violent Younger Dryas climate oscillation seen in shifts in types of pollen in lake beds all over Europe. Evidently drastic climate changes were possible within a human lifetime.
In 1985 a joint UNEP/WMO/ICSU Conference on the "Assessment of the Role of Carbon Dioxide and Other Greenhouse Gases in Climate Variations and Associated Impacts" concluded that greenhouse gases "are expected" to cause significant warming in the next century and that some warming is inevitable.
Meanwhile, ice cores drilled by a Franco-Soviet team at the Vostok Station in Antarctica showed that CO2 and temperature had gone up and down together in wide swings through past ice ages. This confirmed the CO2-temperature relationship in a manner entirely independent of computer climate models, strongly reinforcing the emerging scientific consensus. The findings also pointed to powerful biological and geochemical feedbacks.
In June 1988, James E. Hansen made one of the first assessments that human-caused warming had already measurably affected global climate. Shortly after, a "World Conference on the Changing Atmosphere: Implications for Global Security" gathered hundreds of scientists and others in Toronto. They concluded that the changes in the atmosphere due to human pollution "represent a major threat to international security and are already having harmful consequences over many parts of the globe," and declared that by 2005 the world would be well-advised to push its emissions some 20% below the 1988 level.
The 1980s saw important breakthroughs with regard to global environmental challenges. Ozone depletion was mitigated by the Vienna Convention (1985) and the Montreal Protocol (1987). Acid rain was mainly regulated on national and regional levels.
Colors indicate temperature anomalies (NASA/NOAA; 20 January 2016).
In 1988 the WMO established the Intergovernmental Panel on Climate Change with the support of the UNEP. The IPCC continues its work through the present day, and issues a series of Assessment Reports and supplemental reports that describe the state of scientific understanding at the time each report is prepared. Scientific developments during this period are summarized about once every five to six years in the IPCC Assessment Reports which were published in 1990 (First Assessment Report), 1995 (Second Assessment Report), 2001 (Third Assessment Report), 2007 (Fourth Assessment Report), and 2013/2014 (Fifth Assessment Report).
Since the 1990s, research on climate change has expanded and grown, linking many fields such as atmospheric sciences, numerical modeling, behavioral sciences, geology and economics, or security.
== Engineering and technology ==
One of the prominent traits of the 20th century was the dramatic growth of technology. Organized research and practice of science led to advancement in the fields of communication, engineering, travel, medicine, and war.
The number and types of home appliances increased dramatically due to advancements in technology, electricity availability, and increases in wealth and leisure time. Such basic appliances as washing machines, clothes dryers, furnaces, exercise machines, refrigerators, freezers, electric stoves, and vacuum cleaners all became popular from the 1920s through the 1950s. The microwave oven was built on 25 October 1955 and became popular during the 1980s and have become a standard in all homes by the 1990s. Radios were popularized as a form of entertainment during the 1920s, which extended to television during the 1950s. Cable and satellite television spread rapidly during the 1980s and 1990s. Personal computers began to enter the home during the 1970s–1980s as well. The age of the portable music player grew during the 1960s with the development of the transistor radio, 8-track and cassette tapes, which slowly began to replace record players These were in turn replaced by the CD during the late 1980s and 1990s. The proliferation of the Internet in the mid-to-late 1990s made digital distribution of music (mp3s) possible. VCRs were popularized in the 1970s, but by the end of the 20th century, DVD players were beginning to replace them, making the VHS obsolete by the end of the first decade of the 21st century.
The first airplane was flown in 1903. With the engineering of the faster jet engine in the 1940s, mass air travel became commercially viable.
The assembly line made mass production of the automobile viable. By the end of the 20th century, billions of people had automobiles for personal transportation. The combination of the automobile, motor boats and air travel allowed for unprecedented personal mobility. In western nations, motor vehicle accidents became the greatest cause of death for young people. However, expansion of divided highways reduced the death rate.
The triode tube, transistor and integrated circuit successively revolutionized electronics and computers, leading to the proliferation of the personal computer in the 1980s and cell phones and the public-use Internet in the 1990s.
New materials, most notably stainless steel, Velcro, silicone, teflon, and plastics such as polystyrene, PVC, polyethylene, and nylon came into widespread use for many various applications. These materials typically have tremendous performance gains in strength, temperature, chemical resistance, or mechanical properties over those known prior to the 20th century.
Aluminium became an inexpensive metal and became second only to iron in use.
Semiconductor materials were discovered, and methods of production and purification developed for use in electronic devices. Silicon became one of the purest substances ever produced.
Thousands of chemicals were developed for industrial processing and home use.
== Mathematics ==
The 20th century saw mathematics become a major profession. As in most areas of study, the explosion of knowledge in the scientific age has led to specialization: by the end of the century there were hundreds of specialized areas in mathematics and the Mathematics Subject Classification was dozens of pages long. Every year, thousands of new Ph.D.s in mathematics were awarded, and jobs were available in both teaching and industry. More and more mathematical journals were published and, by the end of the century, the development of the World Wide Web led to online publishing. Mathematical collaborations of unprecedented size and scope took place. An example is the classification of finite simple groups (also called the "enormous theorem"), whose proof between 1955 and 1983 required 500-odd journal articles by about 100 authors, and filling tens of thousands of pages.
In a 1900 speech to the International Congress of Mathematicians, David Hilbert set out a list of 23 unsolved problems in mathematics. These problems, spanning many areas of mathematics, formed a central focus for much of 20th-century mathematics. Today, 10 have been solved, 7 are partially solved, and 2 are still open. The remaining 4 are too loosely formulated to be stated as solved or not.
In 1929 and 1930, it was proved the truth or falsity of all statements formulated about the natural numbers plus one of addition and multiplication, was decidable, i.e. could be determined by some algorithm. In 1931, Kurt Gödel found that this was not the case for the natural numbers plus both addition and multiplication; this system, known as Peano arithmetic, was in fact incompletable. (Peano arithmetic is adequate for a good deal of number theory, including the notion of prime number.) A consequence of Gödel's two incompleteness theorems is that in any mathematical system that includes Peano arithmetic (including all of analysis and geometry), truth necessarily outruns proof, i.e. there are true statements that cannot be proved within the system. Hence mathematics cannot be reduced to mathematical logic, and David Hilbert's dream of making all of mathematics complete and consistent needed to be reformulated.
In 1963, Paul Cohen proved that the continuum hypothesis is independent of (could neither be proved nor disproved from) the standard axioms of set theory. In 1976, Wolfgang Haken and Kenneth Appel used a computer to prove the four color theorem. Andrew Wiles, building on the work of others, proved Fermat's Last Theorem in 1995. In 1998 Thomas Callister Hales proved the Kepler conjecture.
Differential geometry came into its own when Albert Einstein used it in general relativity. Entirely new areas of mathematics such as mathematical logic, topology, and John von Neumann's game theory changed the kinds of questions that could be answered by mathematical methods. All kinds of structures were abstracted using axioms and given names like metric spaces, topological spaces etc. As mathematicians do, the concept of an abstract structure was itself abstracted and led to category theory. Grothendieck and Serre recast algebraic geometry using sheaf theory. Large advances were made in the qualitative study of dynamical systems that Poincaré had begun in the 1890s.
Measure theory was developed in the late 19th and early 20th centuries. Applications of measures include the Lebesgue integral, Kolmogorov's axiomatisation of probability theory, and ergodic theory. Knot theory greatly expanded. Quantum mechanics led to the development of functional analysis. Other new areas include Laurent Schwartz's distribution theory, fixed point theory, singularity theory and René Thom's catastrophe theory, model theory, and Mandelbrot's fractals. Lie theory with its Lie groups and Lie algebras became one of the major areas of study.
Non-standard analysis, introduced by Abraham Robinson, rehabilitated the infinitesimal approach to calculus, which had fallen into disrepute in favour of the theory of limits, by extending the field of real numbers to the Hyperreal numbers which include infinitesimal and infinite quantities. An even larger number system, the surreal numbers were discovered by John Horton Conway in connection with combinatorial games.
The development and continual improvement of computers, at first mechanical analog machines and then digital electronic machines, allowed industry to deal with larger and larger amounts of data to facilitate mass production and distribution and communication, and new areas of mathematics were developed to deal with this: Alan Turing's computability theory; complexity theory; Derrick Henry Lehmer's use of ENIAC to further number theory and the Lucas-Lehmer test; Rózsa Péter's recursive function theory; Claude Shannon's information theory; signal processing; data analysis; optimization and other areas of operations research. In the preceding centuries much mathematical focus was on calculus and continuous functions, but the rise of computing and communication networks led to an increasing importance of discrete concepts and the expansion of combinatorics including graph theory. The speed and data processing abilities of computers also enabled the handling of mathematical problems that were too time-consuming to deal with by pencil and paper calculations, leading to areas such as numerical analysis and symbolic computation. Some of the most important methods and algorithms of the 20th century are: the simplex algorithm, the fast Fourier transform, error-correcting codes, the Kalman filter from control theory and the RSA algorithm of public-key cryptography.
== Physics ==
New areas of physics, like special relativity, general relativity, and quantum mechanics, were developed during the first half of the century. In the process, the internal structure of atoms came to be clearly understood, followed by the discovery of elementary particles.
It was found that all the known forces can be traced to only four fundamental interactions. It was discovered further that two forces, electromagnetism and weak interaction, can be merged in the electroweak interaction, leaving only three different fundamental interactions.
Discovery of nuclear reactions, in particular nuclear fusion, finally revealed the source of solar energy.
Radiocarbon dating was invented, and became a powerful technique for determining the age of prehistoric animals and plants as well as historical objects.
Stellar nucleosynthesis was refined as a theory in 1954 by Fred Hoyle; the theory was supported by astronomical evidence that showed chemical elements were created by nuclear fusion reactions within stars.
=== Quantum mechanics ===
== Social sciences ==
Ivan Pavlov developed the theory of classical conditioning.
The Austrian School of economic theory gained in prominence.
== References == | Wikipedia/20th_century_in_science |
A therapy or medical treatment is the attempted remediation of a health problem, usually following a medical diagnosis. Both words, treatment and therapy, are often abbreviated tx, Tx, or Tx.
As a rule, each therapy has indications and contraindications. There are many different types of therapy. Not all therapies are effective. Many therapies can produce unwanted adverse effects.
Treatment and therapy are often synonymous, especially in the usage of health professionals. However, in the context of mental health, the term therapy may refer specifically to psychotherapy.
== Semantic field ==
The words care, therapy, treatment, and intervention overlap in a semantic field, and thus they can be synonymous depending on context. Moving rightward through that order, the connotative level of holism decreases and the level of specificity (to concrete instances) increases. Thus, in health-care contexts (where its senses are always noncount), the word care tends to imply a broad idea of everything done to protect or improve someone's health (for example, as in the terms preventive care and primary care, which connote ongoing action), although it sometimes implies a narrower idea (for example, in the simplest cases of wound care or postanesthesia care, a few particular steps are sufficient, and the patient's interaction with the provider of such care is soon finished). In contrast, the word intervention tends to be specific and concrete, and thus the word is often countable; for example, one instance of cardiac catheterization is one intervention performed, and coronary care (noncount) can require a series of interventions (count). At the extreme, the piling on of such countable interventions amounts to interventionism, a flawed model of care lacking holistic circumspection—merely treating discrete problems (in billable increments) rather than maintaining health. Therapy and treatment, in the middle of the semantic field, can connote either the holism of care or the discreteness of intervention, with context conveying the intent in each use. Accordingly, they can be used in both noncount and count senses (for example, therapy for chronic kidney disease can involve several dialysis treatments per week).
The words aceology and iamatology are obscure and obsolete synonyms referring to the study of therapies.
The English word therapy comes via Latin therapīa from Ancient Greek: θεραπεία and literally means "curing" or "healing". The term therapeusis is a somewhat archaic doublet of the word therapy.
== Types of therapies ==
Therapy as a treatment for physical or mental condition is based on knowledge usually from one of three separate fields (or a combination of them): conventional medicine (allopathic, Western biomedicine, relying on scientific approach and evidence-based practice), traditional medicine (age-old cultural practices), and alternative medicine (healthcare procedures "not readily integrated into the dominant healthcare model").
=== By chronology, priority, or intensity ===
==== Levels of care ====
Levels of care classify health care into categories of chronology, priority, or intensity, as follows:
Urgent care handles health issues that need to be handled today but are not necessarily emergencies; the urgent care venue can send a patient to the emergency care level if it turns out to be needed.
In the United States (and possibly various other countries), urgent care centers also serve another function as their other main purpose: U.S. primary care practices have evolved in recent decades into a configuration whereby urgent care centers provide portions of primary care that cannot wait a month, because getting an appointment with the primary care practitioner is often subject to a waitlist of 2 to 8 weeks.
Emergency care handles medical emergencies and is a first point of contact or intake for less serious problems, which can be referred to other levels of care as appropriate. This therapy is often given to patients before a definitive diagnosis is made.
Intensive care, also called critical care, is care for extremely ill or injured patients. It thus requires high resource intensity, knowledge, and skill, as well as quick decision making.
Ambulatory care is care provided on an outpatient basis. Typically patients can walk into and out of the clinic under their own power (hence "ambulatory"), usually on the same day. This care type also involves surgery which, according to recent research, offers "generally superior 30-day outcomes relative to inpatient-based care".
Home care is care at home, including care from providers (such as physicians, nurses, and home health aides) making house calls, care from caregivers such as family members, and patient self-care.
Primary care is meant to be the main kind of care in general, and ideally a medical home that unifies care across referred providers. The current trend in this area is digitalization aiming to ensure open access to information about therapy, issues, and recent progress on biomedical research.
Secondary care is care provided by medical specialists and other health professionals who generally do not have first contact with patients, for example, cardiologists, urologists and dermatologists. A patient reaches secondary care as a next step from primary care, typically by provider referral although sometimes by patient self-initiative. According to a systematic review, fields for development secondary care from patients' viewpoint may be classified into four domains that should usefully guide future improvement of this care stage: "barriers to care, communication, coordination, and relationships and personal value".
Tertiary care is specialized consultative care, usually for inpatients and on referral from a primary or secondary health professional, in a facility that has personnel and facilities for advanced medical investigation and treatment, such as a tertiary referral hospital.
Follow-up care is additional care during or after convalescence. Aftercare is generally synonymous with follow-up care. One of the key areas of development–Telehealth, including non-clinical services: provider training, administrative meetings, and continuing medical education–offers opportunities to improve access to care, increase provider and patient productivity through reduced travel, potential expenses savings, and the ability to expand services.
End-of-life care is care near the end of one's life. It often includes the following:
Palliative care is supportive care, most especially (but not necessarily) near the end of life.
Hospice care is palliative care very near the end of life when cure is very unlikely. Its main goal is comfort, both physical and mental. A systematic meta review showed that the most cost-efficient one relates to home-based end-of-life care, including reduced overall "resource use and improved patient and carer outcomes".
==== Lines of therapy ====
Treatment decisions often follow formal or informal algorithmic guidelines. Treatment options can often be ranked or prioritized into lines of therapy: first-line therapy, second-line therapy, third-line therapy, and so on. First-line therapy (sometimes referred to as induction therapy, primary therapy, or front-line therapy) is the first therapy that will be tried. Its priority over other options is usually either: (1) formally recommended on the basis of clinical trial evidence for its best-available combination of efficacy, safety, and tolerability or (2) chosen based on the clinical experience of the physician. If a first-line therapy either fails to resolve the issue or produces intolerable side effects, additional (second-line) therapies may be substituted or added to the treatment regimen, followed by third-line therapies, and so on.
An example of a context in which the formalization of treatment algorithms and the ranking of lines of therapy is very extensive is chemotherapy regimens. Because of the great difficulty in successfully treating some forms of cancer, one line after another may be tried. In oncology the count of therapy lines may reach 10 or even 20.
Often multiple therapies may be tried simultaneously (combination therapy or polytherapy). Thus combination chemotherapy is also called polychemotherapy, whereas chemotherapy with one agent at a time is called single-agent therapy or monotherapy. Single-agent therapy is a care algorithm that focuses on one specific drug or procedure. It utilizes a single therapeutic agent rather than combining multiple ones. Multiagent Therapy is a treatment by two or more drugs or procedures. Comprehensive therapy combines various forms of medical treatment to provide the most effective care for patients.
Adjuvant therapy is therapy given in addition to the primary, main, or initial treatment, but simultaneously (as opposed to second-line therapy). Neoadjuvant therapy is therapy that is begun before the main therapy. Thus one can consider surgical excision of a tumor as the first-line therapy for a certain type and stage of cancer even though radiotherapy is used before it; the radiotherapy is neoadjuvant (chronologically first but not primary in the sense of the main event). Premedication is conceptually not far from this, but the words are not interchangeable; cytotoxic drugs to put a tumor "on the ropes" before surgery delivers the "knockout punch" are called neoadjuvant chemotherapy, not premedication, whereas things like anesthetics or prophylactic antibiotics before dental surgery are called premedication.
Step therapy or stepladder therapy is a specific type of prioritization by lines of therapy. It is controversial in American health care because unlike conventional decision-making about what constitutes first-line, second-line, and third-line therapy, which in the U.S. reflects safety and efficacy first and cost only according to the patient's wishes, step therapy attempts to mix cost containment by someone other than the patient (third-party payers) into the algorithm.
Therapy freedom refers to prescription for use of an unlicensed medicine (without a marketing authorization issued by the licensing authority of the country) and the negotiation between individual and group rights are involved. A comprehensive research in Australia, Czech Republic, India, Israel, Italy, Netherlands, Spain, Serbia, Sweden, UK, and USA showed that the rate of the unlicensed medicine prescription has been reported to range from 0.3 to 35% depending on the country. In many jurisdictions, therapy freedom is limited to cases of no treatment existing that is both well-established and more efficacious.
=== By intent ===
=== By intervention ===
Invasive therapy is achieved either through surgery or through the use of drugs. Medical invasive treatments can be divided into two main categories: pharmacotherapy and surgery.
Noninvasive therapies are medical treatments that do not involve entry into the body. It can be classified into five main categories: neurotherapy, physical therapy, occupational therapy, radiation therapy, and psychotherapy.
=== By therapy composition ===
Treatments can be classified according to the method of treatment:
==== By matter ====
by drugs: pharmacotherapy, chemotherapy (also, medical therapy often means specifically pharmacotherapy)
by medical devices: implantation
cardiac resynchronization therapy
by specific molecules: molecular therapy (although most drugs are specific molecules, molecular medicine refers in particular to medicine relying on molecular biology)
by specific biomolecular targets: targeted therapy
molecular chaperone therapy
by chelation: chelation therapy
by specific chemical elements:
by metals:
by heavy metals:
by gold: chrysotherapy (aurotherapy)
by platinum-containing drugs: platin therapy
by biometals
by lithium: lithium therapy
by potassium: potassium supplementation
by magnesium: magnesium supplementation
by chromium: chromium supplementation; phonemic neurological hypochromium therapy
by copper: copper supplementation
by nonmetals:
by diatomic oxygen: oxygen therapy, hyperbaric oxygen therapy (hyperbaric medicine)
transdermal continuous oxygen therapy
by triatomic oxygen (ozone): ozone therapy
by fluoride: fluoride therapy
by other gases: medical gas therapy
by water:
hydrotherapy
aquatic therapy
rehydration therapy
oral rehydration therapy
water cure (therapy)
by biological materials (biogenic substances, biomolecules, biotic materials, natural products), including their synthetic equivalents: biotherapy
by whole organisms
by viruses: virotherapy
by bacteriophages: phage therapy
by animal interaction: see animal interaction section
by constituents or products of organisms
by plant parts or extracts (but many drugs are derived from plants, even when the term phytotherapy is not used)
scientific type: phytotherapy
traditional (prescientific) type: herbalism
by animal parts: quackery involving shark fins, tiger parts, and so on, often driving threat or endangerment of species
by genes: gene therapy
gene therapy for epilepsy
gene therapy for osteoarthritis
gene therapy for color blindness
gene therapy of the human retina
gene therapy in Parkinson's disease
by epigenetics: epigenetic therapy
by proteins: protein therapy (but many drugs are proteins despite not being called protein therapy)
by enzymes: enzyme replacement therapy
by hormones: hormone therapy
hormonal therapy (oncology)
hormone replacement therapy
estrogen replacement therapy
androgen replacement therapy
hormone replacement therapy (menopause)
transgender hormone therapy
feminizing hormone therapy
masculinizing hormone therapy
antihormone therapy
androgen deprivation therapy
by whole cells: cell therapy (cytotherapy)
by stem cells: stem cell therapy
by immune cells: see immune system products below
by immune system products: immunotherapy, host modulatory therapy
by immune cells:
T-cell vaccination
cell transfer therapy
autologous immune enhancement therapy
TK cell therapy
by humoral immune factors: antibody therapy
by whole serum: serotherapy, including antiserum therapy
by immunoglobulins: immunoglobulin therapy
by monoclonal antibodies: monoclonal antibody therapy
by urine: urine therapy (some scientific forms; many prescientific or pseudoscientific forms)
by food and dietary choices:
medical nutrition therapy
grape therapy (quackery)
by salts (but many drugs are the salts of organic acids, even when drug therapy is not called by names reflecting that)
by salts in the air
by natural dry salt air: "taking the cure" in desert locales (especially common in prescientific medicine; for example, one 19th-century way to treat tuberculosis)
by artificial dry salt air:
low-humidity forms of speleotherapy
negative air ionization therapy
by moist salt air:
by natural moist salt air: seaside cure (especially common in prescientific medicine)
by artificial moist salt air: water vapor forms of speleotherapy
by salts in the water
by mineral water: spa cure ("taking the waters") (especially common in prescientific medicine)
by seawater: seaside cure (especially common in prescientific medicine)
by aroma: aromatherapy
by other materials with mechanism of action unknown
by occlusion with duct tape: duct tape occlusion therapy
==== By energy ====
by electric energy as electric current: electrotherapy, electroconvulsive therapy
Transcranial magnetic stimulation
Vagus nerve stimulation
by magnetic energy:
magnet therapy
pulsed electromagnetic field therapy
magnetic resonance therapy
by electromagnetic radiation (EMR):
by light: light therapy (phototherapy)
ultraviolet light therapy
PUVA therapy
photodynamic therapy
photothermal therapy
cytoluminescent therapy
blood irradiation therapy
by darkness: dark therapy
by lasers: laser therapy
low level laser therapy
by gamma rays: radiosurgery
Gamma Knife radiosurgery
stereotactic radiation therapy
cobalt therapy
by radiation generally: radiation therapy (radiotherapy)
intraoperative radiation therapy
by EMR particles:
particle therapy
proton therapy
electron therapy
intraoperative electron radiation therapy
Auger therapy
neutron therapy
fast neutron therapy
neutron capture therapy of cancer
by radioisotopes emitting EMR:
by nuclear medicine
by brachytherapy
quackery type: electromagnetic therapy (alternative medicine)
by mechanical: manual therapy as massotherapy and therapy by exercise as in physical therapy
inversion therapy
by sound:
by ultrasound:
ultrasonic lithotripsy
extracorporeal shockwave therapy
sonodynamic therapy
by music: music therapy
by temperature
by heat: heat therapy (thermotherapy)
by moderately elevated ambient temperatures: hyperthermia therapy
by dry warm surroundings: Waon therapy
by dry or humid warm surroundings: sauna, including infrared sauna, for sweat therapy
by cold:
by extreme cold to specific tissue volumes: cryotherapy
by ice and compression: cold compression therapy
by ambient cold:
hypothermia therapy for neonatal encephalopathy (in newborns)
targeted temperature management (therapeutic hypothermia, protective hypothermia)
by hot and cold alternation: contrast bath therapy
==== By procedure and human interaction ====
Surgery
by counseling, such as psychotherapy (see also: list of psychotherapies)
systemic therapy
by group psychotherapy
by cognitive behavioral therapy
by cognitive therapy
by behaviour therapy
by dialectical behavior therapy
by cognitive emotional behavioral therapy
by cognitive rehabilitation therapy
by family therapy
by education
by psychoeducation
by information therapy
by speech therapy, physical therapy, occupational therapy, vision therapy, massage therapy, chiropractic or acupuncture
by lifestyle modifications, such as avoiding unhealthy food or maintaining a predictable sleep schedule
by coaching
==== By animal interaction ====
by pets, assistance animals, or working animals: animal-assisted therapy
by horses: equine therapy, hippotherapy
by dogs: pet therapy with therapy dogs, including grief therapy dogs
by cats: pet therapy with therapy cats
by fish: ichthyotherapy (wading with fish), aquarium therapy (watching fish)
by maggots: maggot therapy
by worms:
by internal worms: helminthic therapy
by leeches: leech therapy
by immersion: animal bath
==== By meditation ====
by mindfulness: mindfulness-based cognitive therapy
==== By reading ====
by bibliotherapy
==== By creativity ====
by expression: expressive therapy
by writing: writing therapy
journal therapy
by play: play therapy
by art: art therapy
sensory art therapy
comic book therapy
by gardening: horticultural therapy
by dance: dance therapy
by drama: drama therapy
by recreation: recreational therapy
by music: music therapy
==== By sleeping and waking ====
by deep sleep: deep sleep therapy
by sleep deprivation: wake therapy
== See also ==
== References ==
== External links ==
The dictionary definition of therapy at Wiktionary
"Chapter Nine of the Book of Medicine Dedicated to Mansur, with the Commentary of Sillanus de Nigris" is a Latin book by Rhazes, from 1483, that is known for its ninth chapter, which is about therapeutics | Wikipedia/Therapy |
In statistics and natural language processing, a topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. Topic modeling is a frequently used text-mining tool for discovery of hidden semantic structures in a text body. Intuitively, given that a document is about a particular topic, one would expect particular words to appear in the document more or less frequently: "dog" and "bone" will appear more often in documents about dogs, "cat" and "meow" will appear in documents about cats, and "the" and "is" will appear approximately equally in both. A document typically concerns multiple topics in different proportions; thus, in a document that is 10% about cats and 90% about dogs, there would probably be about 9 times more dog words than cat words. The "topics" produced by topic modeling techniques are clusters of similar words. A topic model captures this intuition in a mathematical framework, which allows examining a set of documents and discovering, based on the statistics of the words in each, what the topics might be and what each document's balance of topics is.
Topic models are also referred to as probabilistic topic models, which refers to statistical algorithms for discovering the latent semantic structures of an extensive text body. In the age of information, the amount of the written material we encounter each day is simply beyond our processing capacity. Topic models can help to organize and offer insights for us to understand large collections of unstructured text bodies. Originally developed as a text-mining tool, topic models have been used to detect instructive structures in data such as genetic information, images, and networks. They also have applications in other fields such as bioinformatics and computer vision.
== History ==
An early topic model was described by Papadimitriou, Raghavan, Tamaki and Vempala in 1998. Another one, called probabilistic latent semantic analysis (PLSA), was created by Thomas Hofmann in 1999. Latent Dirichlet allocation (LDA), perhaps the most common topic model currently in use, is a generalization of PLSA. Developed by David Blei, Andrew Ng, and Michael I. Jordan in 2002, LDA introduces sparse Dirichlet prior distributions over document-topic and topic-word distributions, encoding the intuition that documents cover a small number of topics and that topics often use a small number of words. Other topic models are generally extensions on LDA, such as Pachinko allocation, which improves on LDA by modeling correlations between topics in addition to the word correlations which constitute topics. Hierarchical latent tree analysis (HLTA) is an alternative to LDA, which models word co-occurrence using a tree of latent variables and the states of the latent variables, which correspond to soft clusters of documents, are interpreted as topics.
== Topic models for context information ==
Approaches for temporal information include Block and Newman's determination of the temporal dynamics of topics in the Pennsylvania Gazette during 1728–1800. Griffiths & Steyvers used topic modeling on abstracts from the journal PNAS to identify topics that rose or fell in popularity from 1991 to 2001 whereas Lamba & Madhusushan used topic modeling on full-text research articles retrieved from DJLIT journal from 1981 to 2018. In the field of library and information science, Lamba & Madhusudhan applied topic modeling on different Indian resources like journal articles and electronic theses and resources (ETDs). Nelson has been analyzing change in topics over time in the Richmond Times-Dispatch to understand social and political changes and continuities in Richmond during the American Civil War. Yang, Torget and Mihalcea applied topic modeling methods to newspapers from 1829 to 2008. Mimno used topic modelling with 24 journals on classical philology and archaeology spanning 150 years to look at how topics in the journals change over time and how the journals become more different or similar over time.
Yin et al. introduced a topic model for geographically distributed documents, where document positions are explained by latent regions which are detected during inference.
Chang and Blei included network information between linked documents in the relational topic model, to model the links between websites.
The author-topic model by Rosen-Zvi et al. models the topics associated with authors of documents to improve the topic detection for documents with authorship information.
HLTA was applied to a collection of recent research papers published at major AI and Machine Learning venues. The resulting model is called The AI Tree. The resulting topics are used to index the papers at aipano.cse.ust.hk to help researchers track research trends and identify papers to read, and help conference organizers and journal editors identify reviewers for submissions.
To improve the qualitative aspects and coherency of generated topics, some researchers have explored the efficacy of "coherence scores", or otherwise how computer-extracted clusters (i.e. topics) align with a human benchmark. Coherence scores are metrics for optimising the number of topics to extract from a document corpus.
== Algorithms ==
In practice, researchers attempt to fit appropriate model parameters to the data corpus using one of several heuristics for maximum likelihood fit. A survey by D. Blei describes this suite of algorithms.
Several groups of researchers starting with Papadimitriou et al. have attempted to design algorithms with provable guarantees. Assuming that the data were actually generated by the model in question, they try to design algorithms that probably find the model that was used to create the data. Techniques used here include singular value decomposition (SVD) and the method of moments. In 2012 an algorithm based upon non-negative matrix factorization (NMF) was introduced that also generalizes to topic models with correlations among topics.
In 2017, neural network has been leveraged in topic modeling to make it faster in inference, which has been extended weakly supervised version.
In 2018 a new approach to topic models was proposed: it is based on stochastic block model.
Because of the recent development of LLM, topic modeling has leveraged LLM through contextual embedding and fine tuning.
== Applications of topic models ==
=== To quantitative biomedicine ===
Topic models are being used also in other contexts. For examples uses of topic models in biology and bioinformatics research emerged. Recently topic models has been used to extract information from dataset of cancers' genomic samples.
In this case topics are biological latent variables to be inferred.
=== To analysis of music and creativity ===
Topic models can be used for analysis of continuous signals like music. For instance, they were used to quantify how musical styles change in time, and identify the influence of specific artists on later music creation.
== See also ==
Explicit semantic analysis
Latent semantic analysis
Latent Dirichlet allocation
Hierarchical Dirichlet process
Non-negative matrix factorization
Statistical classification
Unsupervised learning
Mallet (software project)
Gensim
Sentence embedding
== References ==
== Further reading ==
Steyvers, Mark; Griffiths, Tom (2007). "Probabilistic Topic Models". In Landauer, T.; McNamara, D; Dennis, S.; et al. (eds.). Handbook of Latent Semantic Analysis (PDF). Psychology Press. ISBN 978-0-8058-5418-3. Archived from the original (PDF) on 2013-06-24.
Blei, D.M.; Lafferty, J.D. (2009). "Topic Models" (PDF).
Blei, D.; Lafferty, J. (2007). "A correlated topic model of Science". Annals of Applied Statistics. 1 (1): 17–35. arXiv:0708.3601. doi:10.1214/07-AOAS114. S2CID 8872108.
Mimno, D. (April 2012). "Computational Historiography: Data Mining in a Century of Classics Journals" (PDF). Journal on Computing and Cultural Heritage. 5 (1): 1–19. doi:10.1145/2160165.2160168. S2CID 12153151.
Marwick, Ben (2013). "Discovery of Emergent Issues and Controversies in Anthropology Using Text Mining, Topic Modeling, and Social Network Analysis of Microblog Content". In Yanchang, Zhao; Yonghua, Cen (eds.). Data Mining Applications with R. Elsevier. pp. 63–93.
Jockers, M. 2010 Who's your DH Blog Mate: Match-Making the Day of DH Bloggers with Topic Modeling Matthew L. Jockers, posted 19 March 2010
Drouin, J. 2011 Foray Into Topic Modeling Ecclesiastical Proust Archive. posted 17 March 2011
Templeton, C. 2011 Topic Modeling in the Humanities: An Overview Maryland Institute for Technology in the Humanities Blog. posted 1 August 2011
Griffiths, T.; Steyvers, M. (2004). "Finding scientific topics". Proceedings of the National Academy of Sciences. 101 (Suppl 1): 5228–35. Bibcode:2004PNAS..101.5228G. doi:10.1073/pnas.0307752101. PMC 387300. PMID 14872004.
Yang, T., A Torget and R. Mihalcea (2011) Topic Modeling on Historical Newspapers. Proceedings of the 5th ACL-HLT Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities. The Association for Computational Linguistics, Madison, WI. pages 96–104.
Block, S. (January 2006). "Doing More with Digitization: An introduction to topic modeling of early American sources". Common-place the Interactive Journal of Early American Life. 6 (2).
Newman, D.; Block, S. (March 2006). "Probabilistic Topic Decomposition of an Eighteenth-Century Newspaper" (PDF). Journal of the American Society for Information Science and Technology. 57 (5): 753–767. doi:10.1002/asi.20342. S2CID 1484286.
== External links ==
Mimno, David. "Topic modeling bibliography".
Brett, Megan R. "Topic Modeling: A Basic Introduction". Journal of Digital Humanities.
Topic Models Applied to Online News and Reviews Video of a Google Tech Talk presentation by Alice Oh on topic modeling with LDA
Modeling Science: Dynamic Topic Models of Scholarly Research Video of a Google Tech Talk presentation by David M. Blei
Automated Topic Models in Political Science Video of a presentation by Brandon Stewart at the Tools for Text Workshop, 14 June 2010
Shawn Graham, Ian Milligan, and Scott Weingart "Getting Started with Topic Modeling and MALLET". The Programming Historian. Archived from the original on 2014-08-28. Retrieved 2014-05-29.
Blei, David M. "Introductory material and software"
code, demo - example of using LDA for topic modelling | Wikipedia/Topic_model |
Actor–network theory (ANT) is a theoretical and methodological approach to social theory where everything in the social and natural worlds exists in constantly shifting networks of relationships. It posits that nothing exists outside those relationships. All the factors involved in a social situation are on the same level, and thus there are no external social forces beyond what and how the network participants interact at present. Thus, objects, ideas, processes, and any other relevant factors are seen as just as important in creating social situations as humans.
ANT holds that social forces do not exist in themselves, and therefore cannot be used to explain social phenomena. Instead, strictly empirical analysis should be undertaken to "describe" rather than "explain" social activity. Only after this can one introduce the concept of social forces, and only as an abstract theoretical concept, not something which genuinely exists in the world.
Although it is best known for its controversial insistence on the capacity of nonhumans to act or participate in systems or networks or both, ANT is also associated with forceful critiques of conventional and critical sociology. Developed by science and technology studies (STS) scholars Michel Callon, Madeleine Akrich and Bruno Latour, the sociologist John Law, and others, it can more technically be described as a "material-semiotic" method. This means that it maps relations that are simultaneously material (between things) and semiotic (between concepts). It assumes that many relations are both material and semiotic. The term actor-network theory was coined by John Law in 1992 to describe the work being done across case studies in different areas at the Centre de Sociologie de l'Innovation at the time.
The theory demonstrates that everything in the social and natural worlds, human and nonhuman, interacts in shifting networks of relationships without any other elements out of the networks. ANT challenges many traditional approaches by defining nonhumans as actors equal to humans. This claim provides a new perspective when applying the theory in practice.
Broadly speaking, ANT is a constructivist approach in that it avoids essentialist explanations of events or innovations (i.e. ANT explains a successful theory by understanding the combinations and interactions of elements that make it successful, rather than saying it is true and the others are false). Likewise, it is not a cohesive theory in itself. Rather, ANT functions as a strategy that assists people in being sensitive to terms and the often unexplored assumptions underlying them. It is distinguished from many other STS and sociological network theories for its distinct material-semiotic approach.
== Background and context ==
ANT was first developed at the Centre de Sociologie de l'Innovation (CSI) of the École nationale supérieure des mines de Paris in the early 1980s by staff (Michel Callon, Madeleine Akrich, Bruno Latour) and visitors (including John Law). The 1984 book co-authored by John Law and fellow-sociologist Peter Lodge (Science for Social Scientists; London: Macmillan Press Ltd.) is a good example of early explorations of how the growth and structure of knowledge could be analyzed and interpreted through the interactions of actors and networks. Initially created in an attempt to understand processes of innovation and knowledge-creation in science and technology, the approach drew on existing work in STS, on studies of large technological systems, and on a range of French intellectual resources including the semiotics of Algirdas Julien Greimas, the writing of philosopher Michel Serres, and the Annales School of history.
ANT appears to reflect many of the preoccupations of French post-structuralism, and in particular a concern with non-foundational and multiple material-semiotic relations. At the same time, it was much more firmly embedded in English-language academic traditions than most post-structuralist-influenced approaches. Its grounding in (predominantly English) science and technology studies was reflected in an intense commitment to the development of theory through qualitative empirical case-studies. Its links with largely US-originated work on large technical systems were reflected in its willingness to analyse large scale technological developments in an even-handed manner to include political, organizational, legal, technical and scientific factors.
Many of the characteristic ANT tools (including the notions of translation, generalized symmetry and the "heterogeneous network"), together with a scientometric tool for mapping innovations in science and technology ("co-word analysis") were initially developed during the 1980s, predominantly in and around the CSI. The "state of the art" of ANT in the late 1980s is well-described in Latour's 1987 text, Science in Action.
From about 1990 onwards, ANT started to become popular as a tool for analysis in a range of fields beyond STS. It was picked up and developed by authors in parts of organizational analysis, informatics, health studies, geography, sociology, anthropology, archaeology, feminist studies, technical communication, and economics.
As of 2008, ANT is a widespread, if controversial, range of material-semiotic approaches for the analysis of heterogeneous relations. In part because of its popularity, it is interpreted and used in a wide range of alternative and sometimes incompatible ways. There is no orthodoxy in current ANT, and different authors use the approach in substantially different ways. Some authors talk of "after-ANT" to refer to "successor projects" blending together different problem-focuses with those of ANT.
== Key concepts ==
=== Actor/Actant ===
An actor (actant) is something that acts or to which activity is granted by others. It implies no motivation of human individual actors nor of humans in general. An actant can literally be anything provided it is granted to be the source of action. In another word, an actor, in this circumstance, is considered as any entity that does things. For example, in the "Pasteur Network", microorganisms are not inert, they cause unsterilized materials to ferment while leaving behind sterilized materials not affected. If they took other actions, that is, if they did not cooperate with Pasteur – if they did not take action (at least according to Pasteur's intentions) – then Pasteur's story may be a bit different. It is in this sense that Latour can refer to microorganisms as actors.
Under the framework of ANT, the principle of generalized symmetry requires all entities must be described in the same terms before a network is considered. Any differences between entities are generated in the network of relations, and do not exist before any network is applied.
==== Human actors ====
Human normally refers to human beings and their human behaviors.
==== Nonhuman actors ====
Traditionally, nonhuman entities are creatures including plants, animals, geology, and natural forces, as well as a collective human making of arts, languages. In ANT, nonhuman covers multiple entities including things, objects, animals, natural phenomena, material structures, transportation devices, texts, and economic goods. But nonhuman actors do not cover entities such as humans, supernatural beings, and other symbolic objects in nature.
=== Actor-Network ===
As the term implies, the actor-network is the central concept in ANT. The term "network" is somewhat problematic in that it, as Latour notes, has a number of unwanted connotations. Firstly, it implies that what is described takes the shape of a network, which is not necessarily the case. Secondly, it implies "transportation without deformation," which, in ANT, is not possible since any actor-network involves a vast number of translations. Latour, however, still contends that network is a fitting term to use, because "it has no a priori order relation; it is not tied to the axiological myth of a top and of a bottom of society; it makes absolutely no assumption whether a specific locus is macro- or micro- and does not modify the tools to study the element 'a' or the element 'b'." This use of the term "network" is very similar to Deleuze and Guattari's rhizomes; Latour even remarks tongue-in-cheek that he would have no objection to renaming ANT "actant-rhizome ontology" if it only had sounded better, which hints at Latour's uneasiness with the word "theory".
Actor–network theory tries to explain how material–semiotic networks come together to act as a whole; the clusters of actors involved in creating meaning are both material and semiotic. As a part of this it may look at explicit strategies for relating different elements together into a network so that they form an apparently coherent whole. These networks are potentially transient, existing in a constant making and re-making. This means that relations need to be repeatedly "performed" or the network will dissolve. They also assume that networks of relations are not intrinsically coherent, and may indeed contain conflicts. Social relations, in other words, are only ever in process, and must be performed continuously.
The Pasteur story that was mentioned above introduced the patterned network of diverse materials, which is called the idea of 'heterogenous networks'. The basic idea of patterned network is that human is not the only factor or contributor in the society, or in any social activities and networks. Thus, the network composes machines, animals, things, and any other objects. For those nonhuman actors, it might be hard for people to imagine their roles in the network. For example, say two people, Jacob and Mike, are speaking through texts. Within the current technology, they are able to communicate with each other without seeing each other in person. Therefore, when typing or writing, the communication is basically not mediated by either of them, but instead by a network of objects, like their computers or cell phones.
If taken to its logical conclusion, then, nearly any actor can be considered merely a sum of other, smaller actors. A car is an example of a complicated system. It contains many electronic and mechanical components, all of which are essentially hidden from view to the driver, who simply deals with the car as a single object. This effect is known as punctualisation, and is similar to the idea of encapsulation in object-oriented programming.
When an actor network breaks down, the punctualisation effect tends to cease as well. In the automobile example above, a non-working engine would cause the driver to become aware of the car as a collection of parts rather than just a vehicle capable of transporting him or her from place to place. This can also occur when elements of a network act contrarily to the network as a whole. In his book Pandora's Hope, Latour likens depunctualization to the opening of a black box. When closed, the box is perceived simply as a box, although when it is opened all elements inside it become visible.
=== Translation ===
Central to ANT is the concept of translation which is sometimes referred to as sociology of translation, in which innovators attempt to create a forum, a central network in which all the actors agree that the network is worth building and defending. In his widely debated 1986 study of how marine biologists tried to restock the St Brieuc Bay in order to produce more scallops, Michel Callon defined 4 moments of translation:
Problematisation: The researchers attempted to make themselves important to the other players in the drama by identifying their nature and issues, then claiming that they could be remedied if the actors negotiated the 'obligatory passage point' of the researchers' study program.
Interessement: A series of procedures used by the researchers to bind the other actors to the parts that had been assigned to them in that program.
Enrollment: A collection of tactics used by the researchers to define and connect the numerous roles they had assigned to others.
Mobilisation: The researchers utilized a series of approaches to ensure that ostensible spokespeople for various key collectivities were appropriately able to represent those collectivities and were not deceived by the latter.
Also important to the notion is the role of network objects in helping to smooth out the translation process by creating equivalencies between what would otherwise be very challenging people, organizations or conditions to mesh together. Bruno Latour spoke about this particular task of objects in his work Reassembling the Social.
=== Quasi-object ===
For the rethinking of social relations as networks, Latour mobilizes a concept from Michel Serres and expands on it in order “to locate the position of these strange new hybrids”. Quasi-objects are simultaneously quasi-subjects – the prefix quasi denotes that neither ontological status as subject or object is pure or permanent, but that these are dynamic entities whose status shifts, depending on their respective momentous activity and their according position in a collective or network. What is decisive is circulation and participation, from which networks emerge, examples for quasi-objects are language, money, bread, love, or the ball in a soccer game: all of these human or non-human, material or immaterial actants have no agency (and thus, subject-status) in themselves, however, they can be seen as the connective tissue underlying – or even acticating – the interactions in which they are enmeshed. In Reassembling the Social, Latour refers to these in-between actants as “the mediators whose proliferation generates, among many other entities, what could be called quasi-objects and quasi-subjects.”
Actor–network theory refers to these creations as tokens or quasi-objects which are passed between actors within the network. As the token is increasingly transmitted or passed through the network, it becomes increasingly punctualized and also increasingly reified. When the token is decreasingly transmitted, or when an actor fails to transmit the token (e.g., the oil pump breaks), punctualization and reification are decreased as well.
== Other central concepts ==
=== A material semiotic method ===
Although it is called a "theory", ANT does not usually explain "why" a network takes the form that it does. Rather, ANT is a way of thoroughly exploring the relational ties within a network (which can be a multitude of different things). As Latour notes, "explanation does not follow from description; it is description taken that much further." It is not, in other words, a theory "of" anything, but rather a method, or a "how-to book" as Latour puts it.
The approach is related to other versions of material-semiotics (notably the work of philosophers Gilles Deleuze, Michel Foucault, and feminist scholar Donna Haraway). It can also be seen as a way of being faithful to the insights of ethnomethodology and its detailed descriptions of how common activities, habits and procedures sustain themselves. Similarities between ANT and symbolic interactionist approaches such as the newer forms of grounded theory like situational analysis, exist, although Latour objects to such a comparison.
Although ANT is mostly associated with studies of science and technology and with the sociology of science, it has been making steady progress in other fields of sociology as well. ANT is adamantly empirical, and as such yields useful insights and tools for sociological inquiry in general. ANT has been deployed in studies of identity and subjectivity, urban transportation systems, and passion and addiction. It also makes steady progress in political and historical sociology.
=== Intermediaries and mediators ===
The distinction between intermediaries and mediators is key to ANT sociology. Intermediaries are entities which make no difference (to some interesting state of affairs which we are studying) and so can be ignored. They transport the force of some other entity more or less without transformation and so are fairly uninteresting. Mediators are entities which multiply difference and so should be the object of study. Their outputs cannot be predicted by their inputs. From an ANT point of view sociology has tended to treat too much of the world as intermediaries.
For instance, a sociologist might take silk and nylon as intermediaries, holding that the former "means", "reflects", or "symbolises" the upper classes and the latter the lower classes. In such a view the real world silk–nylon difference is irrelevant– presumably many other material differences could also, and do also, transport this class distinction. But taken as mediators these fabrics would have to be engaged with by the analyst in their specificity: the internal real-world complexities of silk and nylon suddenly appear relevant, and are seen as actively constructing the ideological class distinction which they once merely reflected.
For the committed ANT analyst, social things—like class distinctions in taste in the silk and nylon example, but also groups and power—must constantly be constructed or performed anew through complex engagements with complex mediators. There is no stand-alone social repertoire lying in the background to be reflected off, expressed through, or substantiated in, interactions (as in an intermediary conception).
=== Reflexivity ===
Bruno Latour's articulation of reflexivity in Actor-Network Theory (ANT) reframes it as an opportunity rather than a problem. His argument addresses the limitations of reflexivity as traditionally conceived in relativist epistemologies and replaces it with a pragmatic, relational approach tied to ANT's broader principles. Latour argues that the observer is merely one actor among many within the network, eliminating the problem of reflexivity as a paradox of status. Reflexivity instead emerges through the tangible work of navigating and translating between networks, requiring the observer to engage actively, like any other actor, in the labour of connection and translation. This grounded form of reflexivity enhances the observer's role as a "world builder" and reinforces ANT's emphasis on the relational and dynamic nature of knowledge creation.
=== Hybridity ===
The belief that neither a human nor a nonhuman is pure, in the sense that neither is human or nonhuman in an absolute sense, but rather beings created via interactions between the two. Humans are thus regarded as quasi-subjects, while nonhumans are regarded as quasi-objects.
== Actor–network theory and specific disciplines ==
Recently, there has been a movement to introduce actor network theory as an analytical tool to a range of applied disciplines outside of sociology, including nursing, public health, urban studies (Farias and Bender, 2010), and community, urban, and regional planning (Beauregard, 2012; Beauregard and Lieto, 2015; Rydin, 2012; Rydin and Tate, 2016, Tate, 2013).
=== International relations ===
Actor–network theory has become increasingly prominent within the discipline of international relations and political science.
Theoretically, scholars within IR have employed ANT in order to disrupt traditional world political binaries (civilised/barbarian, democratic/autocratic, etc.), consider the implications of a posthuman understanding of IR, explore the infrastructures of world politics, and consider the effects of technological agency.
Empirically, IR scholars have drawn on insights from ANT in order to study phenomena including political violences like the use of torture and drones, piracy and maritime governance, and garbage.
=== Design ===
The actor–network theory can also be applied to design, using a perspective that is not simply limited to an analysis of an object's structure. From the ANT viewpoint, design is seen as a series of features that account for a social, psychological, and economical world. ANT argues that objects are designed to shape human action and mold or influence decisions. In this way, the objects' design serves to mediate human relationships and can even impact our morality, ethics, and politics.
=== Literary criticism ===
The literary critic Rita Felski has argued that ANT offers the fields of literary criticism and cultural studies vital new modes of interpreting and engaging with literary texts. She claims that Latour's model has the capacity to allow "us to wiggle out of the straitjacket of suspicion," and to offer meaningful solutions to the problems associated with critique. The theory has been crucial to her formulation of postcritique. Felski suggests that the purpose of applying ANT to literary studies "is no longer to diminish or subtract from the reality of the texts we study but to amplify their reality, as energetic coactors and vital partners."
=== Anthropology of religion ===
In the study of Christianity by anthropologists, the ANT has been employed in a variety of ways of understanding how humans interact with nonhuman actors. Some have been critical of the field of Anthropology of Religion in its tendency to presume that God is not a social actor. The ANT is used to problematize the role of God, as a nonhuman actor, and speak of how They affect religious practice. Others have used the ANT to speak of the structures and placements of religious buildings, especially in cross-cultural contexts, which can see architecture as agents making God's presence tangible.
== ANT in practice ==
ANT has been considered more than just a theory, but also a methodology. In fact, ANT is a useful method that can be applied in different studies. Moreover, with the development of the digital communication, ANT now is popular in being applied in science field like IS research. In addition, it widen the horizon of researchers from arts field as well.
=== ANT in arts ===
ANT is a big influencer in the development of design. In the past, researchers or scholars from design field mainly view the world as a human interactive situation. No matter what design we [who?] applied, it is for human's action. However, the idea of ANT now applies into design principle, where design starts to be viewed as a connector. As the view of design itself has changed, the design starts to be considered more important in daily lives. Scholars [who?] analyze how design shapes, connects, reflects, interacts our daily activities.
ANT has also been widely applied in museums. ANT proposes that it is difficult to discern the 'hard' from the 'soft' components of the apparatus in curatorial practice; that the object 'in progress' of being curated is slick and difficult to separate from the setting of the experiment or the experimenter's identity.
=== ANT in science ===
In recent years, actor-network theory has gained a lot of traction, and a growing number of IS academics are using it explicitly in their research. Despite the fact that these applications vary greatly, all of the scholars cited below agree that the theory provides new notions and ideas for understanding the socio-technical character of information systems. Bloomfield present an intriguing case study of the development of a specific set of resource management information systems in the UK National Health Service, and they evaluate their findings using concepts from actor-network theory. The actor-network approach does not prioritize social or technological aspects, which mirrors the situation in the case study, where arguments about social structures and technology are intertwined within actors' discourse as they try to persuade others to align with their own goals. The research emphasizes the interpretative flexibility of information technology and systems, in the sense that seemingly similar systems produce drastically different outcomes in different locales as a result of the specific translation and network-building processes that occurred. They show how the boundary between the technological and the social, as well as the link between them, is the topic of constant battles and trials of strength in the creation of facts, rather than taking technology for granted.
== Impact of ANT ==
=== Contributions of nonhuman actors ===
There are at least four contributions of nonhumans as actors in their ANT positions.
Nonhuman actors can be considered as a condition in human social activities. Through the human's formation of nonhuman actors such as durable materials, they provide a stable foundation for interactions in society. Reciprocally, nonhumans' actions and capacities serve as a condition for the possibility of the formation of society.
In Latour's We Have Never Been Modern, his conceptual "parliament of things" consists of social, natural, and discourse together as hybrids. Although the interlocks between human actors and nonhumans effects the modernized society, this parliamentary setting based on nonhuman actors would eliminate such fake modernization, and changes the dichotomy between modern society and premodern society.
Nonhuman actors can be considered as mediators. On the one hand, nonhumans could constantly modify relations between actors. On the other hand, nonhumans share the same features with other actors not solely as means for human actors. In this circumstance, nonhuman actors impact human interactions. It either creates an atmosphere for humans to agree with each other, or lead to conflict as the mediators.
It is noticeable that the status of mediation is more affiliated with intermediaries or means as a stable presence in the corpus of ANT, while mediators function more powers to influence actors and networks. Technical mediation exerts itself on four dimensions: interference, composition, the folding of time and space, and crossing the boundary between signs and things.
Nonhuman actors can be considered as members of moral and political associations. For example, noise is a nonhuman actor if the topic is applied to actor-network theory. Noise is the criteria for humans to regulate themselves to morality, and subject to the limitations inherent in some legal rules for its political effects. After nonhumans are visible actors through their associations with morality and politics, these collectives become inherently regulative principles in social networks.
Nonhuman actors can be considered as gatherings. Alike nonhumans' impacts on morality and politics, they could gather actors from other times and spaces. Interacted with variable ontologies, times, spaces, and durability, nonhumans exert subtle influences within a network.
== Criticism ==
Some critics have argued that research based on ANT perspectives remains entirely descriptive and fails to provide explanations for social processes. ANT—like comparable social scientific methods—requires judgement calls from the researcher as to which actors are important within a network and which are not. Critics argue that the importance of particular actors cannot be determined in the absence of "out-of-network" criteria, such as is a logically proven fact about deceptively coherent systems given Gödel's incompleteness theorems. Similarly, others argue that actor-networks risk degenerating into endless chains of association (six degrees of separation—we are all networked to one another). Other research perspectives such as social constructionism, social shaping of technology, social network theory, normalization process theory, and diffusion of innovations theory are held to be important alternatives to ANT approaches.
=== From STS itself and organizational studies ===
Key early criticism came from other members of the STS community, in particular the "Epistemological Chicken" debate between Collins and Yearley with responses from Latour and Callon as well as Woolgar. In an article in Science as Practice and Culture, sociologist Harry Collins and his co-writer Steven Yearley argue that the ANT approach is a step backwards towards the positivist and realist positions held by early theory of science. Collins and Yearley accused ANTs approach of collapsing into an endless relativist regress.
Whittle and organization studies professor André Spicer note that "ANT has also sought to move beyond deterministic models that trace organizational phenomena back to powerful individuals, social structures, hegemonic discourses or technological effects. Rather, ANT prefers to seek out complex patterns of causality rooted in connections between actors." They argue that ANT's ontological realism makes it "less well equipped for pursuing a critical account of organizations—that is, one which recognises the unfolding nature of reality, considers the limits of knowledge and seeks to challenge structures of domination." This implies that ANT does not account for pre-existing structures, such as power, but rather sees these structures as emerging from the actions of actors within the network and their ability to align in pursuit of their interests. Accordingly, ANT can be seen as an attempt to re-introduce Whig history into science and technology studies; like the myth of the heroic inventor, ANT can be seen as an attempt to explain successful innovators by saying only that they were successful. Likewise, for organization studies, Whittle and Spicer assert that ANT is, "ill-suited to the task of developing political alternatives to the imaginaries of market managerialism."
=== Human agency ===
Actor–network theory insists on the capacity of nonhumans to be actors or participants in networks and systems. Critics including figures such as Langdon Winner maintain that such properties as intentionality fundamentally distinguish humans from animals or from "things" (see Activity Theory). ANT scholars [who?] respond with the following arguments:
They do not attribute intentionality and similar properties to nonhumans.
Their conception of agency does not presuppose intentionality.
They locate agency neither in human "subjects" nor in nonhuman "objects", but in heterogeneous associations of humans and nonhumans.
ANT has been criticized as amoral. Wiebe Bijker has responded to this criticism by stating that the amorality of ANT is not a necessity. Moral and political positions are possible, but one must first describe the network before taking up such positions. This position has been further explored by Stuart Shapiro who contrasts ANT with the history of ecology, and argues that research decisions are moral rather than methodological, but this moral dimension has been sidelined.
=== Misnaming ===
In a workshop called "On Recalling ANT", Latour himself stated that there are four things wrong with actor-network theory: "actor", "network", "theory" and the hyphen. In a later book, however, Latour reversed himself, accepting the wide use of the term, "including the hyphen.": 9 He further remarked how he had been helpfully reminded that the ANT acronym "was perfectly fit for a blind, myopic, workaholic, trail-sniffing, and collective traveler"—qualitative hallmarks of actor-network epistemology.
== See also ==
Annemarie Mol
Helen Verran
Mapping controversies
Science and technology studies (STS)
Obligatory passage point (OPP)
Social construction of technology (SCOT)
Technology dynamics
Theory of structuration (according to which neither agents nor social structure have primacy)
Thing theory
Outline of organizational theory
== References ==
== Further reading ==
Carroll, N., Whelan, E., and Richardson, I. (2012). Service Science – an Actor Network Theory Approach. International Journal of Actor-Network Theory and Technological Innovation (IJANTTI), Volume 4, Number 3, pp. 52–70.
Carroll, N. (2014). Actor-Network Theory: A Bureaucratic View of Public Service Innovation. Chapter 7, p. 115-144. In Ed Tatnall (ed). Technological Advancements and the Impact of Actor-Network Theory, IGI Global.
Online version of the article "On Actor Network Theory: A Few Clarifications", in which Latour responds to criticisms. Archived 2021-04-26 at the Wayback Machine
Introductory article "Dolwick, JS. 2009. The 'Social' and Beyond: Introducing Actor–Network Theory", which includes an analysis of other social theories
ANThology. Ein einführendes Handbuch zur Akteur–Netzwerk-Theorie, von Andréa Belliger und David Krieger, transcript Verlag (German)
Transhumanism as Actor-Network Theory "N00bz & the Actor-Network: Transhumanist Traductions" Archived 2010-10-08 at the Wayback Machine (Humanity+ Magazine) by Woody Evans.
John Law (1992). "Notes on the Theory of the Actor Network: Ordering, Strategy, and Heterogeneity."
John Law (1987). "Technology and Heterogeneous Engineering: The Case of Portuguese Expansion." In W.E. Bijker, T.P. Hughes, and T.J. Pinch (eds.), The Social Construction of Technological Systems: New Directions in the Sociology and History of Technology (Cambridge, MA: MIT Press).
Gianpaolo Baiocchi, Diana Graizbord, and Michael Rodríguez-Muñiz. 2013. "Actor-Network Theory and the ethnographic imagination: An exercise in translation". Qualitative Sociology Volume 36, Issue 4, pp 323–341.
Seio Nakajima. 2013. "Re-imagining Civil Society in Contemporary Urban China: Actor-Network-Theory and Chinese Independent Film Consumption." Qualitative Sociology Volume 36, Issue 4, pp 383–402. [1]
Isaac Marrero-Guillamón. 2013. "Actor-Network Theory, Gabriel Tarde and the Study of an Urban Social Movement: The Case of Can Ricart, Barcelona." Qualitative Sociology Volume 36, Issue 4, pp 403–421. [2]
John Law and Vicky Singleton. 2013. "ANT and Politics: Working in and on the World". Qualitative Sociology Volume 36, Issue 4, pp 485–502.
== External links ==
John Law's actor-network theory resource
Bruno Latour's Page
Normalization Process Theory toolkit Archived 2021-04-26 at the Wayback Machine
Reassembling Ethnography: Actor-Network Theory and Sociology | Wikipedia/Actor–network_theory |
In common usage, technoscience refers to the entire long-standing and global human activity of technology, combined with the relatively recent scientific method that occurred primarily in Europe during the 17th and 18th centuries. Technoscience is the study of how humans interact with technology using the scientific method. Technoscience thus comprises the history of human application of technology and modern scientific methods, ranging from the early development of basic technologies for hunting, agriculture, or husbandry (e.g. the well, the bow, the plow, the harness) and all the way through atomic applications, biotechnology, robotics, and computer sciences. This more common and comprehensive usage of the term technoscience can be found in general textbooks and lectures concerning the history of science.
The relationship with the history of science is important in this subject and also underestimated, for example, by more modern sociologists of science. Instead, it is worth emphasising the links that exist between books on the history of science and technology and the study of the relationship between science and technology within a framework of social developments. We must always consider the generational leap between historical periods and scientific discoveries, the construction of machines, the creation of tools in relation to the technological changes that occurs in very specific situations.
An alternate, more narrow usage occurs in some philosophical science and technology studies. In this usage, technoscience refers specifically to the technological and social context of science. Technoscience recognises that scientific knowledge is not only socially coded and historically situated but sustained and made durable by material (non-human) networks. Technoscience states that the fields of science and technology are linked and grow together, and scientific knowledge requires an infrastructure of technology in order to remain stationary or move forward.
The latter, philosophic use of the term technoscience was popularized by French philosopher Gaston Bachelard in 1953. It was popularized in the French-speaking world by Belgian philosopher Gilbert Hottois in the late 1970s and early 1980s, and entered English academic usage in 1987 with Bruno Latour's book Science in Action.
In translating the concept to English, Latour also combined several arguments about technoscience that had circulated separately within science and technology studies (STS) before into a comprehensive framework:
the intertwinement of scientific and technological development as e.g. shown by the lab studies;
the power of laboratories (and engineering workshops) to change the world as we know and experience it;
the seamless webs that connect scientists, engineers and societal actors in actual practice (cf. John Law's concept of heterogeneous engineering);
the propensity of technoscientific world to create new nature–culture hybrids, and hence to complicate the borders between nature and culture.
== Conceptual levels of philosophical technoscience ==
We look at the concept of technoscience by considering three levels: a descriptive-analytic level, a deconstructivist level, and a visionary level.
=== Descriptive-analytic ===
On a descriptive-analytic level, technoscientific studies examine the decisive role of science and technology in how knowledge is being developed. What is the role played by large research labs in which experiments on organisms are undertaken, when it comes to a certain way of looking at the things surrounding us? To what extent do such investigations, experiments and insights shape views of 'nature' and of human bodies? How do these insights link to the concept of living organisms as biofacts? To what extent do such insights inform technological innovation? Can the laboratory be understood as a metaphor for social structures in their entirety?
=== Deconstructive ===
On a deconstructive level, theoretical work is being undertaken on technoscience to address scientific practices critically, e.g. by Bruno Latour (sociology), by Donna Haraway (history of science), and by Karen Barad (theoretical physics). It is pointed out that scientific descriptions may be only allegedly objective; that descriptions are of a performative character, and that there are ways to de-mystify them. Likewise, new forms of representing those involved in research are being sought.
=== Visionary ===
On a visionary level, the concept of technoscience comprises a number of social, literary, artistic and material technologies from western cultures in the third millennium. This is undertaken in order to focus on the interplay of hitherto separated areas and to question traditional boundary-drawing: this concerns the boundaries drawn between scientific disciplines as well as those commonly upheld for instance between research, technology, the arts and politics. One aim is to broaden the term 'technology' (which by the Greek etymology of 'techné' connotes all of the following: arts, handicraft, and skill) so as to negotiate possibilities of participation in the production of knowledge and to reflect on strategic alliances. Technoscience can be juxtaposed with a number of other innovative interdisciplinary areas of scholarship which have surfaced in these recent years such as technoetic, technoethics and technocriticism.
== Facets ==
=== Social ===
As with any subject, technoscience exists within a broader social context that must be considered. Science & Technology Studies researcher Sergio Sismondo argues, "Neither the technical vision nor the social vision will come into being without the other, though with enough Concerted Effort both may be brought into being together". Despite the frequent separation between innovators and the consumers, Sismondo argues that development of technologies, though stimulated by a technoscientific themes, is an inherently social process.
Technoscience is so deeply embedded in people's everyday lives that its developments exist outside a space for critical thought and evaluation, argues Daniel Lee Kleinman (2005). Those who do attempt to question the perception of progress as being only a matter of more technology are often seen as champions of technological stagnation. The exception to this mentality is when a development is seen as threatening to human or environmental well-being. This holds true with the popular opposition of GMO crops, where the questioning of the validity of monopolized farming and patented genetics was simply not enough to rouse awareness.
=== Political ===
Science and technology are tools that continually change social structures and behaviors. Technoscience can be viewed as a form of government or having the power of government because of its impact on society. The impact extends to public health, safety, the environment, and beyond. Innovations create fundamental changes and drastically change the way people live. For example, C-SPAN and social media give American voters a near real-time view of Congress. This has allowed journalists and the people to hold their elected officials accountable in new ways.
=== Environmental ===
Chlorine chemists and their scientific knowledge helped set the agenda for many environmental problems: PCBs in the Hudson River are polychlorinated biphenols; DDT, dieldrin, and aldrin are chlorinated pesticides; CFCs that deplete the ozone layer are chlorofluorocarbons. Industry actually manufactured the chemicals and consumers purchased them. Therefore, one can determine that chemists are not the sole cause for these issues, but they are not blameless.
== See also ==
Bernard Stiegler
Feminist technoscience
Technocriticism
Technoethics
== Notes ==
== References ==
Steven Lukes, Power (1974), A Radical View, London: Macmillan
Bruno Latour and Steve Woolgar (1979). Laboratory Life: the Social Construction of Scientific Facts. Princeton University Press. ISBN 0-691-09418-7
Gilbert Hottois (1984). Le signe et la technique. La philosophie à l'épreuve de la technique, Paris, Aubier Montaigne, Coll. "Res, L'invention philosophique", p. 59–60.
Langdon Winner (1986), The Whale and the Reactor: The Search for Limits in an Age of High Technology, Chicago: University of Chicago Press
Stanley Aronowitz, Barbara Martinsons and Michael Menser (1995), Technoscience and Cyberculture, Routledge
Adam Schaff (1990). A sociedade informática: as conseqüências sociais da segunda revolução industrial. Editora Brasiliense. ISBN 85-11-14081-6
Don Ihde (2003) Chasing Technoscience: Matrix for Materiality. Indiana University Press. ISBN 0-253-21606-0
Sergio Sismondo (2004). An Introduction to Science and Technology Studies. Blackwell Publishing. ISBN 978-0-631-23444-9
Daniel Lee Kleinman (2005), Science and Technology in Society: From Biotechnology to the Internet. Blackwell Pub
Mike Michael (2006), Technoscience And Everyday Life: The Complex Simplicities of the Mundane, Open University Press
Kristin Asdal, Brita Brenna, Ingunn Moser (2007), Technoscience: The Politics of Interventions, Akademika Publishing ISBN 978-8-274-773004
"Hudson River PCBs — Background and Site Information". United States Environmental Protection Agency. Retrieved 2007-12-31.
Hans Lenk (2007), Global TechnoScience and Responsibility, LIT Verlag
Don Ihde (2009), Postphenomenology and Technoscience: The Peking University Lectures, State University of New York
Adele E. Clarke and al. (2010), Biomedicalization: Technoscience, Health, and Illness in the U.S., Duke University Press
Bruce Braun and Sarah J. Whatmore (2010), Political Matter: Technoscience, Democracy, and Public Life, University Of Minnesota Press ISBN 978-0-816-670895
Marja Ylonen and Luigi Pellizzoni (2012), Neoliberalism and Technoscience: Critical Assessments, Ashgate Publishing Limited
Edward Woodhouse (2013), The Future of Technological Civilization. Print; University Readers
Guglielmo Rinzivillo (2020), Raccontare la tecnoscienza. Storia di macchine, strumenti, idee per fare funzionare il mondo, Roma, Edizioni Nuova Cultura (ISBN 978-88-3365-349-5; ISSN 2284-0567).
== External links ==
International Journal of Feminist Technoscience (open access journal with open peer review) | Wikipedia/Technoscience |
Commensurability is a concept in the philosophy of science whereby scientific theories are said to be "commensurable" if scientists can discuss the theories using a shared nomenclature that allows direct comparison of them to determine which one is more valid or useful. On the other hand, theories are incommensurable if they are embedded in starkly contrasting conceptual frameworks whose languages do not overlap sufficiently to permit scientists to directly compare the theories or to cite empirical evidence favoring one theory over the other. Discussed by Ludwik Fleck in the 1930s, and popularized by Thomas Kuhn in the 1960s, the problem of incommensurability results in scientists talking past each other, as it were, while comparison of theories is muddled by confusions about terms, contexts and consequences.
== Introduction of the term ==
In 1962, Thomas Kuhn and Paul Feyerabend both independently introduced the idea of incommensurability to the philosophy of science. In both cases, the concept came from mathematics; in its original sense, it is defined as the absence of a common unit of measurement that would allow a direct and exact measurement of two variables, such as the prediction of the diagonal of a square from the relationship of its sides.
The term commensurability was coined because of a series of problems that both authors found when trying to interpret successive scientific theories. Its implementation is better understood thanks to the critiques that both Kuhn and Feyerabend have made in response to certain theses proposed by followers of the received view of theories. These include the famous thesis on the accumulation of scientific knowledge, which states that the body of scientific knowledge has been increasing with the passage of time. Both Kuhn and Feyerabend reject this thesis, in favor of a model that sees both revolutions and periods of normalcy in the history of science.
Another equally important thesis proposes the existence of a neutral language of comparison which can be used to formulate the empirical consequences of two competing theories. This would allow one to choose the theory with the greatest empirically verified contents or explanatory powers—or the greatest content that is not falsified if the formulation is Popperian.
The idea at the root of this second thesis does not just relate to the existence of said language but also implies at least two further postulates. Firstly, this choice between theories presupposes that they can be intertranslated, for example between theory A and its successor B – and in the case of Popper that B can be deduced from A. Secondly, it is assumed that the choice is always carried out under the same standards of rationality.
In both cases, the concept of incommensurability makes the viability of the thesis impossible. In the first, by showing that certain empirical consequences are lost between successive theories. In the second case, by confirming that it is possible to make a rational choice between theories even when they can not be translated into a neutral language. However, although the reasons for the introduction of these counter arguments, and the criticism from which they arise, are the same, the sense in which the coauthors use them are in no way identical. For this reason the idea of incommensurability will be discussed for each coauthor separately.
== Perspectives ==
=== Feyerabend's perspectives ===
Feyerabend locates incommensurability within a principle from the field of semantics which has the underlying idea that the change in significance in the basic terms of a theory changes the totality of the terms of the new theory, so that there are no empirically common meanings between T and T'.
Feyerabend is credited with coining the modern philosophical sense of "incommensurability," which lays the foundation for much of his philosophy of science. He first presented his notion of incommensurability in 1952 to Karl Popper's London School of Economics seminar and to a gathering of illustrious Wittgensteinians (Elizabeth Anscombe, Peter Geach, H. L. A. Hart and Georg Henrik von Wright) in Anscombe's Oxford flat. Feyerabend argued that frameworks of thought, and thus scientific paradigms, can be incommensurable for three reasons. Briefly put, Feyerabend's notion of incommensurability is as follows:
The interpretation of observations is implicitly influenced by theoretical assumptions. It is therefore impossible to describe or evaluate observations independently of theory.
Paradigms often have different assumptions about which intellectual and operational scientific methods result in valid scientific knowledge.
Paradigms can be based on different assumptions regarding the structure of their domain, which makes it impossible to compare them in a meaningful way. The adoption of a new theory includes and is dependent upon the adoption of new terms. Thus, scientists are using different terms when talking about different theories. Those who hold different, competing theories to be true will be talking over one another, in the sense that they cannot a priori arrive at agreement given two different discourses with two different theoretical language and dictates.
According to Feyerabend, the idea of incommensurability cannot be captured in formal logic, because it is a phenomenon outside of logic's domain.
==== Theories ====
In 1989, Feyerabend presented an idea informed by Popper's critical rationalism whereby "investigation starts with a problem. The problem is the result of a conflict between an expectation and an observation, which, in its turn, is formed by the expectation." (Feyerabend, 1989; pp. 96). Scientific methodology then resolves problems by inventing theories that should be relevant and falsifiable, at least to a greater degree than any other alternative solution. Once an alternative theory is presented the critical phase commences regarding T' which must answer the following questions: (a) why has theory T been successful up until now and (b) why has it failed. If the new theory T' answers both questions then T is discarded.
That is, a new theory T', in order to be an adequate successor to the refuted theory T, must have a collection of additional predictions regarding T (Class A), as well as a collection of successful predictions that coincide to a certain degree with the old theory (Class S). These Class S predictions constitute those parts of the new theory containing new truths, and they therefore exclude a series of consequences of T—the failures in the old theory—which are part of the untrue (false) contents of the new theory (Class F).
Given this model it is possible to construct relational statements between certain terms from T and from T', which will be the basis for the comparison between the theories. This will allow a choice between the two in the light of their empirical contents. But, if we come across a theory T' in which Class S is empty then the theories are incommensurable with each other.
However, Feyerabend clarifies this by stating that, incommensurability between T and T' will depend on the interpretation given to the theories. If this is instrumental, every theory that refers to the same language of observation will be commensurable. In the same way, if a realist perspective is sought then it will favour a unified position which employs the most highly abstracted terms of whatever theory is being considered in order to describe both theories, giving a significance to the observational statements as a function of these terms, or, at least to replace the habitual use they are given.
It can be noted that the instrumentalist interpretation recognizes the existence of certain statements whose truth is not only dependent on the observational statements but also on the evaluation criteria they are subjected to, which are anchored in the theories. For example, to affirm the relational character of longitude, this asseveration can not be decided solely using observational terms. Its truth value, in part, depends on the theory that establishes the sense in which the terms are used. In this case they relate to quantum mechanics (QM) as opposed to classical mechanics (CM). In this sense, the instrumentalist position only deals with the empirical consequences and leaves to one side the relationship that the concepts have with each other.
In this same way Feyerabend comments that:
It is certain, of course, that the relativist scheme has very often given us numbers that are practically identical to the numbers obtained from CM, but this does not mean that the concepts are very similar...[For] even if ...yielding strictly identical predictions can be used as an argument to show that the concepts must match, at least in this case, different magnitudes based on different concepts can give identical values for their respective scales while being different magnitudes...[So] it is not possible to make a comparison of the contents, nor is it possible to make a judgement regarding its verisimilitude.
==== Realist objections ====
In relation to realist objections, Feyerabend returns to an argument elaborated by Carnap and comments that the use of such abstract concepts leads to an impossible position, as "...theoretical terms receive their interpretation by being connected with an observational language and those terms are empty without that connection." (Feyerabend, pp. 373). As before it follows that they can not be used to confer significance to the observational language as this observational language is its only source of significance, with which it is not possible to make a translation but only a restatement of the term.
Therefore, Feyerabend considers that both the instrumentalist and the realist interpretations are flawed, as they try to defend the idea that incommensurability is a legitimately unsolvable idea with which to revoke the theses of the accumulation of knowledge and panrationalism in science.
This leads to the following consideration: if each new theory has its own observational basis, within the meaning of the theoretical framework, how can we hope that the observations that are produced could eventually refute it. Furthermore, how can we actually recognize that the new position explains what it is supposed to explain or if it is deviating off into other areas and therefore how can the theories be definitively compared.
Feyerabend's answer to the first consideration lies in noting that the initial terms of a theory depend on the postulates of the theory and their associated grammatical rules, in addition, the predictions derived from the theory also depend on the underlying conditions of the system. Feyerabend doesn't explore the point further, but it can be assumed that if the prediction does not agree with the observation and if we have a high degree of confidence in the description that we have made from the initial conditions than we can be sure that the error must be present in our theory and in its underlying terms.
In dealing with the second consideration Feyerabend asks "why should it be necessary to have a terminology that allows us to say that two theories refer to the same experiment. This supposes a unificationist or possibly a realist aspiration, whose objective appears to be the truth, however, it is assumed that the theory can be compared under a criterion of empirical adequacy. Such an approach would build on the relationship established between the observational statement that describes the outcome of an experiment formulated for each theory independently, which is compared with the predictions that each theory posits. In this way the selection is made when a theory is an empirically better fit. If the objection to the possible deviation of the new theory is not answered it is irrelevant as often history has shown that in fact differing points of view change or modify their fields of application, for example the physics of Aristotle and Newton."
==== Theory selection ====
The above implies that the process of choosing between theories does not obey a universal rationality. Feyerabend has the following view regarding whether the absence of a universal rationality constitutes an irrational position:
No, because each particular episode is rational in the sense that some of its features can be explained in terms of reasons which were either accepted at the time of its occurrence or invented in the course of its development. Yes, because even these local reasons which change from age to age are never sufficient to explain all the important features of a particular episode.
Feyerabend uses this reasoning to try to shed light on one of Popper's arguments, which says that we are always able to change any statement, even those reference systems that guide our critical thinking. However, the two thinkers reach different conclusions, Popper assumes that it is always possible to make a criticism once the new criteria have been accepted, so the selection can be seen as the result of a rationality "a posteriori" to the selection. While, Feyerabend's position is that this solution is merely a verbal ornament whenever the standards are influenced by Popper's first world, the physical world, and they are not just developed in the third world. That is, the standards are influenced by the expectations of their originators, the stances they imply and the ways of interpreting the world they favour, but this is strictly analogous to the same process of the scientific revolution, that leads us to believe that the thesis of incommensurability can also be applied to standards, as is shown by the following asseveration:
Even the most puritanical rationalist will then be forced to stop reasoning and to use propaganda and coercion, not because some of his reasons have ceased to be valid, but because the psychological conditions which make them effective, and capable of influencing others, have disappeared. And what is the use of an argument that leaves people unmoved?
Feyerabend states that the Popperian criticism is either related to certain clearly defined procedures, or is totally abstract and leaves others with the task of fleshing it out later with specific contents, making Popper's rationality a "mere verbal ornament." This does not imply that Feyerabend is an irrationalist but that he considers that the process of scientific change can not be explained in its totality in the light of some rationality, precisely because of incommensurability.
=== Kuhn's perspectives ===
The second coauthor of the thesis of incommensurability is Thomas Kuhn, who introduced it in his 1962 book, The Structure of Scientific Revolutions, in which he describes it as a universal property that defines the relationship between successive paradigms. Under this meaning incommensurability goes beyond the field of semantics and covers everything relating to its practical application, from the study of problems to the associated methods and rules for their resolution. However, the meaning of the term was continually refined throughout Kuhn's work, he first placed it within the field of semantics and applied a narrow definition, but later he redefined it in a taxonomic sense, wherein changes are found in the relationships between similarities and differences that the subjects of a defining matrix draw over the world.
In The Structure of Scientific Revolutions Kuhn wrote that "the historian of science may be tempted to exclaim that when paradigms change, the world itself changes with them".: 111 According to Kuhn, the proponents of different scientific paradigms cannot fully appreciate or understand the other's point of view because they are, as a way of speaking, living in different worlds. Kuhn gave three reasons for this inability:
Proponents of competing paradigms have different ideas about the importance of solving various scientific problems, and about the standards that a solution should satisfy.
The vocabulary and problem-solving methods that the paradigms use can be different: the proponents of competing paradigms utilize a different conceptual network.
The proponents of different paradigms see the world in a different way because of their scientific training and prior experience in research.
In a postscript (1969) to The Structure of Scientific Revolutions, Kuhn added that he thought that incommensurability was, at least in part, a consequence of the role of similarity sets in normal science. Competing paradigms group concepts in different ways, with different similarity relations. According to Kuhn, this causes fundamental problems in communication between proponents of different paradigms. It is difficult to change such categories in one's mind, because the groups have been learned by means of exemplars instead of definitions. This problem cannot be resolved by using a neutral language for communication, according to Kuhn, since the difference occurs prior to the application of language.
Kuhn's thinking on incommensurability was probably in some part influenced by his reading of Michael Polanyi who held that there can be a logical gap between belief systems and who also said that scientists from different schools, "think differently, speak a different language, live in a different world."
==== Phases ====
Given his changing definition of incommensurability Pérez Ransanz has identified three phases in Kuhn's work, or at least in how it deals with this concept. As we have seen above the first phase was seen in The Structure of Scientific Revolutions and it is characterized by an overall vision that is applied to paradigms. This perspective was replaced in the 1970s by a localist and semanticist vision in which incommensurability is now defined as the relationship between two theories that are articulated in two languages that are not completely interchangeable, as Kuhn states in the following extract:
The phrase "without common measure" is converted into "without common language". To state that two theories are incommensurable means that there is no neutral language, or other type of language, into which both theories, conceived as sets of statements, can be translated without remainder or loss... [Although] the majority of the terms shared by the two theories function in the same way in both...
The above only prohibits one type of comparison, that which is carried out between the statements of these two theories in a one-to-one relationship. An idea that underlies this formulation is that translation implies symmetry and transitivity so that if theory T is translatable with theory T', then T' can be translated to T, and furthermore if there is a third theory T and this can be translated to T', then theories T and T' cannot be incommensurable, as long as the transitive relationship and the symmetrical relationship assures that their statements can be compared one to another.
Kuhn did not deny that two incommensurable theories may have a common reference environment and in this sense he did not state that it was impossible to compare them, his thesis solely refers to the ability to translate the statements belonging to two theories in a one-to-one relationship, as is shown in the following passage:
The terms that retain their meanings following a change in theory provide a suitable base for the discussion of the differences and for the comparisons that are relevant in the selection of theories. [Continued in a footnote] It may be noted that these terms are not independent of the theory, but they are simply used in the same way in the two theories in question. It follows that the comparison is a process that compares the two theories, it is not a process that can evaluate the theories separately.
This is relevant because it allow us to elucidate that Kuhn's sense of rationality is linked to the ability to comprehend, and not to the same capacity for translation.
In the third stage of Kuhn's work the formulation of the thesis of incommensurability became refined in taxonomic terms and is explained as a function of the change in the relations of similarity and difference between two theories. Kuhn declared that this change relates to the concepts of Class A not only because there is a change in the way of referring to the concepts but also because their underlying structure becomes altered, that is, the meaning changes – its intention – but also its reference. In this way Kuhn states that not all of the semantic changes are changes that lead to incommensurability, they are only those that, by being made in the basic categories, operate in a holistic manner meaning that all the relationships between these terms becomes altered. This uses taxonomic terms to define incommensurability as the impossibility to prove the taxonomic structures of two theories, an impossibility that is expressed as a necessarily incomplete translation of the terms.
==== Taxonomic characterization ====
Taxonomic characterization allowed Kuhn to postulate his no-overlap principle, since, if the taxonomic categories are divisions in a logical sense then this implies that the relations established between these concepts and the rest are necessarily hierarchical. It is for exactly this type of relationship that the changes in categories are holistic, as the modification of a category necessarily implies the modification of the surrounding categories, which explains why once the change takes place the taxonomies can not be comparable – they are isomorphic.
This characterization was already present in Kuhn's writing along with remnants of semantic characterization, which he developed in full towards the end of the 1980s in his taxonomic characterization. An advantage of this characterization is the belief that the criteria that allow the identification of a concept with its references are many and varied, so that a coincidence of criteria is not necessary for successful communication except for those categories that are implicated. Kuhn saw the relations between concepts as existing in a multidimensional space, the categories consist of partitions in this space and they must coincide between the communicators, although this is not the case for the criteria that establish a connection between this space and the associated reference.
==== Reluctance ====
An important clarification that should be made, and which constantly appears in Kuhn's writing, is his reluctance to equate translation and interpretation, a comparison that Kuhn attributes to the analytical tradition of philosophy. Translation is an almost mechanical activity which produces a Quinean translation manual that relates sequences of words in such a way that their truth values are conserved. However, the process of interpretation implies the development of translation hypotheses, which have to be successful when they allow external preferences to be understood in a coherent and meaningful way. Kuhn then rejected the idea of a universal translatability but not the principle of universal intelligibility, a distinction that is very important in understanding Kuhn's rejection of his critics, such as Popper and Davidson.
However, without a doubt the previous idea invites us to question how is it that we are able to interpret in the first place. Kuhn's solution consists in affirming that this is like learning a new language. How is it that we are able to learn a new language when we are confronted with a holistic change such as is implied by the notion of incommensurability? Kuhn's work suggests four aspects to this question:
Firstly, in order to carry out such an assimilation it is necessary that the complementary vocabulary is easily understood.
Secondly, definitions must fulfill a minimal role, it is the paradigmatic examples that introduce the use of the new concepts, in such a way that an ostensive or stipulative component is essential.
Thirdly, class concepts cannot be learned in isolation, but in relation to a series of contrast sets.
Fourthly, the process of learning involves the generation of expectations, which are the basis of the projectability of the class terms, in such a way that in their turn they form the basis of, among other things, inductive inferences. And lastly, as the criteria for relating the class and its reference vary, this forms the way of learning the subject matter.
=== Conclusion ===
It can be concluded that Kuhn's idea of incommensurability, despite its various reformulations, manages to seriously problematize both the idea of accumulation of a neutral language as well as of the very idea of a neutral language, without falling into irrationalism nor stating that the common reference level is irrelevant. An idea that differentiates him from Feyerabend who states in books such as Problems of Empiricism and Against Method that if the new theory deviates into new areas, this is not a problem of the theory, as often the conceptual progress leads to the disappearance and not to the refutation or resolution of the old questions.
== Meta-incommensurability ==
A more general notion of incommensurability has been applied to the sciences at the meta-level in two significant ways.
Eric Oberheim and Paul Hoyningen-Huene argue that realist and anti-realist philosophies of science are also incommensurable, thus scientific theories themselves may be meta-incommensurable.
Similarly, Nicholas Best describes a different type of incommensurability between philosophical theories of meaning. He argues that if the meaning of a first-order scientific theory depends on its second-order theory of meaning, then two first order theories will be meta-incommensurable if they depend on substantially different theories of meaning. Whereas Kuhn and Feyerabend's concepts of incommensurability do not imply complete incomparability of scientific concepts, this incommensurability of meaning does.
== Notes ==
== Bibliography ==
=== Primary bibliography ===
=== Secondary bibliography ===
== External links ==
Bibliography on Inconmensurabilidad – Leibniz Universität Hannover (in English)
Incommensurability Online – Volume of Abstracts – Leibniz Universität Hannover (in English)
An article by Errol Morris critiquing Kuhn's ideas of incommensurability. (in English)
The Incommensurability of Scientific Theories in the Stanford Encyclopedia of Philosophy | Wikipedia/Commensurability_(philosophy_of_science) |
Post-normal science (PNS) was developed in the 1990s by Silvio Funtowicz and Jerome R. Ravetz. It is a problem-solving strategy appropriate when "facts [are] uncertain, values in dispute, stakes high and decisions urgent", conditions often present in policy-relevant research. In those situations, PNS recommends suspending temporarily the traditional scientific ideal of truth, concentrating on quality as assessed by internal and extended peer communities.
PNS can be considered as complementing the styles of analysis based on risk and cost-benefit analysis prevailing at that time and integrating concepts of a new critical science developed in previous works by the same authors.
PNS is not a new scientific method following Aristotle and Bacon, a new paradigm in the Kuhnian sense, or an attempt to reach a new ‘normal’. It is instead, a set of insights to guide actionable and robust knowledge production for policy decision making and action in challenges like pandemics, ecosystems collapse, biodiversity loss and, in general, sustainability transitions.
== Context ==
According to its proponents Silvio Funtowicz and Jerome R. Ravetz, the name "post-normal science" echoes the seminal work on modern science by Thomas Kuhn. For Carrozza PNS can be "framed in terms of a call for the ‘democratization of expertise’", and as a "reaction against long-term trends of ‘scientization’ of politics—the tendency towards assigning to experts a critical role in policymaking while marginalizing laypeople". For Mike Hulme (2007), writing on The Guardian, climate change seems to fall into the category of issues which are best dealt with in the context of PNS and notes that “Disputes in post-normal science focus as often on the process of science - who gets funded, who evaluates quality, who has the ear of policy - as on the facts of science”. Climate science as PNS was already proposed by the late Stephen Schneider, and a similar linkage was propose for the workings of the Intergovernmental Panel on Climate Change.
From the ecological perspective post-normal science can be situated in the context of 'crisis disciplines' – a term coined by the conservation biologist Michael E. Soulé to indicate approaches addressing fears, emerging in the seventies, that the world was on the verge of ecological collapse. In this respect Michael Egan defines PNS as a 'survival science'. More recently PNS has been defined as a movement of ‘informed critical resistance, reform and the making of futures’.
Moving from PNS Ziauddin Sardar developed the concept of Postnormal Times (PNT). Sardar was the editor of FUTURES when it published the article ‘Science for the post-normal age’ presently the most cited paper of the journal. A recent review of academic literature conducted on the Web of Science and encompassing the topics of Futures studies, Foresight, Forecasting and Anticipation Practice identifies the same paper as "the all-time publication that received the highest number of citations".
== Content ==
"At birth Post-normal science was conceived as an inclusive set of robust insights more than as an exclusive fully structured theory or field of practice". Some of the ideas underpinning PNS can already be found in a work published in 1983 and entitled "Three types of risk assessment: a methodological analysis" This and subsequent works show that PNS concentrates on few aspects of the complex relation between science and policy: the communication of uncertainty, the assessment of quality, and the justification and practice of the extended peer communities.
Coming to the PNS diagram (figure above) the horizontal axis represents ‘Systems Uncertainties’ and the vertical one ‘Decision Stakes’. The three quadrants identify Applied Science, Professional Consultancy, and Post-Normal Science. Different standards of quality and styles of analysis are appropriate to different regions in the diagram, i.e. post-normal science does not claim relevance and cogency on all of science's application but only on those defined by the PNS's mantram with a fourfold challenge: ‘facts uncertain, values in dispute, stakes high and decisions urgent’. For applied research science's own peer quality control system will suffice (or so was assumed at the moment PNS was formulated in the early nineties), while professional consultancy was considered appropriate for these settings which cannot be ‘peer-reviewed’, and where the skills and the tacit knowledge of a practitioner are needed at the forefront, e.g. in a surgery room, or in a house on fire. Here a surgeon or a firefighter takes a difficult technical decision based on her or his training and appreciation of the situation (the Greek concept of ‘Metis’ as discussed by J. C. Scott.)
== Complexity ==
There are important linkages between PNS and complexity science, e.g. system ecology (C. S. Holling) and hierarchy theory (Arthur Koestler), see e.g. the work of Joseph Tainter, Timothy F. H. Allen and Thomas W. Hoekstra on transition from fossil to renewable fuels. In PNS, complexity is respected through its recognition of a multiplicity of legitimate perspectives on any issue; this is close to the meaning espoused by Robert Rosen (theoretical biologist). Reflexivity is realised through the extension of accepted ‘facts’ beyond the supposedly objective productions of traditional research. Also, the new participants in the process are not treated as passive learners at the feet of the experts, being coercively convinced through scientific demonstration. Rather, they will form an ‘extended peer community’, sharing the work of quality assurance of the scientific inputs to the process, and arriving at a resolution of issues through debate and dialogue. The necessity to embrace complexity in a post-normal perspective to understand and face zoonoses is argumented by David Waltner-Toews.
== Extended peer community ==
In PNS extended peer communities are spaces where perspectives, values, styles of knowing and power differentials are expressed in a context of inequalities and conflict. Resolutions, compromises and knowledge co-production are contingent and not necessarily achievable.
== Applications ==
Beside its dominating influence in the literature on 'futures', PNS is considered to have influenced the ecological ‘conservation versus preservation debate’, especially via its reading by American pragmatist Bryan G. Norton. According to Jozef Keulartz the PNS concept of "extended peer community" influenced how Norton's developed his 'convergence hypothesis'. The hypothesis posits that ecologists of different orientation will converge once they start thinking 'as a mountain', or as a planet. For Norton this will be achieved via deliberative democracy, which will pragmatically overcome the black and white divide between conservationists and preservationists. More recently it has been argued that conservation science, embedded as it is in a multi-layered governance structures of policy-makers, practitioners, and stakeholders, is itself an 'extended peer community', and as a result conservation has always been ‘post-normal’.
Other authors attribute to PNS the role of having stimulated the take up of transdisciplinary methodological frameworks, reliant on the social constructivist perspective embedded in PNS.
Post-normal science is intended as applicable to most instances where the use of evidence is contested due to different norms and values. Typical instances are in the use of evidence based policy and in evaluation.
As summarized in a recent work "the ideas and concepts of post normal science bring about the emergence of new problem solving strategies in which the role of science is appreciated in its full context of the complexity and the uncertainty of natural systems and the relevance of human commitments and values."
For Peter Gluckman (2014), chief science advisor to the Prime Minister of New Zealand, post-normal science approaches are today appropriate for a host of problems including "eradication of exogenous pests […], offshore oil prospecting, legalization of recreational psychotropic drugs, water quality, family violence, obesity, teenage morbidity and suicide, the ageing population, the prioritization of early-childhood education, reduction of agricultural greenhouse gases, and balancing economic growth and environmental sustainability".
Conservation science is also a field where PNS is suggested as to fill the space between research, policy, and implementation, as well as to ensure pluralism in analysis. Ecosystem services are a topical subject for PNS.
Reviews of the history and evolution of PNS, its definitions, conceptualizations,
and uses can be found in Turnpenny et al., 2011, and in The Routledge Handbook of Ecological Economics (Nature and Society). Articles on PNS are published in Nature and related journals.
== Criticism ==
A criticism of post-normal science is offered by Weingart (1997) for whom post-normal science does not introduce a new epistemology but retraces earlier debates linked to the so-called "finalization thesis". For Jörg Friedrichs – comparing the issues of climate change and peak energy – an extension of the peer community has taken place in the climate science community, transforming climate scientists into ‘stealth advocates’, while scientists working on energy security – without PNS, would still maintain their credentials of neutrality and objectivity. Another criticism is that the extended peer community's use undermines the scientific method's use of empiricism and that its goal would be better addressed by providing greater science education.
== The crisis of science ==
It has been argued that post-normal science scholars have been prescient in anticipating the present crisis in science's quality control and reproducibility. A group of scholars of post-normal science orientation has published in 2016 a volume on the topic, discussing inter alia what this community perceive as the root causes of the present science's crisis.
== Quantitative approaches ==
Among the quantitative styles of analysis which make reference to post-normal science one can mention NUSAP for numerical information, sensitivity auditing for indicators and mathematical modelling, Quantitative storytelling for exploring multiple frames in a quantitative analysis, and MUSIASEM in the field of social metabolism. A work where these approaches are suggested for sustainability is in.
== Mathematical modelling ==
In relation to mathematical modelling post-normal science suggests a participatory approach, whereby ‘models to predict and control the future’ are replaced by ‘models to map our ignorance about the future’, in the process exploring and revealing the metaphors embedded in the model. PNS is also known for its definition of garbage in, garbage out (GIGO): in modelling GIGO occurs when the uncertainties in the inputs must be suppressed, lest the outputs become completely indeterminate.
== COVID-19 ==
On 25 March 2020, in the midst of the COVID-19 pandemic, a group of scholars of post-normal orientation published on the blog section of the STEPS Centre (for Social, Technological and Environmental Pathways to Sustainability) at the University of Sussex. The piece argues that the COVID-19 emergency has all the elements of a post-normal science context, and notes that "this pandemic offers society an occasion to open a fresh discussion on whether we now need to learn how to do science in a different way".
== Special issues ==
The journal FUTURES devoted several specials issues to post-normal science.
The first was in 1999 and included two editorial pieces, from Jerome Ravetz and Silvio Funtowicz, and from Jerome Ravetz.
The second special issue, edited by Merryl Wyn Davies, was entitled "Post normal times" in 2011. This was a selection of papers from the symposium "Post Normal Science – perspectives & prospectives 26-27th June 2009, Oxford." A summary of the abstracts can be found on the NUSAP net.
The third special issue on post-normal science was in 2017. This special issue contains a selection of papers discussed at the University of Bergen's Centre for the Study of the Sciences and the Humanities between 2014 and 2016. The issue includes also two extended commentaries on the present crisis in science and the post-fact/post-truth discourse, one from Europe and one from Japan.
Another special issue on post-normal science was published in 2011 on the journal Science, Technology, & Human Values.
== References ==
== Bibliography ==
Ravetz, Jerome R. (1979). Scientific knowledge and its social problems. Oxford: Oxford Univ. Press. ISBN 978-0-19-519721-1.
Ravetz, Jerome R. (September 1987). "Usable Knowledge, Usable Ignorance: Incomplete Science with Policy Implications". Knowledge. 9 (1): 87–116. doi:10.1177/107554708700900104.
Funtowicz, S.O. and J.R. Ravetz (1990). Uncertainty and Quality in Science for Policy. Kluwer Academic Publishers, the Netherlands.
Ravetz, Jerome R. (2005). The No nonsense guide to science. Oxford: New Internationalist.
== External links ==
NUSAP.net
Article on The Guardian 14 March 2007
More articles on PNS
Report from Secretariat of the International Seabed Authority about "post-normal science for recalibration of policy instruments." | Wikipedia/Post-normal_science |
Normal science, identified and elaborated on by Thomas Samuel Kuhn in The Structure of Scientific Revolutions, is the regular work of scientists theorizing, observing, and experimenting within a settled paradigm or explanatory framework. Regarding science as puzzle-solving, Kuhn explained normal science as slowly accumulating detail in accord with established broad theory, without questioning or challenging the underlying assumptions of that theory.
== Route to normal science ==
Kuhn stressed that historically, the route to normal science could be a difficult one. Prior to the formation of a shared paradigm or research consensus, would-be scientists were reduced to the accumulation of random facts and unverified observations, in the manner recorded by Pliny the Elder or Francis Bacon, while simultaneously beginning the foundations of their field from scratch through a plethora of competing theories.
Arguably at least the social sciences remain at such a pre-paradigmatic level today.
== Normal science at work ==
Kuhn considered that the bulk of scientific work was that done by the 'normal' scientist, as they engaged with the threefold task of articulating the paradigm, precisely evaluating key paradigmatic facts, and testing those new points at which the theoretical paradigm is open to empirical appraisal.
Paradigms are central to Kuhn's conception of normal science. Scientists derive rules from paradigms, which also guide research by providing a framework for action that encompasses all the values, techniques, and theories shared by the members of a scientific community. Paradigms gain recognition from more successfully solving acute problems than their competitors. Normal science aims to improve the match between a paradigm's predictions and the facts of interest to a paradigm. It does not aim to discover new phenomena.
According to Kuhn, normal science encompasses three classes of scientific problems. The first class of scientific problems is the determination of significant fact, such as the position and magnitude of stars in different galaxies. When astronomers use special telescopes to verify Copernican predictions, they engage the second class: the matching of facts with theory, an attempt to demonstrate agreement between the two. Improving the value of the gravitational constant is an example of articulating a paradigm theory, which is the third class of scientific problems.
== Breakdown of consensus ==
The normal scientist presumes that all values, techniques, and theories falling within the expectations of the prevailing paradigm are accurate. Anomalies represent challenges to be puzzled out and solved within the prevailing paradigm. Only if an anomaly or series of anomalies resists successful deciphering long enough and for enough members of the scientific community will the paradigm itself gradually come under challenge during what Kuhn deems a crisis of normal science. If the paradigm is unsalvageable, it will be subjected to a paradigm shift.
Kuhn lays out the progression of normal science that culminates in scientific discovery at the time of a paradigm shift: first, one must become aware of an anomaly in nature that the prevailing paradigm cannot explain. Then, one must conduct an extended exploration of this anomaly. The crisis only ends when one discards the old paradigm and successfully maps the original anomaly onto a new paradigm. The scientific community embraces a new set of expectations and theories that govern the work of normal science. Kuhn calls such discoveries scientific revolutions. Successive paradigms replace each other and are necessarily incompatible with each other.
In this way however, according to Kuhn, normal science possesses a built-in mechanism that ensures the relaxation of the restrictions that previously bound research, whenever the paradigm from which they derive ceases to function effectively. Kuhn's framework restricts the permissibility of paradigm falsification to moments of scientific discovery.
== Criticism ==
Kuhn's normal science is characterized by upheaval over cycles of puzzle-solving and scientific revolution, as opposed to cumulative improvement. In Kuhn's historicism, moving from one paradigm to the next completely changes the universe of scientific assumptions. Imre Lakatos has accused Kuhn of falling back on irrationalism to explain scientific progress. Lakatos relates Kuhnian scientific change to a mystical or religious conversion ungoverned by reason.
With the aim of presenting scientific revolutions as rational progress, Lakatos provided an alternative framework of scientific inquiry in his paper Falsification and the Methodology of Scientific Research Programmes. His model of the research programme preserves cumulative progress in science where Kuhn's model of successive irreconcilable paradigms in normal science does not. Lakatos' basic unit of analysis is not a singular theory or paradigm, but rather the entire research programme that contains the relevant series of testable theories. Each theory within a research programme has the same common assumptions and is supposed by a belt of more modest auxiliary hypotheses that serve to explain away potential threats to the theory's core assumptions. Lakatos evaluates problem shifts, changes to auxiliary hypotheses, by their ability to produce new facts, better predictions, or additional explanations. Lakatos' conception of a scientific revolution involves the replacement of degenerative research programmes by progressive research programmes. Rival programmes persist as minority views.
Lakatos is also concerned that Kuhn's position may result in the controversial position of relativism, for Kuhn accepts multiple conceptions of the world under different paradigms. Although the developmental process he describes in science is characterized by an increasingly detailed and refined understanding of nature, Kuhn does not conceive of science as a process of evolution towards any goal or telos. He has noted his own sparing use of the word truth in his writing.
An additional consequence of Kuhn's relavitism, which poses a problem for the philosophy of science, is his blurred demarcation between science and non-science. Unlike Karl Popper's deductive method of falsification, under Kuhn, scientific discoveries that do not fit the established paradigm do not immediately falsify the paradigm. They are treated as anomalies within the paradigm that warrant further research, until a scientific revolution refutes the entire paradigm.
== See also ==
== References ==
== Further reading ==
W. O. Hagstrom, The Scientific Community (1965)
== External links ==
Paradigms and normal science | Wikipedia/Normal_science |
Logology is the study of all things related to science and its practitioners—philosophical, biological, psychological, societal, historical, political, institutional, financial. The term "logology" is back-formed from the suffix "-logy", as in "geology", "anthropology", etc., in the sense of the "study of science".
The word "logology" provides grammatical variants not available with the earlier terms "science of science" and "sociology of science", such as "logologist", "logologize", "logological", and "logologically". The emerging field of metascience is a subfield of logology.
== Origins ==
The early 20th century brought calls, initially from sociologists, for the creation of a new, empirically based science that would study the scientific enterprise itself. The early proposals were put forward with some hesitancy and tentativeness. The new meta-science would be given a variety of names, including "science of knowledge", "science of science", "sociology of science", and "logology".
Florian Znaniecki, who is considered to be the founder of Polish academic sociology, and who in 1954 also served as the 44th president of the American Sociological Association, opened a 1923 article:
[T]hough theoretical reflection on knowledge—which arose as early as Heraclitus and the Eleatics—stretches... unbroken... through the history of human thought to the present day... we are now witnessing the creation of a new science of knowledge [author's emphasis] whose relation to the old inquiries may be compared with the relation of modern physics and chemistry to the 'natural philosophy' that preceded them, or of contemporary sociology to the 'political philosophy' of antiquity and the Renaissance. [T]here is beginning to take shape a concept of a single, general theory of knowledge... permitting of empirical study.... This theory... is coming to be distinguished clearly from epistemology, from normative logic, and from a strictly descriptive history of knowledge."
A dozen years later, Polish husband-and-wife sociologists Stanisław Ossowski and Maria Ossowska (the Ossowscy) took up the same subject in an article on "The Science of Science" whose 1935 English-language version first introduced the term "science of science" to the world. The article postulated that the new discipline would subsume such earlier ones as epistemology, the philosophy of science, the psychology of science, and the sociology of science. The science of science would also concern itself with questions of a practical character such as social and state policy in relation to science, such as the organization of institutions of higher learning, of research institutes, and of scientific expeditions, and the protection of scientific workers, etc. It would concern itself as well with historical questions: the history of the conception of science, of the scientist, of the various disciplines, and of learning in general.
In their 1935 paper, the Ossowscy mentioned the German philosopher Werner Schingnitz (1899–1953) who, in fragmentary 1931 remarks, had enumerated some possible types of research in the science of science and had proposed his own name for the new discipline: scientiology. The Ossowscy took issue with the name:
Those who wish to replace the expression 'science of science' by a one-word term [that] sound[s] international, in the belief that only after receiving such a name [will] a given group of [questions be] officially dubbed an autonomous discipline, [might] be reminded of the name 'mathesiology', proposed long ago for similar purposes [by the French mathematician and physicist André-Marie Ampère (1775–1836)]."
Yet, before long, in Poland, the unwieldy three-word term nauka o nauce, or science of science, was replaced by the more versatile one-word term naukoznawstwo, or logology, and its natural variants: naukoznawca or logologist, naukoznawczy or logological, and naukoznawczo or logologically. And just after World War II, only 11 years after the Ossowscy's landmark 1935 paper, the year 1946 saw the founding of the Polish Academy of Sciences' quarterly Zagadnienia Naukoznawstwa (Logology) –— long before similar journals in many other countries.
The new discipline also took root elsewhere—in English-speaking countries, without the benefit of a one-word name.
== Science ==
=== The term ===
The word "science", from the Latin "scientia" (meaning "knowledge"), signifies somewhat different things in different languages. In English, "science", when unqualified, generally refers to the exact, natural, or hard sciences. The corresponding terms in other languages, for example French, German, and Polish, refer to a broader domain that includes not only the exact sciences (logic and mathematics) and the natural sciences (physics, chemistry, biology, Earth sciences, astronomy, etc.) but also the engineering sciences, social sciences (human geography, psychology, cultural anthropology, sociology, political science, economics, linguistics, archaeology, etc.), and humanities (philosophy, history, classics, literary theory, etc.).
University of Amsterdam humanities professor Rens Bod points out that science—defined as a set of methods that describes and interprets observed or inferred phenomena, past or present, aimed at testing hypotheses and building theories—applies to such humanities fields as philology, art history, musicology, philosophy, religious studies, historiography, and literary studies.
Bod gives a historic example of scientific textual analysis. In 1440 the Italian philologist Lorenzo Valla exposed the Latin document Donatio Constantini, or The Donation of Constantine – which was used by the Catholic Church to legitimize its claim to lands in the Western Roman Empire – as a forgery. Valla used historical, linguistic, and philological evidence, including counterfactual reasoning, to rebut the document. Valla found words and constructions in the document that could not have been used by anyone in the time of Emperor Constantine I, at the beginning of the fourth century C.E. For example, the late Latin word feudum, meaning fief, referred to the feudal system, which would not come into existence until the medieval era, in the seventh century C.E. Valla's methods were those of science, and inspired the later scientifically-minded work of Dutch humanist Erasmus of Rotterdam (1466–1536), Leiden University professor Joseph Justus Scaliger (1540–1609), and philosopher Baruch Spinoza (1632–1677). Here it is not the experimental method dominant in the exact and natural sciences, but the comparative method central to the humanities, that reigns supreme.
=== Knowability ===
Science's search for the truth about various aspects of reality entails the question of the very knowability of reality. Philosopher Thomas Nagel writes: "[In t]he pursuit of scientific knowledge through the interaction between theory and observation... we test theories against their observational consequences, but we also question or reinterpret our observations in light of theory. (The choice between geocentric and heliocentric theories at the time of the Copernican Revolution is a vivid example.) ...
How things seem is the starting point for all knowledge, and its development through further correction, extension, and elaboration is inevitably the result of more seemings—considered judgments about the plausibility and consequences of different theoretical hypotheses. The only way to pursue the truth is to consider what seems true, after careful reflection of a kind appropriate to the subject matter, in light of all the relevant data, principles, and circumstances."
The question of knowability is approached from a different perspective by physicist-astronomer Marcelo Gleiser: "What we observe is not nature itself but nature as discerned through data we collect from machines. In consequence, the scientific worldview depends on the information we can acquire through our instruments. And given that our tools are limited, our view of the world is necessarily myopic. We can see only so far into the nature of things, and our ever shifting scientific worldview reflects this fundamental limitation on how we perceive reality." Gleiser cites the condition of biology before and after the invention of the microscope or gene sequencing; of astronomy before and after the telescope; of particle physics before and after colliders or fast electronics. "[T]he theories we build and the worldviews we construct change as our tools of exploration transform. This trend is the trademark of science."
Writes Gleiser: "There is nothing defeatist in understanding the limitations of the scientific approach to knowledge.... What should change is a sense of scientific triumphalism—the belief that no question is beyond the reach of scientific discourse.
"There are clear unknowables in science—reasonable questions that, unless currently accepted laws of nature are violated, we cannot find answers to. One example is the multiverse: the conjecture that our universe is but one among a multitude of others, each potentially with a different set of laws of nature. Other universes lie outside our causal horizon, meaning that we cannot receive or send signals to them. Any evidence for their existence would be circumstantial: for example, scars in the radiation permeating space because of a past collision with a neighboring universe."
Gleiser gives three further examples of unknowables, involving the origins of the universe; of life; and of mind:
"Scientific accounts of the origin of the universe are incomplete because they must rely on a conceptual framework to even begin to work: energy conservation, relativity, quantum physics, for instance. Why does the universe operate under these laws and not others?
"Similarly, unless we can prove that only one or very few biochemical pathways exist from nonlife to life, we cannot know for sure how life originated on Earth.
"For consciousness, the problem is the jump from the material to the subjective—for example, from firing neurons to the experience of pain or the color red. Perhaps some kind of rudimentary consciousness could emerge in a sufficiently complex machine. But how could we tell? How do we establish—as opposed to conjecture—that something is conscious?" Paradoxically, writes Gleiser, it is through our consciousness that we make sense of the world, even if imperfectly. "Can we fully understand something of which we are a part?"
Among all the sciences (i.e., disciplines of learning, writ large) there seems to exist an inverse relation between precision and intuitiveness. The most intuitive of the disciplines, aptly termed the "humanities", relate to common human experience and, even at their most exact, are thrown back on the comparative method; less intuitive and more precise than the humanities are the social sciences; while, at the base of the inverted pyramid of the disciplines, physics (concerned with mattergy – the matter and energy comprising the universe) is, at its deepest, the most precise discipline and at the same time utterly non-intuitive.
=== Facts and theories ===
Theoretical physicist and mathematician Freeman Dyson explains that "[s]cience consists of facts and theories":
"Facts are supposed to be true or false. They are discovered by observers or experimenters. A scientist who claims to have discovered a fact that turns out to be wrong is judged harshly....
"Theories have an entirely different status. They are free creations of the human mind, intended to describe our understanding of nature. Since our understanding is incomplete, theories are provisional. Theories are tools of understanding, and a tool does not need to be precisely true in order to be useful. Theories are supposed to be more-or-less true... A scientist who invents a theory that turns out to be wrong is judged leniently."
Dyson cites a psychologist's description of how theories are born: "We can't live in a state of perpetual doubt, so we make up the best story possible and we live as if the story were true." Dyson writes: "The inventor of a brilliant idea cannot tell whether it is right or wrong." The passionate pursuit of wrong theories is a normal part of the development of science. Dyson cites, after Mario Livio, five famous scientists who made major contributions to the understanding of nature but also believed firmly in a theory that proved wrong.
Charles Darwin explained the evolution of life with his theory of natural selection of inherited variations, but he believed in a theory of blending inheritance that made the propagation of new variations impossible. He never read Gregor Mendel's studies that showed that the laws of inheritance would become simple when inheritance was considered as a random process. Though Darwin in 1866 did the same experiment that Mendel had, Darwin did not get comparable results because he failed to appreciate the statistical importance of using very large experimental samples. Eventually, Mendelian inheritance by random variation would, no thanks to Darwin, provide the raw material for Darwinian selection to work on.
William Thomson (Lord Kelvin) discovered basic laws of energy and heat, then used these laws to calculate an estimate of the age of the Earth that was too short by a factor of fifty. He based his calculation on the belief that the Earth's mantle was solid and could transfer heat from the interior to the surface only by conduction. It is now known that the mantle is partly fluid and transfers most of the heat by the far more efficient process of convection, which carries heat by a massive circulation of hot rock moving upward and cooler rock moving downward. Kelvin could see the eruptions of volcanoes bringing hot liquid from deep underground to the surface; but his skill in calculation blinded him to processes, such as volcanic eruptions, that could not be calculated.
Linus Pauling discovered the chemical structure of protein and proposed a completely wrong structure for DNA, which carries hereditary information from parent to offspring. Pauling guessed a wrong structure for DNA because he assumed that a pattern that worked for protein would also work for DNA. He overlooked the gross chemical differences between protein and DNA. Francis Crick and James Watson paid attention to the differences and found the correct structure for DNA that Pauling had missed a year earlier.
Astronomer Fred Hoyle discovered the process by which the heavier elements essential to life are created by nuclear reactions in the cores of massive stars. He then proposed a theory of the history of the universe known as steady-state cosmology, which has the universe existing forever without an initial Big Bang (as Hoyle derisively dubbed it). He held his belief in the steady state long after observations proved that the Big Bang had happened.
Albert Einstein discovered the theory of space, time, and gravitation known as general relativity, and then added a cosmological constant, later known as dark energy. Subsequently, Einstein withdrew his proposal of dark energy, believing it unnecessary. Long after his death, observations suggested that dark energy really exists, so that Einstein's addition to the theory may have been right; and his withdrawal, wrong.
To Mario Livio's five examples of scientists who blundered, Dyson adds a sixth: himself. Dyson had concluded, on theoretical principles, that what was to become known as the W-particle, a charged weak boson, could not exist. An experiment conducted at CERN, in Geneva, later proved him wrong. "With hindsight I could see several reasons why my stability argument would not apply to W-particles. [They] are too massive and too short-lived to be a constituent of anything that resembles ordinary matter."
=== Truth ===
Harvard University historian of science Naomi Oreskes points out that the truth of scientific findings can never be assumed to be finally, absolutely settled. The history of science offers many examples of matters that scientists once thought to be settled and which have proven not to be, such as the concepts of Earth being the center of the universe, the absolute nature of time and space, the stability of continents, and the cause of infectious disease.
Science, writes Oreskes, is not a fixed, immutable set of discoveries but "a process of learning and discovery [...]. Science can also be understood as an institution (or better, a set of institutions) that facilitates this work.
It is often asserted that scientific findings are true because scientists use "the scientific method". But, writes Oreskes, "we can never actually agree on what that method is. Some will say it is empiricism: observation and description of the world. Others will say it is the experimental method: the use of experience and experiment to test hypotheses. (This is cast sometimes as the hypothetico-deductive method, in which the experiment must be framed as a deduction from theory, and sometimes as falsification, where the point of observation and experiment is to refute theories, not to confirm them.) Recently a prominent scientist claimed the scientific method was to avoid fooling oneself into thinking something is true that is not, and vice versa."
In fact, writes Oreskes, the methods of science have varied between disciplines and across time. "Many scientific practices, particularly statistical tests of significance, have been developed with the idea of avoiding wishful thinking and self-deception, but that hardly constitutes 'the scientific method.'"
Science, writes Oreskes, "is not simple, and neither is the natural world; therein lies the challenge of science communication. [...] Our efforts to understand and characterize the natural world are just that: efforts. Because we're human, we often fall flat."
"Scientific theories", according to Oreskes, "are not perfect replicas of reality, but we have good reason to believe that they capture significant elements of it."
=== Empiricism ===
Steven Weinberg, 1979 Nobel laureate in physics, and a historian of science, writes that the core goal of science has always been the same: "to explain the world"; and in reviewing earlier periods of scientific thought, he concludes that only since Isaac Newton has that goal been pursued more or less correctly. He decries the "intellectual snobbery" that Plato and Aristotle showed in their disdain for science's practical applications, and he holds Francis Bacon and René Descartes to have been the "most overrated" among the forerunners of modern science (they tried to prescribe rules for conducting science, which "never works").
Weinberg draws parallels between past and present science, as when a scientific theory is "fine-tuned" (adjusted) to make certain quantities equal, without any understanding of why they should be equal. Such adjusting vitiated the celestial models of Plato's followers, in which different spheres carrying the planets and stars were assumed, with no good reason, to rotate in exact unison. But, Weinberg writes, a similar fine-tuning also besets current efforts to understand the "dark energy" that is speeding up the expansion of the universe.
Ancient science has been described as having gotten off to a good start, then faltered. The doctrine of atomism, propounded by the pre-Socratic philosophers Leucippus and Democritus, was naturalistic, accounting for the workings of the world by impersonal processes, not by divine volitions. Nevertheless, these pre-Socratics come up short for Weinberg as proto-scientists, in that they apparently never tried to justify their speculations or to test them against evidence.
Weinberg believes that science faltered early on due to Plato's suggestion that scientific truth could be attained by reason alone, disregarding empirical observation, and due to Aristotle's attempt to explain nature teleologically—in terms of ends and purposes. Plato's ideal of attaining knowledge of the world by unaided intellect was "a false goal inspired by mathematics"—one that for centuries "stood in the way of progress that could be based only on careful analysis of careful observation." And it "never was fruitful" to ask, as Aristotle did, "what is the purpose of this or that physical phenomenon."
A scientific field in which the Greek and Hellenistic world did make progress was astronomy. This was partly for practical reasons: the sky had long served as compass, clock, and calendar. Also, the regularity of the movements of heavenly bodies made them simpler to describe than earthly phenomena. But not too simple: though the sun, moon and "fixed stars" seemed regular in their celestial circuits, the "wandering stars"—the planets—were puzzling; they seemed to move at variable speeds, and even to reverse direction. Writes Weinberg: "Much of the story of the emergence of modern science deals with the effort, extending over two millennia, to explain the peculiar motions of the planets."
The challenge was to make sense of the apparently irregular wanderings of the planets on the assumption that all heavenly motion is actually circular and uniform in speed. Circular, because Plato held the circle to be the most perfect and symmetrical form; and therefore circular motion, at uniform speed, was most fitting for celestial bodies. Aristotle agreed with Plato. In Aristotle's cosmos, everything had a "natural" tendency to motion that fulfilled its inner potential. For the cosmos' sublunary part (the region below the Moon), the natural tendency was to move in a straight line: downward, for earthen things (such as rocks) and water; upward, for air and fiery things (such as sparks). But in the celestial realm things were not composed of earth, water, air, or fire, but of a "fifth element", or "quintessence," which was perfect and eternal. And its natural motion was uniformly circular. The stars, the Sun, the Moon, and the planets were carried in their orbits by a complicated arrangement of crystalline spheres, all centered around an immobile Earth.
The Platonic-Aristotelian conviction that celestial motions must be circular persisted stubbornly. It was fundamental to the astronomer Ptolemy's system, which improved on Aristotle's in conforming to the astronomical data by allowing the planets to move in combinations of circles called "epicycles".
It even survived the Copernican Revolution. Copernicus was conservative in his Platonic reverence for the circle as the heavenly pattern. According to Weinberg, Copernicus was motivated to dethrone the Earth in favor of the Sun as the immobile center of the cosmos largely by aesthetic considerations: he objected to the fact that Ptolemy, though faithful to Plato's requirement that heavenly motion be circular, had departed from Plato's other requirement that it be of uniform speed. By putting the sun at the center—actually, somewhat off-center—Copernicus sought to honor circularity while restoring uniformity. But to make his system fit the observations as well as Ptolemy's system, Copernicus had to introduce still more epicycles. That was a mistake that, writes Weinberg, illustrates a recurrent theme in the history of science: "A simple and beautiful theory that agrees pretty well with observation is often closer to the truth than a complicated ugly theory that agrees better with observation."
The planets, however, do not move in perfect circles but in ellipses. It was Johannes Kepler, about a century after Copernicus, who reluctantly (for he too had Platonic affinities) realized this. Thanks to his examination of the meticulous observations compiled by astronomer Tycho Brahe, Kepler "was the first to understand the nature of the departures from uniform circular motion that had puzzled astronomers since the time of Plato."
The replacement of circles by supposedly ugly ellipses overthrew Plato's notion of perfection as the celestial explanatory principle. It also destroyed Aristotle's model of the planets carried in their orbits by crystalline spheres; writes Weinberg, "there is no solid body whose rotation can produce an ellipse." Even if a planet were attached to an ellipsoid crystal, that crystal's rotation would still trace a circle. And if the planets were pursuing their elliptical motion through empty space, then what was holding them in their orbits?
Science had reached the threshold of explaining the world not geometrically, according to shape, but dynamically, according to force. It was Isaac Newton who finally crossed that threshold. He was the first to formulate, in his "laws of motion", the concept of force. He demonstrated that Kepler's ellipses were the very orbits the planets would take if they were attracted toward the Sun by a force that decreased as the square of the planet's distance from the Sun. And by comparing the Moon's motion in its orbit around the Earth to the motion of, perhaps, an apple as it falls to the ground, Newton deduced that the forces governing them were quantitatively the same. "This," writes Weinberg, "was the climactic step in the unification of the celestial and terrestrial in science."
By formulating a unified explanation of the behavior of planets, comets, moons, tides, and apples, writes Weinberg, Newton "provided an irresistible model for what a physical theory should be"—a model that fit no preexisting metaphysical criterion. In contrast to Aristotle, who claimed to explain the falling of a rock by appeal to its inner striving, Newton was unconcerned with finding a deeper cause for gravity. He declared in a postscript to the second, 1713 edition of his Philosophiæ Naturalis Principia Mathematica: "I have not as yet been able to deduce from phenomena the reason for these properties of gravity, and I do not feign hypotheses. It is enough that gravity really exists and acts according to the laws that we have set forth." What mattered were his mathematically stated principles describing this force, and their ability to account for a vast range of phenomena.
About two centuries later, in 1915, a deeper explanation for Newton's law of gravitation was found in Albert Einstein's general theory of relativity: gravity could be explained as a manifestation of the curvature in spacetime resulting from the presence of matter and energy. Successful theories like Newton's, writes Weinberg, may work for reasons that their creators do not understand—reasons that deeper theories will later reveal. Scientific progress is not a matter of building theories on a foundation of reason, but of unifying a greater range of phenomena under simpler and more general principles.
==== Absence of evidence ====
Naomi Oreskes cautions against making "the classic error of conflating absence of evidence with evidence of absence [emphases added]." She cites two examples of this error that were perpetrated in 2016 and 2023.
In 2016 the Cochrane Library, a collection of databases in medicine and other healthcare specialties, published a report that was widely understood to indicate that flossing one's teeth confers no advantage to dental health. But the American Academy of Periodontology, dental professors, deans of dental schools, and clinical dentists all held that clinical practice shows differences in tooth and gum health between those who floss and those who don't.
Oreskes explains that "Cochrane Reviews base their findings on randomized controlled trials (RCTs), often called the 'gold standard' of scientific evidence." But many questions can't be answered well using this method, and some can't be answered at all. "Nutrition is a case in point. [Y]ou can't control what people eat, and when you ask... what they have eaten, many people lie. Flossing is similar. One survey concluded that one in four Americans who claimed to floss regularly was fibbing."
In 2023 Cochrane published a report determining that wearing surgical masks "probably makes little or no difference" in slowing the spread of respiratory illnesses such as COVID-19. Mass media reduced this to the claim that masks did not work. The Cochrane Library's editor-in-chief objected to such characterizations of the review; she said the report had not concluded that "masks don't work", but rather that the "results were inconclusive." The report had made clear that its conclusions were about the quality and capaciousness of available evidence, which the authors felt were insufficient to prove that masking was effective. The report's authors were "uncertain whether wearing [surgical] masks or N95/P2 respirators helps to slow the spread of respiratory viruses." Still, they were also uncertain about that uncertainty [emphasis added], stating that their confidence in their conclusion was "low to moderate."
Subsequently the report's lead author confused the public by stating that mask-wearing "Makes no difference – none of it", and that Covid policies were "evidence-free": he thus perpetrated what Oreskes calls "the [...] error of conflating absence of evidence with evidence of absence." Studies have in fact shown that U.S. states with mask mandates saw a substantial decline in Covid spread within days of mandate orders being signed; in the period from 31 March to 22 May 2020, more than 200,000 cases were avoided.
Oreskes calls the Cochrane report's neglect of the epidemiological evidence – because it didn't meet Cochrane's rigid standard – "methodological fetishism," when scientists "fixate on a preferred methodology and dismiss studies that don't follow it."
=== Artificial intelligence ===
The term "artificial intelligence" (AI) was coined in 1955 by John McCarthy when he and other computer scientists were planning a workshop and did not want to invite Norbert Wiener, the brilliant, pugnacious, and increasingly philosophical (rather than practical) author on feedback mechanisms who had coined the term "cybernetics". The new term artificial intelligence, writes Kenneth Cukier, "set in motion decades of semantic squabbles ('Can machines think?') and fueled anxieties over malicious robots... If McCarthy... had chosen a blander phrase—say, 'automation studies'—the concept might not have appealed as much to Hollywood [movie] producers and [to] journalists..." Similarly Naomi Oreskes has commented: "[M]achine 'intelligence'... isn't intelligence at all but something more like 'machine capability.'"
As machines have become increasingly capable, specific tasks considered to require "intelligence", such as optical character recognition, have often been removed from the definition of AI, a phenomenon known as the "AI effect". It has been quipped that "AI is whatever hasn't been done yet."
Since 1950, when Alan Turing proposed what has come to be called the "Turing test," there has been speculation whether machines such as computers can possess intelligence; and, if so, whether intelligent machines could become a threat to human intellectual and scientific ascendancy—or even an existential threat to humanity. John Searle points out common confusion about the correct interpretation of computation and information technology. "For example, one routinely reads that in exactly the same sense in which Garry Kasparov… beat Anatoly Karpov in chess, the computer called Deep Blue played and beat Kasparov.... [T]his claim is [obviously] suspect. In order for Kasparov to play and win, he has to be conscious that he is playing chess, and conscious of a thousand other things... Deep Blue is conscious of none of these things because it is not conscious of anything at all. Why is consciousness so important? You cannot literally play chess or do much of anything else cognitive if you are totally disassociated from consciousness."
Searle explains that, "in the literal, real, observer-independent sense in which humans compute, mechanical computers do not compute. They go through a set of transitions in electronic states that we can interpret computationally. The transitions in those electronic states are absolute or observer-independent, but the computation is observer-relative. The transitions in physical states are just electrical sequences unless some conscious agent can give them a computational interpretation.... There is no psychological reality at all to what is happening in the [computer]."
"[A] digital computer", writes Searle, "is a syntactical machine. It manipulates symbols and does nothing else. For this reason, the project of creating human intelligence by designing a computer program that will pass the Turing Test... is doomed from the start. The appropriately programmed computer has a syntax [rules for constructing or transforming the symbols and words of a language] but no semantics [comprehension of meaning].... Minds, on the other hand, have mental or semantic content."
Like Searle, Christof Koch, chief scientist and president of the Allen Institute for Brain Science, in Seattle, is doubtful about the possibility of "intelligent" machines attaining consciousness, because "[e]ven the most sophisticated brain simulations are unlikely to produce conscious feelings." According to Koch,
Whether machines can become sentient [is important] for ethical reasons. If computers experience life through their own senses, they cease to be purely a means to an end determined by their usefulness to... humans. Per GNW [the Global Neuronal Workspace theory], they turn from mere objects into subjects... with a point of view.... Once computers' cognitive abilities rival those of humanity, their impulse to push for legal and political rights will become irresistible – the right not to be deleted, not to have their memories wiped clean, not to suffer pain and degradation. The alternative, embodied by IIT [Integrated Information Theory], is that computers will remain only supersophisticated machinery, ghostlike empty shells, devoid of what we value most: the feeling of life itself."
Professor of psychology and neural science Gary Marcus points out a so far insuperable stumbling block to artificial intelligence: an incapacity for reliable disambiguation. "[V]irtually every sentence [that people generate] is ambiguous, often in multiple ways. Our brain is so good at comprehending language that we do not usually notice." A prominent example is known as the "pronoun disambiguation problem" ("PDP"): a machine has no way of determining to whom or what a pronoun in a sentence—such as "he", "she" or "it"—refers.
Marcus has described current large language models as "approximations to [...] language use rather than language understanding".
Computer scientist Pedro Domingos writes: "AIs are like autistic savants and will remain so for the foreseeable future.... AIs lack common sense and can easily make errors that a human never would... They are also liable to take our instructions too literally, giving us precisely what we asked for instead of what we actually wanted.
Kai-Fu Lee, a Beijing-based venture capitalist, artificial-intelligence (AI) expert with a Ph.D. in computer science from Carnegie Mellon University, and author of the 2018 book, AI Superpowers: China, Silicon Valley, and the New World Order, emphasized in a 2018 PBS Amanpour interview with Hari Sreenivasan that AI, with all its capabilities, will never be capable of creativity or empathy. Bill Gates, interviewed in 2025 by Walter Isaacson on Amanpour and Company, similarly said that artificial intelligence possesses no sentience and is incapable of human feeling or understanding.
Parallel views were expressed in a 23 May 2025 Firing Line interview by Fei-Fei Li, co-director of the Stanford Institute for Human-Centered Artificial Intelligence. She emphasized that "AI is a tool" that can help humanity in many ways but that it should not be subjected to hyperbolae, either laudatory or alarmist (e.g., that it "will end humanity"); that, in order to avoid harmful applications ("Any technology can harm people"), it requires a "good regulatory framework"; and that AI has no "emotional intelligence" or creativity.
Paul Scharre writes in Foreign Affairs that "Today's AI technologies are powerful but unreliable." George Dyson, historian of computing, writes (in what might be called "Dyson's Law") that "Any system simple enough to be understandable will not be complicated enough to behave intelligently, while any system complicated enough to behave intelligently will be too complicated to understand." Computer scientist Alex Pentland writes: "Current AI machine-learning algorithms are, at their core, dead simple stupid. They work, but they work by brute force."
"Artificial intelligence" is synonymous with "machine intelligence." The more perfectly adapted an AI program is to a given task, the less applicable it will be to other specific tasks. An abstracted, AI general intelligence is a remote prospect, if feasible at all. Melanie Mitchell notes that an AI program called AlphaGo bested one of the world's best Go players, but that its "intelligence" is nontransferable: it cannot "think" about anything except Go. Mitchell writes: "We humans tend to overestimate AI advances and underestimate the complexity of our own intelligence." Writes Paul Taylor: "Perhaps there is a limit to what a computer can do without knowing that it is manipulating imperfect representations of an external reality."
Humankind may not be able to outsource, to machines, its creative efforts in the sciences, technology, and culture.
Gary Marcus cautions against being taken in by deceptive claims about artificial general intelligence capabilities that are put out in press releases by self-interested companies which tell the press and public "only what the companies want us to know." Marcus writes:
Although deep learning has advanced the ability of machines to recognize patterns in data, it has three major flaws. The patterns that it learns are, ironically, superficial not conceptual; the results it creates are hard to interpret; and the results are difficult to use in the context of other processes, such as memory and reasoning. As Harvard University computer scientist Les Valiant noted, "The central challenge [going forward] is to unify the formulation of... learning and reasoning."
James Gleick writes: "Agency is what distinguishes us from machines. For biological creatures, reason and purpose come from acting in the world and experiencing the consequences. Artificial intelligences – disembodied, strangers to blood, sweat, and tears – have no occasion for that."
=== Uncertainty ===
A central concern for science and scholarship is the reliability and reproducibility of their findings. Of all fields of study, none is capable of such precision as physics. But even there the results of studies, observations, and experiments cannot be considered absolutely certain and must be treated probabilistically; hence, statistically.
In 1925 British geneticist and statistician Ronald Fisher published Statistical Methods for Research Workers, which established him as the father of modern statistics. He proposed a statistical test that summarized the compatibility of data with a given proposed model and produced a "p value". He counselled pursuing results with p values below 0.05 and not wasting time on results above that. Thus arose the idea that a p value less than 0.05 constitutes "statistical significance" – a mathematical definition of "significant" results.
The use of p values, ever since, to determine the statistical significance of experimental results has contributed to an illusion of certainty and to reproducibility crises in many scientific fields, especially in experimental economics, biomedical research, and psychology.
Every statistical model relies on a set of assumptions about how data are collected and analyzed and about how researchers decide to present their results. These results almost always center on null-hypothesis significance testing, which produces a p value. Such testing does not address the truth head-on but obliquely: significance testing is meant to indicate only whether a given line of research is worth pursuing further. It does not say how likely the hypothesis is to be true, but instead addresses an alternative question: if the hypothesis were false, how unlikely would the data be? The importance of "statistical significance", reflected in the p value, can be exaggerated or overemphasized – something that readily occurs with small samples. That has caused replication crises.
Some scientists have advocated "redefining statistical significance", shifting its threshold from 0.05 to 0.005 for claims of new discoveries. Others say such redefining does no good because the real problem is the very existence of a threshold.
Some scientists prefer to use Bayesian methods, a more direct statistical approach which takes initial beliefs, adds in new evidence, and updates the beliefs. Another alternative procedure is to use the surprisal, a mathematical quantity that adjust p values to produce bits – as in computer bits – of information; in that perspective, 0.05 is a weak standard.
When Ronald Fisher embraced the concept of "significance" in the early 20th century, it meant "signifying" but not "important". Statistical "significance" has, since, acquired am excessive connotation of confidence in the validity of the experimental results. Statistician Andrew Gelman says, "The original sin is people wanting certainty when it's not appropriate." "Ultimately", writes Lydia Denworth, "a successful theory is one that stands up repeatedly to decades of scrutiny."
Increasingly, attention is being given to the principles of open science, such as publishing more detailed research protocols and requiring authors to follow prespecified analysis plans and to report when they deviate from them.
== Discovery ==
=== Discoveries and inventions ===
Fifty years before Florian Znaniecki published his 1923 paper proposing the creation of an empirical field of study to study the field of science, Aleksander Głowacki (better known by his pen name, Bolesław Prus) had made the same proposal. In an 1873 public lecture "On Discoveries and Inventions", Prus said:
Until now there has been no science that describes the means for making discoveries and inventions, and the generality of people, as well as many men of learning, believe that there never will be. This is an error. Someday a science of making discoveries and inventions will exist and will render services. It will arise not all at once; first only its general outline will appear, which subsequent researchers will correct and elaborate, and which still later researchers will apply to individual branches of knowledge.
Prus defines "discovery" as "the finding out of a thing that has existed and exists in nature, but which was previously unknown to people"; and "invention" as "the making of a thing that has not previously existed, and which nature itself cannot make."
He illustrates the concept of "discovery":
Until 400 years ago, people thought that the Earth comprised just three parts: Europe, Asia, and Africa; it was only in 1492 that the Genoese, Christopher Columbus, sailed out from Europe into the Atlantic Ocean and, proceeding ever westward, after [10 weeks] reached a part of the world that Europeans had never known. In that new land he found copper-colored people who went about naked, and he found plants and animals different from those in Europe; in short, he had discovered a new part of the world that others would later name "America." We say that Columbus had discovered America, because America had already long existed on Earth.
Prus illustrates the concept of "invention":
[As late as] 50 years ago, locomotives were unknown, and no one knew how to build one; it was only in 1828 that the English engineer Stephenson built the first locomotive and set it in motion. So we say that Stephenson invented the locomotive, because this machine had not previously existed and could not by itself have come into being in nature; it could only have been made by man.
According to Prus, "inventions and discoveries are natural phenomena and, as such, are subject to certain laws." Those are the laws of "gradualness", "dependence", and "combination".
1. The law of gradualness. No discovery or invention arises at once perfected, but is perfected gradually; likewise, no invention or discovery is the work of a single individual but of many individuals, each adding his little contribution.
2. The law of dependence. An invention or discovery is conditional on the prior existence of certain known discoveries and inventions. ...If the rings of Saturn can [only] be seen through telescopes, then the telescope had to have been invented before the rings could have been seen. [...]
3. The law of combination. Any new discovery or invention is a combination of earlier discoveries and inventions, or rests on them. When I study a new mineral, I inspect it, I smell it, I taste it ... I combine the mineral with a balance and with fire...in this way I learn ever more of its properties.
Each of Prus' three "laws" entails important corollaries. The law of gradualness implies the following:
a) Since every discovery and invention requires perfecting, let us not pride ourselves only on discovering or inventing something completely new, but let us also work to improve or get to know more exactly things that are already known and already exist. [...]
b) The same law of gradualness demonstrates the necessity of expert training. Who can perfect a watch, if not a watchmaker with a good comprehensive knowledge of his métier? Who can discover new characteristics of an animal, if not a naturalist?
From the law of dependence flow the following corollaries:
a) No invention or discovery, even one seemingly without value, should be dismissed, because that particular trifle may later prove very useful. There would seem to be no simpler invention than the needle, yet the clothing of millions of people, and the livelihoods of millions of seamstresses, depend on the needle's existence. Even today's beautiful sewing machine would not exist, had the needle not long ago been invented.
b) The law of dependence teaches us that what cannot be done today, might be done later. People give much thought to the construction of a flying machine that could carry many persons and parcels. The inventing of such a machine will depend, among other things, on inventing a material that is, say, as light as paper and as sturdy and fire-resistant as steel.
Finally, Prus' corollaries to his law of combination:
a) Anyone who wants to be a successful inventor, needs to know a great many things—in the most diverse fields. For if a new invention is a combination of earlier inventions, then the inventor's mind is the ground on which, for the first time, various seemingly unrelated things combine. Example: The steam engine combines the kettle for cooking Rumford's Soup, the pump, and the spinning wheel.
[...] What is the connection among zinc, copper, sulfuric acid, a magnet, a clock mechanism, and an urgent message? All these had to come together in the mind of the inventor of the telegraph... [...]
The greater the number of inventions that come into being, the more things a new inventor must know; the first, earliest and simplest inventions were made by completely uneducated people—but today's inventions, particularly scientific ones, are products of the most highly educated minds. [...]
b) A second corollary concerns societies that wish to have inventors. I said that a new invention is created by combining the most diverse objects; let us see where this takes us.
Suppose I want to make an invention, and someone tells me: Take 100 different objects and bring them into contact with one another, first two at a time, then three at a time, finally four at a time, and you will arrive at a new invention. Imagine that I take a burning candle, charcoal, water, paper, zinc, sugar, sulfuric acid, and so on, 100 objects in all, and combine them with one another, that is, bring into contact first two at a time: charcoal with flame, water with flame, sugar with flame, zinc with flame, sugar with water, etc. Each time, I shall see a phenomenon: thus, in fire, sugar will melt, charcoal will burn, zinc will heat up, and so on. Now I will bring into contact three objects at a time, for example, sugar, zinc and flame; charcoal, sugar and flame; sulfuric acid, zinc and water; etc., and again I shall experience phenomena. Finally I bring into contact four objects at a time, for example, sugar, zinc, charcoal, and sulfuric acid. Ostensibly this is a very simple method, because in this fashion I could make not merely one but a dozen inventions. But will such an effort not exceed my capability? It certainly will. A hundred objects, combined in twos, threes and fours, will make over 4 million combinations; so if I made 100 combinations a day, it would take me over 110 years to exhaust them all!
But if by myself I am not up to the task, a sizable group of people will be. If 1,000 of us came together to produce the combinations that I have described, then any one person would only have to carry out slightly more than 4,000 combinations. If each of us performed just 10 combinations a day, together we would finish them all in less than a year and a half: 1,000 people would make an invention which a single man would have to spend more than 110 years to make…
The conclusion is quite clear: a society that wants to win renown with its discoveries and inventions has to have a great many persons working in every branch of knowledge. One or a few men of learning and genius mean nothing today, or nearly nothing, because everything is now done by large numbers. I would like to offer the following simile: Inventions and discoveries are like a lottery; not every player wins, but from among the many players a few must win. The point is not that John or Paul, because they want to make an invention and because they work for it, shall make an invention; but where thousands want an invention and work for it, the invention must appear, as surely as an unsupported rock must fall to the ground.
But, asks Prus, "What force drives [the] toilsome, often frustrated efforts [of the investigators]? What thread will clew these people through hitherto unexplored fields of study?"
[T]he answer is very simple: man is driven to efforts, including those of making discoveries and inventions, by needs; and the thread that guides him is observation: observation of the works of nature and of man.
I have said that the mainspring of all discoveries and inventions is needs. In fact, is there any work of man that does not satisfy some need? We build railroads because we need rapid transportation; we build clocks because we need to measure time; we build sewing machines because the speed of [unaided] human hands is insufficient. We abandon home and family and depart for distant lands because we are drawn by curiosity to see what lies elsewhere. We forsake the society of people and we spend long hours in exhausting contemplation because we are driven by a hunger for knowledge, by a desire to solve the challenges that are constantly thrown up by the world and by life!
Needs never cease; on the contrary, they are always growing. While the pauper thinks about a piece of bread for lunch, the rich man thinks about wine after lunch. The foot traveler dreams of a rudimentary wagon; the railroad passenger demands a heater. The infant is cramped in its cradle; the mature man is cramped in the world. In short, everyone has his needs, and everyone desires to satisfy them, and that desire is an inexhaustible source of new discoveries, new inventions, in short, of all progress.
But needs are general, such as the needs for food, sleep and clothing; and special, such as needs for a new steam engine, a new telescope, a new hammer, a new wrench. To understand the former needs, it suffices to be a human being; to understand the latter needs, one must be a specialist—an expert worker. Who knows better than a tailor what it is that tailors need, and who better than a tailor knows how to find the right way to satisfy the need?
Now consider how observation can lead man to new ideas; and to that end, as an example, let us imagine how, more or less, clay products came to be invented.
Suppose that somewhere there lived on clayey soil a primitive people who already knew fire. When rain fell on the ground, the clay turned doughy; and if, shortly after the rain, a fire was set on top of the clay, the clay under the fire became fired and hardened. If such an event occurred several times, the people might observe and thereafter remember that fired clay becomes hard like stone and does not soften in water. One of the primitives might also, when walking on wet clay, have impressed deep tracks into it; after the sun had dried the ground and rain had fallen again, the primitives might have observed that water remains in those hollows longer than on the surface. Inspecting the wet clay, the people might have observed that this material can be easily kneaded in one's fingers and accepts various forms.
Some ingenious persons might have started shaping clay into various animal forms [...] etc., including something shaped like a tortoise shell, which was in use at the time. Others, remembering that clay hardens in fire, might have fired the hollowed-out mass, thereby creating the first [clay] bowl.
After that, it was a relatively easy matter to perfect the new invention; someone else could discover clay more suitable for such manufactures; someone else could invent a glaze, and so on, with nature and observation at every step pointing out to man the way to invention. [...]
[This example] illustrates how people arrive at various ideas: by closely observing all things and wondering about all things.
Take another example. [S]ometimes, in a pane of glass, we find disks and bubbles, looking through which we see objects more distinctly than with the naked eye. Suppose that an alert person, spotting such a bubble in a pane, took out a piece of glass and showed it to others as a toy. Possibly among them there was a man with weak vision who found that, through the bubble in the pane, he saw better than with the naked eye. Closer investigation showed that bilaterally convex glass strengthens weak vision, and in this way eyeglasses were invented. People may first have cut glass for eyeglasses from glass panes, but in time others began grinding smooth pieces of glass into convex lenses and producing proper eyeglasses.
The art of grinding eyeglasses was known almost 600 years ago. A couple of hundred years later, the children of a certain eyeglass grinder, while playing with lenses, placed one in front of another and found that they could see better through two lenses than through one. They informed their father about this curious occurrence, and he began producing tubes with two magnifying lenses and selling them as a toy. Galileo, the great Italian scientist, on learning of this toy, used it for a different purpose and built the first telescope.
This example, too, shows us that observation leads man by the hand to inventions. This example again demonstrates the truth of gradualness in the development of inventions, but above all also the fact that education amplifies man's inventiveness. A simple lens-grinder formed two magnifying glasses into a toy—while Galileo, one of the most learned men of his time, made a telescope. As Galileo's mind was superior to the craftsman's mind, so the invention of the telescope was superior to the invention of a toy. [...]
The three laws [that have been discussed here] are immensely important and do not apply only to discoveries and inventions, but they pervade all of nature. An oak does not immediately become an oak but begins as an acorn, then becomes a seedling, later a little tree, and finally a mighty oak: we see here the law of gradualness. A seed that has been sown will not germinate until it finds sufficient heat, water, soil and air: here we see the law of dependence. Finally, no animal or plant, or even stone, is something homogeneous and simple but is composed of various organs: here we see the law of combination.
Prus holds that, over time, the multiplication of discoveries and inventions has improved the quality of people's lives and has expanded their knowledge. "This gradual advance of civilized societies, this constant growth in knowledge of the objects that exist in nature, this constant increase in the number of tools and useful materials, is termed progress, or the growth of civilization." Conversely, Prus warns, "societies and people that do not make inventions or know how to use them, lead miserable lives and ultimately perish."
=== Reproducibility ===
A fundamental feature of the scientific enterprise is reproducibility of results. "For decades", writes Shannon Palus, "it has been... an open secret that a [considerable part] of the literature in some fields is plain wrong." This effectively sabotages the scientific enterprise and costs the world many billions of dollars annually in wasted resources. Militating against reproducibility is scientists' reluctance to share techniques, for fear of forfeiting one's advantage to other scientists. Also, scientific journals and tenure committees tend to prize impressive new results rather than gradual advances that systematically build on existing literature. Scientists who quietly fact-check others' work or spend extra time ensuring that their own protocols are easy for other researchers to understand, gain little for themselves.
With a view to improving reproducibility of scientific results, it has been suggested that research-funding agencies finance only projects that include a plan for making their work transparent. In 2016 the U.S. National Institutes of Health introduced new application instructions and review questions to encourage scientists to improve reproducibility. The NIH requests more information on how the study builds on previous work, and a list of variables that could affect the study, such as the sex of animal subjects—a previously overlooked factor that led many studies to describe phenomena found in male animals as universal.
Likewise, the questions that a funder can ask in advance could be asked by journals and reviewers. One solution is "registered reports", a preregistration of studies whereby a scientist submits, for publication, research analysis and design plans before actually doing the study. Peer reviewers then evaluate the methodology, and the journal promises to print the results, no matter what they are. In order to prevent over-reliance on preregistered studies—which could encourage safer, less venturesome research, thus over-correcting the problem—the preregistered-studies model could be operated in tandem with the traditional results-focused model, which may sometimes be more friendly to serendipitous discoveries.
The "replication crisis" is compounded by a finding, published in a study summarized in 2021 by historian of science Naomi Oreskes, that nonreplicable studies are cited oftener than replicable ones: in other words, that bad science seems to get more attention than good science. If a substantial proportion of science is unreplicable, it will not provide a valid basis for decision-making and may delay the use of science for developing new medicines and technologies. It may also undermine the public's trust, making it harder to get people vaccinated or act against climate change.
The study tracked papers – in psychology journals, economics journals, and in Science and Nature – with documented failures of replication. The unreplicable papers were cited more than average, even after news of their unreplicability had been published.
"These results," writes Oreskes, "parallel those of a 2018 study. An analysis of 126,000 rumor cascades on Twitter showed that false news spread faster and reached more people than verified true claims. [I]t was people, not [ro]bots, who were responsible for the disproportionate spread of falsehoods online."
=== Rediscovery ===
A 2016 Scientific American report highlights the role of rediscovery in science. Indiana University Bloomington researchers combed through 22 million scientific papers published over the previous century and found dozens of "Sleeping Beauties"—studies that lay dormant for years before getting noticed. The top finds, which languished longest and later received the most intense attention from scientists, came from the fields of chemistry, physics, and statistics. The dormant findings were wakened by scientists from other disciplines, such as medicine, in search of fresh insights, and by the ability to test once-theoretical postulations. Sleeping Beauties will likely become even more common in the future because of increasing accessibility of scientific literature. The Scientific American report lists the top 15 Sleeping Beauties: 7 in chemistry, 5 in physics, 2 in statistics, and 1 in metallurgy. Examples include:
Herbert Freundlich's "Concerning Adsorption in Solutions" (1906), the first mathematical model of adsorption, when atoms or molecules adhere to a surface. Today both environmental remediation and decontamination in industrial settings rely heavily on adsorption.
A. Einstein, B. Podolsky and N. Rosen, "Can Quantum-Mechanical Description of Physical Reality Be Considered Complete?" Physical Review, vol. 47 (May 15, 1935), pp. 777–780. This famous thought experiment in quantum physics—now known as the EPR paradox, after the authors' surname initials—was discussed theoretically when it first came out. It was not until the 1970s that physics had the experimental means to test quantum entanglement.
J[ohn] Turkevich, P. C. Stevenson, J. Hillier, "A Study of the Nucleation and Growth Processes in the Synthesis of Colloidal Gold", Discuss. Faraday. Soc., 1951, 11, pp. 55–75, explains how to suspend gold nanoparticles in liquid. It owes its awakening to medicine, which now employs gold nanoparticles to detect tumors and deliver drugs.
William S. Hummers and Richard E Offeman, "Preparation of Graphitic Oxide", Journal of the American Chemical Society, vol. 80, no. 6 (March 20, 1958), p. 1339, introduced Hummers' Method, a technique for making graphite oxide. Recent interest in graphene's potential has brought the 1958 paper to attention. Graphite oxide could serve as a reliable intermediate for the 2-D material.
=== Multiple discovery ===
Historians and sociologists have remarked the occurrence, in science, of "multiple independent discovery". Sociologist Robert K. Merton defined such "multiples" as instances in which similar discoveries are made by scientists working independently of each other. "Sometimes the discoveries are simultaneous or almost so; sometimes a scientist will make a new discovery which, unknown to him, somebody else has made years before." Commonly cited examples of multiple independent discovery are the 17th-century independent formulation of calculus by Isaac Newton, Gottfried Wilhelm Leibniz, and others; the 18th-century independent discovery of oxygen by Carl Wilhelm Scheele, Joseph Priestley, Antoine Lavoisier, and others; and the 19th-century independent formulation of the theory of evolution of species by Charles Darwin and Alfred Russel Wallace.
Merton contrasted a "multiple" with a "singleton" — a discovery that has been made uniquely by a single scientist or group of scientists working together. He believed that it is multiple discoveries, rather than unique ones, that represent the common pattern in science.
Multiple discoveries in the history of science provide evidence for evolutionary models of science and technology, such as memetics (the study of self-replicating units of culture), evolutionary epistemology (which applies the concepts of biological evolution to study of the growth of human knowledge), and cultural selection theory (which studies sociological and cultural evolution in a Darwinian manner). A recombinant-DNA-inspired "paradigm of paradigms", describing a mechanism of "recombinant conceptualization", predicates that a new concept arises through the crossing of pre-existing concepts and facts. This is what is meant when one says that a scientist, scholar, or artist has been "influenced by" another — etymologically, that a concept of the latter's has "flowed into" the mind of the former.
The phenomenon of multiple independent discoveries and inventions can be viewed as a consequence of Bolesław Prus' three laws of gradualness, dependence, and combination (see "Discoveries and inventions", above). The first two laws may, in turn, be seen as corollaries to the third law, since the laws of gradualness and dependence imply the impossibility of certain scientific or technological advances pending the availability of certain theories, facts, or technologies that must be combined to produce a given scientific or technological advance.
=== Technology ===
Technology – the application of discoveries to practical matters – showed a remarkable acceleration in what economist Robert J. Gordon has identified as "the special century" that spanned the period up to 1970. By then, he writes, all the key technologies of modern life were in place: sanitation, electricity, mechanized agriculture, highways, air travel, telecommunications, and the like. The one signature technology of the 21st century has been the iPhone. Meanwhile, a long list of much-publicized potential major technologies remain in the prototype phase, including self-driving cars, flying cars, augmented-reality glasses, gene therapy, and nuclear fusion. An urgent goal for the 21st century, writes Gordon, is to undo some of the consequences of the last great technology boom by developing affordable zero- and negative-emissions technologies.
Technology is the sum of techniques, skills, methods, and processes used in the production of goods or services or in the accomplishment of objectives, such as scientific investigation. Paradoxically, technology, so conceived, has sometimes been noted to take primacy over the ends themselves – even to their detriment. Laura Grego and David Wright, writing in 2019 in Scientific American, observe that "Current U.S. missile defense plans are being driven largely by technology, politics and fear. Missile defenses will not allow us to escape our vulnerability to nuclear weapons. Instead large-scale developments will create barriers to taking real steps toward reducing nuclear risks—by blocking further cuts in nuclear arsenals and potentially spurring new deployments."
== Psychology of science ==
=== Habitus ===
Yale University physicist-astronomer Priyamvada Natarajan, writing of the virtually-simultaneous 1846 discovery of the planet Neptune by Urbain Le Verrier and John Couch Adams (after other astronomers, as early as Galileo Galilei in 1612, had unwittingly observed the planet), comments:
The episode is but one of many that proves science is not a dispassionate, neutral, and objective endeavor but rather one in which the violent clash of ideas and personal ambitions often combines with serendipity to propel new discoveries.
=== Nonconformance ===
A practical question concerns the traits that enable some individuals to achieve extraordinary results in their fields of work—and how such creativity can be fostered. Melissa Schilling, a student of innovation strategy, has identified some traits shared by eight major innovators in natural science or technology: Benjamin Franklin (1706–90), Thomas Edison (1847–1931), Nikola Tesla (1856–1943), Maria Skłodowska Curie (1867–1934), Dean Kamen (born 1951), Steve Jobs (1955–2011), Albert Einstein (1879–1955), and Elon Musk (born 1971).
Schilling chose innovators in natural science and technology rather than in other fields because she found much more consensus about important contributions to natural science and technology than, for example, to art or music. She further limited the set to individuals associated with multiple innovations. "When an individual is associated with only a single major invention, it is much harder to know whether the invention was caused by the inventor's personal characteristics or by simply being at the right place at the right time."
The eight individuals were all extremely intelligent, but "that is not enough to make someone a serial breakthrough innovator." Nearly all these innovators showed very high levels of social detachment, or separateness (a notable exception being Benjamin Franklin). "Their isolation meant that they were less exposed to dominant ideas and norms, and their sense of not belonging meant that even when exposed to dominant ideas and norms, they were often less inclined to adopt them." From an early age, they had all shown extreme faith in their ability to overcome obstacles—what psychology calls "self-efficacy".
"Most [of them, writes Schilling] were driven by idealism, a superordinate goal that was more important than their own comfort, reputation, or families. Nikola Tesla wanted to free mankind from labor through unlimited free energy and to achieve international peace through global communication. Elon Musk wants to solve the world's energy problems and colonize Mars. Benjamin Franklin was seeking greater social harmony and productivity through the ideals of egalitarianism, tolerance, industriousness, temperance, and charity. Marie Curie had been inspired by Polish Positivism's argument that Poland, which was under Tsarist Russian rule, could be preserved only through the pursuit of education and technological advance by all Poles—including women."
Most of the innovators also worked hard and tirelessly because they found work extremely rewarding. Some had an extremely high need for achievement. Many also appeared to find work autotelic—rewarding for its own sake. A surprisingly large portion of the breakthrough innovators have been autodidacts—self-taught persons—and excelled much more outside the classroom than inside.
"Almost all breakthrough innovation," writes Schilling, "starts with an unusual idea or with beliefs that break with conventional wisdom.... However, creative ideas alone are almost never enough. Many people have creative ideas, even brilliant ones. But usually we lack the time, knowledge, money, or motivation to act on those ideas." It is generally hard to get others' help in implementing original ideas because the ideas are often initially hard for others to understand and value. Thus each of Schilling's breakthrough innovators showed extraordinary effort and persistence. Even so, writes Schilling, "being at the right place at the right time still matter[ed]."
==== Lichenology ====
When Swiss botanist Simon Schwendener discovered in the 1860s that lichens were a symbiotic partnership between a fungus and an alga, his finding at first met with resistance from the scientific community. After his discovery that the fungus—which cannot make its own food—provides the lichen's structure, while the alga's contribution is its photosynthetic production of food, it was found that in some lichens a cyanobacterium provides the food—and a handful of lichen species contain both an alga and a cyanobacterium, along with the fungus.
A self-taught naturalist, Trevor Goward, has helped create a paradigm shift in the study of lichens and perhaps of all life-forms by doing something that people did in pre-scientific times: going out into nature and closely observing. His essays about lichens were largely ignored by most researchers because Goward has no scientific degrees and because some of his radical ideas are not supported by rigorous data.
When Goward told Toby Spribille, who at the time lacked a high-school education, about some of his lichenological ideas, Goward recalls, "He said I was delusional." Ultimately Spribille passed a high-school equivalency examination, obtained a Ph.D. in lichenology at the University of Graz in Austria, and became an assistant professor of the ecology and evolution of symbiosis at the University of Alberta. In July 2016 Spribille and his co-authors published a ground-breaking paper in Science revealing that many lichens contain a second fungus.
Spribille credits Goward with having "a huge influence on my thinking. [His essays] gave me license to think about lichens in [an unorthodox way] and freed me to see the patterns I worked out in Bryoria with my co-authors." Even so, "one of the most difficult things was allowing myself to have an open mind to the idea that 150 years of literature may have entirely missed the theoretical possibility that there would be more than one fungal partner in the lichen symbiosis." Spribille says that academia's emphasis on the canon of what others have established as important is inherently limiting.
=== Leadership ===
Contrary to previous studies indicating that higher intelligence makes for better leaders in various fields of endeavor, later research suggests that, at a certain point, a higher IQ can be viewed as harmful. Decades ago, psychologist Dean Simonton suggested that brilliant leaders' words may go over people's heads, their solutions could be more complicated to implement, and followers might find it harder to relate to them. At last, in the July 2017 Journal of Applied Psychology, he and two colleagues published the results of actual tests of the hypothesis.
Studied were 379 men and women business leaders in 30 countries, including the fields of banking, retail, and technology. The managers took IQ tests—an imperfect but robust predictor of performance in many areas—and each was rated on leadership style and effectiveness by an average of 8 co-workers. IQ correlated positively with ratings of leadership effectiveness, strategy formation, vision, and several other characteristics—up to a point. The ratings peaked at an IQ of about 120, which is higher than some 80% of office workers. Beyond that, the ratings declined. The researchers suggested that the ideal IQ could be higher or lower in various fields, depending on whether technical or social skills are more valued in a given work culture.
Psychologist Paul Sackett, not involved in the research, comments: "To me, the right interpretation of the work would be that it highlights a need to understand what high-IQ leaders do that leads to lower perceptions by followers. The wrong interpretation would be,'Don't hire high-IQ leaders.'" The study's lead author, psychologist John Antonakis, suggests that leaders should use their intelligence to generate creative metaphors that will persuade and inspire others. "I think the only way a smart person can signal their intelligence appropriately and still connect with the people," says Antonakis, "is to speak in charismatic ways."
== Sociology of science ==
=== Specialization ===
Academic specialization produces great benefits for science and technology by focusing effort on discrete disciplines. But excessively narrow specialization can act as a roadblock to productive collaboration between traditional disciplines.
In 2017, in Manhattan, James Harris Simons, a noted mathematician and retired founder of one of the world's largest hedge funds, inaugurated the Flatiron Institute, a nonprofit enterprise whose goal is to apply his hedge fund's analytical strategies to projects dedicated to expanding knowledge and helping humanity. He has established computational divisions for research in astrophysics, biology, and quantum physics, and an interdisciplinary division for climate modelling that interfaces geology, oceanography, atmospheric science, biology, and climatology.
The latter, fourth Flatiron Institute division was inspired by a 2017 presentation to the institute's leadership by John Grotzinger, a "bio-geoscientist" from the California Institute of Technology, who explained the challenges of climate modelling. Grotzinger was a specialist in historical climate change—specifically, what had caused the great Permian extinction, during which virtually all species died. To properly assess this cataclysm, one had to understand both the rock record and the ocean's composition, but geologists did not interact much with physical oceanographers. Grotzinger's own best collaboration had resulted from a fortuitous lunch with an oceanographer. Climate modelling was an intrinsically difficult problem made worse by the information silos of academia. "If you had it all under one umbrella... it could result [much sooner] in a major breakthrough." Simons and his team found Grotzinger's presentation compelling, and the Flatiron Institute decided to establish its fourth and final computational division.
=== Mentoring ===
Sociologist Harriet Zuckerman, in her 1977 study of natural-science Nobel laureates in the United States, was struck by the fact that more than half (48) of the 92 laureates who did their prize-winning research in the U.S. by 1972 had worked either as students, postdoctorates, or junior collaborators under older Nobel laureates. Furthermore, those 48 future laureates had worked under a total of 71 laureate masters.
Social viscosity ensures that not every qualified novice scientist attains access to the most productive centers of scientific thought. Nevertheless, writes Zuckerman, "To some extent, students of promise can choose masters with whom to work and masters can choose among the cohorts of students who present themselves for study. This process of bilateral assortative selection is conspicuously at work among the ultra-elite of science. Actual and prospective members of that elite select their scientist parents and therewith their scientist ancestors just as later they select their scientist progeny and therewith their scientist descendants."
Zuckerman writes: "[T]he lines of elite apprentices to elite masters who had themselves been elite apprentices, and so on indefinitely, often reach far back into the history of science, long before 1900, when [Alfred] Nobel's will inaugurated what now amounts to the International Academy of Sciences. As an example of the many long historical chains of elite masters and apprentices, consider the German-born English laureate Hans Krebs (1953), who traces his scientific lineage [...] back through his master, the 1931 laureate Otto Warburg. Warburg had studied with Emil Fis[c]her [1852–1919], recipient of a prize in 1902 at the age of 50, three years before it was awarded [in 1905] to his teacher, Adolf von Baeyer [1835–1917], at age 70. This lineage of four Nobel masters and apprentices has its own pre-Nobelian antecedents. Von Baeyer had been the apprentice of F[riedrich] A[ugust] Kekulé [1829–1896], whose ideas of structural formulae revolutionized organic chemistry and who is perhaps best known for the often retold story about his having hit upon the ring structure of benzene in a dream (1865). Kekulé himself had been trained by the great organic chemist Justus von Liebig (1803–1873), who had studied at the Sorbonne with the master J[oseph] L[ouis] Gay-Lussac (1778–1850), himself once apprenticed to Claude Louis Berthollet (1748–1822). Among his many institutional and cognitive accomplishments, Berthollet helped found the École Polytechnique, served as science advisor to Napoleon in Egypt, and, more significant for our purposes here, worked with [Antoine] Lavoisier [1743–1794] to revise the standard system of chemical nomenclature."
=== Collaboration ===
Sociologist Michael P. Farrell has studied close creative groups and writes: "Most of the fragile insights that laid the foundation of a new vision emerged not when the whole group was together, and not when members worked alone, but when they collaborated and repsonded to one another in pairs." François Jacob, who, with Jacques Monod, pioneered the study of gene regulation, notes that by the mid-20th century, most research in molecular biology was conducted by twosomes. "Two are better than one for dreaming up theories and constructing models," writes Jacob. "For with two minds working on a problem, ideas fly thicker and faster. They are bounced from partner to partner.... And in the process, illusions are sooner nipped in the bud." As of 2018, in the previous 35 years, some half of Nobel Prizes in Physiology or Medicine had gone to scientific partnerships. James Somers describes a remarkable partnership between Google's top software engineers, Jeff Dean and Sanjay Ghemawat.
Twosome collaborations have also been prominent in creative endeavors outside the natural sciences and technology; examples are Claude Monet's and Pierre-Auguste Renoir's 1869 joint creation of Impressionism, Pablo Picasso's and Georges Braque's six-year collaborative creation of Cubism, and John Lennon's and Paul McCartney's collaborations on Beatles songs. "Everyone", writes James Somers, "falls into creative ruts, but two people rarely do so at the same time."
The same point was made by Francis Crick, member of a famous scientific duo, Francis Crick and James Watson, who together discovered the structure of the genetic material, DNA. At the end of a PBS television documentary on James Watson, in a video clipping Crick explains to Watson that their collaboration had been crucial to their discovery because, when one of them was wrong, the other would set him straight.
=== Politics ===
==== Big Science ====
What has been dubbed "Big Science" emerged from the United States' World War II Manhattan Project that produced the world's first nuclear weapons; and Big Science has since been associated with physics, which requires massive particle accelerators. In biology, Big Science debuted in 1990 with the Human Genome Project to sequence human DNA. In 2013 neuroscience became a Big Science domain when the U.S. announced a BRAIN Initiative and the European Union announced a Human Brain Project. Major new brain-research initiatives were also announced by Israel, Canada, Australia, New Zealand, Japan, and China.
Earlier successful Big Science projects had habituated politicians, mass media, and the public to view Big Science programs with sometimes uncritical favor.
The U.S.'s BRAIN Initiative was inspired by concern about the spread and cost of mental disorders and by excitement about new brain-manipulation technologies such as optogenetics. After some early false starts, the U.S. National Institute of Mental Health let the country's brain scientists define the BRAIN Initiative, and this led to an ambitious interdisciplinary program to develop new technological tools to better monitor, measure, and simulate the brain. Competition in research was ensured by the National Institute of Mental Health's peer-review process.
In the European Union, the European Commission's Human Brain Project got off to a rockier start because political and economic considerations obscured questions concerning the feasibility of the Project's initial scientific program, based principally on computer modeling of neural circuits. Four years earlier, in 2009, fearing that the European Union would fall further behind the U.S. in computer and other technologies, the European Union had begun creating a competition for Big Science projects, and the initial program for the Human Brain Project seemed a good fit for a European program that might take a lead in advanced and emerging technologies. Only in 2015, after over 800 European neuroscientists threatened to boycott the European-wide collaboration, were changes introduced into the Human Brain Project, supplanting many of the original political and economic considerations with scientific ones.
As of 2019, the European Union's Human Brain Project had not lived up to its extravagant promise.
=== Funding ===
==== Government funding ====
Nathan Myhrvold, former Microsoft chief technology officer and founder of Microsoft Research, argues that the funding of basic science cannot be left to the private sector—that "without government resources, basic science will grind to a halt." He notes that Albert Einstein's general theory of relativity, published in 1915, did not spring full-blown from his brain in a eureka moment; he worked at it for years—finally driven to complete it by a rivalry with mathematician David Hilbert. The history of almost any iconic scientific discovery or technological invention—the lightbulb, the transistor, DNA, even the Internet—shows that the famous names credited with the breakthrough "were only a few steps ahead of a pack of competitors." Some writers and elected officials have used this phenomenon of "parallel innovation" to argue against public financing of basic research: government, they assert, should leave it to companies to finance the research they need.
Myhrvold writes that such arguments are dangerously wrong: without government support, most basic scientific research will never happen. "This is most clearly true for the kind of pure research that has delivered... great intellectual benefits but no profits, such as the work that brought us the Higgs boson, or the understanding that a supermassive black hole sits at the center of the Milky Way, or the discovery of methane seas on the surface of Saturn's moon Titan. Company research laboratories used to do this kind of work: experimental evidence for the Big Bang was discovered at AT&T's Bell Labs, resulting in a Nobel Prize. Now those days are gone."
Even in applied fields such as materials science and computer science, writes Myhrvold, "companies now understand that basic research is a form of charity—so they avoid it." Bell Labs scientists created the transistor, but that invention earned billions for Intel and Microsoft. Xerox PARC engineers invented the modern graphical user interface, but Apple and Microsoft profited most. IBM researchers pioneered the use of giant magnetoresistance to boost hard-disk capacity but soon lost the disk-drive business to Seagate and Western Digital.
Company researchers now have to focus narrowly on innovations that can quickly bring revenue; otherwise the research budget could not be justified to the company's investors. "Those who believe profit-driven companies will altruistically pay for basic science that has wide-ranging benefits—but mostly to others and not for a generation—are naive.... If government were to leave it to the private sector to pay for basic research, most science would come to a screeching halt. What research survived would be done largely in secret, for fear of handing the next big thing to a rival."
Governmental investment is equally vital in the field of biological research. According to William A. Haseltine, a former Harvard Medical School professor and founder of that university's cancer and HIV / AIDS research departments, early efforts to control the COVID-19 pandemic were hampered by governments and industry everywhere having "pulled the plug on coronavirus research funding in 2006 after the first SARS [...] pandemic faded away and again in the years immediately following the MERS [outbreak, also caused by a coronavirus] when it seemed to be controllable. [...] The development of promising anti-SARS and MERS drugs, which might have been active against SARS–CoV-2 [in the Covid-19 pandemic] as well, was left unfinished for lack of money." Haseltine continues:
We learned from the HIV crisis that it was important to have research pipelines already established. [It was c]ancer research in the 1950s, 1960s and 1970s [that] built a foundation for HIV / Aids studies. [During those decades t]he government [had] responded to public concerns, sharply increasing federal funding of cancer research [...]. These efforts [had] culminated in Congress's approval of President Richard Nixon's National Cancer Act in 1971. This [had] built the science we needed to identify and understand HIV in the 1980s, although of course no one knew that payoff was coming.
In the 1980s the Reagan administration did not want to talk about AIDS or commit much funding to HIV research. [But o]nce the news broke that actor Rock Hudson was seriously ill with AIDS, [...] $320 million [were added to] the fiscal 1986 budget for AIDS research. [...] I helped [...] design this first congressionally funded AIDS research program with Anthony Fauci, the doctor now leading [the U.S.] fight against COVID-19. [...]
[The] tool set for virus and pharmaceutical research has improved enormously in the past 36 years since HIV was discovered. What used to take five or 10 years in the 1980s and 1990s in many cases now can be done in five or 10 months. We can rapidly identify and synthesize chemicals to predict which drugs will be effective. We can do cryoelectron microscopy to probe virus structures and simulate molecule-by-molecule interactions in a matter of weeks – something that used to take years. The lesson is to never let down our guard when it comes to funding antiviral research. We would have no hope of beating COVID-19 if it were not for the molecular biology gains we made during earlier virus battles. What we learn this time around will help us [...] during the next pandemic, but we must keep the money coming.
==== Private funding ====
A complementary perspective on the funding of scientific research is given by D.T. Max, writing about the Flatiron Institute, a computational center set up in 2017 in Manhattan to provide scientists with mathematical assistance. The Flatiron Institute was established by James Harris Simons, a mathematician who had used mathematical algorithms to make himself a Wall Street billionaire. The institute has three computational divisions dedicated respectively to astrophysics, biology, and quantum physics, and is working on a fourth division for climate modeling that will involve interfaces of geology, oceanography, atmospheric science, biology, and climatology.
The Flatiron Institute is part of a trend in the sciences toward privately funded research. In the United States, basic science has traditionally been financed by universities or the government, but private institutes are often faster and more focused. Since the 1990s, when Silicon Valley began producing billionaires, private institutes have sprung up across the U.S. In 1997 Larry Ellison launched the Ellison Medical Foundation to study the biology of aging. In 2003 Paul Allen founded the Allen Institute for Brain Science. In 2010 Eric Schmidt founded the Schmidt Ocean Institute.
These institutes have done much good, partly by providing alternatives to more rigid systems. But private foundations also have liabilities. Wealthy benefactors tend to direct their funding toward their personal enthusiasms. And foundations are not taxed; much of the money that supports them would otherwise have gone to the government.
==== Funding biases ====
John P.A. Ioannidis, of Stanford University Medical School, writes that "There is increasing evidence that some of the ways we conduct, evaluate, report and disseminate research are miserably ineffective. A series of papers in 2014 in The Lancet... estimated that 85 percent of investment in biomedical research is wasted. Many other disciplines have similar problems." Ioannidis identifies some science-funding biases that undermine the efficiency of the scientific enterprise, and proposes solutions:
Funding too few scientists: "[M]ajor success [in scientific research] is largely the result of luck, as well as hard work. The investigators currently enjoying huge funding are not necessarily genuine superstars; they may simply be the best connected." Solutions: "Use a lottery to decide which grant applications to fund (perhaps after they pass a basic review).... Shift... funds from senior people to younger researchers..."
No reward for transparency: "Many scientific protocols, analysis methods, computational processes and data are opaque. [M]any top findings cannot be reproduced. That is the case for two out of three top psychology papers, one out of three top papers in experimental economics and more than 75 percent of top papers identifying new cancer drug targets. [S]cientists are not rewarded for sharing their techniques." Solutions: "Create better infrastructure for enabling transparency, openness and sharing. Make transparency a prerequisite for funding. [P]referentially hire, promote or tenure... champions of transparency."
No encouragement for replication: Replication is indispensable to the scientific method. Yet, under pressure to produce new discoveries, researchers tend to have little incentive, and much counterincentive, to try replicating results of previous studies. Solutions: "Funding agencies must pay for replication studies. Scientists' advancement should be based not only on their discoveries but also on their replication track record."
No funding for young scientists: "Werner Heisenberg, Albert Einstein, Paul Dirac and Wolfgang Pauli made their top contributions in their mid-20s." But the average age of biomedical scientists receiving their first substantial grant is 46. The average age for a full professor in the U.S. is 55. Solutions: "A larger proportion of funding should be earmarked for young investigators. Universities should try to shift the aging distribution of their faculty by hiring more young investigators."
Biased funding sources: "Most funding for research and development in the U.S. comes not from the government but from private, for-profit sources, raising unavoidable conflicts of interest and pressure to deliver results favorable to the sponsor." Solutions: "Restrict or even ban funding that has overt conflicts of interest. Journals should not accept research with such conflicts. For less conspicuous conflicts, at a minimum ensure transparent and thorough disclosure."
Funding the wrong fields: "Well-funded fields attract more scientists to work for them, which increases their lobbying reach, fueling a vicious circle. Some entrenched fields absorb enormous funding even though they have clearly demonstrated limited yield or uncorrectable flaws." Solutions: "Independent, impartial assessment of output is necessary for lavishly funded fields. More funds should be earmarked for new fields and fields that are high risk. Researchers should be encouraged to switch fields, whereas currently they are incentivized to focus in one area."
Not spending enough: The U.S. military budget ($886 billion) is 24 times the budget of the National Institutes of Health ($37 billion). "Investment in science benefits society at large, yet attempts to convince the public often make matters worse when otherwise well-intentioned science leaders promise the impossible, such as promptly eliminating all cancer or Alzheimer's disease." Solutions: "We need to communicate how science funding is used by making the process of science clearer, including the number of scientists it takes to make major accomplishments.... We would also make a more convincing case for science if we could show that we do work hard on improving how we run it."
Rewarding big spenders: "Hiring, promotion and tenure decisions primarily rest on a researcher's ability to secure high levels of funding. But the expense of a project does not necessarily correlate with its importance. Such reward structures select mostly for politically savvy managers who know how to absorb money." Solutions: "We should reward scientists for high-quality work, reproducibility and social value rather than for securing funding. Excellent research can be done with little to no funding other than protected time. Institutions should provide this time and respect scientists who can do great work without wasting tons of money."
No funding for high-risk ideas: "The pressure that taxpayer money be 'well spent' leads government funders to back projects most likely to pay off with a positive result, even if riskier projects might lead to more important, but less assured, advances. Industry also avoids investing in high-risk projects... Innovation is extremely difficult, if not impossible, to predict..." Solutions: "Fund excellent scientists rather than projects and give them freedom to pursue research avenues as they see fit. Some institutions such as Howard Hughes Medical Institute already use this model with success." It must be communicated to the public and to policy-makers that science is a cumulative investment, that no one can know in advance which projects will succeed, and that success must be judged on the total agenda, not on a single experiment or result.
Lack of good data: "There is relatively limited evidence about which scientific practices work best. We need more research on research ('meta-research') to understand how to best perform, evaluate, review, disseminate and reward science." Solutions: "We should invest in studying how to get the best science and how to choose and reward the best scientists."
=== Diversity ===
Naomi Oreskes, professor of the history of science at Harvard University, writes about the desirability of diversity in the backgrounds of scientists.
The history of science is rife with [...] cases of misogyny, prejudice and bias. For centuries biologists promoted false theories of female inferiority, and scientific institutions typically barred women's participation. Historian of science [...] Margaret Rossiter has documented how, in the mid-19th century, female scientists created their own scientific societies to compensate for their male colleagues' refusal to acknowledge their work. Sharon Bertsch McGrayne filled an entire volume with the stories of women who should have been awarded the Nobel Prize for work that they did in collaboration with male colleagues – or, worse, that they had stolen by them. [...] Racial bias has been at least as pernicious as gender bias; it was scientists, after all, who codified the concept of race as a biological category that was not simply descriptive but also hierarchical.
[...] [C]ognitive science shows that humans are prone to bias, misperception, motivated reasoning and other intellectual pitfalls. Because reasoning is slow and difficult, we rely on heuristics – intellectual shortcuts that often work but sometimes fail spectacularly. (Believing that men are, in general, better than women in math is one tiring example.) [...]
[...] Science is a collective effort, and it works best when scientific communities are diverse. [H]eterogeneous communities are more likely than homogeneous ones to be able to identify blind spots and correct them. Science does not correct itself; scientists correct one another through critical interrogation. And that means being willing to interrogate not just claims about the external world but claims about [scientists'] own practices and processes as well.
=== Sexual bias ===
Claire Pomeroy, president of the Lasker Foundation, which is dedicated to advancing medical research, points out that women scientists continue to be subjected to discrimination in professional advancement.
Though the percentage of doctorates awarded to women in life sciences in the United States increased from 15 to 52 percent between 1969 and 2009, only a third of assistant professors and less than a fifth of full professors in biology-related fields in 2009 were women. Women make up only 15 percent of permanent department chairs in medical schools and barely 16 percent of medical-school deans.
The problem is a culture of unconscious bias that leaves many women feeling demoralized and marginalized. In one study, science faculty were given identical résumés in which the names and genders of two applicants were interchanged; both male and female faculty judged the male applicant to be more competent and offered him a higher salary.
Unconscious bias also appears as "microassaults" against women scientists: purportedly insignificant sexist jokes and insults that accumulate over the years and undermine confidence and ambition. Writes Claire Pomeroy: "Each time it is assumed that the only woman in the lab group will play the role of recording secretary, each time a research plan becomes finalized in the men's lavatory between conference sessions, each time a woman is not invited to go out for a beer after the plenary lecture to talk shop, the damage is reinforced."
"When I speak to groups of women scientists," writes Pomeroy, "I often ask them if they have ever been in a meeting where they made a recommendation, had it ignored, and then heard a man receive praise and support for making the same point a few minutes later. Each time the majority of women in the audience raise their hands. Microassaults are especially damaging when they come from a high-school science teacher, college mentor, university dean or a member of the scientific elite who has been awarded a prestigious prize—the very people who should be inspiring and supporting the next generation of scientists."
=== Sexual harassment ===
Sexual harassment is more prevalent in academia than in any other social sector except the military. A June 2018 report by the National Academies of Sciences, Engineering, and Medicine states that sexual harassment hurts individuals, diminishes the pool of scientific talent, and ultimately damages the integrity of science.
Paula Johnson, co-chair of the committee that drew up the report, describes some measures for preventing sexual harassment in science. One would be to replace trainees' individual mentoring with group mentoring, and to uncouple the mentoring relationship from the trainee's financial dependence on the mentor. Another way would be to prohibit the use of confidentiality agreements in connection with harassment cases.
A novel approach to the reporting of sexual harassment, dubbed Callisto, that has been adopted by some institutions of higher education, lets aggrieved persons record experiences of sexual harassment, date-stamped, without actually formally reporting them. This program lets people see if others have recorded experiences of harassment from the same individual, and share information anonymously.
=== Deterrent stereotypes ===
Psychologist Andrei Cimpian and philosophy professor Sarah-Jane Leslie have proposed a theory to explain why American women and African-Americans are often subtly deterred from seeking to enter certain academic fields by a misplaced emphasis on genius. Cimpian and Leslie had noticed that their respective fields are similar in their substance but hold different views on what is important for success. Much more than psychologists, philosophers value a certain kind of person: the "brilliant superstar" with an exceptional mind. Psychologists are more likely to believe that the leading lights in psychology grew to achieve their positions through hard work and experience. In 2015, women accounted for less than 30% of doctorates granted in philosophy; African-Americans made up only 1% of philosophy Ph.D.s. Psychology, on the other hand, has been successful in attracting women (72% of 2015 psychology Ph.D.s) and African-Americans (6% of psychology Ph.D.s).
An early insight into these disparities was provided to Cimpian and Leslie by the work of psychologist Carol Dweck. She and her colleagues had shown that a person's beliefs about ability matter a great deal for that person's ultimate success. A person who sees talent as a stable trait is motivated to "show off this aptitude" and to avoid making mistakes. By contrast, a person who adopts a "growth mindset" sees his or her current capacity as a work in progress: for such a person, mistakes are not an indictment but a valuable signal highlighting which of their skills are in need of work. Cimpian and Leslie and their collaborators tested the hypothesis that attitudes, about "genius" and about the unacceptability of making mistakes, within various academic fields may account for the relative attractiveness of those fields for American women and African-Americans. They did so by contacting academic professionals from a wide range of disciplines and asking them whether they thought that some form of exceptional intellectual talent was required for success in their field. The answers received from almost 2,000 academics in 30 fields matched the distribution of Ph.D.s in the way that Cimpian and Leslie had expected: fields that placed more value on brilliance also conferred fewer Ph.D.s on women and African-Americans. The proportion of women and African-American Ph.D.s in psychology, for example, was higher than the parallel proportions for philosophy, mathematics, or physics.
Further investigation showed that non-academics share similar ideas of which fields require brilliance. Exposure to these ideas at home or school could discourage young members of stereotyped groups from pursuing certain careers, such as those in the natural sciences or engineering. To explore this, Cimpian and Leslie asked hundreds of five-, six-, and seven-year-old boys and girls questions that measured whether they associated being "really, really smart" (i.e., "brilliant") with their sex. The results, published in January 2017 in Science, were consistent with scientific literature on the early acquisition of sex stereotypes. Five-year-old boys and girls showed no difference in their self-assessment; but by age six, girls were less likely to think that girls are "really, really smart." The authors next introduced another group of five-, six-, and seven-year-olds to unfamiliar gamelike activities that the authors described as being "for children who are really, really smart." Comparison of boys' and girls' interest in these activities at each age showed no sex difference at age five but significantly greater interest from boys at ages six and seven—exactly the ages when stereotypes emerge.
Cimpian and Leslie conclude that, "Given current societal stereotypes, messages that portray [genius or brilliance] as singularly necessary [for academic success] may needlessly discourage talented members of stereotyped groups."
=== Academic snobbery ===
Largely as a result of his growing popularity, astronomer and science popularizer Carl Sagan, creator of the 1980 PBS TV Cosmos series, came to be ridiculed by scientist peers and failed to receive tenure at Harvard University in the 1960s and membership in the National Academy of Sciences in the 1990s. The eponymous "Sagan effect" persists: as a group, scientists still discourage individual investigators from engaging with the public unless they are already well-established senior researchers.
The operation of the Sagan effect deprives society of the full range of expertise needed to make informed decisions about complex questions, including genetic engineering, climate change, and energy alternatives. Fewer scientific voices mean fewer arguments to counter antiscience or pseudoscientific discussion. The Sagan effect also creates the false impression that science is the domain of older white men (who dominate the senior ranks), thereby tending to discourage women and minorities from considering science careers.
A number of factors contribute to the Sagan effect's durability. At the height of the Scientific Revolution in the 17th century, many researchers emulated the example of Isaac Newton, who dedicated himself to physics and mathematics and never married. These scientists were viewed as pure seekers of truth who were not distracted by more mundane concerns. Similarly, today anything that takes scientists away from their research, such as having a hobby or taking part in public debates, can undermine their credibility as researchers.
Another, more prosaic factor in the Sagan effect's persistence may be professional jealousy.
However, there appear to be some signs that engaging with the rest of society is becoming less hazardous to a career in science. So many people have social-media accounts now that becoming a public figure is not as unusual for scientists as previously. Moreover, as traditional funding sources stagnate, going public sometimes leads to new, unconventional funding streams. A few institutions such as Emory University and the Massachusetts Institute of Technology may have begun to appreciate outreach as an area of academic activity, in addition to the traditional roles of research, teaching, and administration. Exceptional among federal funding agencies, the National Science Foundation now officially favors popularization.
=== Institutional snobbery ===
Like infectious diseases, ideas in academia are contagious. But why some ideas gain great currency while equally good ones remain in relative obscurity had been unclear. A team of computer scientists has used an epidemiological model to simulate how ideas move from one academic institution to another. The model-based findings, published in October 2018, show that ideas originating at prestigious institutions cause bigger "epidemics" than equally good ideas from less prominent places. The finding reveals a big weakness in how science is done. Many highly trained people with good ideas do not obtain posts at the most prestigious institutions; much good work published by workers at less prestigious places is overlooked by other scientists and scholars because they are not paying attention.
Naomi Oreskes remarks on another drawback to deprecating public universities in favor of Ivy League schools: "In 1970 most jobs did not require a college degree. Today nearly all well-paying ones do. With the rise of artificial intelligence and the continued outsourcing of low-skilled and de-skilled jobs overseas, that trend most likely will accelerate. Those who care about equity of opportunity should pay less attention to the lucky few who get into Harvard or other highly selective private schools and more to public education, because for most Americans, the road to opportunity runs through public schools."
=== Public relations ===
Resistance, among some of the public, to accepting vaccination and the reality of climate change may be traceable partly to several decades of partisan attacks on government, leading to distrust of government science and then of science generally.
Many scientists themselves have been loth to involve themselves in public policy debates for fear of losing credibility: they worry that if they participate in public debate on a contested question, they will be viewed as biased and discounted as partisan. However, studies show that most people want to hear from scientists on matters within their areas of expertise. Research also suggests that scientists can feel comfortable offering policy advice within their fields. "The ozone story", writes Naomi Oreskes, "is a case in point: no one knew better than ozone scientists about the cause of the dangerous hole and therefore what needed to be done to fix it."
Oreskes, however, identifies a factor that does "turn off" the public: scientists' frequent use of jargon – of expressions that tend to be misinterpreted by, or incomprehensible to, laypersons.
In climatological parlance, "positive feedback" refers to amplifying feedback loops, such as the ice-albedo feedback. ("Albedo", another piece of jargon, simply means "reflectivity".) The positive loop in question develops when global warming causes Arctic ice to melt, exposing water that is darker and reflects less of the sun's warming rays, leading to more warming, which leads to more melting... and so on. In climatology, such positive feedback is a bad thing; but for most laypersons, "it conjures reassuring images, such as receiving praise from your boss.".
When astronomers say "metals," they mean any element heavier than helium, which includes oxygen and nitrogen, a usage that is massively confusing not just to laypersons but also to chemists. [To astronomers] [t]he Big Dipper isn't a constellation [...] it is an "asterism" [...] In AI, there is machine "intelligence," which isn't intelligence at all but something more like "machine capability." In ecology, there are "ecosystem services," which you might reasonably think refers to companies that clean up oil spills, but it is [actually] ecological jargon for all the good things that the natural world does for us. [T]hen there's [...] the theory of "communication accommodation," which means speaking so that the listener can understand.
=== Publish or perish ===
"[R]esearchers," writes Naomi Oreskes, "are often judged more by the quantity of their output than its quality. Universities [emphasize] metrics such as the numbers of published papers and citations when they make hiring, tenure and promotion decisions."
When – for a number of possible reasons – publication in legitimate peer-reviewed journals is not feasible, this often creates a perverse incentive to publish in "predatory journals", which do not uphold scientific standards. Some 8,000 such journals publish 420,000 papers annually – nearly a fifth of the scientific community's annual output of 2.5 million papers. The papers published in a predatory journal are listed in scientific databases alongside legitimate journals, making it hard to discern the difference.
One reason why some scientists publish in predatory journals is that prestigious scientific journals may charge scientists thousands of dollars for publishing, whereas a predatory journal typically charges less than $200. (Hence authors of papers in the predatory journals are disproportionately located in less wealthy countries and institutions.)
Publishing in predatory journals can be life-threatening when physicians and patients accept spurious claims about medical treatments; and invalid studies can wrongly influence public policy. More such predatory journals are appearing every year. In 2008 Jeffrey Beall, a University of Colorado librarian, developed a list of predatory journals which he updated for several years.
Naomi Oreskes argues that, "[t]o put an end to predatory practices, universities and other research institutions need to find ways to correct the incentives that lead scholars to prioritize publication quantity... Setting a maximum limit on the number of articles that hiring or funding committees can consider might help... as could placing less importance on the number of citations an author gets. After all, the purpose of science is not merely to produce papers. It is to produce papers that tell us something truthful and meaningful about the world."
==== Data fabrication ====
The perverse incentive to "publish or perish" is often facilitated by the fabrication of data. A classic example is the identical-twin-studies results of Cyril Burt, which – soon after Burt's death – were found to have been based on fabricated data.
Writes Gideon Lewish-Kraus:
"One of the confounding things about the social sciences is that observational evidence can produce only correlations. [For example, t]o what extent is dishonesty [which is the subject of a number of social-science studies] a matter of character, and to what extent a matter of situation? Research misconduct is sometimes explained away by incentives – the publishing requirements for the job market, or the acclaim that can lead to consulting fees and Davos appearances. [...] The differences between p-hacking and fraud is one of degree. And once it becomes customary within a field to inflate results, the field selects for researchers inclined to do so."
Joe Simmons, a behavioral-science professor, writes:
"[A] field cannot reward truth if it does not or cannot decipher it, so it rewards other things instead. Interestingness. Novelty. Speed. Impact. Fantasy. And it effectively punishes the opposite. Intuitive Findings. Incremental Progress. Care. Curiosity. Reality."
==== Accelerating science ====
Harvard University historian of science Naomi Oreskes writes that a theme at the 2024 World Economic Forum in Davos, Switzerland, was a "perceived need to 'accelerate breakthroughs in research and technology.'"
"[R]ecent years", however, writes Oreskes, "[have] seen important papers, written by prominent scientists and published in prestigious journals, retracted because of questionable data or methods." For example, the Davos meeting took place after the resignations – over questionably reliable academic papers – in 2023 of Stanford University president Marc Tessier-Lavigne and, in 2024, of Harvard University president Claudine Gay. "In one interesting case, Frances H. Arnold of the California Institute of Technology, who shared the 2018 Nobel Prize in Chemistry, voluntarily retracted a paper when her lab was unable to replicate her results – but after the paper had been published." Such incidents, suggests Oreskes, are likely to erode public trust in science and in experts generally.
Academics at leading universities in the United States and Europe are subject to perverse incentives to produce results – and lots of them – quickly. A study has put the number of papers published around 2023 by scientists and other scholars at over seven million annually, compared with less than a million in 1980. Another study found 265 authors – two-thirds in the medical and life sciences – who published on average a paper every five days.
"Good science [and scholarship take] time", writes Oreskes. "More than 50 years elapsed between the 1543 publication of Copernicus's magnum opus... and the broad scientific acceptance of the heliocentric model... Nearly a century passed between biochemist Friedrich Miescher's identification of the DNA molecule and suggestion that it might be involved in inheritance and the elucidation of its double-helix structure in the 1950s. And it took just about half a century for geologists and geophysicists to accept geophysicist Alfred Wegener's idea of continental drift."
== See also ==
== Notes ==
== References ==
== Bibliography ==
== Further reading ==
== External links ==
American Masters: Decoding Watson - PBS documentary about James Watson, co-discoverer of the structure of DNA, including interviews with Watson, his family, and colleagues. 2019-01-02.
Return to top of page. | Wikipedia/Logology_(science) |
Model-dependent realism is a view of scientific inquiry that focuses on the role of scientific models of phenomena. It claims reality should be interpreted based upon these models, and where several models overlap in describing a particular subject, multiple, equally valid, realities exist. It claims that it is meaningless to talk about the "true reality" of a model as we can never be absolutely certain of anything. The only meaningful thing is the usefulness of the model. The term "model-dependent realism" was coined by Stephen Hawking and Leonard Mlodinow in their 2010 book The Grand Design.
== Overview ==
Model-dependent realism asserts that all we can know about "reality" consists of networks of world pictures that explain observations by connecting them by rules to concepts defined in models. Will an ultimate theory of everything be found? Hawking and Mlodinow suggest it is unclear:
In the history of science we have discovered a sequence of better and better theories or models, from Plato to the classical theory of Newton to modern quantum theories. It is natural to ask: Will this sequence eventually reach an end point, an ultimate theory of the universe, that will include all forces and predict every observation we can make, or will we continue forever finding better theories, but never one that cannot be improved upon? We do not yet have a definitive answer to this question...
A world picture consists of the combination of a set of observations accompanied by a conceptual model and by rules connecting the model concepts to the observations. Different world pictures that describe particular data equally well all have equal claims to be valid. There is no requirement that a world picture be unique, or even that the data selected include all available observations. The universe of all observations at present is covered by a network of overlapping world pictures and, where overlap occurs; multiple, equally valid, world pictures exist. At present, science requires multiple models to encompass existing observations:
Like the overlapping maps in a Mercator projection, where the ranges of different versions overlap, they predict the same phenomena. But just as there is no flat map that is a good representation of the earth's entire surface, there is no single theory that is a good representation of observations in all situations Where several models are found for the same phenomena, no single model is preferable to the others within that domain of overlap.
== Model selection ==
While not rejecting the idea of "reality-as-it-is-in-itself", model-dependent realism suggests that we cannot know "reality-as-it-is-in-itself", but only an approximation of it provided by the intermediary of models. The view of models in model-dependent realism also is related to the instrumentalist approach to modern science, that a concept or theory should be evaluated by how effectively it explains and predicts phenomena, as opposed to how accurately it describes objective reality (a matter possibly impossible to establish). A model is a good model if it:
Is elegant
Contains few arbitrary or adjustable elements
Agrees with and explains all existing observations
Makes detailed predictions about future observations that can disprove or falsify the model if they are not borne out.
"If the modifications needed to accommodate new observations become too baroque, it signals the need for a new model." Of course, an assessment like that is subjective, as are the other criteria. According to Hawking and Mlodinow, even very successful models in use today do not satisfy all these criteria, which are aspirational in nature.
== See also ==
== References ==
== Further reading ==
Mark Colyvan (2001). "§4.3 The role of confirmation theory". The Indispensability of Mathematics. Oxford University Press. pp. 78–79. ISBN 0198031440.
Thomas Kuhn (1977). "Chapter 13: Objectivity, value judgment, and theory choice". The Essential Tension: Selected Studies in Scientific Tradition and Change (7th ed.). University of Chicago Press. pp. 321–322. ISBN 0226458067. An on-line excerpt stating Kuhn's criteria is found here and they also are discussed by Bird, Alexander (Aug 11, 2011). "Thomas Kuhn". In Edward N. Zalta (ed.). The Stanford Encyclopedia of Philosophy (Spring 2013 Edition).
John Worrall (1990). "Scientific revolutions and scientific rationality". In C Wade Savage (ed.). Scientific theories; Volume 14 of Minnesota Studies in the Philosophy of Science. University of Minnesota Press. p. 333. ISBN 0816618011.
Daniel Williams (2011). "How Concepts of Self-Regulation Explain Human Knowledge" (PDF). The Bent of Tau Beta Pi. Tau Beta Pi.
== External links ==
Edwards, Chris. Stephen Hawking's other controversial theory: Model Dependent Realism in The Grand Design (critical essay), Skeptic (Altadena, CA), March 22, 2011 | Wikipedia/Model-dependent_realism |
Interdisciplinarity or interdisciplinary studies involves the combination of multiple academic disciplines into one activity (e.g., a research project). It draws knowledge from several fields such as sociology, anthropology, psychology, economics, etc. It is related to an interdiscipline or an interdisciplinary field, which is an organizational unit that crosses traditional boundaries between academic disciplines or schools of thought, as new needs and professions emerge. Large engineering teams are usually interdisciplinary, as a power station or mobile phone or other project requires the melding of several specialties. However, the term "interdisciplinary" is sometimes confined to academic settings.
The term interdisciplinary is applied within education and training pedagogies to describe studies that use methods and insights of several established disciplines or traditional fields of study. Interdisciplinarity involves researchers, students, and teachers in the goals of connecting and integrating several academic schools of thought, professions, or technologies—along with their specific perspectives—in the pursuit of a common task. The epidemiology of HIV/AIDS or global warming requires understanding of diverse disciplines to solve complex problems. Interdisciplinary may be applied where the subject is felt to have been neglected or even misrepresented in the traditional disciplinary structure of research institutions, for example, women's studies or ethnic area studies. Interdisciplinarity can likewise be applied to complex subjects that can only be understood by combining the perspectives of two or more fields.
The adjective interdisciplinary is most often used in educational circles when researchers from two or more disciplines pool their approaches and modify them so that they are better suited to the problem at hand, including the case of the team-taught course where students are required to understand a given subject in terms of multiple traditional disciplines. Interdisciplinary education fosters cognitive flexibility and prepares students to tackle complex, real-world problems by integrating knowledge from multiple fields. This approach emphasizes active learning, critical thinking, and problem-solving skills, equipping students with the adaptability needed in an increasingly interconnected world. For example, the subject of land use may appear differently when examined by different disciplines, for instance, biology, chemistry, economics, geography, and politics.
== Development ==
Although "interdisciplinary" and "interdisciplinarity" are frequently viewed as twentieth century terms, the concept has historical antecedents, most notably Greek philosophy. Julie Thompson Klein attests that "the roots of the concepts lie in a number of ideas that resonate through modern discourse—the ideas of a unified science, general knowledge, synthesis and the integration of knowledge", while Giles Gunn says that Greek historians and dramatists took elements from other realms of knowledge (such as medicine or philosophy) to further understand their own material. The building of Roman roads required men who understood surveying, material science, logistics and several other disciplines. Any broadminded humanist project involves interdisciplinarity, and history shows a crowd of cases, as seventeenth-century Leibniz's task to create a system of universal justice, which required linguistics, economics, management, ethics, law philosophy, politics, and even sinology.
Interdisciplinary programs sometimes arise from a shared conviction that the traditional disciplines are unable or unwilling to address an important problem. For example, social science disciplines such as anthropology and sociology paid little attention to the social analysis of technology throughout most of the twentieth century. As a result, many social scientists with interests in technology have joined science, technology and society programs, which are typically staffed by scholars drawn from numerous disciplines. They may also arise from new research developments, such as nanotechnology, which cannot be addressed without combining the approaches of two or more disciplines. Examples include quantum information processing, an amalgamation of quantum physics and computer science, and bioinformatics, combining molecular biology with computer science. Sustainable development as a research area deals with problems requiring analysis and synthesis across economic, social and environmental spheres; often an integration of multiple social and natural science disciplines. Interdisciplinary research is also key to the study of health sciences, for example in studying optimal solutions to diseases. Some institutions of higher education offer accredited degree programs in Interdisciplinary Studies.
At another level, interdisciplinarity is seen as a remedy to the harmful effects of excessive specialization and isolation in information silos. On some views, however, interdisciplinarity is entirely indebted to those who specialize in one field of study—that is, without specialists, interdisciplinarians would have no information and no leading experts to consult. Others place the focus of interdisciplinarity on the need to transcend disciplines, viewing excessive specialization as problematic both epistemologically and politically. When interdisciplinary collaboration or research results in new solutions to problems, much information is given back to the various disciplines involved. Therefore, both disciplinarians and interdisciplinarians may be seen in complementary relation to one another.
== Barriers ==
Because most participants in interdisciplinary ventures were trained in traditional disciplines, they must learn to appreciate differences of perspectives and methods. For example, a discipline that places more emphasis on quantitative rigor may produce practitioners who are more scientific in their training than others; in turn, colleagues in "softer" disciplines who may associate quantitative approaches with difficulty grasp the broader dimensions of a problem and lower rigor in theoretical and qualitative argumentation. An interdisciplinary program may not succeed if its members remain stuck in their disciplines (and in disciplinary attitudes). Those who lack experience in interdisciplinary collaborations may also not fully appreciate the intellectual contribution of colleagues from those disciplines. From the disciplinary perspective, however, much interdisciplinary work may be seen as "soft", lacking in rigor, or ideologically motivated; these beliefs place barriers in the career paths of those who choose interdisciplinary work. For example, interdisciplinary grant applications are often refereed by peer reviewers drawn from established disciplines; interdisciplinary researchers may experience difficulty getting funding for their research. In addition, untenured researchers know that, when they seek promotion and tenure, it is likely that some of the evaluators will lack commitment to interdisciplinarity. They may fear that making a commitment to interdisciplinary research will increase the risk of being denied tenure.
Interdisciplinary programs may also fail if they are not given sufficient autonomy. For example, interdisciplinary faculty are usually recruited to a joint appointment, with responsibilities in both an interdisciplinary program (such as women's studies) and a traditional discipline (such as history). If the traditional discipline makes the tenure decisions, new interdisciplinary faculty will be hesitant to commit themselves fully to interdisciplinary work. Other barriers include the generally disciplinary orientation of most scholarly journals, leading to the perception, if not the fact, that interdisciplinary research is hard to publish. In addition, since traditional budgetary practices at most universities channel resources through the disciplines, it becomes difficult to account for a given scholar or teacher's salary and time. During periods of budgetary contraction, the natural tendency to serve the primary constituency (i.e., students majoring in the traditional discipline) makes resources scarce for teaching and research comparatively far from the center of the discipline as traditionally understood. For these same reasons, the introduction of new interdisciplinary programs is often resisted because it is perceived as a competition for diminishing funds.
Due to these and other barriers, interdisciplinary research areas are strongly motivated to become disciplines themselves. If they succeed, they can establish their own research funding programs and make their own tenure and promotion decisions. In so doing, they lower the risk of entry. Examples of former interdisciplinary research areas that have become disciplines, many of them named for their parent disciplines, include neuroscience, cybernetics, biochemistry and biomedical engineering. These new fields are occasionally referred to as "interdisciplines". On the other hand, even though interdisciplinary activities are now a focus of attention for institutions promoting learning and teaching, as well as organizational and social entities concerned with education, they are practically facing complex barriers, serious challenges and criticism. The most important obstacles and challenges faced by interdisciplinary activities in the past two decades can be divided into "professional", "organizational", and "cultural" obstacles.
== Interdisciplinary studies and studies of interdisciplinarity ==
An initial distinction should be made between interdisciplinary studies, which can be found spread across the academy today, and the study of interdisciplinarity, which involves a much smaller group of researchers. The former is instantiated in thousands of research centers across the US and the world. The latter has one US organization, the Association for Interdisciplinary Studies (founded in 1979), two international organizations, the International Network of Inter- and Transdisciplinarity (founded in 2010) and the Philosophy of/as Interdisciplinarity Network (founded in 2009). The US's research institute devoted to the theory and practice of interdisciplinarity, the Center for the Study of Interdisciplinarity at the University of North Texas, was founded in 2008 but is closed as of 1 September 2014, the result of administrative decisions at the University of North Texas.
An interdisciplinary study is an academic program or process seeking to synthesize broad perspectives, knowledge, skills, interconnections, and epistemology in an educational setting. Interdisciplinary programs may be founded in order to facilitate the study of subjects which have some coherence, but which cannot be adequately understood from a single disciplinary perspective (for example, women's studies or medieval studies). More rarely, and at a more advanced level, interdisciplinarity may itself become the focus of study, in a critique of institutionalized disciplines' ways of segmenting knowledge.
In contrast, studies of interdisciplinarity raise to self-consciousness questions about how interdisciplinarity works, the nature and history of disciplinarity, and the future of knowledge in post-industrial society. Researchers at the Center for the Study of Interdisciplinarity have made the distinction between philosophy 'of' and 'as' interdisciplinarity, the former identifying a new, discrete area within philosophy that raises epistemological and metaphysical questions about the status of interdisciplinary thinking, with the latter pointing toward a philosophical practice that is sometimes called 'field philosophy'.
Perhaps the most common complaint regarding interdisciplinary programs, by supporters and detractors alike, is the lack of synthesis—that is, students are provided with multiple disciplinary perspectives but are not given effective guidance in resolving the conflicts and achieving a coherent view of the subject. Others have argued that the very idea of synthesis or integration of disciplines presupposes questionable politico-epistemic commitments. Critics of interdisciplinary programs feel that the ambition is simply unrealistic, given the knowledge and intellectual maturity of all but the exceptional undergraduate; some defenders concede the difficulty, but insist that cultivating interdisciplinarity as a habit of mind, even at that level, is both possible and essential to the education of informed and engaged citizens and leaders capable of analyzing, evaluating, and synthesizing information from multiple sources in order to render reasoned decisions.
While much has been written on the philosophy and promise of interdisciplinarity in academic programs and professional practice, social scientists are increasingly interrogating academic discourses on interdisciplinarity, as well as how interdisciplinarity actually works—and does not—in practice. Some have shown, for example, that some interdisciplinary enterprises that aim to serve society can produce deleterious outcomes for which no one can be held to account.
=== Politics of interdisciplinary studies ===
Since 1998, there has been an ascendancy in the value of interdisciplinary research and teaching and a growth in the number of bachelor's degrees awarded at U.S. universities classified as multi- or interdisciplinary studies. The number of interdisciplinary bachelor's degrees awarded annually rose from 7,000 in 1973 to 30,000 a year by 2005 according to data from the National Center of Educational Statistics (NECS). In addition, educational leaders from the Boyer Commission to Carnegie's President Vartan Gregorian to Alan I. Leshner, CEO of the American Association for the Advancement of Science have advocated for interdisciplinary rather than disciplinary approaches to problem-solving in the 21st century. This has been echoed by federal funding agencies, particularly the National Institutes of Health under the direction of Elias Zerhouni, who has advocated that grant proposals be framed more as interdisciplinary collaborative projects than single-researcher, single-discipline ones.
At the same time, many thriving longstanding bachelor's in interdisciplinary studies programs in existence for 30 or more years, have been closed down, in spite of healthy enrollment. Examples include Arizona International (formerly part of the University of Arizona), the School of Interdisciplinary Studies at Miami University, and the Department of Interdisciplinary Studies at Wayne State University; others such as the Department of Interdisciplinary Studies at Appalachian State University, and George Mason University's New Century College, have been cut back. Stuart Henry has seen this trend as part of the hegemony of the disciplines in their attempt to recolonize the experimental knowledge production of otherwise marginalized fields of inquiry. This is due to threat perceptions seemingly based on the ascendancy of interdisciplinary studies against traditional academia.
== Examples ==
Communication science: Communication studies takes up theories, models, concepts, etc. of other, independent disciplines such as sociology, political science and economics and thus decisively develops them.
Environmental science: Environmental science is an interdisciplinary earth science aimed at addressing environmental issues such as global warming and pollution, and involves the use of a wide range of scientific disciplines including geology, chemistry, physics, ecology, and oceanography. Faculty members of environmental programs often collaborate in interdisciplinary teams to solve complex global environmental problems. Those who study areas of environmental policy such as environmental law, sustainability, and environmental justice, may also seek knowledge in the environmental sciences to better develop their expertise and understanding in their fields.
Knowledge management: Knowledge management discipline exists as a cluster of divergent schools of thought under an overarching knowledge management umbrella by building on works in computer science, economics, human resource management, information systems, organizational behavior, philosophy, psychology, and strategic management.
Liberal arts education: A select realm of disciplines that cut across the humanities, social sciences, and hard sciences, initially intended to provide a well-rounded education. Several graduate programs exist in some form of Master of Arts in Liberal Studies to continue to offer this interdisciplinary course of study.
Materials science: Field that combines the scientific and engineering aspects of materials, particularly solids. It covers the design, discovery and application of new materials by incorporating elements of physics, chemistry, and engineering.
Permaculture: A holistic design science that provides a framework for making design decisions in any sphere of human endeavor, but especially in land use and resource security.
Provenance research: Interdisciplinary research comes into play when clarifying the path of artworks into public and private art collections and also in relation to human remains in natural history collections.
Sports science: Sport science is an interdisciplinary science that researches the problems and manifestations in the field of sport and movement in cooperation with a number of other sciences, such as sociology, ethics, biology, medicine, biomechanics or pedagogy.
Transport sciences: Transport sciences are a field of science that deals with the relevant problems and events of the world of transport and cooperates with the specialised legal, ecological, technical, psychological or pedagogical disciplines in working out the changes of place of people, goods, messages that characterise them.
Venture research: Venture research is an interdisciplinary research area located in the human sciences that deals with the conscious entering into and experiencing of borderline situations. For this purpose, the findings of evolutionary theory, cultural anthropology, social sciences, behavioral research, differential psychology, ethics or pedagogy are cooperatively processed and evaluated.
== Historical examples ==
There are many examples of when a particular idea, almost in the same period, arises in different disciplines. One case is the shift from the approach of focusing on "specialized segments of attention" (adopting one particular perspective), to the idea of "instant sensory awareness of the whole", an attention to the "total field", a "sense of the whole pattern, of form and function as a unity", an "integral idea of structure and configuration". This has happened in painting (with cubism), physics, poetry, communication and educational theory. According to Marshall McLuhan, this paradigm shift was due to the passage from an era shaped by mechanization, which brought sequentiality, to the era shaped by the instant speed of electricity, which brought simultaneity.
== Efforts to simplify and defend the concept ==
An article in the Social Science Journal attempts to provide a simple, common-sense, definition of interdisciplinarity, bypassing the difficulties of defining that concept and obviating the need for such related concepts as transdisciplinarity, pluridisciplinarity, and multidisciplinary:
To begin with, a discipline can be conveniently defined as any comparatively self-contained and isolated domain of human experience which possesses its own community of experts. Interdisciplinarity is best seen as bringing together distinctive components of two or more disciplines. In academic discourse, interdisciplinarity typically applies to four realms: knowledge, research, education, and theory. Interdisciplinary knowledge involves familiarity with components of two or more disciplines. Interdisciplinary research combines components of two or more disciplines in the search or creation of new knowledge, operations, or artistic expressions. Interdisciplinary education merges components of two or more disciplines in a single program of instruction. Interdisciplinary theory takes interdisciplinary knowledge, research, or education as its main objects of study.
In turn, interdisciplinary richness of any two instances of knowledge, research, or education can be ranked by weighing four variables: number of disciplines involved, the "distance" between them, the novelty of any particular combination, and their extent of integration.
Interdisciplinary knowledge and research are important because:
"Creativity often requires interdisciplinary knowledge.
Immigrants often make important contributions to their new field.
Disciplinarians often commit errors which can be best detected by people familiar with two or more disciplines.
Some worthwhile topics of research fall in the interstices among the traditional disciplines.
Many intellectual, social, and practical problems require interdisciplinary approaches.
Interdisciplinary knowledge and research serve to remind us of the unity-of-knowledge ideal.
Interdisciplinarians enjoy greater flexibility in their research.
More so than narrow disciplinarians, interdisciplinarians often treat themselves to the intellectual equivalent of traveling in new lands.
Interdisciplinarians may help breach communication gaps in the modern academy, thereby helping to mobilize its enormous intellectual resources in the cause of greater social rationality and justice.
By bridging fragmented disciplines, interdisciplinarians might play a role in the defense of academic freedom."
== Quotations ==
"The modern mind divides, specializes, thinks in categories: the Greek instinct was the opposite, to take the widest view, to see things as an organic whole [...]. The Olympic games were designed to test the arete of the whole man, not a merely specialized skill [...]. The great event was the pentathlon, if you won this, you were a man. Needless to say, the Marathon race was never heard of until modern times: the Greeks would have regarded it as a monstrosity."
"Previously, men could be divided simply into the learned and the ignorant, those more or less the one, and those more or less the other. But your specialist cannot be brought in under either of these two categories. He is not learned, for he is formally ignorant of all that does not enter into his specialty; but neither is he ignorant, because he is 'a scientist,' and 'knows' very well his own tiny portion of the universe. We shall have to say that he is a learned ignoramus, which is a very serious matter, as it implies that he is a person who is ignorant, not in the fashion of the ignorant man, but with all the petulance of one who is learned in his own special line."
"It is the custom among those who are called 'practical' men to condemn any man capable of a wide survey as a visionary: no man is thought worthy of a voice in politics unless he ignores or does not know nine-tenths of the most important relevant facts."
== See also ==
== References ==
== Further reading ==
Alderman, Harold; Chiappori, Pierre Andre; Haddad, Lawrence; Hoddinott, John (1995). "Unitary Versus Collective Models of the Household: Time to Shift the Burden of Proof?". World Bank Research Observer. 10 (1): 1–19. doi:10.1093/wbro/10.1.1.
Augsburg, Tanya (2005). Becoming Interdisciplinary: An Introduction to Interdisciplinary Studies. Kendall/Hunt.
Association for Interdisciplinary Studies
Bagchi, Amiya Kumar (1982). The Political Economy of Underdevelopment. New York: Cambridge University Press.
Bernstein, Henry (1973). "Introduction: Development and The Social Sciences". In Henry Bernstein (ed.). Underdevelopment and Development: The Third World Today. Harmondsworth: Penguin. pp. 13–30. ISBN 9780140807233.
Center for the Study of Interdisciplinarity
Centre for Interdisciplinary Research in the Arts (University of Manchester)
Chambers, Robert (2001), "Qualitative approaches: self-criticism and what can be gained from quantitative approaches", in Kanbur, Ravi (ed.), Qual–quant: qualitative and quantitative poverty appraisal - complementaries, tensions, and the way forward (PDF), Ithaca, New York: Cornell University, pp. 22–25.
Chubin, D. E. (1976). "The conceptualization of scientific specialties". The Sociological Quarterly. 17 (4): 448–476. doi:10.1111/j.1533-8525.1976.tb01715.x.
College for Interdisciplinary Studies, University of British Columbia, Vancouver, British Columbia, Canada
Callard, Felicity; Fitzgerald, Des (2015). Rethinking Interdisciplinarity across the Social Sciences and Neurosciences. Basingstoke: Palgrave Macmillan.
Davies. M.; Devlin, M. (2007). "Interdisciplinary Higher Education: Implications for Teaching and Learning" (PDF). Centre for the Study of Higher Education, The University of Melbourne. Archived from the original (PDF) on 2 December 2007. Retrieved 7 November 2007.
Frank, Roberta: "'Interdisciplitarity': The First Half Century", Issues in Integrative Studies 6 (1988): 139-151.
Frodeman, R.; Mitcham, C. (Fall 2007). "New Directions in Interdisciplinarity: Broad, Deep, and Critical". Bulletin of Science, Technology & Society. 27 (6): 506–514. doi:10.1177/0270467607308284. S2CID 145008466.
Franks, D.; Dale, P.; Hindmarsh, R.; Fellows, C.; Buckridge, M.; Cybinski, P. (2007). "Interdisciplinary foundations: reflecting on interdisciplinarity and three decades of teaching and research at Griffith University, Australia". Studies in Higher Education. 32 (2): 167–185. doi:10.1080/03075070701267228. S2CID 144173921.
Frodeman, R., Klein, J.T., and Mitcham, C. Oxford Handbook of Interdisciplinarity. Oxford University Press, 2010.
The Evergreen State College, Olympia, Washington
Gram Vikas (2007) Annual Report, p. 19.
Granovetter, Mark (1985). "Economic Action and Social Structure: The Problem of Embeddedness" (PDF). The American Journal of Sociology. 91 (3): 481–510. doi:10.1086/228311. S2CID 17242802. Archived from the original (PDF) on 2 August 2014. Retrieved 25 October 2017.
Hang Seng Centre for Cognitive Studies
Harriss, John (2002). "The Case for Cross-Disciplinary Approaches in International Development". World Development. 30 (3): 487–496. doi:10.1016/s0305-750x(01)00115-2.
Henry, Stuart (2005). "Disciplinary hegemony meets interdisciplinary ascendancy: Can interdisciplinary/integrative studies survive, and if so how?" (PDF). Issues in Integrative Studies. 23: 1–37.
Indiresan, P.V. (1990) Managing Development: Decentralisation, Geographical Socialism And Urban Replication. India: Sage
Interdisciplinary Arts Department, Columbia College Chicago
Interdisciplinarity and tenure/
Interdisciplinary Studies Project, Harvard University School of Education, Project Zero
Jackson, Cecile (2002). "Disciplining Gender?". World Development. 30 (3): 497–509. doi:10.1016/s0305-750x(01)00113-9.
Jacobs, J.A.; Frickel, S. (2009). "Interdisciplinarity: A Critical Assessment" (PDF). Annual Review of Sociology. 35: 43–65. doi:10.1146/annurev-soc-070308-115954.
Johnston, R (2003). "Integrating methodologists into teams of substantive experts" (PDF). Studies in Intelligence. 47 (1). Archived from the original (PDF) on 10 August 2006. Retrieved 8 August 2006.
Kanbur, Ravi (March 2002). "Economics, social science and development" (PDF). World Development. 30 (3): 477–486. doi:10.1016/S0305-750X(01)00117-6. hdl:1813/57796.
Kanbur, Ravi (2003), "Q-squared?: a commentry on qualitative and quantitative poverty appraisal", in Kanbur, Ravi (ed.), Q-squared, combining qualitative and quantitative methods in poverty appraisal, Delhi Bangalore: Permanent Black Distributed by Orient Longman, pp. 2–27, ISBN 9788178240534.
Kaplan Andreas (2021). Emerald (ed.). Higher Education at the Crossroads of Disruption: the University of the 21st Century.
Klein, Julie Thompson (1996) Crossing Boundaries: Knowledge, Disciplinarities, and Interdisciplinarities (University Press of Virginia)
Klein, Julie Thompson (2006) "Resources for interdisciplinary studies." Change, (Mark/April). 52–58
Klein, Julie Thompson and Thorsten Philipp (2023), "Interdisciplinarity" in Handbook Transdisciplinary Learning. Eds. Thorsten Philipp und Tobias Schmohl, 195-204. Bielefeld: transcript. doi: 10.14361/9783839463475-021.
Kleinberg, Ethan (2008). "Interdisciplinary studies at the crossroads". Liberal Education. 94 (1): 6–11.
Kockelmans, Joseph J. editor (1979) Interdisciplinarity and Higher Education, The Pennsylvania State University Press ISBN 9780271038261.
Lipton, Michael (1970). "Interdisciplinary Studies in Less Developed Countries". Journal of Development Studies. 7 (1): 5–18. doi:10.1080/00220387008421343.
Yifang Ma, Roberta Sinatra, Michael Szell, Interdisciplinarity: A Nobel Opportunity, November 2018
Gerhard Medicus [1] Gerhard Medicus: Being Human – Bridging the Gap between the Sciences of Body and Mind, Berlin 2017 VWB]
Moran, Joe. (2002). Interdisciplinarity.
Morson, Gary Saul and Morton O. Schapiro (2017). Cents and Sensibility: What Economics Can Learn from the Humanities. (Princeton University Press)
NYU Gallatin School of Individualized Study, New York, NY
Poverty Action Lab
Ravallion, Martin (2003), "Can qualitative methods help quantitative poverty", in Kanbur, Ravi (ed.), Q-squared, combining qualitative and quantitative methods in poverty appraisal, Delhi Bangalore: Permanent Black Distributed by Orient Longman, pp. 58–67, ISBN 9788178240534
Rhoten, D. (2003). A multi-method analysis of the social and technical conditions for interdisciplinary collaboration.
School of Social Ecology at the University of California, Irvine
Schuurman, F.J. (2000). "Paradigms Lost, paradigms regained? Development studies in the twenty-first century". Third World Quarterly. 21 (1): 7–20. doi:10.1080/01436590013198. S2CID 145181997.
Sen, Amartya (1999). Development as freedom. New York: Oxford University Press. ISBN 9780198297581.
Siskin, L.S. & Little, J.W. (1995). The Subjects in Question. Teachers College Press. about the departmental organization of high schools and efforts to change that.
Stiglitz, Joseph (2002) Globalisation and its Discontents, United States of America, W.W. Norton and Company
Sumner, A and M. Tribe (2008) International Development Studies: Theories and Methods in Research and Practice, London: Sage
Thorbecke, Eric. (2006) "The Evolution of the Development Doctrine, 1950–2005". UNU-WIDER Research Paper No. 2006/155. United Nations University, World Institute for Development Economics Research
Trans- & inter-disciplinary science approaches- A guide to on-line resources on integration and trans- and inter-disciplinary approaches.
Truman State University's Interdisciplinary Studies Program
Waldman, Amy (2003). "Distrust Opens the Door for Polio in India". The New York Times. Retrieved 4 November 2008.
Peter Weingart and Nico Stehr, eds. 2000. Practicing Interdisciplinarity (University of Toronto Press)
Peter Weingart; Britta Padberg (30 April 2014). University Experiments in Interdisciplinarity: Obstacles and Opportunities. transcript Verlag. ISBN 978-3-8394-2616-6.
White, Howard (2002). "Combining Quantitative and Qualitative Approaches in Poverty Analysis". World Development. 30 (3): 511–522. doi:10.1016/s0305-750x(01)00114-0.
== External links ==
Association for Interdisciplinary Studies
National Science Foundation Workshop Report: Interdisciplinary Collaboration in Innovative Science and Engineering Fields
Rethinking Interdisciplinarity online conference, organized by the Institut Nicod, CNRS, Paris [broken]
Center for the Study of Interdisciplinarity at the University of North Texas
Labyrinthe. Atelier interdisciplinaire, a journal (in French), with a special issue on La Fin des Disciplines?
Rupkatha Journal on Interdisciplinary Studies in Humanities: An Online Open Access E-Journal, publishing articles on a number of areas
Article about interdisciplinary modeling (in French with an English abstract)
Wolf, Dieter. Unity of Knowledge, an interdisciplinary project
SystemsX.ch – The Swiss Initiative in Systems Biology
Tackling Your Inner 5-Year-Old: Saving the world requires an interdisciplinary perspective | Wikipedia/Interdisciplinary_science |
The history of science during the Age of Enlightenment traces developments in science and technology during the Age of Reason, when Enlightenment ideas and ideals were being disseminated across Europe and North America. Generally, the period spans from the final days of the 16th- and 17th-century Scientific Revolution until roughly the 19th century, after the French Revolution (1789) and the Napoleonic era (1799–1815). The scientific revolution saw the creation of the first scientific societies, the rise of Copernicanism, and the displacement of Aristotelian natural philosophy and Galen's ancient medical doctrine. By the 18th century, scientific authority began to displace religious authority, and the disciplines of alchemy and astrology lost scientific credibility.
While the Enlightenment cannot be pigeonholed into a specific doctrine or set of dogmas, science came to play a leading role in Enlightenment discourse and thought. Many Enlightenment writers and thinkers had backgrounds in the sciences and associated scientific advancement with the overthrow of religion and traditional authority in favour of the development of free speech and thought. Broadly speaking, Enlightenment science greatly valued empiricism and rational thought, and was embedded with the Enlightenment ideal of advancement and progress. As with most Enlightenment views, the benefits of science were not seen universally; Jean-Jacques Rousseau criticized the sciences for distancing man from nature and not operating to make people happier.
Science during the Enlightenment was dominated by scientific societies and academies, which had largely replaced universities as centres of scientific research and development. Societies and academies were also the backbone of the maturation of the scientific profession. Another important development was the popularization of science among an increasingly literate population. Philosophes introduced the public to many scientific theories, most notably through the Encyclopédie and the popularization of Newtonianism by Voltaire as well as by Émilie du Châtelet, the French translator of Newton's Philosophiæ Naturalis Principia Mathematica. Some historians have marked the 18th century as a drab period in the history of science; however, the century saw significant advancements in the practice of medicine, mathematics, and physics; the development of biological taxonomy; a new understanding of magnetism and electricity; and the maturation of chemistry as a discipline, which established the foundations of modern chemistry.
== Universities ==
The number of universities in Paris remained relatively constant throughout the 18th century. Europe had about 105 universities and colleges by 1700. North America had 44, including the newly founded Harvard and Yale. The number of university students remained roughly the same throughout the Enlightenment in most Western nations, excluding Britain, where the number of institutions and students increased. University students were generally males from affluent families, seeking a career in either medicine, law, or the Church. The universities themselves existed primarily to educate future physicians, lawyers and members of the clergy.
The study of science under the heading of natural philosophy was divided into physics and a conglomerate grouping of chemistry and natural history, which included anatomy, biology, geology, mineralogy, and zoology. Most European universities taught a Cartesian form of mechanical philosophy in the early 18th century, and only slowly adopted Newtonianism in the mid-18th century. A notable exception were universities in Spain, which under the influence of Catholicism focused almost entirely on Aristotelian natural philosophy until the mid-18th century; they were among the last universities to do so. Another exception occurred in the universities of Germany and Scandinavia, where University of Halle professor Christian Wolff taught a form of Cartesianism modified by Leibnizian physics.
Before the 18th century, science courses were taught almost exclusively through formal lectures. The structure of courses began to change in the first decades of the 18th century, when physical demonstrations were added to lectures. Pierre Polinière and Jacques Rohault were among the first individuals to provide demonstrations of physical principles in the classroom. Experiments ranged from swinging a bucket of water at the end of a rope, demonstrating that centrifugal force would hold the water in the bucket, to more impressive experiments involving the use of an air-pump. One particularly dramatic air-pump demonstration involved placing an apple inside the glass receiver of the air-pump, and removing air until the resulting vacuum caused the apple to explode. Polinière's demonstrations were so impressive that he was granted an invitation to present his course to Louis XV in 1722.
Some attempts at reforming the structure of the science curriculum were made during the 18th century and the first decades of the 19th century. Beginning around 1745, the Hats party in Sweden made propositions to reform the university system by separating natural philosophy into two separate faculties of physics and mathematics. The propositions were never put into action, but they represent the growing calls for institutional reform in the later part of the 18th century. In 1777, the study of arts at Kraków and Vilna in Poland was divided into the two new faculties of moral philosophy and physics. However, the reform did not survive beyond 1795 and the Third Partition. During the French Revolution, all colleges and universities in France were abolished and reformed in 1808 under the single institution of the Université imperiale. The Université divided the arts and sciences into separate faculties, something that had never before been done before in Europe. The United Kingdom of the Netherlands employed the same system in 1815. However, the other countries of Europe did not adopt a similar division of the faculties until the mid-19th century.
Universities in France tended to serve a downplayed role in the development of science during the Enlightenment; that role was dominated by the scientific academies, such as the French Academy of Sciences. The contributions of universities in Britain were mixed. On the one hand, the University of Cambridge began teaching Newtonianism early in the Enlightenment, but failed to become a central force behind the advancement of science. On the other end of the spectrum were Scottish universities, which had strong medical faculties and became centres of scientific development. Under Frederick II, German universities began to promote the sciences. Christian Wolff's unique blend of Cartesian-Leibnizian physics began to be adopted in universities outside of Halle. The University of Göttingen, founded in 1734, was far more liberal than its counterparts, allowing professors to plan their own courses and select their own textbooks. Göttingen also emphasized research and publication. A further influential development in German universities was the abandonment of Latin in favour of the German vernacular.
In the 17th century, the Netherlands had played a significant role in the advancement of the sciences, including Isaac Beeckman's mechanical philosophy and Christiaan Huygens' work on the calculus and in astronomy. Professors at universities in the Dutch Republic were among the first to adopt Newtonianism. From the University of Leiden, Willem 's Gravesande's students went on to spread Newtonianism to Harderwijk and Franeker, among other Dutch universities, and also to the University of Amsterdam.
While the number of universities did not dramatically increase during the Enlightenment, new private and public institutions added to the provision of education. Most of the new institutions emphasized mathematics as a discipline, making them popular with professions that required some working knowledge of mathematics, such as merchants, military and naval officers, and engineers. Universities, on the other hand, maintained their emphasis on the classics, Greek, and Latin, encouraging the popularity of the new institutions with individuals who had not been formally educated.
== Societies and Academies ==
Scientific academies and societies grew out of the Scientific Revolution as the creators of scientific knowledge in contrast to the scholasticism of the university. During the Enlightenment, some societies created or retained links to universities. However, contemporary sources distinguished universities from scientific societies by claiming that the university's utility was in the transmission of knowledge, while societies functioned to create knowledge. As the role of universities in institutionalized science began to diminish, learned societies became the cornerstone of organized science. After 1700 a tremendous number of official academies and societies were founded in Europe and by 1789 there were over seventy official scientific societies . In reference to this growth, Bernard de Fontenelle coined the term "the Age of Academies" to describe the 18th century.
National scientific societies were founded throughout the Enlightenment era in the urban hotbeds of scientific development across Europe. In the 17th century the Royal Society of London (1662), the Paris Académie Royale des Sciences (1666), and the Berlin Akademie der Wissenschaften (1700) were founded. Around the start of the 18th century, the Academia Scientiarum Imperialis (1724) in St. Petersburg, and the Kungliga Vetenskapsakademien (Royal Swedish Academy of Sciences) (1739) were created. Regional and provincial societies emerged from the 18th century in Bologna, Bordeaux, Copenhagen, Dijon, Lyons, Montpellier and Uppsala. Following this initial period of growth, societies were founded between 1752 and 1785 in Barcelona, Brussels, Dublin, Edinburgh, Göttingen, Mannheim, Munich, Padua and Turin. The development of unchartered societies, such as the private the Naturforschende Gesellschaft of Danzig (1743) and Lunar Society of Birmingham (1766–1791), occurred alongside the growth of national, regional and provincial societies.
Official scientific societies were chartered by the state in order to provide technical expertise. This advisory capacity offered scientific societies the most direct contact between the scientific community and government bodies available during the Enlightenment. State sponsorship was beneficial to the societies as it brought finance and recognition, along with a measure of freedom in management. Most societies were granted permission to oversee their own publications, control the election of new members, and the administration of the society. Membership in academies and societies was therefore highly selective. In some societies, members were required to pay an annual fee to participate. For example, the Royal Society depended on contributions from its members, which excluded a wide range of artisans and mathematicians on account of the expense. Society activities included research, experimentation, sponsoring essay prize contests, and collaborative projects between societies. A dialogue of formal communication also developed between societies and society in general through the publication of scientific journals. Periodicals offered society members the opportunity to publish, and for their ideas to be consumed by other scientific societies and the literate public. Scientific journals, readily accessible to members of learned societies, became the most important form of publication for scientists during the Enlightenment.
== Periodicals ==
Academies and societies served to disseminate Enlightenment science by publishing the scientific works of their members, as well as their proceedings. At the beginning of the 18th century, the Philosophical Transactions of the Royal Society, published by the Royal Society of London, was the only scientific periodical being published on a regular, quarterly basis. The Paris Academy of Sciences, formed in 1666, began publishing in volumes of memoirs rather than a quarterly journal, with periods between volumes sometimes lasting years. While some official periodicals may have published more frequently, there was still a long delay from a paper's submission for review to its actual publication. Smaller periodicals, such as Transactions of the American Philosophical Society, were only published when enough content was available to complete a volume. At the Paris Academy, there was an average delay of three years for publication. At one point the period extended to seven years. The Paris Academy processed submitted articles through the Comité de Librarie, which had the final word on what would or would not be published. In 1703, the mathematician Antoine Parent began a periodical, Researches in Physics and Mathematics, specifically to publish papers that had been rejected by the Comité.
The limitations of such academic journals left considerable space for the rise of independent periodicals. Some eminent examples include Johann Ernst Immanuel Walch's Der Naturforscher (The Natural Investigator) (1725–1778), Journal des sçavans (1665–1792), the Jesuit Mémoires de Trévoux (1701–1779), and Leibniz's Acta Eruditorum (Reports/Acts of the Scholars) (1682–1782). Independent periodicals were published throughout the Enlightenment and excited scientific interest in the general public. While the journals of the academies primarily published scientific papers, independent periodicals were a mix of reviews, abstracts, translations of foreign texts, and sometimes derivative, reprinted materials. Most of these texts were published in the local vernacular, so their continental spread depended on the language of the readers. For example, in 1761 Russian scientist Mikhail Lomonosov correctly attributed the ring of light around Venus, visible during the planet's transit, as the planet's atmosphere; however, because few scientists understood Russian outside of Russia, his discovery was not widely credited until 1910.
Some changes in periodicals occurred during the course of the Enlightenment. First, they increased in number and size. There was also a move away from publishing in Latin in favour of publishing in the vernacular. Experimental descriptions became more detailed and began to be accompanied by reviews. In the late 18th century, a second change occurred when a new breed of periodical began to publish monthly about new developments and experiments in the scientific community. The first of this kind of journal was François Rozier's Observations sur la physiques, sur l'histoire naturelle et sur les arts, commonly referred to as "Rozier's journal", which was first published in 1772. The journal allowed new scientific developments to be published relatively quickly compared to annuals and quarterlies. A third important change was the specialization seen in the new development of disciplinary journals. With a wider audience and ever increasing publication material, specialized journals such as Curtis' Botanical Magazine (1787) and the Annals de Chimie (1789) reflect the growing division between scientific disciplines in the Enlightenment era.
== Encyclopedias and dictionaries ==
Although the existence of dictionaries and encyclopedia spanned into ancient times, and would be nothing new to Enlightenment readers, the texts changed from simply defining words in a long running list to far more detailed discussions of those words in 18th-century encyclopedic dictionaries. The works were part of an Enlightenment movement to systematize knowledge and provide education to a wider audience than the educated elite. As the 18th century progressed, the content of encyclopedias also changed according to readers' tastes. Volumes tended to focus more strongly on secular affairs, particularly science and technology, rather than matters of theology.
Along with secular matters, readers also favoured an alphabetical ordering scheme over cumbersome works arranged along thematic lines. The historian Charles Porset, commenting on alphabetization, has said that "as the zero degree of taxonomy, alphabetical order authorizes all reading strategies; in this respect it could be considered an emblem of the Enlightenment." For Porset, the avoidance of thematic and hierarchical systems thus allows free interpretation of the works and becomes an example of egalitarianism. Encyclopedias and dictionaries also became more popular during the Age of Reason as the number of educated consumers who could afford such texts began to multiply. In the later half of the 18th century, the number of dictionaries and encyclopedias published by decade increased from 63 between 1760 and 1769 to approximately 148 in the decade proceeding the French Revolution (1780–1789). Along with growth in numbers, dictionaries and encyclopedias also grew in length, often having multiple print runs that sometimes included in supplemented editions.
The first technical dictionary was drafted by John Harris and entitled Lexicon Technicum: Or, An Universal English Dictionary of Arts and Sciences. Harris' book avoided theological and biographical entries; instead it concentrated on science and technology. Published in 1704, the Lexicon technicum was the first book to be written in English that took a methodical approach to describing mathematics and commercial arithmetic along with the physical sciences and navigation. Other technical dictionaries followed Harris' model, including Ephraim Chambers' Cyclopaedia (1728), which included five editions, and was a substantially larger work than Harris'. The folio edition of the work even included foldout engravings. The Cyclopaedia emphasized Newtonian theories, Lockean philosophy, and contained thorough examinations of technologies, such as engraving, brewing, and dyeing. In Germany, practical reference works intended for the uneducated majority became popular in the 18th century. The Marperger Curieuses Natur-, Kunst-, Berg-, Gewerkund Handlungs-Lexicon (1712) explained terms that usefully described the trades and scientific and commercial education. Jablonksi Allgemeines Lexicon (1721) was better known than the Handlungs-Lexicon, and underscored technical subjects rather than scientific theory. For example, over five columns of text were dedicated to wine, while geometry and logic were allocated only twenty-two and seventeen lines, respectively. The first edition of the Encyclopædia Britannica (1771) was modelled along the same lines as the German lexicons.
However, the prime example of reference works that systematized scientific knowledge in the age of Enlightenment were universal encyclopedias rather than technical dictionaries. It was the goal of universal encyclopedias to record all human knowledge in a comprehensive reference work. The most well-known of these works is Denis Diderot and Jean le Rond d'Alembert's Encyclopédie, ou dictionnaire raisonné des sciences, des arts et des métiers. The work, which began publication in 1751, was composed of thirty-five volumes and over 71 000 separate entries. A great number of the entries were dedicated to describing the sciences and crafts in detail. In d'Alembert's Preliminary Discourse to the Encyclopedia of Diderot, the work's massive goal to record the extent of human knowledge in the arts and sciences is outlined:
As an Encyclopédie, it is to set forth as well as possible the order and connection of the parts of human knowledge. As a Reasoned Dictionary of the Sciences, Arts, and Trades, it is to contain the general principles that form the basis of each science and each art, liberal or mechanical, and the most essential facts that make up the body and substance of each.
The massive work was arranged according to a "tree of knowledge". The tree reflected the marked division between the arts and sciences, which was largely a result of the rise of empiricism. Both areas of knowledge were united by philosophy, or the trunk of the tree of knowledge. The Enlightenment's desacrilization of religion was pronounced in the tree's design, particularly where theology accounted for a peripheral branch, with black magic as a close neighbour. As the Encyclopédie gained popularity, it was published in quarto and octavo editions after 1777. The quarto and octavo editions were much less expensive than previous editions, making the Encyclopédie more accessible to the non-elite. Robert Darnton estimates that there were approximately 25 000 copies of the Encyclopédie in circulation throughout France and Europe before the French Revolution. The extensive, yet affordable encyclopedia came to represent the transmission of Enlightenment and scientific education to an expanding audience.
== Popularization of science ==
One of the most important developments that the Enlightenment era brought to the discipline of science was its popularization. An increasingly literate population seeking knowledge and education in both the arts and the sciences drove the expansion of print culture and the dissemination of scientific learning. The new literate population was due to a high rise in the availability of food. This enabled many people to rise out of poverty, and instead of paying more for food, they had money for education. Popularization was generally part of an overarching Enlightenment ideal that endeavoured "to make information available to the greatest number of people." As public interest in natural philosophy grew during the 18th century, public lecture courses and the publication of popular texts opened up new roads to money and fame for amateurs and scientists who remained on the periphery of universities and academies.
=== British coffeehouses ===
An early example of science emanating from the official institutions into the public realm was the British coffeehouse. With the establishment of coffeehouses, a new public forum for political, philosophical and scientific discourse was created. In the mid-16th century, coffeehouses popped up around Oxford, where the academic community began to capitalize on the unregulated conversation that the coffeehouse allowed. The new social space began to be used by some scholars as a place to discuss science and experiments outside of the laboratory of the official institution. Coffeehouse patrons were only required to purchase a dish of coffee to participate, leaving the opportunity for many, regardless of financial means, to benefit from the conversation. Education was a central theme and some patrons began offering lessons and lectures to others. The chemist Peter Staehl provided chemistry lessons at Tilliard's coffeehouse in the early 1660s. As coffeehouses developed in London, customers heard lectures on scientific subjects, such as astronomy and mathematics, for an exceedingly low price. Notable Coffeehouse enthusiasts included John Aubrey, Robert Hooke, James Brydges, and Samuel Pepys.
=== Public lectures ===
Public lecture courses offered some scientists who were unaffiliated with official organizations a forum to transmit scientific knowledge, at times even their own ideas, and the opportunity to carve out a reputation and, in some instances, a living. The public, on the other hand, gained both knowledge and entertainment from demonstration lectures. Between 1735 and 1793, there were over seventy individuals offering courses and demonstrations for public viewers in experimental physics. Class sizes ranged from one hundred to four or five hundred attendees. Courses varied in duration from one to four weeks, to a few months, or even the entire academic year. Courses were offered at virtually any time of day; the latest occurred at 8:00 or 9:00 at night. One of the most popular start times was 6:00 pm, allowing the working population to participate and signifying the attendance of the nonelite. Barred from the universities and other institutions, women were often in attendance at demonstration lectures and constituted a significant number of auditors.
The importance of the lectures was not in teaching complex mathematics or physics, but rather in demonstrating to the wider public the principles of physics and encouraging discussion and debate. Generally, individuals presenting the lectures did not adhere to any particular brand of physics, but rather demonstrated a combination of different theories. New advancements in the study of electricity offered viewers demonstrations that drew far more inspiration among the laity than scientific papers could hold. An example of a popular demonstration used by Jean-Antoine Nollet and other lecturers was the 'electrified boy'. In the demonstration, a young boy would be suspended from the ceiling, horizontal to the floor, with silk chords. An electrical machine would then be used to electrify the boy. Essentially becoming a magnet, he would then attract a collection of items scattered about him by the lecturer. Sometimes a young girl would be called from the auditors to touch or kiss the boy on the cheek, causing sparks to shoot between the two children in what was dubbed the 'electric kiss'. Such marvels would certainly have entertained the audience, but the demonstration of physical principles also served an educational purpose. One 18th-century lecturer insisted on the utility of his demonstrations, stating that they were "useful for the good of society."
=== Popular science in print ===
Increasing literacy rates in Europe during the course of the Enlightenment enabled science to enter popular culture through print. More formal works included explanations of scientific theories for individuals lacking the educational background to comprehend the original scientific text. Sir Isaac Newton's celebrated Philosophiae Naturalis Principia Mathematica was published in Latin and remained inaccessible to readers without education in the classics until Enlightenment writers began to translate and analyze the text in the vernacular. The first French introduction to Newtonianism and the Principia was Eléments de la philosophie de Newton, published by Voltaire in 1738. Émilie du Châtelet's translation of the Principia, published after her death in 1756, also helped to spread Newton's theories beyond scientific academies and the university.
However, science took an ever greater step towards popular culture before Voltaire's introduction and Châtelet's translation. The publication of Bernard de Fontenelle's Conversations on the Plurality of Worlds (1686) marked the first significant work that expressed scientific theory and knowledge expressly for the laity, in the vernacular, and with the entertainment of readers in mind. The book was produced specifically for women with an interest in scientific writing and inspired a variety of similar works. These popular works were written in a discursive style, which was laid out much more clearly for the reader than the complicated articles, treatises, and books published by the academies and scientists. Charles Leadbetter's Astronomy (1727) was advertised as "a Work entirely New" that would include "short and easie [sic] Rules and Astronomical Tables." Francesco Algarotti, writing for a growing female audience, published Il Newtonianism per le dame, which was a tremendously popular work and was translated from Italian into English by Elizabeth Carter. A similar introduction to Newtonianism for women was produced by Henry Pembarton. His A View of Sir Isaac Newton's Philosophy was published by subscription. Extant records of subscribers show that women from a wide range of social standings purchased the book, indicating the growing number of scientifically inclined female readers among the middling class. During the Enlightenment, women also began producing popular scientific works themselves. Sarah Trimmer wrote a successful natural history textbook for children entitled The Easy Introduction to the Knowledge of Nature (1782), which was published for many years after in eleven editions.
The influence of science also began appearing more commonly in poetry and literature during the Enlightenment. Some poetry became infused with scientific metaphor and imagery, while other poems were written directly about scientific topics. Sir Richard Blackmore committed the Newtonian system to verse in Creation, a Philosophical Poem in Seven Books (1712). After Newton's death in 1727, poems were composed in his honour for decades. James Thomson (1700–1748) penned his "Poem to the Memory of Newton," which mourned the loss of Newton, but also praised his science and legacy:
While references to the sciences were often positive, there were some Enlightenment writers who criticized scientists for what they viewed as their obsessive, frivolous careers. Other antiscience writers, including William Blake, chastised scientists for attempting to use physics, mechanics and mathematics to simplify the complexities of the universe, particularly in relation to God. The character of the evil scientist was invoked during this period in the romantic tradition. For example, the characterization of the scientist as a nefarious manipulator in the work of Ernst Theodor Wilhelm Hoffmann.
== Women in science ==
During the Enlightenment era, women were excluded from scientific societies, universities and learned professions. Women were educated, if at all, through self-study, tutors, and by the teachings of more open-minded fathers. With the exception of daughters of craftsmen, who sometimes learned their father's profession by assisting in the workshop, learned women were primarily part of elite society. A consequence of the exclusion of women from societies and universities that prevented much independent research was their inability to access scientific instruments, such as the microscope. In fact, restrictions were so severe in the 18th century that women, including midwives, were forbidden to use forceps. That particular restriction exemplified the increasingly constrictive, male-dominated medical community. Over the course of the 18th century, male surgeons began to assume the role of midwives in gynaecology. Some male satirists also ridiculed scientifically minded women, describing them as neglectful of their domestic role. The negative view of women in the sciences reflected the sentiment apparent in some Enlightenment texts that women need not, nor ought to be educated; the opinion is exemplified by Jean-Jacques Rousseau in Émile:
A woman’s education must... be planned in relation to man. To be pleasing in his sight, to win his respect and love, to train him in childhood, to tend him in manhood, to counsel and console, to make his life pleasant and happy, these are the duties of woman for all time, and this is what she should be taught while she is young.
Despite these limitations, there was support for women in the sciences among some men, and many made valuable contributions to science during the 18th century. Two notable women who managed to participate in formal institutions were Laura Bassi and the Russian Princess Yekaterina Dashkova. Bassi was an Italian physicist who received a PhD from the University of Bologna and began teaching there in 1732. Dashkova became the director of the Russian Imperial Academy of Sciences of St. Petersburg in 1783. Her personal relationship with Empress Catherine the Great (r. 1762–1796) allowed her to obtain the position, which marked in history the first appointment of a woman to the directorship of a scientific academy. Eva Ekeblad became the first woman inducted into the Royal Swedish Academy of Science (1748).
More commonly, women participated in the sciences through an association with a male relative or spouse. Caroline Herschel began her astronomical career, although somewhat reluctantly at first, by assisting her brother William Herschel. Caroline Herschel is most remembered for her discovery of eight comets and her Index to Flamsteed's Observations of the Fixed Stars (1798). On August 1, 1786, Herschel discovered her first comet, much to the excitement of scientifically minded women. Fanny Burney commented on the discovery, stating that "the comet was very small, and had nothing grand or striking in its appearance; but it is the first lady's comet, and I was very desirous to see it." Marie-Anne Pierette Paulze worked collaboratively with her husband, Antoine Lavoisier. Aside from assisting in Lavoisier's laboratory research, she was responsible for translating a number of English texts into French for her husband's work on the new chemistry. Paulze also illustrated many of her husband's publications, such as his Treatise on Chemistry (1789).
Many other women became illustrators or translators of scientific texts. In France, Madeleine Françoise Basseporte was employed by the Royal Botanical Garden as an illustrator. Englishwoman Mary Delany developed a unique method of illustration. Her technique involved using hundreds of pieces of coloured-paper to recreate lifelike renditions of living plants. German born Maria Sibylla Merian along with her daughters including Dorothea Maria Graff were involved in the careful scientific study of insects and the natural world. Using mostly watercolor, gauche on vellum, She became one of the leading entomologists of the 18th century. Maria Sibylla and her daughter Dorothea traveled to Suriname to study the different life stages of insects there and the plants on which they lived. On their return, Merian published in 1705 the lavishly illustrated Metamorphosis Surinamensis.
Noblewomen sometimes cultivated their own botanical gardens, including Mary Somerset and Margaret Harley. Scientific translation sometimes required more than a grasp on multiple languages. Besides translating Newton's Principia into French, Émilie du Châtelet expanded Newton's work to include recent progress made in mathematical physics after his death.
== Disciplines ==
=== Astronomy ===
Building on the body of work forwarded by Copernicus, Kepler and Newton, 18th-century astronomers refined telescopes, produced star catalogues, and worked towards explaining the motions of heavenly bodies and the consequences of universal gravitation. Among the prominent astronomers of the age was Edmund Halley. In 1705, Halley correctly linked historical descriptions of particularly bright comets to the reappearance of just one, which would later be named Halley's Comet, based on his computation of the orbits of comets. Halley also changed the theory of the Newtonian universe, which described the fixed stars. When he compared the ancient positions of stars to their contemporary positions, he found that they had shifted. James Bradley, while attempting to document stellar parallax, realized that the unexplained motion of stars he had early observed with Samuel Molyneux was caused by the aberration of light. The discovery was proof of a heliocentric model of the universe, since it is the revolution of the earth around the sun that causes an apparent motion in the observed position of a star. The discovery also led Bradley to a fairly close estimate to the speed of light.
Observations of Venus in the 18th century became an important step in describing atmospheres. During the 1761 transit of Venus, the Russian scientist Mikhail Lomonosov observed a ring of light around the planet. Lomonosov attributed the ring to the refraction of sunlight, which he correctly hypothesized was caused by the atmosphere of Venus. Further evidence of Venus' atmosphere was gathered in observations by Johann Hieronymus Schröter in 1779. The planet also offered Alexis Claude de Clairaut an opportunity to work his considerable mathematical skills when he computed the mass of Venus through complex mathematical calculations.
However, much astronomical work of the period becomes shadowed by one of the most dramatic scientific discoveries of the 18th century. On 13 March 1781, amateur astronomer William Herschel spotted a new planet with his powerful reflecting telescope. Initially identified as a comet, the celestial body later came to be accepted as a planet. Soon after, the planet was named Georgium Sidus by Herschel and was called Herschelium in France. The name Uranus, as proposed by Johann Bode, came into widespread usage after Herschel's death. On the theoretical side of astronomy, the English natural philosopher John Michell first proposed the existence of dark stars in 1783. Michell postulated that if the density of a stellar object became great enough, its attractive force would become so large that even light could not escape. He also surmised that the location of a dark star could be determined by the strong gravitational force it would exert on surrounding stars. While differing somewhat from a black hole, the dark star can be understood as a predecessor to the black holes resulting from Albert Einstein's general theory of relativity.
=== Chemistry ===
The chemical revolution was a period in the 18th century marked by significant advancements in the theory and practice of chemistry. Despite the maturity of most of the sciences during the scientific revolution, by the mid-18th century chemistry had yet to outline a systematic framework or theoretical doctrine. Elements of alchemy still permeated the study of chemistry, and the belief that the natural world was composed of the classical elements of earth, water, air and fire remained prevalent. The key achievement of the chemical revolution has traditionally been viewed as the abandonment of phlogiston theory in favour of Antoine Lavoisier's oxygen theory of combustion; however, more recent studies attribute a wider range of factors as contributing forces behind the chemical revolution.
Developed under Johann Joachim Becher and Georg Ernst Stahl, phlogiston theory was an attempt to account for products of combustion. According to the theory, a substance called phlogiston was released from flammable materials through burning. The resulting product was termed calx, which was considered a 'dephlogisticated' substance in its 'true' form. The first strong evidence against phlogiston theory came from pneumatic chemists in Britain during the later half of the 18th century. Joseph Black, Joseph Priestley and Henry Cavendish all identified different gases that composed air; however, it was not until Antoine Lavoisier discovered in the fall of 1772 that, when burned, sulphur and phosphorus "gain[ed] in weight" that the phlogiston theory began to unravel.
Lavoisier subsequently discovered and named oxygen, described its role in animal respiration and the calcination of metals exposed to air (1774–1778). In 1783, Lavoisier found that water was a compound of oxygen and hydrogen. Lavoisier's years of experimentation formed a body of work that contested phlogiston theory. After reading his "Reflections on Phlogiston" to the Academy in 1785, chemists began dividing into camps based on the old phlogiston theory and the new oxygen theory. A new form of chemical nomenclature, developed by Louis Bernard Guyton de Morveau, with assistance from Lavoisier, classified elements binomially into a genus and a species. For example, burned lead was of the genus oxide and species lead. Transition to and acceptance of Lavoisier's new chemistry varied in pace across Europe. The new chemistry was established in Glasgow and Edinburgh early in the 1790s, but was slow to become established in Germany. Eventually the oxygen-based theory of combustion drowned out the phlogiston theory and in the process created the basis of modern chemistry.
== See also ==
Scientific method
Rationalism
== Notes ==
== References == | Wikipedia/Science_in_the_Age_of_Enlightenment |
Fringe science refers to ideas whose attributes include being highly speculative or relying on premises already refuted. The chance of ideas rejected by editors and published outside the mainstream being correct is remote.: 58 When the general public does not distinguish between science and imitators, it risks exploitation,: 173 and in some cases, a "yearning to believe or a generalized suspicion of experts is a very potent incentive to accepting some pseudoscientific claims".: 176
The term "fringe science" covers everything from novel hypotheses, which can be tested utilizing the scientific method, to wild ad hoc hypotheses and mumbo jumbo. This has resulted in a tendency to dismiss all fringe science as the domain of pseudoscientists, hobbyists, and quacks.
A concept that was once accepted by the mainstream scientific community may become fringe science because of a later evaluation of previous research. For example, focal infection theory, which held that focal infections of the tonsils or teeth are a primary cause of systemic disease, was once considered to be medical fact. It has since been dismissed because of a lack of evidence.
== Description ==
The boundary between fringe science and pseudoscience is disputed. Friedlander writes that there is no widespread understanding of what separates science from nonscience or pseudoscience.: 183 Pseudoscience, however, is something that is not scientific but is incorrectly characterised as science.
The term may be considered pejorative. For example, Lyell D. Henry Jr. wrote, "Fringe science [is] a term also suggesting kookiness."
Continental drift was rejected for decades lacking conclusive evidence before plate tectonics was accepted.: 5
The confusion between science and pseudoscience, between honest scientific error and genuine scientific discovery, is not new, and it is a permanent feature of the scientific landscape .... Acceptance of new science can come slowly.: 161
== Examples ==
=== Historical ===
Some historical ideas that are considered to have been refuted by mainstream science are:
Wilhelm Reich's work with orgone, a physical energy he claimed to have discovered, contributed to his alienation from the psychiatric community. He was eventually sentenced to two years in a federal prison, where he died. At that time and continuing today, scientists disputed his claim that he had scientific evidence for the existence of orgone. Nevertheless, amateurs and a few fringe researchers continued to believe that orgone is real.
Focal infection theory (FIT), as the primary cause of systemic disease, rapidly became accepted by mainstream dentistry and medicine after World War I. This acceptance was largely based upon what later turned out to be fundamentally flawed studies. As a result, millions of people were subjected to needless dental extractions and surgeries. The original studies supporting FIT began falling out of favor in the 1930s. By the late 1950s, it was regarded as a fringe theory.
The Clovis First theory held that the Clovis culture was the first culture in North America. It was long regarded as a mainstream theory until mounting evidence of a pre-Clovis culture discredited it.
=== Modern ===
Relatively recent fringe sciences include:
Aubrey de Grey, featured in a 2006 60 Minutes special report, is studying human longevity. He calls his work "strategies for engineered negligible senescence" (SENS). Many mainstream scientists believe his research is fringe science (especially his view of the importance of nuclear epimutations and his timeline for antiaging therapeutics). In a 2005 article in Technology Review (part of a larger series), it was stated that "SENS is highly speculative. Many of its proposals have not been reproduced, nor could they be reproduced with today's scientific knowledge and technology. Echoing Myhrvold, we might charitably say that de Grey's proposals exist in a kind of antechamber of science, where they wait (possibly in vain) for independent verification. SENS does not compel the assent of many knowledgeable scientists; but neither is it demonstrably wrong."
A nuclear fusion reaction called cold fusion, which occurs near room temperature and pressure, was reported by chemists Martin Fleischmann and Stanley Pons in March 1989. Numerous research efforts at the time were unable to replicate their results. Subsequently, several scientists have worked on cold fusion or have participated in international conferences on it. In 2004, the United States Department of Energy commissioned a panel on cold fusion to reexamine the concept. They wanted to determine whether their policies should be altered because of new evidence.
The theory of abiogenic petroleum origin holds that petroleum was formed from deep carbon deposits, perhaps dating to the formation of the Earth. The ubiquity of hydrocarbons in the Solar System may be evidence that there may be more petroleum on Earth than commonly thought and that petroleum may originate from carbon-bearing fluids that migrate upward from the Earth's mantle. Abiogenic hypotheses saw a revival in the last half of the twentieth century by Russian and Ukrainian scientists. More interest was generated in the West after the 1999 publication by Thomas Gold of The Deep Hot Biosphere. Gold's version of the theory is partly based on the existence of a biosphere composed of thermophile bacteria in the Earth's crust, which might explain the existence of specific biomarkers in extracted petroleum.
=== Accepted as mainstream ===
Some theories that were once rejected as fringe science but were eventually accepted as mainstream science include:
Plate tectonics
The existence of Troy
Heliocentrism
Norse colonization of the Americas
The Big Bang theory
Helicobacter pylori bacteria as the causative agent of peptic ulcer disease
The germ theory of disease
Neanderthal-Homo sapiens hybridization
== Responding to fringe science ==
Michael W. Friedlander has suggested some guidelines for responding to fringe science, which, he argues, is a more difficult problem: 174 than scientific misconduct. His suggested methods include impeccable accuracy, checking cited sources, not overstating orthodox science, thorough understanding of the Wegener continental drift example, examples of orthodox science investigating radical proposals, and prepared examples of errors from fringe scientists.: 178-9
Friedlander suggests that fringe science is necessary so mainstream science will not atrophy. Scientists must evaluate the plausibility of each new fringe claim, and certain fringe discoveries "will later graduate into the ranks of accepted" — while others "will never receive confirmation".: 173
Margaret Wertheim profiled many "outsider scientists" in her book Physics on the Fringe, who receive little or no attention from professional scientists. She describes all of them as trying to make sense of the world using the scientific method but in the face of being unable to understand modern science's complex theories. She also finds it fair that credentialed scientists do not bother spending a lot of time learning about and explaining problems with the fringe theories of uncredentialed scientists since the authors of those theories have not taken the time to understand the mainstream theories they aim to disprove.
=== Controversies ===
As Donald E. Simanek asserts, "Too often speculative and tentative hypotheses of cutting edge science are treated as if they were scientific truths, and so accepted by a public eager for answers." However, the public is ignorant that "As science progresses from ignorance to understanding it must pass through a transitional phase of confusion and uncertainty."
The media also play a role in propagating the belief that certain fields of science are controversial. In their 2003 paper "Optimising Public Understanding of Science and Technology in Europe: A Comparative Perspective", Jan Nolin et al. write that "From a media perspective it is evident that controversial science sells, not only because of its dramatic value, but also since it is often connected to high-stake societal issues."
== See also ==
Books
13 Things That Don't Make Sense (a book by Michael Brooks)
The Structure of Scientific Revolutions (a book by Thomas S. Kuhn)
== References ==
== Bibliography ==
Ben-Yehuda, Nachman (1990). The politics and morality of deviance: moral panics, drug abuse, deviant science, and reversed stigmatization. SUNY series in deviance and social control. Albany: State University of New York Press. OCLC 19128625.
Brante, Thomas; Fuller, Steve; Lynch, William (1993). Controversial science: from content to contention. Albany, New York: State University of New York Press. OCLC 26096166.
Brooks, M. (2008). 13 Things That Don't Make Sense. New York: Doubleday. OCLC 213480209.
—— (31 March 2009). "Why science doesn't make sense". The Daily Telegraph. Archived from the original on 2009-04-04. Retrieved 2 April 2009.
Brown, George E. Jr. (23 October 1996). Environmental science under siege: fringe science and the 104th Congress. Washington, D.C.: Democratic Caucus of the Committee on Science, U.S. House of Representatives. OCLC 57343997.
Cooke, R. M. (1991). Experts in uncertainty: opinion and subjective probability in science. New York: Oxford University Press. ISBN 0-19-506465-8. OCLC 22710786.
CSICOP On-line: Scientifically Investigating Paranormal and Fringe Science Claims Archived 2014-03-16 at the Wayback Machine—Committee for Skeptical Inquiry
de Jager, Cornelis (March 1990). "Science, fringe science and pseudo-science". Quarterly Journal of the Royal Astronomical Society. 31 (1): 31–45. Bibcode:1990QJRAS..31...31D. ISSN 0035-8738.
Dutch, Steven I. (January 1982). "Notes on the nature of fringe science". Journal of Geological Education. 30 (1): 6–13. Bibcode:1982JGeoE..30....6D. doi:10.5408/0022-1368-30.1.6. ISSN 0022-1368. OCLC 92686827.
Frazier, Kendrick (1981). Paranormal borderlands of science. Buffalo, New York: Prometheus Books. ISBN 0-87975-148-7. OCLC 251487947.
Friedlander, Michael W. (February 1995). At the Fringes of Science. Boulder, Colorado: Westview Press. ISBN 0-8133-2200-6. OCLC 31046052.
Friedman, Sharon M; Dunwoody, Sharon; Rogers, Carol L, eds. (1998). Communicating uncertainty: Media coverage of new and controversial science. Mahwah, New Jersey; London: Lawrence Erlbaum. ISBN 0-8058-2727-7. OCLC 263560777.
Mauskopf, SH (1979). The reception of unconventional science. Boulder, Colorado: Westview Press. ISBN 0-89158-297-5. OCLC 4495634.
Mousseau, Marie-Catherine (2003). "Parapsychology: Science or Pseudo-Science?" (PDF). Journal of Scientific Exploration. 17 (2): 271–282. ISSN 0892-3310. Archived from the original (PDF) on 2009-11-27.
Truzzi, Marcello (1998). "The Perspective of Anomalistics". Anomalistics. Center for Scientific Anomalies Research. Archived from the original on February 6, 2009. Retrieved 2009-04-14.
== External links ==
Media related to Fringe science at Wikimedia Commons | Wikipedia/Fringe_science |
A science fair or engineering fair is an event hosted by a school that offers students the opportunity to experience the practices of science and engineering for themselves. In the United States, the Next Generation Science Standards makes experiencing the practices of science and engineering one of the three pillars of science education. Students perform some sort of research and then present their experiment in a poster session or other display format.
== History ==
Science fairs began in the United States in New York City in the 1930s under the auspices of a civic organization called the American Institute of the City of New York with the effort led in New York City by Morris Meister who later founded the Bronx High School of Science. Meister believed in the educational ideas of John Dewey that focused on doing rather than just learning what already had been done. The goals of the after-school science club federation were twofold: "to aid in the development of the scientific leaders of the next generation and at the same time foster a better understanding of science among its laymen".
Initially, science fairs were mostly exhibits and demonstration projects or mere displays of projects. This changed after the 1939 New York World's Fair. Increasingly, science and engineering fairs became viewed by many as a way to encourage and help students find their way into science and engineering career paths. Popularity of science fairs in the United States increased in the 1950s along with interest in the sciences after the world witnessed the use of the first two atomic weapons and the dawn of television. As the decade progressed, science stories in the news, such as Jonas Salk's vaccine for polio and the launch of Sputnik, brought science fiction to reality and attracted increasing numbers of students at every level to fairs.
== Goals ==
Science and engineering fairs attract students at every level—elementary, middle and high school—to compete in science and technology activities. Science fairs also can allow for students with intense interest in the sciences to be paired with mentors from nearby colleges and universities, so that the students have access to instruction and equipment that the local schools do not provide. Since 2017, Frederick Grinnell (biologist) and colleagues have been studying what student experiences in high school science and engineering fair increase student interest in science and engineering. Along with mentoring by scientists, coaching students for their science fair interviews, has been shown to be very important for student success.
== International events ==
Most countries have regional science fairs in which interested students can freely participate. Winners of these regional fairs send students to national fairs such as the International Science and Engineering Fair (ISEF) and Canada-Wide Science Fair (CWSF). National science fairs typically send winners to international fairs such as ISEF (which is a national and an international science fair) and EUCYS. Currently, the biotechnology company-sponsored Regeneron Science Talent Search offers a grand prize of a $250,000 scholarship. The 2018 documentary Science Fair chronicles the competition.
== See also ==
Google Science Fair
Interest Fair
== References ==
== Further reading ==
== External links ==
The WWW Virtual Library: Science Fairs
"Science Fair organisers and participating schools' reflections about science fairs" best-practice report
Science Buddies List Of Science Fairs | Wikipedia/Science_fair |
The regulation of science refers to use of law, or other ruling, by academic or governmental bodies to allow or restrict science from performing certain practices, or researching certain scientific areas.
Science could be regulated by legislation if areas are seen as harmful, immoral, or dangerous. For these reasons science regulation may be closely related to religion, culture and society.
Science regulation is often a bioethical issue related to practices such as abortion and euthanasia, and areas of research such as stem-cell research and cloning synthetic biology.
== United States ==
=== Biomedical research ===
Unjust events such as the St. Louis tragedy or the Tuskegee syphilis experiment have prompted regulations in biomedical research. Over the years, regulations have been extended to encompass animal welfare and research misconduct. The federal government also monitors the production and sale of the results of biomedical research such as drugs and biopharmaceuticals. The FDA and the Department of Health and Human Services oversee the implementation of these regulations.
The Dickey–Wicker Amendment prohibits the Department of Health and Human Services (HHS) from using appropriated funds for the creation of human embryos for research purposes or for research in which human embryos are destroyed.
==== Human subject research ====
The issue of experimentation on human subjects gained prominence after World War II and the revelation of atrocities committed in the name of science. In the United States, the 1962 Kefauver-Harris amendments to the FDA included for the first time a requirement for informed consent of participants. In 1966, a policy statement by the U.S Surgeon General required that all human subject research go through independent prior review. The National Research Act of 1974 institutionalized this review process by requiring that research centers establish Institutional Review Boards (IRBs).
Universities, hospitals, and other research institutions set up these IRBs to review all the research done at the institution. These boards, generally composed of both scientific peers from the institution and lay persons, are tasked with assessing the risks and benefits associated with the use of human subjects, in addition to the adequacy of the protection and consent of the participants. The IRBs can approve research proposals, make modifications, or disapprove them entirely. Research projects cannot receive federal funding without approval from an IRB. Noncompliance can also induce sanctions from the institution, such as revoked access to facilities and subjects, suspension, and dismissal.
The National Research Act of 1974 also set up the National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research, which produced the Belmont Report (Report on Ethical Principles and Guidelines for the Protection of Human Subjects of Research) in 1979. This report established a moral framework for the regulation of research involving human subjects.
==== Animal welfare ====
The Animal Welfare Act of 1966 sets standards of treatment of animals in research experiments. It requires all research facilities to register with the USDA and allows officials to conduct unannounced facility inspections. The Health Research Extension Act of 1985 requires that all research facilities using animals establish Institutional Animal Care and Use Committees (IACUCs) to evaluate twice a year the institutions' activities involving animals. The IACUCs report to the NIH Office of Laboratory Animal Welfare annually.
==== Research misconduct ====
The Health Research Extension Act of 1985 led to the establishment of the Office of Research Integrity (ORI) within the Department of Health and Human Services. ORI is responsible for reviewing research misconduct allegations and developing policies to improve the responsible conduct of research.
==== Commercialization ====
Two divisions of the Food and Drug Administration (FDA) are in charge of monitoring the production and sale of drugs. The Center for Drug Evaluation and Research (CDER) is responsible for reviewing new drug applications and requires clinical trials as proof of effectiveness. The Center for Biologics Evaluation and Research (CBER) is responsible for implementing federal regulations of biopharmaceuticals such as vaccines, blood components, gene therapies, etc. They approve new drugs on the basis of safety and effectiveness, and issue licenses, which allow companies to market their products.
=== Nuclear energy research ===
Nuclear energy is historically linked to issues of national security. From 1942 to 1946, nuclear research was controlled by the military, which conducted research in secrecy. In 1946, the Atomic Energy Act handed over control to civilians, although the government retained a tight monopoly over nuclear energy. The 1954 amendment to this act enabled private industry to pursue non-military applications of nuclear research.
The Energy Reorganization Act of 1974 established the Nuclear Regulatory Commission (NRC), in charge of licensing and safety. The Chernobyl and Fukushima accidents raised concerns and public apprehension over the safety of nuclear power. As a result, the NRC strengthened safety regulations for nuclear power plants.
=== Teaching ===
Science education is a controversial subject in the United States. Several states banned the teaching of evolution in the 20th century, most notably the state of Tennessee with the Butler Act of 1925. It was followed by the Scopes Trial, in which the state of Tennessee accused Scopes, a high school teacher, of teaching evolution. Although he was found guilty and fined, the trial showed declining public support for Fundamentalists. The Scopes Trial had an important impact in the larger creation versus evolution debate. In the following decades, the term "evolution" was omitted in many biology textbooks, even when the text discusses it. These bans on teaching evolution were overturned by a Supreme Court ruling in Epperson v. Arkansas in 1968. Since 2001, there has been a resurgence of anti-evolution bills, one of which, the Louisiana Science Education Act, was passed. This Act allows public schools to use supplementary material that is critical of the scientific theories such as evolution and global warming in science classrooms.
The U.S. government and state legislatures have also enacted regulations promoting science education. The National Defense Education Act of 1958 was passed soon after the Soviet Union's launch of Sputnik 1 and linked education with issues of national security. This law provided funding for scholarships and science programs. In 2013, 26 state governments worked together to produce the Next Generation Science Standards, which sets expectations for K–12 science education.
== International regulations ==
The Nuremberg Code was written as part of the trials of Nazi doctors after World War II. It introduced ten ethical principles regarding human experimentation, the first of which requires informed consent from human subjects. It also states that experimentation on humans must be necessary to society, be preceded by studies on animals, and protect subjects from injury, disability and death. The Nuremberg Code was very influential in shaping regulations of scientific research across the world. For example, the Helsinki Declaration of 1964 was developed by the World Medical Association and establishes ethical principles for the medical community.
== See also ==
Ethics committee
Intelligent design in politics
Lysenkoism
Politicization of science
Right to science and culture
Scientific freedom
== References == | Wikipedia/Regulation_of_science |
Thermodynamic work is one of the principal kinds of process by which a thermodynamic system can interact with and transfer energy to its surroundings. This results in externally measurable macroscopic forces on the system's surroundings, which can cause mechanical work, to lift a weight, for example, or cause changes in electromagnetic, or gravitational variables. Also, the surroundings can perform thermodynamic work on a thermodynamic system, which is measured by an opposite sign convention.
For thermodynamic work, appropriately chosen externally measured quantities are exactly matched by values of or contributions to changes in macroscopic internal state variables of the system, which always occur in conjugate pairs, for example pressure and volume or magnetic flux density and magnetization.
In the International System of Units (SI), work is measured in joules (symbol J). The rate at which work is performed is power, measured in joules per second, and denoted with the unit watt (W).
== History ==
=== 1824 ===
Work, i.e. "weight lifted through a height", was originally defined in 1824 by Sadi Carnot in his famous paper Reflections on the Motive Power of Fire, where he used the term motive power for work. Specifically, according to Carnot:
We use here motive power to express the useful effect that a motor is capable of producing. This effect can always be likened to the elevation of a weight to a certain height. It has, as we know, as a measure, the product of the weight multiplied by the height to which it is raised.
=== 1845 ===
In 1845, the English physicist James Joule wrote a paper On the mechanical equivalent of heat for the British Association meeting in Cambridge. In this paper, he reported his best-known experiment, in which the mechanical power released through the action of a "weight falling through a height" was used to turn a paddle-wheel in an insulated barrel of water.
In this experiment, the motion of the paddle wheel, through agitation and friction, heated the body of water, so as to increase its temperature. Both the temperature change
Δ
T
{\displaystyle \Delta T}
of the water and the height of the fall
Δ
h
{\displaystyle \Delta h}
of the weight
m
g
{\displaystyle mg}
were recorded. Using these values, Joule was able to determine the mechanical equivalent of heat. Joule estimated a mechanical equivalent of heat to be 819 ft•lbf/Btu (4.41 J/cal). The modern day definitions of heat, work, temperature, and energy all have connection to this experiment. In this arrangement of apparatus, it never happens that the process runs in reverse, with the water driving the paddles so as to raise the weight, not even slightly. Mechanical work was done by the apparatus of falling weight, pulley, and paddles, which lay in the surroundings of the water. Their motion scarcely affected the volume of the water. A quantity of mechanical work, measured as force × distance in the surroundings, that does not change the volume of the water, is said to be isochoric. Such work reaches the system only as friction, through microscopic modes, and is irreversible. It does not count as thermodynamic work. The energy supplied by the fall of the weight passed into the water as heat.
== Overview ==
=== Conservation of energy ===
A fundamental guiding principle of thermodynamics is the conservation of energy. The total energy of a system is the sum of its internal energy, of its potential energy as a whole system in an external force field, such as gravity, and of its kinetic energy as a whole system in motion. Thermodynamics has special concern with transfers of energy, from a body of matter, such as, for example a cylinder of steam, to the surroundings of the body, by mechanisms through which the body exerts macroscopic forces on its surroundings so as to lift a weight there; such mechanisms are the ones that are said to mediate thermodynamic work.
Besides transfer of energy as work, thermodynamics admits transfer of energy as heat. For a process in a closed (no transfer of matter) thermodynamic system, the first law of thermodynamics relates changes in the internal energy (or other cardinal energy function, depending on the conditions of the transfer) of the system to those two modes of energy transfer, as work, and as heat. Adiabatic work is done without matter transfer and without heat transfer. In principle, in thermodynamics, for a process in a closed system, the quantity of heat transferred is defined by the amount of adiabatic work that would be needed to effect the change in the system that is occasioned by the heat transfer. In experimental practice, heat transfer is often estimated calorimetrically, through change of temperature of a known quantity of calorimetric material substance.
Energy can also be transferred to or from a system through transfer of matter. The possibility of such transfer defines the system as an open system, as opposed to a closed system. By definition, such transfer is neither as work nor as heat.
Changes in the potential energy of a body as a whole with respect to forces in its surroundings, and in the kinetic energy of the body moving as a whole with respect to its surroundings, are by definition excluded from the body's cardinal energy (examples are internal energy and enthalpy).
=== Nearly reversible transfer of energy by work in the surroundings ===
In the surroundings of a thermodynamic system, external to it, all the various mechanical and non-mechanical macroscopic forms of work can be converted into each other with no limitation in principle due to the laws of thermodynamics, so that the energy conversion efficiency can approach 100% in some cases; such conversion is required to be frictionless, and consequently adiabatic. In particular, in principle, all macroscopic forms of work can be converted into the mechanical work of lifting a weight, which was the original form of thermodynamic work considered by Carnot and Joule (see History section above). Some authors have considered this equivalence to the lifting of a weight as a defining characteristic of work. For example, with the apparatus of Joule's experiment in which, through pulleys, a weight descending in the surroundings drives the stirring of a thermodynamic system, the descent of the weight can be diverted by a re-arrangement of pulleys, so that it lifts another weight in the surroundings, instead of stirring the thermodynamic system.
Such conversion may be idealized as nearly frictionless, though it occurs relatively quickly. It usually comes about through devices that are not simple thermodynamic systems (a simple thermodynamic system is a homogeneous body of material substances). For example, the descent of the weight in Joule's stirring experiment reduces the weight's total energy. It is described as loss of gravitational potential energy by the weight, due to change of its macroscopic position in the gravity field, in contrast to, for example, loss of the weight's internal energy due to changes in its entropy, volume, and chemical composition. Though it occurs relatively rapidly, because the energy remains nearly fully available as work in one way or another, such diversion of work in the surroundings may be idealized as nearly reversible, or nearly perfectly efficient.
In contrast, the conversion of heat into work in a heat engine can never exceed the Carnot efficiency, as a consequence of the second law of thermodynamics. Such energy conversion, through work done relatively rapidly, in a practical heat engine, by a thermodynamic system on its surroundings, cannot be idealized, not even nearly, as reversible.
Thermodynamic work done by a thermodynamic system on its surroundings is defined so as to comply with this principle. Historically, thermodynamics was about how a thermodynamic system could do work on its surroundings.
=== Work done by and on a simple thermodynamic system ===
Thermodynamic work and ordinary mechanical work are to be distinguished. Thermodynamic work is defined by the changes of the thermodynamic system's own internal state variables, such as volume, electric polarization, and magnetization, but excluding temperature and entropy. Ordinary mechanical work includes work done by compression, as well as shaft work, stirring, and rubbing; but shaft work, stirring, and rubbing are not thermodynamic work in so far as they do not change the volume of the system, though they change the temperature or entropy of the system. Work without change of volume is known as isochoric work, for example when friction acts on the surface or in the interior of the system.
In a process of transfer of energy from or to a thermodynamic system, the change of internal energy of the system is defined in theory by the amount of adiabatic work that would have been necessary to reach the final from the initial state, such adiabatic work being measurable only through the externally measurable mechanical or deformation variables of the system, that provide full information about the forces exerted by the surroundings on the system during the process. In the case of some of Joule's measurements, the process was so arranged that some heating that occurred outside the system (in the substance of the paddles) by the frictional process also led to heat transfer from the paddles into the system during the process, so that the quantity of work done by the surrounds on the system could be calculated as shaft work, an external mechanical variable.
The amount of energy transferred as thermodynamic work is measured through quantities defined externally to the system of interest, that belong to its surroundings, but that are matched by internal state variables of the system, such as pressure. In an important sign convention, preferred in chemistry and by many physicists, thermodynamic work that adds to the internal energy of the system is counted as positive. On the other hand, for historical reasons, an oft-encountered sign convention, preferred in physics, is to consider thermodynamic work done by the system on its surroundings as positive.
=== Processes not described by macroscopic work ===
Transfer of thermal energy through direct contact between a closed system and its surroundings, is by the microscopic thermal motions of particles and their associated inter-molecular potential energies. The microscopic description of such processes are the province of statistical mechanics, not of macroscopic thermodynamics. Another kind of energy transfer is by radiation, performing work on the system. Radiative transfer of energy is irreversible in the sense that it occurs only from a hotter to a colder system. There are several forms of dissipative transduction of energy that can occur internally within a system at a microscopic level, such as friction including bulk and shear viscosity chemical reaction, unconstrained expansion as in Joule expansion and in diffusion, and phase change.
=== Open systems ===
For an open system, the first law of thermodynamics admits three forms of energy transfer, as work, as heat, and as energy associated with matter that is transferred. The latter cannot be split uniquely into heat and work components.
One-way convection of internal energy is a form a transport of energy but is not, as sometimes mistakenly supposed (a relic of the caloric theory of heat), transfer of energy as heat, because one-way convection is transfer of matter; nor is it transfer of energy as work. Nevertheless, if the wall between the system and its surroundings is thick and contains fluid, in the presence of a gravitational field, convective circulation within the wall can be considered as indirectly mediating transfer of energy as heat between the system and its surroundings, though the source and destination of the transferred energy are not in direct contact.
=== Fictively imagined reversible thermodynamic "processes" ===
For purposes of theoretical calculations about a thermodynamic system, one can imagine fictive idealized thermodynamic "processes" that occur so slowly that they do not incur friction within or on the surface of system; they can then be regarded as virtually reversible. These fictive processes proceed along paths on geometrical surfaces that are described exactly by a characteristic equation of the thermodynamic system. Those geometrical surfaces are the loci of possible states of thermodynamic equilibrium for the system. Really possible thermodynamic processes, occurring at practical rates, even when they occur only by work assessed in the surroundings as adiabatic, without heat transfer, always incur friction within the system, and so are always irreversible. The paths of such really possible processes always depart from those geometrical characteristic surfaces. Even when they occur only by work assessed in the surroundings as adiabatic, without heat transfer, such departures always entail entropy production.
=== Joule heating and rubbing ===
The definition of thermodynamic work is in terms of the changes of the system's extensive deformation (and chemical constitutive and certain other) state variables, such as volume, molar chemical constitution, or electric polarisation. Examples of state variables that are not extensive deformation or other such variables are temperature T and entropy S, as for example in the expression U = U(S, V, {Nj}). Changes of such variables are not actually physically measureable by use of a single simple adiabatic thermodynamic process; they are processes that occur neither by thermodynamic work nor by transfer of matter, and therefore are said occur by heat transfer. The quantity of thermodynamic work is defined as work done by the system on its surroundings. According to the second law of thermodynamics, such work is irreversible. To get an actual and precise physical measurement of a quantity of thermodynamic work, it is necessary to take account of the irreversibility by restoring the system to its initial condition by running a cycle, for example a Carnot cycle, that includes the target work as a step. The work done by the system on its surroundings is calculated from the quantities that constitute the whole cycle. A different cycle would be needed to actually measure the work done by the surroundings on the system. This is a reminder that rubbing the surface of a system appears to the rubbing agent in the surroundings as mechanical, though not thermodynamic, work done on the system, not as heat, but appears to the system as heat transferred to the system, not as thermodynamic work. The production of heat by rubbing is irreversible; historically, it was a piece of evidence for the rejection of the caloric theory of heat as a conserved substance. The irreversible process known as Joule heating also occurs through a change of a non-deformation extensive state variable.
Accordingly, in the opinion of Lavenda, work is not as primitive concept as is heat, which can be measured by calorimetry. This opinion does not negate the now customary thermodynamic definition of heat in terms of adiabatic work.
Known as a thermodynamic operation, the initiating factor of a thermodynamic process is, in many cases, a change in the permeability of a wall between the system and the surroundings. Rubbing is not a change in wall permeability. Kelvin's statement of the second law of thermodynamics uses the notion of an "inanimate material agency"; this notion is sometimes regarded as puzzling. The triggering of a process of rubbing can occur only in the surroundings, not in a thermodynamic system in its own state of internal thermodynamic equilibrium. Such triggering may be described as a thermodynamic operation.
== Formal definition ==
In thermodynamics, the quantity of work done by a closed system on its surroundings is defined by factors strictly confined to the interface of the surroundings with the system and to the surroundings of the system, for example, an extended gravitational field in which the system sits, that is to say, to things external to the system.
A main concern of thermodynamics is the properties of materials. Thermodynamic work is defined for the purposes of thermodynamic calculations about bodies of material, known as thermodynamic systems. Consequently, thermodynamic work is defined in terms of quantities that describe the states of materials, which appear as the usual thermodynamic state variables, such as volume, pressure, temperature, chemical composition, and electric polarization. For example, to measure the pressure inside a system from outside it, the observer needs the system to have a wall that can move by a measurable amount in response to pressure differences between the interior of the system and the surroundings. In this sense, part of the definition of a thermodynamic system is the nature of the walls that confine it.
Several kinds of thermodynamic work are especially important. One simple example is pressure–volume work. The pressure of concern is that exerted by the surroundings on the surface of the system, and the volume of interest is the negative of the increment of volume gained by the system from the surroundings. It is usually arranged that the pressure exerted by the surroundings on the surface of the system is well defined and equal to the pressure exerted by the system on the surroundings. This arrangement for transfer of energy as work can be varied in a particular way that depends on the strictly mechanical nature of pressure–volume work. The variation consists in letting the coupling between the system and surroundings be through a rigid rod that links pistons of different areas for the system and surroundings. Then for a given amount of work transferred, the exchange of volumes involves different pressures, inversely with the piston areas, for mechanical equilibrium. This cannot be done for the transfer of energy as heat because of its non-mechanical nature.
Another important kind of work is isochoric work, i.e., work that involves no eventual overall change of volume of the system between the initial and the final states of the process. Examples are friction on the surface of the system as in Rumford's experiment; shaft work such as in Joule's experiments; stirring of the system by a magnetic paddle inside it, driven by a moving magnetic field from the surroundings; and vibrational action on the system that leaves its eventual volume unchanged, but involves friction within the system. Isochoric mechanical work for a body in its own state of internal thermodynamic equilibrium is done only by the surroundings on the body, not by the body on the surroundings, so that the sign of isochoric mechanical work with the physics sign convention is always negative.
When work, for example pressure–volume work, is done on its surroundings by a closed system that cannot pass heat in or out because it is confined by an adiabatic wall, the work is said to be adiabatic for the system as well as for the surroundings. When mechanical work is done on such an adiabatically enclosed system by the surroundings, it can happen that friction in the surroundings is negligible, for example in the Joule experiment with the falling weight driving paddles that stir the system. Such work is adiabatic for the surroundings, even though it is associated with friction within the system. Such work may or may not be isochoric for the system, depending on the system and its confining walls. If it happens to be isochoric for the system (and does not eventually change other system state variables such as magnetization), it appears as a heat transfer to the system, and does not appear to be adiabatic for the system.
== Sign convention ==
In the early history of thermodynamics, a positive amount of work done by the system on the surroundings leads to energy being lost from the system. This historical sign convention has been used in many physics textbooks and is used in the present article.
According to the first law of thermodynamics for a closed system, any net change in the internal energy U must be fully accounted for, in terms of heat Q entering the system and work W done by the system:
Δ
U
=
Q
−
W
.
{\displaystyle \Delta U=Q-W.\;}
An alternate sign convention is to consider the work performed on the system by its surroundings as positive. This leads to a change in sign of the work, so that
Δ
U
=
Q
+
W
{\displaystyle \Delta U=Q+W}
. This convention has historically been used in chemistry, and has been adopted by most physics textbooks.
This equation reflects the fact that the heat transferred and the work done are not properties of the state of the system. Given only the initial state and the final state of the system, one can only say what the total change in internal energy was, not how much of the energy went out as heat, and how much as work. This can be summarized by saying that heat and work are not state functions of the system. This is in contrast to classical mechanics, where net work exerted by a particle is a state function.
== Pressure–volume work ==
Pressure–volume work (or PV or P-V work) occurs when the volume V of a system changes. PV work is often measured in units of litre-atmospheres where 1L·atm = 101.325J. However, the litre-atmosphere is not a recognized unit in the SI system of units, which measures P in pascals (Pa), V in m3, and PV in joules (J), where 1 J = 1 Pa·m3. PV work is an important topic in chemical thermodynamics.
For a process in a closed system, occurring slowly enough for accurate definition of the pressure on the inside of the system's wall that moves and transmits force to the surroundings, described as quasi-static, work is represented by the following equation between differentials:
δ
W
=
P
d
V
{\displaystyle \delta W=P\,dV}
where
δ
W
{\displaystyle \delta W}
(inexact differential) denotes an infinitesimal increment of work done by the system, transferring energy to the surroundings;
P
{\displaystyle P}
denotes the pressure inside the system, that it exerts on the moving wall that transmits force to the surroundings. In the alternative sign convention the right hand side has a negative sign.
d
V
{\displaystyle dV}
(exact differential) denotes an infinitesimal increment of the volume of the system.
Moreover,
W
=
∫
V
i
V
f
P
d
V
.
{\displaystyle W=\int _{V_{i}}^{V_{f}}P\,dV.}
where
W
{\displaystyle W}
denotes the work done by the system during the whole of the reversible process.
The first law of thermodynamics can then be expressed as
d
U
=
δ
Q
−
P
d
V
.
{\displaystyle dU=\delta Q-PdV\,.}
(In the alternative sign convention where W = work done on the system,
δ
W
=
−
P
d
V
{\displaystyle \delta W=-P\,dV}
. However,
d
U
=
δ
Q
−
P
d
V
{\displaystyle dU=\delta Q-P\,dV}
is unchanged.)
=== Path dependence ===
PV work is path-dependent and is, therefore, a thermodynamic process function. In general, the term
P
d
V
{\displaystyle P\,dV}
is not an exact differential. The statement that a process is quasi-static gives important information about the process but does not determine the P–V path uniquely, because the path can include several slow goings backwards and forward in volume, slowly enough to exclude friction within the system occasioned by departure from the quasi-static requirement. An adiabatic wall is one that does not permit passage of energy by conduction or radiation.
The first law of thermodynamics states that
Δ
U
=
Q
−
W
{\displaystyle \Delta U=Q-W}
.
For a quasi-static adiabatic process,
δ
Q
=
0
{\displaystyle \delta Q=0}
so that
Q
=
∫
δ
Q
=
0.
{\displaystyle Q=\int \delta Q=0.}
Also
δ
W
=
P
d
V
{\displaystyle \delta W=PdV}
so that
W
=
∫
δ
W
=
∫
P
d
V
.
{\displaystyle W=\int \delta W=\int P\,dV.}
It follows that
d
U
=
−
δ
W
{\displaystyle dU=-\delta W}
so that
Δ
U
=
−
∫
P
d
V
.
{\displaystyle \Delta U=-\int P\,dV.}
Internal energy is a state function so its change depends only on the initial and final states of a process. For a quasi-static adiabatic process, the change in internal energy is equal to minus the integral amount of work done by the system, so the work also depends only on the initial and final states of the process and is one and the same for every intermediate path. As a result, the work done by the system also depends on the initial and final states.
If the process path is other than quasi-static and adiabatic, there are indefinitely many different paths, with significantly different work amounts, between the initial and final states. (Again the internal energy change depends only on the initial and final states as it is a state function).
In the current mathematical notation, the differential
δ
W
{\displaystyle \delta W}
is an inexact differential.
In another notation, δW is written đW (with a horizontal line through the d). This notation indicates that đW is not an exact one-form. The line-through is merely a flag to warn us there is actually no function (0-form) W which is the potential of đW. If there were, indeed, this function W, we should be able to just use Stokes Theorem to evaluate this putative function, the potential of đW, at the boundary of the path, that is, the initial and final points, and therefore the work would be a state function. This impossibility is consistent with the fact that it does not make sense to refer to the work on a point in the PV diagram; work presupposes a path.
== Other mechanical types of work ==
There are several ways of doing mechanical work, each in some way related to a force acting through a distance. In basic mechanics, the work done by a constant force F on a body displaced a distance s in the direction of the force is given by
W
=
F
s
{\displaystyle W=Fs}
If the force is not constant, the work done is obtained by integrating the differential amount of work,
W
=
∫
1
2
F
d
s
.
{\displaystyle W=\int _{1}^{2}F\,ds.}
=== Rotational work ===
Energy transmission with a rotating shaft is very common in engineering practice. Often the torque T applied to the shaft is constant which means that the force F applied is constant. For a specified constant torque, the work done during n revolutions is determined as follows: A force F acting through a moment arm r generates a torque T
T
=
F
r
⟹
F
=
T
r
{\displaystyle T=Fr\implies F={\frac {T}{r}}}
This force acts through a distance s, which is related to the radius r by
s
=
2
r
π
n
{\displaystyle s=2r\pi n}
The shaft work is then determined from:
W
s
=
F
s
=
2
π
n
T
{\displaystyle W_{s}=Fs=2\pi nT}
The power transmitted through the shaft is the shaft work done per unit time, which is expressed as
W
˙
s
=
2
π
T
n
˙
{\displaystyle {\dot {W}}_{s}=2\pi T{\dot {n}}}
=== Spring work ===
When a force is applied on a spring, and the length of the spring changes by a differential amount dx, the work done is
∂
w
s
=
F
d
x
{\displaystyle \partial w_{s}=Fdx}
For linear elastic springs, the displacement x is proportional to the force applied
F
=
K
x
,
{\displaystyle F=Kx,}
where K is the spring constant and has the unit of N/m. The displacement x is measured from the undisturbed position of the spring (that is, X = 0 when F = 0). Substituting the two equations
W
s
=
1
2
k
(
x
1
2
−
x
2
2
)
{\displaystyle W_{s}={\frac {1}{2}}k\left(x_{1}^{2}-x_{2}^{2}\right)}
,
where x1 and x2 are the initial and the final displacement of the spring respectively, measured from the undisturbed position of the spring.
=== Work done on elastic solid bars ===
Solids are often modeled as linear springs because under the action of a force they contract or elongate, and when the force is lifted, they return to their original lengths, like a spring. This is true as long as the force is in the elastic range, that is, not large enough to cause permanent or plastic deformation. Therefore, the equations given for a linear spring can also be used for elastic solid bars. Alternately, we can determine the work associated with the expansion or contraction of an elastic solid bar by replacing the pressure P by its counterpart in solids, normal stress σ = F/A in the work expansion
W
=
∫
1
2
F
d
x
.
{\displaystyle W=\int _{1}^{2}F\,dx.}
W
=
∫
1
2
A
σ
d
x
.
{\displaystyle W=\int _{1}^{2}A\sigma \,dx.}
where A is the cross sectional area of the bar.
=== Work associated with the stretching of liquid film ===
Consider a liquid film such as a soap film suspended on a wire frame. Some force is required to stretch this film by the movable portion of the wire frame. This force is used to overcome the microscopic forces between molecules at the liquid-air interface. These microscopic forces are perpendicular to any line in the surface and the force generated by these forces per unit length is called the surface tension σ whose unit is N/m. Therefore, the work associated with the stretching of a film is called surface tension work, and is determined from
W
s
=
∫
1
2
σ
s
d
A
.
{\displaystyle W_{s}=\int _{1}^{2}\sigma _{s}\,dA.}
where dA=2b dx is the change in the surface area of the film. The factor 2 is due to the fact that the film has two surfaces in contact with air. The force acting on the moveable wire as a result of surface tension effects is F = 2b σ, where σ is the surface tension force per unit length.
== Free energy and exergy ==
The amount of useful work which may be extracted from a thermodynamic system is determined by the second law of thermodynamics. Under many practical situations this can be represented by the thermodynamic availability, or Exergy, function. Two important cases are: in thermodynamic systems where the temperature and volume are held constant, the measure of useful work attainable is the Helmholtz free energy function; and in systems where the temperature and pressure are held constant, the measure of useful work attainable is the Gibbs free energy.
== Non-mechanical forms of work ==
Non-mechanical work in thermodynamics is work caused by external force fields that a system is exposed to. The action of such forces can be initiated by events in the surroundings of the system, or by thermodynamic operations on the shielding walls of the system.
The non-mechanical work of force fields can have either positive or negative sign, work being done by the system on the surroundings, or vice versa. Work done by force fields can be done indefinitely slowly, so as to approach the fictive reversible quasi-static ideal, in which entropy is not created in the system by the process.
In thermodynamics, non-mechanical work is to be contrasted with mechanical work that is done by forces in immediate contact between the system and its surroundings. If the putative 'work' of a process cannot be defined as either long-range work or else as contact work, then sometimes it cannot be described by the thermodynamic formalism as work at all. Nevertheless, the thermodynamic formalism allows that energy can be transferred between an open system and its surroundings by processes for which work is not defined. An example is when the wall between the system and its surrounds is not considered as idealized and vanishingly thin, so that processes can occur within the wall, such as friction affecting the transfer of matter across the wall; in this case, the forces of transfer are neither strictly long-range nor strictly due to contact between the system and its surroundings; the transfer of energy can then be considered as convection, and assessed in sum just as transfer of internal energy. This is conceptually different from transfer of energy as heat through a thick fluid-filled wall in the presence of a gravitational field, between a closed system and its surroundings; in this case there may convective circulation within the wall but the process may still be considered as transfer of energy as heat between the system and its surroundings; if the whole wall is moved by the application of force from the surroundings, without change of volume of the wall, so as to change the volume of the system, then it is also at the same time transferring energy as work. A chemical reaction within a system can lead to electrical long-range forces and to electric current flow, which transfer energy as work between system and surroundings, though the system's chemical reactions themselves (except for the special limiting case in which in they are driven through devices in the surroundings so as to occur along a line of thermodynamic equilibrium) are always irreversible and do not directly interact with the surroundings of the system.
Non-mechanical work contrasts with pressure–volume work. Pressure–volume work is one of the two mainly considered kinds of mechanical contact work. A force acts on the interfacing wall between system and surroundings. The force is due to the pressure exerted on the interfacing wall by the material inside the system; that pressure is an internal state variable of the system, but is properly measured by external devices at the wall. The work is due to change of system volume by expansion or contraction of the system. If the system expands, in the present article it is said to do positive work on the surroundings. If the system contracts, in the present article it is said to do negative work on the surroundings. Pressure–volume work is a kind of contact work, because it occurs through direct material contact with the surrounding wall or matter at the boundary of the system. It is accurately described by changes in state variables of the system, such as the time courses of changes in the pressure and volume of the system. The volume of the system is classified as a "deformation variable", and is properly measured externally to the system, in the surroundings. Pressure–volume work can have either positive or negative sign. Pressure–volume work, performed slowly enough, can be made to approach the fictive reversible quasi-static ideal.
Non-mechanical work also contrasts with shaft work. Shaft work is the other of the two mainly considered kinds of mechanical contact work. It transfers energy by rotation, but it does not eventually change the shape or volume of the system. Because it does not change the volume of the system it is not measured as pressure–volume work, and it is called isochoric work. Considered solely in terms of the eventual difference between initial and final shapes and volumes of the system, shaft work does not make a change. During the process of shaft work, for example the rotation of a paddle, the shape of the system changes cyclically, but this does not make an eventual change in the shape or volume of the system. Shaft work is a kind of contact work, because it occurs through direct material contact with the surrounding matter at the boundary of the system. A system that is initially in a state of thermodynamic equilibrium cannot initiate any change in its internal energy. In particular, it cannot initiate shaft work. This explains the curious use of the phrase "inanimate material agency" by Kelvin in one of his statements of the second law of thermodynamics. Thermodynamic operations or changes in the surroundings are considered to be able to create elaborate changes such as indefinitely prolonged, varied, or ceased rotation of a driving shaft, while a system that starts in a state of thermodynamic equilibrium is inanimate and cannot spontaneously do that. Thus the sign of shaft work is always negative, work being done on the system by the surroundings. Shaft work can hardly be done indefinitely slowly; consequently it always produces entropy within the system, because it relies on friction or viscosity within the system for its transfer. The foregoing comments about shaft work apply only when one ignores that the system can store angular momentum and its related energy.
Examples of non-mechanical work modes include
Electric field work – where the force is defined by the surroundings' voltage (the electrical potential) and the generalized displacement is change of spatial distribution of electrical charge
Electrical polarization work – where the force is defined by the surroundings' electric field strength and the generalized displacement is change of the polarization of the medium (the sum of the electric dipole moments of the molecules)
Magnetic work – where the force is defined by the surroundings' magnetic field strength and the generalized displacement is change of total magnetic dipole moment
== Gravitational work ==
Gravitational work is defined by the force on a body measured in a gravitational field. It may cause a generalized displacement in the form of change of the spatial distribution of the matter within the system. The system gains internal energy (or other relevant cardinal quantity of energy, such as enthalpy) through internal friction. As seen by the surroundings, such frictional work appears as mechanical work done on the system, but as seen by the system, it appears as transfer of energy as heat. When the system is in its own state of internal thermodynamic equilibrium, its temperature is uniform throughout. If the volume and other extensive state variables, apart from entropy, are held constant over the process, then the transferred heat must appear as increased temperature and entropy; in a uniform gravitational field, the pressure of the system will be greater at the bottom than at the top.
By definition, the relevant cardinal energy function is distinct from the gravitational potential energy of the system as a whole; the latter may also change as a result of gravitational work done by the surroundings on the system. The gravitational potential energy of the system is a component of its total energy, alongside its other components, namely its cardinal thermodynamic (e.g. internal) energy and its kinetic energy as a whole system in motion.
== See also ==
Electrochemical hydrogen compressor
Chemical reactions
Microstate (statistical mechanics) - includes Microscopic definition of work
== References == | Wikipedia/Work_(thermodynamics) |
The design of experiments (DOE), also known as experiment design or experimental design, is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation. The term is generally associated with experiments in which the design introduces conditions that directly affect the variation, but may also refer to the design of quasi-experiments, in which natural conditions that influence the variation are selected for observation.
In its simplest form, an experiment aims at predicting the outcome by introducing a change of the preconditions, which is represented by one or more independent variables, also referred to as "input variables" or "predictor variables." The change in one or more independent variables is generally hypothesized to result in a change in one or more dependent variables, also referred to as "output variables" or "response variables." The experimental design may also identify control variables that must be held constant to prevent external factors from affecting the results. Experimental design involves not only the selection of suitable independent, dependent, and control variables, but planning the delivery of the experiment under statistically optimal conditions given the constraints of available resources. There are multiple approaches for determining the set of design points (unique combinations of the settings of the independent variables) to be used in the experiment.
Main concerns in experimental design include the establishment of validity, reliability, and replicability. For example, these concerns can be partially addressed by carefully choosing the independent variable, reducing the risk of measurement error, and ensuring that the documentation of the method is sufficiently detailed. Related concerns include achieving appropriate levels of statistical power and sensitivity.
Correctly designed experiments advance knowledge in the natural and social sciences and engineering, with design of experiments methodology recognised as a key tool in the successful implementation of a Quality by Design (QbD) framework. Other applications include marketing and policy making. The study of the design of experiments is an important topic in metascience.
== History ==
=== Statistical experiments, following Charles S. Peirce ===
A theory of statistical inference was developed by Charles S. Peirce in "Illustrations of the Logic of Science" (1877–1878) and "A Theory of Probable Inference" (1883), two publications that emphasized the importance of randomization-based inference in statistics.
==== Randomized experiments ====
Charles S. Peirce randomly assigned volunteers to a blinded, repeated-measures design to evaluate their ability to discriminate weights.
Peirce's experiment inspired other researchers in psychology and education, which developed a research tradition of randomized experiments in laboratories and specialized textbooks in the 1800s.
==== Optimal designs for regression models ====
Charles S. Peirce also contributed the first English-language publication on an optimal design for regression models in 1876. A pioneering optimal design for polynomial regression was suggested by Gergonne in 1815. In 1918, Kirstine Smith published optimal designs for polynomials of degree six (and less).
=== Sequences of experiments ===
The use of a sequence of experiments, where the design of each may depend on the results of previous experiments, including the possible decision to stop experimenting, is within the scope of sequential analysis, a field that was pioneered by Abraham Wald in the context of sequential tests of statistical hypotheses. Herman Chernoff wrote an overview of optimal sequential designs, while adaptive designs have been surveyed by S. Zacks. One specific type of sequential design is the "two-armed bandit", generalized to the multi-armed bandit, on which early work was done by Herbert Robbins in 1952.
== Fisher's principles ==
A methodology for designing experiments was proposed by Ronald Fisher, in his innovative books: The Arrangement of Field Experiments (1926) and The Design of Experiments (1935). Much of his pioneering work dealt with agricultural applications of statistical methods. As a mundane example, he described how to test the lady tasting tea hypothesis, that a certain lady could distinguish by flavour alone whether the milk or the tea was first placed in the cup. These methods have been broadly adapted in biological, psychological, and agricultural research.
Comparison
In some fields of study it is not possible to have independent measurements to a traceable metrology standard. Comparisons between treatments are much more valuable and are usually preferable, and often compared against a scientific control or traditional treatment that acts as baseline.
Randomization
Random assignment is the process of assigning individuals at random to groups or to different groups in an experiment, so that each individual of the population has the same chance of becoming a participant in the study. The random assignment of individuals to groups (or conditions within a group) distinguishes a rigorous, "true" experiment from an observational study or "quasi-experiment". There is an extensive body of mathematical theory that explores the consequences of making the allocation of units to treatments by means of some random mechanism (such as tables of random numbers, or the use of randomization devices such as playing cards or dice). Assigning units to treatments at random tends to mitigate confounding, which makes effects due to factors other than the treatment to appear to result from the treatment.
The risks associated with random allocation (such as having a serious imbalance in a key characteristic between a treatment group and a control group) are calculable and hence can be managed down to an acceptable level by using enough experimental units. However, if the population is divided into several subpopulations that somehow differ, and the research requires each subpopulation to be equal in size, stratified sampling can be used. In that way, the units in each subpopulation are randomized, but not the whole sample. The results of an experiment can be generalized reliably from the experimental units to a larger statistical population of units only if the experimental units are a random sample from the larger population; the probable error of such an extrapolation depends on the sample size, among other things.
Statistical replication
Measurements are usually subject to variation and measurement uncertainty; thus they are repeated and full experiments are replicated to help identify the sources of variation, to better estimate the true effects of treatments, to further strengthen the experiment's reliability and validity, and to add to the existing knowledge of the topic. However, certain conditions must be met before the replication of the experiment is commenced: the original research question has been published in a peer-reviewed journal or widely cited, the researcher is independent of the original experiment, the researcher must first try to replicate the original findings using the original data, and the write-up should state that the study conducted is a replication study that tried to follow the original study as strictly as possible.
Blocking
Blocking is the non-random arrangement of experimental units into groups (blocks) consisting of units that are similar to one another. Blocking reduces known but irrelevant sources of variation between units and thus allows greater precision in the estimation of the source of variation under study.
Orthogonality
Orthogonality concerns the forms of comparison (contrasts) that can be legitimately and efficiently carried out. Contrasts can be represented by vectors and sets of orthogonal contrasts are uncorrelated and independently distributed if the data are normal. Because of this independence, each orthogonal treatment provides different information to the others. If there are T treatments and T − 1 orthogonal contrasts, all the information that can be captured from the experiment is obtainable from the set of contrasts.
Multifactorial experiments
Use of multifactorial experiments instead of the one-factor-at-a-time method. These are efficient at evaluating the effects and possible interactions of several factors (independent variables). Analysis of experiment design is built on the foundation of the analysis of variance, a collection of models that partition the observed variance into components, according to what factors the experiment must estimate or test.
== Example ==
This example of design experiments is attributed to Harold Hotelling, building on examples from Frank Yates. The experiments designed in this example involve combinatorial designs.
Weights of eight objects are measured using a pan balance and set of standard weights. Each weighing measures the weight difference between objects in the left pan and any objects in the right pan by adding calibrated weights to the lighter pan until the balance is in equilibrium. Each measurement has a random error. The average error is zero; the standard deviations of the probability distribution of the errors is the same number σ on different weighings; errors on different weighings are independent. Denote the true weights by
θ
1
,
…
,
θ
8
.
{\displaystyle \theta _{1},\dots ,\theta _{8}.\,}
We consider two different experiments:
Weigh each object in one pan, with the other pan empty. Let Xi be the measured weight of the object, for i = 1, ..., 8.
Do the eight weighings according to the following schedule—a weighing matrix:
left pan
right pan
1st weighing:
1
2
3
4
5
6
7
8
(empty)
2nd:
1
2
3
8
4
5
6
7
3rd:
1
4
5
8
2
3
6
7
4th:
1
6
7
8
2
3
4
5
5th:
2
4
6
8
1
3
5
7
6th:
2
5
7
8
1
3
4
6
7th:
3
4
7
8
1
2
5
6
8th:
3
5
6
8
1
2
4
7
{\displaystyle {\begin{array}{lcc}&{\text{left pan}}&{\text{right pan}}\\\hline {\text{1st weighing:}}&1\ 2\ 3\ 4\ 5\ 6\ 7\ 8&{\text{(empty)}}\\{\text{2nd:}}&1\ 2\ 3\ 8\ &4\ 5\ 6\ 7\\{\text{3rd:}}&1\ 4\ 5\ 8\ &2\ 3\ 6\ 7\\{\text{4th:}}&1\ 6\ 7\ 8\ &2\ 3\ 4\ 5\\{\text{5th:}}&2\ 4\ 6\ 8\ &1\ 3\ 5\ 7\\{\text{6th:}}&2\ 5\ 7\ 8\ &1\ 3\ 4\ 6\\{\text{7th:}}&3\ 4\ 7\ 8\ &1\ 2\ 5\ 6\\{\text{8th:}}&3\ 5\ 6\ 8\ &1\ 2\ 4\ 7\end{array}}}
Let Yi be the measured difference for i = 1, ..., 8. Then the estimated value of the weight θ1 is
θ
^
1
=
Y
1
+
Y
2
+
Y
3
+
Y
4
−
Y
5
−
Y
6
−
Y
7
−
Y
8
8
.
{\displaystyle {\widehat {\theta }}_{1}={\frac {Y_{1}+Y_{2}+Y_{3}+Y_{4}-Y_{5}-Y_{6}-Y_{7}-Y_{8}}{8}}.}
Similar estimates can be found for the weights of the other items:
θ
^
2
=
Y
1
+
Y
2
−
Y
3
−
Y
4
+
Y
5
+
Y
6
−
Y
7
−
Y
8
8
.
θ
^
3
=
Y
1
+
Y
2
−
Y
3
−
Y
4
−
Y
5
−
Y
6
+
Y
7
+
Y
8
8
.
θ
^
4
=
Y
1
−
Y
2
+
Y
3
−
Y
4
+
Y
5
−
Y
6
+
Y
7
−
Y
8
8
.
θ
^
5
=
Y
1
−
Y
2
+
Y
3
−
Y
4
−
Y
5
+
Y
6
−
Y
7
+
Y
8
8
.
θ
^
6
=
Y
1
−
Y
2
−
Y
3
+
Y
4
+
Y
5
−
Y
6
−
Y
7
+
Y
8
8
.
θ
^
7
=
Y
1
−
Y
2
−
Y
3
+
Y
4
−
Y
5
+
Y
6
+
Y
7
−
Y
8
8
.
θ
^
8
=
Y
1
+
Y
2
+
Y
3
+
Y
4
+
Y
5
+
Y
6
+
Y
7
+
Y
8
8
.
{\displaystyle {\begin{aligned}{\widehat {\theta }}_{2}&={\frac {Y_{1}+Y_{2}-Y_{3}-Y_{4}+Y_{5}+Y_{6}-Y_{7}-Y_{8}}{8}}.\\[5pt]{\widehat {\theta }}_{3}&={\frac {Y_{1}+Y_{2}-Y_{3}-Y_{4}-Y_{5}-Y_{6}+Y_{7}+Y_{8}}{8}}.\\[5pt]{\widehat {\theta }}_{4}&={\frac {Y_{1}-Y_{2}+Y_{3}-Y_{4}+Y_{5}-Y_{6}+Y_{7}-Y_{8}}{8}}.\\[5pt]{\widehat {\theta }}_{5}&={\frac {Y_{1}-Y_{2}+Y_{3}-Y_{4}-Y_{5}+Y_{6}-Y_{7}+Y_{8}}{8}}.\\[5pt]{\widehat {\theta }}_{6}&={\frac {Y_{1}-Y_{2}-Y_{3}+Y_{4}+Y_{5}-Y_{6}-Y_{7}+Y_{8}}{8}}.\\[5pt]{\widehat {\theta }}_{7}&={\frac {Y_{1}-Y_{2}-Y_{3}+Y_{4}-Y_{5}+Y_{6}+Y_{7}-Y_{8}}{8}}.\\[5pt]{\widehat {\theta }}_{8}&={\frac {Y_{1}+Y_{2}+Y_{3}+Y_{4}+Y_{5}+Y_{6}+Y_{7}+Y_{8}}{8}}.\end{aligned}}}
The question of design of experiments is: which experiment is better?
The variance of the estimate X1 of θ1 is σ2 if we use the first experiment. But if we use the second experiment, the variance of the estimate given above is σ2/8. Thus the second experiment gives us 8 times as much precision for the estimate of a single item, and estimates all items simultaneously, with the same precision. What the second experiment achieves with eight would require 64 weighings if the items are weighed separately. However, note that the estimates for the items obtained in the second experiment have errors that correlate with each other.
Many problems of the design of experiments involve combinatorial designs, as in this example and others.
== Avoiding false positives ==
False positive conclusions, often resulting from the pressure to publish or the author's own confirmation bias, are an inherent hazard in many fields.
Use of double-blind designs can prevent biases potentially leading to false positives in the data collection phase. When a double-blind design is used, participants are randomly assigned to experimental groups but the researcher is unaware of what participants belong to which group. Therefore, the researcher can not affect the participants' response to the intervention.
Experimental designs with undisclosed degrees of freedom are a problem, in that they can lead to conscious or unconscious "p-hacking": trying multiple things until you get the desired result. It typically involves the manipulation – perhaps unconsciously – of the process of statistical analysis and the degrees of freedom until they return a figure below the p<.05 level of statistical significance.
P-hacking can be prevented by preregistering researches, in which researchers have to send their data analysis plan to the journal they wish to publish their paper in before they even start their data collection, so no data manipulation is possible.
Another way to prevent this is taking a double-blind design to the data-analysis phase, making the study triple-blind, where the data are sent to a data-analyst unrelated to the research who scrambles up the data so there is no way to know which participants belong to before they are potentially taken away as outliers.
Clear and complete documentation of the experimental methodology is also important in order to support replication of results.
== Discussion topics when setting up an experimental design ==
An experimental design or randomized clinical trial requires careful consideration of several factors before actually doing the experiment. An experimental design is the laying out of a detailed experimental plan in advance of doing the experiment. Some of the following topics have already been discussed in the principles of experimental design section:
How many factors does the design have, and are the levels of these factors fixed or random?
Are control conditions needed, and what should they be?
Manipulation checks: did the manipulation really work?
What are the background variables?
What is the sample size? How many units must be collected for the experiment to be generalisable and have enough power?
What is the relevance of interactions between factors?
What is the influence of delayed effects of substantive factors on outcomes?
How do response shifts affect self-report measures?
How feasible is repeated administration of the same measurement instruments to the same units at different occasions, with a post-test and follow-up tests?
What about using a proxy pretest?
Are there confounding variables?
Should the client/patient, researcher or even the analyst of the data be blind to conditions?
What is the feasibility of subsequent application of different conditions to the same units?
How many of each control and noise factors should be taken into account?
The independent variable of a study often has many levels or different groups. In a true experiment, researchers can have an experimental group, which is where their intervention testing the hypothesis is implemented, and a control group, which has all the same element as the experimental group, without the interventional element. Thus, when everything else except for one intervention is held constant, researchers can certify with some certainty that this one element is what caused the observed change. In some instances, having a control group is not ethical. This is sometimes solved using two different experimental groups. In some cases, independent variables cannot be manipulated, for example when testing the difference between two groups who have a different disease, or testing the difference between genders (obviously variables that would be hard or unethical to assign participants to). In these cases, a quasi-experimental design may be used.
== Causal attributions ==
In the pure experimental design, the independent (predictor) variable is manipulated by the researcher – that is – every participant of the research is chosen randomly from the population, and each participant chosen is assigned randomly to conditions of the independent variable. Only when this is done is it possible to certify with high probability that the reason for the differences in the outcome variables are caused by the different conditions. Therefore, researchers should choose the experimental design over other design types whenever possible. However, the nature of the independent variable does not always allow for manipulation. In those cases, researchers must be aware of not certifying about causal attribution when their design doesn't allow for it. For example, in observational designs, participants are not assigned randomly to conditions, and so if there are differences found in outcome variables between conditions, it is likely that there is something other than the differences between the conditions that causes the differences in outcomes, that is – a third variable. The same goes for studies with correlational design.
== Statistical control ==
It is best that a process be in reasonable statistical control prior to conducting designed experiments. When this is not possible, proper blocking, replication, and randomization allow for the careful conduct of designed experiments.
To control for nuisance variables, researchers institute control checks as additional measures. Investigators should ensure that uncontrolled influences (e.g., source credibility perception) do not skew the findings of the study. A manipulation check is one example of a control check. Manipulation checks allow investigators to isolate the chief variables to strengthen support that these variables are operating as planned.
One of the most important requirements of experimental research designs is the necessity of eliminating the effects of spurious, intervening, and antecedent variables. In the most basic model, cause (X) leads to effect (Y). But there could be a third variable (Z) that influences (Y), and X might not be the true cause at all. Z is said to be a spurious variable and must be controlled for. The same is true for intervening variables (a variable in between the supposed cause (X) and the effect (Y)), and anteceding variables (a variable prior to the supposed cause (X) that is the true cause). When a third variable is involved and has not been controlled for, the relation is said to be a zero order relationship. In most practical applications of experimental research designs there are several causes (X1, X2, X3). In most designs, only one of these causes is manipulated at a time.
== Experimental designs after Fisher ==
Some efficient designs for estimating several main effects were found independently and in near succession by Raj Chandra Bose and K. Kishen in 1940 at the Indian Statistical Institute, but remained little known until the Plackett–Burman designs were published in Biometrika in 1946. About the same time, C. R. Rao introduced the concepts of orthogonal arrays as experimental designs. This concept played a central role in the development of Taguchi methods by Genichi Taguchi, which took place during his visit to Indian Statistical Institute in early 1950s. His methods were successfully applied and adopted by Japanese and Indian industries and subsequently were also embraced by US industry albeit with some reservations.
In 1950, Gertrude Mary Cox and William Gemmell Cochran published the book Experimental Designs, which became the major reference work on the design of experiments for statisticians for years afterwards.
Developments of the theory of linear models have encompassed and surpassed the cases that concerned early writers. Today, the theory rests on advanced topics in linear algebra, algebra and combinatorics.
As with other branches of statistics, experimental design is pursued using both frequentist and Bayesian approaches: In evaluating statistical procedures like experimental designs, frequentist statistics studies the sampling distribution while Bayesian statistics updates a probability distribution on the parameter space.
Some important contributors to the field of experimental designs are C. S. Peirce, R. A. Fisher, F. Yates, R. C. Bose, A. C. Atkinson, R. A. Bailey, D. R. Cox, G. E. P. Box, W. G. Cochran, W. T. Federer, V. V. Fedorov, A. S. Hedayat, J. Kiefer, O. Kempthorne, J. A. Nelder, Andrej Pázman, Friedrich Pukelsheim, D. Raghavarao, C. R. Rao, Shrikhande S. S., J. N. Srivastava, William J. Studden, G. Taguchi and H. P. Wynn.
The textbooks of D. Montgomery, R. Myers, and G. Box/W. Hunter/J.S. Hunter have reached generations of students and practitioners. Furthermore, there is ongoing discussion of experimental design in the context of model building for models either static or dynamic models, also known as system identification.
== Human participant constraints ==
Laws and ethical considerations preclude some carefully designed
experiments with human subjects. Legal constraints are dependent on
jurisdiction. Constraints may involve
institutional review boards, informed consent
and confidentiality affecting both clinical (medical) trials and
behavioral and social science experiments.
In the field of toxicology, for example, experimentation is performed
on laboratory animals with the goal of defining safe exposure limits
for humans. Balancing
the constraints are views from the medical field. Regarding the randomization of patients,
"... if no one knows which therapy is better, there is no ethical
imperative to use one therapy or another." (p 380) Regarding
experimental design, "...it is clearly not ethical to place subjects
at risk to collect data in a poorly designed study when this situation
can be easily avoided...". (p 393)
== See also ==
Adversarial collaboration – Method of research
Bayesian experimental design
Block design – Structure in combinatorial mathematics
Box–Behnken design – Experimental designs for response surface methodology
Central composite design – Experimental design in statistical mathematics
Clinical trial – Phase of clinical research in medicine
Clinical study design – Plan for research in clinical medicine
Computer experiment – Experiment used to study computer simulation
Control variable – Experimental element which is not changed throughout the experiment
Controlling for a variable – Binning data according to measured values of the variable
Experimetrics (econometrics-related experiments)
Factor analysis – Statistical method
Fractional factorial design – Statistical experimental design approach
Glossary of experimental design
Grey box model – Mathematical data production model with limited structure
Industrial engineering – Branch of engineering which deals with the optimization of complex processes or systems
Instrument effect
Law of large numbers – Averages of repeated trials converge to the expected value
Manipulation checks – certain kinds of secondary evaluations of an experimentPages displaying wikidata descriptions as a fallback
Multifactor design of experiments software
One-factor-at-a-time method – Method of designing experiments
Optimal design – Experimental design that is optimal with respect to some statistical criterionPages displaying short descriptions of redirect targets
Plackett–Burman design – Type of experimental design
Probabilistic design – Discipline within engineering design
Protocol (natural sciences) – Procedural method for the design and implementation of an experimentPages displaying short descriptions of redirect targets
Quasi-experimental design – Empirical interventional studyPages displaying short descriptions of redirect targets
Randomized block design – Design of experiments to collect similar contexts togetherPages displaying short descriptions of redirect targets
Randomized controlled trial – Form of scientific experiment
Research design – Overall strategy utilized to carry out research
Robust parameter design – technique for design of processes and experimentsPages displaying wikidata descriptions as a fallback
Sample size determination – Statistical considerations on how many observations to make
Supersaturated designs – Type of experimental design
Royal Commission on Animal Magnetism – 1784 French scientific bodies' investigations involving systematic controlled trials
Survey sampling – Statistical selection process
System identification – Statistical methods to build mathematical models of dynamical systems from measured data
Taguchi methods – Statistical methods to improve the quality of manufactured goods
== References ==
=== Sources ===
== External links ==
A chapter from a "NIST/SEMATECH Handbook on Engineering Statistics" at NIST
Box–Behnken designs from a "NIST/SEMATECH Handbook on Engineering Statistics" at NIST | Wikipedia/Experimental_design |
Mill's methods are five methods of induction described by philosopher John Stuart Mill in his 1843 book A System of Logic. They are intended to establish a causal relationship between two or more groups of data, analyzing their respective differences and similarities.
== The methods ==
=== Direct method of agreement ===
If two or more instances of the phenomenon under investigation have only one circumstance in common, the circumstance in which alone all the instances agree, is the cause (or effect) of the given phenomenon.
For a property to be a necessary condition it must always be present if the effect is present. Since this is so, then we are interested in looking at cases where the effect is present and taking note of which properties, among those considered to be 'possible necessary conditions' are present and which are absent. Obviously, any properties which are absent when the effect is present cannot be necessary conditions for the effect. This method is also referred to more generally within comparative politics as the most different systems design.
Symbolically, the method of agreement can be represented as:
A B C D occur together with w x y z
A E F G occur together with w t u v
——————————————————
Therefore A is the cause, or the effect, of w.
To further illustrate this concept, consider two structurally different countries. Country A is a former colony, has a centre-left government, and has a federal system with two levels of government. Country B has never been a colony, has a centre-left government and is a unitary state. One factor that both countries have in common, the dependent variable in this case, is that they have a system of universal health care. Comparing the factors known about the countries above, a comparative political scientist would conclude that the government sitting on the centre-left of the spectrum would be the independent variable which causes a system of universal health care, since it is the only one of the factors examined which holds constant between the two countries, and the theoretical backing for that relationship is sound; social democratic (centre-left) policies often include universal health care.
=== Method of difference ===
If an instance in which the phenomenon under investigation occurs, and an instance in which it does not occur, have every circumstance save one in common, that one occurring only in the former; the circumstance in which alone the two instances differ, is the effect, or cause, or an indispensable part of the cause, of the phenomenon.
This method is also known more generally as the most similar systems design within comparative politics.
A B C D occur together with w x y z
B C D occur together with x y z
——————————————————
Therefore A is the cause, or the effect, or a part of the cause of w.
As an example of the method of difference, consider two similar countries. Country A has a centre-right government, a unitary system and was a former colony. Country B has a centre-right government, a unitary system but was never a colony. The difference between the countries is that Country A readily supports anti-colonial initiatives, whereas Country B does not. The method of difference would identify the independent variable to be the status of each country as a former colony or not, with the dependant variable being supportive for anti-colonial initiatives. This is because, out of the two similar countries compared, the difference between the two is whether or not they were formerly a colony. This then explains the difference on the values of the dependent variable, with the former colony being more likely to support decolonization than the country with no history of being a colony.
=== Indirect method of difference ===
If two or more instances in which the phenomenon occurs have only one circumstance in common, while two or more instances in which it does not occur have nothing in common save the absence of that circumstance; the circumstance in which alone the two sets of instances differ, is the effect, or cause, or a necessary part of the cause, of the phenomenon.
Also called the "Joint Method of Agreement and Difference", this principle is a combination of two methods of agreement. Despite the name, it is weaker than the direct method of difference and does not include it.
Symbolically, the Joint method of agreement and difference can be represented as:
A B C occur together with x y z
A D E occur together with x v w
F G occur with y w
——————————————————
Therefore A is the cause, or the effect, or a part of the cause of x.
=== Method of residue ===
Subduct from any phenomenon such part as is known by previous inductions to be the effect of certain antecedents, and the residue of the phenomenon is the effect of the remaining antecedents.
If a range of factors are believed to cause a range of phenomena, and we have matched all the factors, except one, with all the phenomena, except one, then the remaining phenomenon can be attributed to the remaining factor.
Symbolically, the Method of Residue can be represented as:
A B C occur together with x y z
B is known to be the cause of y
C is known to be the cause of z
——————————————————
Therefore A is the cause or effect of x.
=== Method of concomitant variations ===
Whatever phenomenon varies in any manner whenever another phenomenon varies in some particular manner, is either a cause or an effect of that phenomenon, or is connected with it through some fact of causation.
If across a range of circumstances leading to a phenomenon, some property of the phenomenon varies in tandem with some factor existing in the circumstances, then the phenomenon can be associated with that factor. For instance, suppose that various samples of water, each containing both salt and lead, were found to be toxic. If the level of toxicity varied in tandem with the level of lead, one could attribute the toxicity to the presence of lead.
Symbolically, the method of concomitant variation can be represented as (with ± representing a shift):
A B C occur together with x y z
A± B C results in x± y z.
—————————————————————
Therefore A and x are causally connected
Unlike the preceding four inductive methods, the method of concomitant variation doesn't involve the elimination of any circumstance. Changing the magnitude of one factor results in the change in the magnitude of another factor.
== See also ==
Causal inference
Controlled scientific experiments
Baconian method
Bayesian network
Koch's postulates
== References ==
== Further reading ==
Copi, Irving M.; Cohen, Carl (2001). Introduction to Logic. Prentice Hall. ISBN 978-0-13-033735-1.
Ducheyne, Steffen (2008). "J.S. Mill's Canons of Induction: From true causes to provisional ones". History and Philosophy of Logic. 29 (4): 361–376. CiteSeerX 10.1.1.671.6256. doi:10.1080/01445340802164377. S2CID 170478055.
Kreeft, Peter (2009). Socratic Logic, A Logic Text Using Socratic Method, Platonic Questions, and Aristotelian Principles. St. Augustine's Press, South Bend, Indiana. ISBN 978-1-890318-89-5.
== External links ==
Causal Reasoning—Provides some examples
Mill's methods for identifying causes—Provides some examples | Wikipedia/Mill's_Methods |
Science in the ancient world encompasses the earliest history of science from the protoscience of prehistory and ancient history to late antiquity. In ancient times, culture and knowledge were passed through oral tradition. The development of writing further enabled the preservation of knowledge and culture, allowing information to spread accurately.
The earliest scientific traditions of the ancient world developed in the Ancient Near East, with Ancient Egypt and Babylonia in Mesopotamia. Later traditions of science during classical antiquity were advanced in ancient Persia, Greece, Rome, India, China, and Mesoamerica. Aside from alchemy and astrology that waned in importance during the Age of Enlightenment, civilizations of the ancient world laid the roots of modern sciences.
== Ancient Near East ==
=== Mesopotamia ===
Around 3500 BC, in Sumer (now Iraq), the Mesopotamian people began preserving some observations of the cosmos with extremely thorough numerical data.
==== Mathematics ====
Pythagorean theorem has demonstrated evidence of ancient writing forms. It was recorded in the 18th century BC on the Mesopotamian cuneiform tablet known as Plimpton 322. The columns of numbers in the tablet generates several Pythagorean triples such as (3, 4, 5) and (5, 12, 13).
==== Astronomy ====
Babylonian astronomy was "the first and highly successful attempt at giving a refined mathematical description of astronomical phenomena." According to the historian Asger Aaboe, "all subsequent varieties of scientific astronomy, in the Hellenistic world, in India, in Islam, and in the West—if not indeed all subsequent endeavour in the exact sciences—depend upon Babylonian astronomy in decisive and fundamental ways".
Scribes recorded observations of the cosmos such as the motions of the stars, the planets, and the Moon on clay tablets. The cuneiform style of writing revealed that astronomers used mathematical calculations to observe the motions of the planets. Astronomical periods identified by Mesopotamian scientists remain widely used in Western calendars: the solar year and the lunar month. Using data, Mesopotamians developed arithmetical methods to compute the changing length of daylight during the year, and to predict the Lunar phases and planets along with eclipses of the Sun and Moon.
Only a few astronomers' names are known, such as Kidinnu, a Chaldean astronomer and mathematician. Kiddinu's value for the solar year is in use for modern calendars. Hipparchus used this data to calculate the precession of the Earth's axis. Fifteen hundred years after Kiddinu, Al-Battani used the collected data and improved Hipparchus' value for the precession. Al-Batani's value, 54.5 arc-seconds per year, compares well with the current value of 49.8 arc-seconds per year (26,000 years for Earth's axis to round the circle of nutation). Astronomy and astrology were considered to be the same thing, as evidenced by the practice of this science in Babylonia by priests. Mesopotamian astronomy became more astrology-based later in the civilisation, studying the stars in terms of horoscopes and omens.
==== Archaeology ====
Following the Late Bronze Age collapse, the practice of various sciences continued in post–Iron Age Mesopotamia. For instance, in the nascent history of archaeology, king Nabonidus of the Neo-Babylonian Empire was a pioneer in the analysis of artifacts. Foundation deposits of king Naram-Sin of the Akkadian Empire dated circa 2200 BC were discovered and analyzed by Nabonidus around the 550 BC. These deposits belonged to the temples of Shamash the sun god and the warrior goddess Annunitum in Sippar, and Naram-Sin's temple to the moon god in Harran, which were restored by Nabonidus. Nabonidus was the first known figure in history to make an attempt at dating archaeological artifacts found at excavated sites, though his estimates were inaccurate by hundreds of years.
=== Egypt ===
Significant advances in ancient Egypt included astronomy, mathematics, and medicine. Egypt was also a centre of alchemical research for much of the Western world.
==== Architecture, engineering, and mathematics ====
Ancient Egyptian geometry was a necessary outgrowth of surveying to preserve the layout and ownership of farmland, which was flooded annually by the Nile. The 3–4–5 right triangle and other rules of thumb served to represent rectilinear structures, including architecture such as post and lintel structures.
==== Writing ====
Egyptian hieroglyphs served as the basis for the Proto-Sinaitic script, the ancestor of the Phoenician alphabet from which the later Hebrew, Greek, Latin, Arabic, and Cyrillic alphabets were derived. The city of Alexandria retained preeminence with its library, which was damaged by fire when it fell under Roman rule, being destroyed before 642. With it, a large amount of antique literature and knowledge was lost.
==== Medicine ====
The Edwin Smith Papyrus is one of the first medical documents still extant, and perhaps the earliest document that attempts to describe and analyse the brain: it might be seen as the very beginnings of modern neuroscience. However, while ancient Egyptian medicine had some effective practices, it was not without its ineffective and sometimes harmful practices. Medical historians believe that ancient Egyptian pharmacology was largely ineffective. Nevertheless, it applies the following components: examination, diagnosis, treatment and prognosis, to the treatment of disease, which display strong parallels to the basic empirical method of science and according to G. E. R. Lloyd played a significant role in the development of this methodology. The Ebers papyrus (c. 1550 BC) also contains evidence of traditional empiricism.
According to a paper published by Michael D. Parkins, 72% of 260 medical prescriptions in the Hearst Papyrus had no curative elements. According to Parkins, sewage pharmacology first began in ancient Egypt and was continued through the Middle Ages. Practices such as applying cow dung to wounds, ear piercing and tattooing, and chronic ear infections were important factors in developing tetanus. Frank J. Snoek wrote that Egyptian medicine used fly specks, lizard blood, swine teeth, and other such remedies which he believes could have been harmful.
=== Persia ===
In the Sasanian Empire, great attention was given to mathematics and astronomy. The Academy of Gondishapur is a prominent example in this regard. Astronomical tables date to this period, and Sassanid observatories were later imitated by Muslim astronomers and astrologers of the Islamic Golden Age. In the mid-Sassanid era, an influx of knowledge came to Persia from the West in the form of views and traditions of Greece which, following the spread of Christianity, accompanied Syriac language. In the Early Middle Ages, Persia became a stronghold of Islamic science. After the establishment of Umayyad and Abbasid states, many Iranian scholars were sent to the capitals of these Islamic dynasties.
== Greco-Roman world ==
The legacy of classical antiquity included substantial advances in factual knowledge, especially in anatomy, zoology, botany, mineralogy, geography, mathematics and astronomy. Scholars advanced their awareness of the importance of certain scientific problems, especially those related to the problem of change and its causes. In the Hellenistic period, scholars frequently employed the principles developed in earlier Greek thought: the application of mathematics and deliberate empirical research.
=== Scientific practices ===
In classical antiquity, the inquiry into the workings of the universe took place both in investigations aimed at practical goals, such as calendar-making and medicine, and in abstract investigations known as natural philosophy. The ancient people who are considered the first scientists may have thought of themselves as "natural philosophers", as practitioners of a skilled profession, or as followers of a religious tradition.
Scientific thought in classical antiquity became tangible beginning in the 6th century BC in the pre-Socratic philosophy of Thales and Pythagoras. Thales, the "father of science", was the first to postulate non-supernatural explanations for natural phenomena such as lightning and earthquake. Pythagoras founded the Pythagorean school, which investigated mathematics and was the first to postulate that the Earth is spherical.
In about 385 BC, Plato founded the Academy. Aristotle, Plato's student, began the "scientific revolution" of the Hellenistic period culminating in the 3rd and 2nd centuries with scholars such as Eratosthenes, Euclid, Aristarchus of Samos, Hipparchus, and Archimedes. Plato and Aristotle's development of deductive reasoning was particularly useful to later scientific inquiry.
=== Architecture and engineering ===
=== Astronomy ===
The level of achievement in Hellenistic astronomy and engineering is shown by the Antikythera mechanism. The astronomer Aristarchus of Samos was the first known person to propose a heliocentric model of the Solar System, while the geographer Eratosthenes accurately calculated the circumference of the Earth. Hipparchus produced the first systematic star catalogue.
=== Mathematics ===
The mathematician Euclid laid down the foundations of mathematical rigour and introduced the concepts of definition, axiom, theorem and proof still in use today in his Elements. Archimedes is credited with using the method of exhaustion to calculate the area under the arc of a parabola with the summation of an infinite series, and gave a remarkably accurate approximation of pi. He is also known in physics for his studies on hydrostatics and the principle of the lever.
=== Medicine ===
In medicine, Herophilos was the first to base his conclusions on the dissection of the human body and to describe the nervous system. Hippocrates and his followers were the first to describe many diseases and medical conditions. Galen performed many audacious operations—including brain and eye surgeries—that were not tried again for more than a millennia.
=== Mineralogy ===
Theophrastus wrote some of the earliest descriptions of plants and animals, establishing the first taxonomy and looking at minerals in terms of their properties such as hardness. Pliny the Elder produced the encyclopedia Natural HIstory in 77 AD. He accurately describes the octahedral shape of the diamond. His recognition of the importance of crystal shape is a precursor to modern crystallography, while mentioning numerous other minerals presages mineralogy. He also recognises that other minerals have characteristic crystal shapes, but in one example, confuses the crystal habit with the work of lapidaries. He was also the first to recognise that amber was a fossilized resin from pine trees because he had seen samples with trapped insects within them.
== Indian subcontinent ==
=== Mathematics and engineering ===
Excavations at Harappa, Mohenjo-daro and other sites of the Indus Valley Civilisation (IVC) have uncovered evidence of the use of "practical mathematics". The people of the IVC manufactured bricks whose dimensions were in the proportion 4:2:1, considered favourable for the stability of a brick structure. They used a standardised system of weights based on set ratios, with the unit weight equaling approximately 28 grams (1 oz). They mass-produced weights in regular geometrical shapes, which included hexahedra, barrels, cones, and cylinders, thereby demonstrating knowledge of basic geometry. Inhabitants of the IVC also tried to standardise the measurement of length to a high degree of accuracy. They designed the Mohenjo-Daro ruler, whose unit of length (34 millimetres (1.3 in)) was divided into ten equal parts. Bricks manufactured in ancient Mohenjo-Daro often had dimensions that were integral multiples of this unit of length.
The main authors of classical Indian mathematics (400 AD to 1200 AD) were scholars like Mahaviracharya, Aryabhata, Brahmagupta, and Bhāskara II. Indian mathematicians made early contributions to the study of the decimal system, zero, negative numbers, arithmetic, and algebra. Trigonometry, having been introduced to ancient India through Greek works, was further advanced in India. The modern definitions of sine and cosine were developed in India.
The Hindu–Arabic numeral system was developed in ancient India and spread to the later Islamic world to Al-Andalus where it was adopted (without the zero) by the French monk Gerbert of Aurillac, who would become Pope Sylvester II. Sylvester spread its usage throughout medieval Europe in the 11th century with the reintroduction of the Greco-Roman abacus calculating tool. The Bakhshali manuscript features negative numbers; it was compiled at an uncertain date between 200 AD and as late as 600 AD, after which they were used with certainty by Indian mathematician Brahmagupta.
=== Medicine ===
Mehrgarh, a Neolithic IVC site, provides the earliest known evidence for in vivo drilling of human teeth, with recovered samples dated to 7000–5500 BC.
Ayurveda medicine traces its origins to the Atharvaveda and is connected to Hinduism. The Sushruta Samhita of Sushruta appeared during the first millennium BC. Ayurvedic practice was flourishing during the time of the Buddha (around 520 BC), and in this period ayurvedic practitioners were commonly using mercuric–sulphur medicines. An important ayurvedic practitioner of this period was Nagarjuna. During the regime of Chandragupta II (375–415 AD), ayurveda was part of mainstream Indian medical techniques, and continued to be so until the Colonial period.
=== Astronomy ===
Early astronomy in India, as in other cultures, was intertwined with religion.The first textual mention of astronomical concepts comes from the Vedas. According to Sarma, "One finds in the Rigveda intelligent speculations about the genesis of the universe from nonexistence, the configuration of the universe, the spherical self-supporting Earth, and the year of 360 days divided into 12 equal parts of 30 days each with a periodical intercalary month."
Classical Indian astronomy documented in literature spans the Maurya Empire (with the Vedanga Jyotisha) to the Vijayanagara Empire (with the Kerala school). Classical Indian astronomy can be said to begin in the 5th century. Aryabhata produced the Aryabhatiya and the lost Arya-siddhānta, and Varāhamihira wrote the Pancha-siddhantika. Indian astronomy and astrology are based upon sidereal calculations, though a tropical system was also used in a few cases.
=== Alchemy ===
Alchemy was popular in India. Indian alchemist and philosopher Kaṇāda introduced the concept of anu, which he defined as matter which could not be subdivided. This is analogous to the concept of the atom in modern science.
=== Linguistics ===
Linguistics (along with phonology and morphology) first arose among Indian grammarians studying Sanskrit. Hemachandra wrote grammars of Sanskrit and Prakrit. His Siddha-Hema-Śabdanuśāśana included six Prakrit languages. He produced the only known grammar of Apabhraṃśa, illustrating it with the folk literature. Pāṇini's Sanskrit grammar contains a particularly detailed description of Sanskrit morphology, phonology, and roots.
== China and East Asia ==
=== Inventions ===
In his Science and Civilisation in China, Joseph Needham outlined China's "Four Great Inventions" (papermaking, compass, printing, and gunpowder). Needham highlighted the Han dynasty in particular as one of the most pivotal eras for Chinese sciences, noting the period's significant advancements in astronomy and calendar-making, the systematic documentation of living organisms in early forms of botany and zoology, and the philosophical skepticism and rationalism of the age embodied in works such as the Lunheng by Wang Chong.
Concurring with Needham, professors Jin Guantao, Fan Hongye, and Liu Qingfeng emphasize the Han dynasty as a unique period for Chinese scientific advancements comparable to the medieval Song dynasty. They also write that the protoscientific ideas of Mohism developed during the Warring States period could have provided a definitive structure for Chinese science, but was hindered by Chinese theology and dynastic royal promotion of Confucianism and its literary classics. Needham and other sinologists indicate that cultural factors prevented Chinese achievements from developing into what might be considered modern science, as the religious and philosophical framework of Chinese intellectuals hampered their efforts to rationalize the laws of nature.
=== Engineering ===
Greek astronomer Eratosthenes is the first known inventor of the armillary sphere in 255 BC. It is uncertain when the armillary sphere first appeared in China, though the Western Han astronomer Geng Shouchang was the first in China to add an equatorial ring to its design in 52 BC, with Jia Kui adding an ecliptic ring in 84 AD, followed by Zhang Heng adding the horizon and meridian rings.
Works by Zhang Heng were highly influential throughout later Chinese history. As a horologist, Zhang demonstrated the movement of recorded stars and planets by being the first to apply the hydropower of water wheels and water clock timer for automatically rotating the assembled rings of his armillary sphere, a model that would directly inspire the liquid escapement in astronomical clockworks pioneered in the Tang dynasty by Yi Xing and used by Song dynasty scientist Su Song in building his chain drive and water-driven astronomical clock tower. Zhang was not the first in China to utilize the motive power of waterwheels, since they were used in ferrous metallurgy by Du Shi to operate the bellows of a blast furnace to make pig iron, and the cupola furnace to make cast iron. Zhang invented a seismometer device with an inverted pendulum that detected the cardinal direction of distant earthquakes. It is unclear if Zhang invented or simply improved the designs of the odometer cart for measuring traveled distances and the non-magnetic south-pointing chariot that used differential gears to constantly point southward for navigation, though Three Kingdoms era engineer Ma Jun created a successful model of the chariot.
The odometer cart, depicted in Eastern Han art, was most likely invented in Western Han China by Luoxia Hong around 110 BC and separately by the Greeks (either Archimedes in the 3rd century BC or Hero of Alexandria in the 1st century AD).
=== Cartography ===
In cartography, Qin maps dating to the 4th century BC have been discovered and the Western Jin dynasty official Pei Xiu is the first known Chinese cartographer to have used a geometric grid reference that allowed for measurements on a graduated scale and for topographical elevation, though this might have been based on a rectangular grid system in maps made by Zhang Heng that are now lost.
=== Mathematics ===
In regards to mathematics, The Nine Chapters on the Mathematical Art, compiled in its entirety by 179 AD during the Eastern Han, is perhaps also the first text to utilize negative numbers. These were symbolized by counting rods in a slanted position, while red rods symbolizing negative numbers versus black rods that symbolize positive numbers may date back to the Western Han period.
Zhang Heng approximated pi as 3.162 using the square root of 10 (with an 8:5 ratio of the volume of a cube to an inscribed sphere), though this was less accurate than the earlier Liu Xin who calculated it as 3.154 using an unknown method. Zhang's calculation was improved upon by Three Kingdoms–era mathematician Liu Heng in his 263 AD commentary on The Nine Chapters on the Mathematical Art, providing a pi algorithm with a value of 3.14159, while Liu Song and Southern Qi–era mathematician Zu Chongzhi reached a value of 3.141592, the most accurate figure Chinese would achieve before exposure to Western mathematics.
=== Astronomy ===
Early Chinese astronomy provides an example of the exhaustive documentation of the natural world and observable universe that often preoccupied Chinese scholars. Chinese star names are mentioned in oracle bone inscriptions of the Shang dynasty. Lists of stars along the ecliptic in the Chinese Twenty-Eight Mansions were provided on lacquerware of the 433 BC Tomb of Marquis Yi of Zeng and in the Lüshi Chunqiu encyclopedia of Qin statesman Lü Buwei, but it was not until the Han dynasty that full star catalogues were published that listed all stars in the observable celestial sphere. The Mawangdui Silk Texts, interred within a Western Han tomb in 168 BC, provide writings and ink illustrations of Chinese star maps showing Chinese constellations as well as comets. The Warring States–era astronomers Shi Shen and Gan De are traditionally thought to have published star catalogues in the 4th century BC, but it was the star catalogue of Sima Qian (145–86 BC) in his "Book of Celestial Offices" (天官書; Tianguan shu) in the Records of the Grand Historian that provided the model for all later Chinese star catalogues. Chinese constellations were later adopted in medieval Korean astronomy and Japanese astronomy. Building upon the star catalogue of Sima Qian that featured 90 constellations, the star catalogue of Zhang Heng published in 120 AD featured 124 constellations.
Nascent scientific ideas were established during the late Zhou dynasty and proliferated in the Han dynasty. Much like the earlier Aristotle in Greece, Wang Chong accurately described the water cycle of Earth but was dismissed by his contemporaries. However, Wang (similar to the Roman Lucretius) inaccurately criticized the then-mainstream Han Chinese hypotheses that the Sun and Moon are spherical and that the Moon is illuminated by the reflection of sunlight—the correct hypotheses being advocated by astronomer and music theorist Jing Fang and expanded upon by the polymath scientist and inventor Zhang Heng. Zhang theorized that the celestial sphere was round and structured like an egg with the Earth as its yolk, a geocentric model that was largely accepted in the contemporary Greco-Roman world.
=== Writing and linguistics ===
Analytical approaches were also applied to writing itself. Though the Erya of the Warring States period provides a basic dictionary, the first analytical Chinese dictionary to explain and dissect the logographic Chinese written characters, with 9,353 characters listed and categorized by radicals, was the Shuowen Jiezi composed by the Eastern Han philologist and politician Xu Shen.
=== Medicine ===
A seminal work of traditional Chinese medicine was the Huangdi Neijing (Yellow Emperor's Inner Canon) compiled between the 3rd and 2nd centuries BC, which viewed the human body's organs and tissues (zangfu) through the lens of the metaphysical five phases and yin and yang. The Huangdi Neijing also stated a belief in two circulatory channels of qi vital energy. Physicians of the Han dynasty believed that pulse diagnosis could be used to determine which organs in the body emitted qi energy, and therefore the ailments suffered by patients. The Huangdi Neijing is the first known Chinese text to describe the use of acupuncture, while golden acupuncture needles have been discovered in the tomb of Liu Sheng, Prince of Zhongshan (d. 113 BC) and stone-carved artworks of the Eastern Han period depict the practice. The Huangdi Neijing is also the first known text to describe diabetes and link it to the excessive consumption of sweet and fatty foods.
In surgery, Han texts offered practical advice for certain procedures such as clinical lancing of abscesses. The first known physician in China to describe the use anesthesia for patients undergoing surgery was the Eastern Han physician Hua Tuo, who utilized his knowledge of Chinese herbology based in the Huangdi Neijing to create an ointment that healed surgical wounds within a month. One of his surgical procedures was the removal of a dead fetus from the womb of a woman whom he diagnosed and cured of her ailments. Hua's contemporary physician and pharmacologist Zhang Zhongjing preserved much of the medical knowledge known in China by the Eastern Han period in his major work Shanghan Lun (Treatise on Cold Injury and Miscellaneous Disorders) as well as the Jingui Yaolüe (Essential Medical Treasures of the Golden Chamber ).
Outside the major canon of Chinese medicine established during the Han period, modern archaeology has revealed previous Chinese discoveries in medicine. The Shuihudi Qin bamboo texts, dated to the 3rd century BC, provide some of the earliest known descriptions of the symptoms of leprosy (predating the Roman author Aulus Cornelius Celsus and perhaps also the Indian Sushruta Samhita, the oldest version of which is indeterminable). The Mawangdui silk texts of the 2nd century BC provide illustrated diagrams with textual captions for exercises in calisthenics.
== Pre-Columbian Mesoamerica ==
=== Writing ===
During the Middle Formative Period (c. 900 BC – c. 300 BC) of Pre-Columbian Mesoamerica, either the script of the Zapotec civilization or the script of the Olmec civilization (with the Cascajal Block being perhaps the earliest evidence) represent the earliest full writing systems of the Americas.
The Maya script, developed by the Maya civilization between 400–200 BC during its Preclassic period, was rooted in the Olmec and Zapotec writing systems, and became widespread in use by 100 BC. The Classic Maya language was built on the shared heritage of the Olmecs by developing the most sophisticated systems of writing, astronomy, calendrical science, and mathematics among urbanized Mesoamerican peoples.
=== Mathematics ===
The Maya developed a positional numeral system with a base of 20 that included the use of zero for constructing their calendars, with individual symbolic characters for numbers 1 through 19.
=== Astronomy ===
The Zapotec created the first known astronomical calendar in Mesoamerica, though this was possibly under heavy influence by the Olmecs.
Maya writing contains easily discernible calendar dates in the form of logograms representing numbers, coefficients, and calendar periods amounting to 20 days (within 360-day years) and even 20 years for tracking social, religious, political, and economic events.
== References ==
== Bibliography ==
Inventions (Pocket Guides). Publisher: DK CHILDREN; Pocket edition (March 15, 1995). ISBN 1-56458-889-0. ISBN 978-1-56458-889-0
Aaboe, Asger. Episodes from the Early History of Astronomy. Springer, 2001.
Chaney, Eric (May 2016). "Religion and the Rise and Fall of Islamic Science" (PDF).
Evans, James. The History and Practice of Ancient Astronomy. New York: Oxford University Press, 1998.
Faruqi, Yasmeen (2006). "Contributions of Islamic scholars to the scientific enterprise". International Education Journal. 7 (4): 391–399. ERIC EJ854295.
Lindberg, David C. The Beginnings of Western Science: The European Scientific Tradition in Philosophical, Religious, and Institutional Context, 600 BC. to AD. 1450. Chicago: University of Chicago Press, 1992.
Lloyd, G. E. R. Greek Science after Aristotle. New York: W.W. Norton & Co, 1973. ISBN 0-393-00780-4.
Nasser, Mona; Tibi, Aida; Savage-Smith, Emilie (1 February 2009). "Ibn Sina's Canon of Medicine: 11th century rules for assessing the effects of drugs". Journal of the Royal Society of Medicine. 102 (2): 78–80. doi:10.1258/jrsm.2008.08k040. PMC 2642865. PMID 19208873.
Needham, Joseph, Science and Civilization in China, volume 1. (Cambridge University Press, 1954)
Pedersen, Olaf. Early Physics and Astronomy: A Historical Introduction. 2nd edition. Cambridge: Cambridge University Press, 1993.
Sardar, Marika. “Astronomy and Astrology in the Medieval Islamic World.” Metmuseum.org, https://www.metmuseum.org/toah/hd/astr/hd_astr.htm.
Tibi, Selma (April 2006). "Al-Razi and Islamic medicine in the 9th century". Journal of the Royal Society of Medicine. 99 (4): 206–207. doi:10.1177/014107680609900425. PMC 1420785. PMID 16574977.
Upton, Joseph M. (1933). "A Manuscript of 'The Book of the Fixed Stars' by ʿAbd Ar-Raḥmān Aṣ-Ṣūfī". Metropolitan Museum Studies. 4 (2): 179–197. doi:10.2307/1522800. JSTOR 1522800. | Wikipedia/Science_in_the_ancient_world |
The French Academy of Sciences (French: Académie des sciences, [akademi de sjɑ̃s]) is a learned society, founded in 1666 by Louis XIV at the suggestion of Jean-Baptiste Colbert, to encourage and protect the spirit of French scientific research. It was at the forefront of scientific developments in Europe in the 17th and 18th centuries, and is one of the earliest Academies of Sciences.
Currently headed by Patrick Flandrin (President of the academy), it is one of the five Academies of the Institut de France.
== History ==
The Academy of Sciences traces its origin to Colbert's plan to create a general academy. He chose a small group of scholars who met on 22 December 1666 in the King's library, near the present-day Bibliothèque Nationale, and thereafter held twice-weekly working meetings there in the two rooms assigned to the group. The first 30 years of the academy's existence were relatively informal, since no statutes had as yet been laid down for the institution.
In contrast to its British counterpart, the academy was founded as an organ of government. In Paris, there were not many membership openings, to fill positions there were contentious elections. The election process was at least a 6-stage process with rules and regulations that allowed for chosen candidates to canvas other members and for current members to consider postponing certain stages of the process if the need would arise. Elections in the early days of the academy were important activities, and as such made up a large part of the proceedings at the academy, with many meetings being held regarding the election to fill a single vacancy within the academy. That is not to say that discussion of candidates and the election process as a whole was relegated to the meetings. Members that belonged to the vacancy's respective field would continue discussion of potential candidates for the vacancy in private. Being elected into the academy did not necessarily guarantee being a full member, in some cases, one would enter the academy as an associate or correspondent before being appointed as a full member of the academy.
The election process was originally only to replace members from a specific section. For example, if someone whose study was mathematics was either removed or resigned from his position, the following election process nominated only those whose focus was also mathematics in order to fill that discipline's vacancy. That led to some periods of time in which no specialists for specific fields of study could be found, which left positions in those fields vacant since they could not be filled with people in other disciplines.
The needed reform came late in the 20th century, in 1987, when the academy decided against the practice and to begin filling vacancies with people with new disciplines. This reform was not only aimed at further diversifying the disciplines under the academy, but also to help combat the internal aging of the academy itself. The academy was expected to remain apolitical, and to avoid discussion of religious and social issues.
On 20 January 1699, Louis XIV gave the Company its first rules. The academy received the name of Royal Academy of Sciences and was installed in the Louvre in Paris. Following this reform, the academy began publishing a volume each year with information on all the work done by its members and obituaries for members who had died. This reform also codified the method by which members of the academy could receive pensions for their work.
The academy was originally organized by the royal reform hierarchically into the following groups: Pensionaires, Pupils, Honoraires, and Associés.
The reform also added new groups not previously recognized, such as Vétéran. Some of these role's member limits were expanded and some roles even removed or combined throughout the course of academy's history. The Honoraires group establish by this reform in 1699 whose members were directly appointed by the King was recognized until its abolishment in 1793.
Membership in the academy the exceeded 100 officially-recognised full members only in 1976, 310 years after the academy's inception in 1666. The membership increase came with a large-scale reorganization in 1976. Under this reorganization, 130 resident members, 160 correspondents, and 80 foreign associates could be elected.
A vacancy opens only upon the death of members, as they serve for life. During elections, half of the vacancies are reserved for people less than 55 years old. This was created as an attempt to encourage younger members to join the academy.
The reorganization also divided the academy into 2 divisions:
One division, Division 1, covers the applications of mathematics and physical sciences,
the other, Division 2, covers the applications of chemical, natural, biological, and medical sciences.
On 8 August 1793, the National Convention abolished all the academies. On 22 August 1795, a National Institute of Sciences and Arts was put in place, bringing together the old academies of the sciences, literature and arts, among them the Académie française and the Académie des sciences.
Also in 1795, The academy determined these 10 titles (first 4 in Division 1 and the others in Division 2) to be their newly accepted branches of scientific study:
Mathematics
Mechanics
Astronomy
Physics
Chemistry
Mineralogy
Botany
Agriculture
Anatomy and Zoology
Medicine and Surgery
The last two sections are bundled since there were many good candidates fit to be elected for those practices, and the competition was stiff. Some individuals like Francois Magendie had made stellar advancements in their selected fields of study, that warranted a possible addition of new fields. However, even someone like Magendie that had made breakthroughs in Physiology and impressed the academy with his hands-on vivisection experiments, could not get his study into its own category. Despite Magendie being one of the leading innovators of his time, it was still a battle for him to become an official member of the academy, a feat he would later accomplish in 1821. He further improved the reverence of the academy when he and anatomist Charles Bell produced the widely known "Bell-Magendie Law".
From 1795 until 1914, the first world war, the French Academy of Science was the most prevalent organization of French science. Almost all the old members of the previously abolished Académie were formally re-elected and retook their ancient seats. Among the exceptions was Dominique, comte de Cassini, who refused to take his seat. Membership in the academy was not restricted to scientists: in 1798 Napoleon Bonaparte was elected a member of the academy and three years later a president in connection with his Egyptian expedition, which had a scientific component. In 1816, the again renamed "Royal Academy of Sciences" became autonomous, while forming part of the Institute of France; the head of State became its patron. In the Second Republic, the name returned to Académie des sciences. During this period, the academy was funded by and accountable to the Ministry of Public Instruction.
The academy came to control French patent laws in the course of the eighteenth century, acting as the liaison of artisans' knowledge to the public domain. As a result, academicians dominated technological activities in France.
The academy proceedings were published under the name Comptes rendus de l'Académie des Sciences (1835–1965). The Comptes rendus is now a journal series with seven titles. The publications can be found on site of the French National Library.
In 1818 the French Academy of Sciences launched a competition to explain the properties of light. The civil engineer Augustin-Jean Fresnel entered the competition by submitting a new wave theory of light. Siméon Denis Poisson, one of the members of the judging committee, studied Fresnel's theory in detail. Being a supporter of the particle-theory of light, he looked for a way to disprove it. Poisson thought that he had found a flaw when he demonstrate that Fresnel's theory predicts that an on-axis bright spot would exist in the shadow of a circular obstacle, where there should be complete darkness according to the particle-theory of light. The Poisson spot is not easily observed in every-day situations and so it was only natural for Poisson to interpret it as an absurd result and that it should disprove Fresnel's theory. However, the head of the committee, Dominique-François-Jean Arago, and who incidentally later became Prime Minister of France, decided to perform the experiment in more detail. He molded a 2-mm metallic disk to a glass plate with wax. To everyone's surprise he succeeded in observing the predicted spot, which convinced most scientists of the wave-nature of light.
For three centuries women were not allowed as members of the academy. This meant that many women scientists were excluded, including two-time Nobel Prize winner Marie Curie, Nobel winner Irène Joliot-Curie, mathematician Sophie Germain, and many other deserving women scientists. The first woman admitted as a correspondent member was a student of Curie's, Marguerite Perey, in 1962. The first female full member was Yvonne Choquet-Bruhat in 1979.
Membership in the academy is highly geared towards representing common French populace demographics. French population increases and changes in the early 21st century led to the academy expanding reference population sizes by reform in the early 2002.
The overwhelming majority of members leave the academy posthumously, with a few exceptions of removals, transfers, and resignations. The last member to be removed from the academy was in 1944. Removal from the academy was often for not performing to standards, not performing at all, leaving the country, or political reasons. In some rare occasions, a member has been elected twice and subsequently removed twice. This is the case for Marie-Adolphe Carnot.
== Government interference ==
The most direct involvement of the government in the affairs of the institute came in the initial nomination of members in 1795, but as its members nominated constituted only one third of the membership and most of these had previously been elected as members of the respective academies under the old regime, few objections were raised. Moreover, these nominated members were then completely free to nominate the remaining members of the institute. Members expected to remain such for life, but interference occurred in a few cases where the government suddenly terminated membership for political reasons. The other main interference came when the government refused to accept the result of academy elections. The academies control by the government was apparent in 1803, when Bonaparte decided on a general reorganization. His principal concern was not the First class but the Second, which included political scientists who were potential critics of his government. Bonaparte abolished the second class completely and, after a few expulsions, redistributed its remaining members, together with those of the Third class, into a new Second class concerned with literature and a new Third class devoted to the fine arts. Still this relationship between the academy and the government was not a one-way affair, as members expected to receive their payment of an honorarium.
== Decline ==
Although the academy still exists today, after World War I, the reputation and status of the academy was largely questioned. One factor behind its decline was the development from a meritocracy to gerontocracy: a shift from those with demonstrated scientific ability leading the academy to instead favoring those with seniority. It became known as a sort of "hall of fame" that lost control, real and symbolic, of the professional scientific diversity in France at the time. Another factor was that in the span of five years, 1909 to 1914, funding to science faculties considerably dropped, eventually leading to a financial crisis in France.
== Present use ==
Today the academy is one of five academies comprising the Institut de France. Its members are elected for life. Currently, there are 150 full members, 300 corresponding members, and 120 foreign associates. They are divided into two scientific groups: the Mathematical and Physical sciences and their applications and the Chemical, Biological, Geological and Medical sciences and their applications. The academy currently has five missions that it pursues. These being the encouraging of the scientific life, promoting the teaching of science, transmitting knowledge between scientific communities, fostering international collaborations, and ensuring a dual role of expertise and advise. The French Academy of Science originally focused its development efforts into creating a true co-development Euro-African program beginning in 1997. Since then they have broadened their scope of action to other regions of the world. The standing committee COPED is in charge of the international development projects undertaken by the French Academy of Science and their associates. The current president of COPED is Pierre Auger, the vice president is Michel Delseny, and the honorary president is Francois Gros. All of which are current members of the French Academy of Science. COPED has hosted several workshops or colloquia in Paris, involving representatives from African academies, universities or research centers, addressing a variety of themes and challenges dealing with African development and covering a large field spectrum. Specifically higher education in sciences, and research practices in basic and applied sciences that deal with various aspects relevant to development (renewable energy, infectious diseases, animal pathologies, food resources, access to safe water, agriculture, urban health, etc.).
== Current committees and working parties ==
The Academic Standing Committees and Working Parties prepare the advice notes, policy statements and the Academic Reports. Some have a statutory remit, such as the Select Committee, the Committee for International Affairs and the Committee for Scientists' Rights, some are created ad hoc by the academy and approved formally by vote in a members-only session.
Today the academies standing committees and working parties include:
The Academic Standing Committee in charge of the Biennial Report on Science and Technology
The Academic Standing Committee for Science, Ethics and Society
The Academic Standing Committee for the Environment
The Academic Standing Committee for Space Research
The Academic Standing Committee for Science and Metrology
The Academic Standing Committee for the Science History and Epistemology
The Academic Standing Committee for Science and Safety Issues
The Academic Standing Committee for Science Education and Training
The Academic Standing La main à la pâte Committee
The Academic Standing Committee for the Defense of Scientists' Rights (CODHOS)
The Academic Standing Committee for International Affairs (CORI)
The French Committee for International Scientific Unions (COFUSI)
The Academic Standing Committee for Scientific and Technological International Relations (CARIST)
The Academic Standing Committee for Developing Countries (COPED)
The Inter-academic Group for Development (GID) – Cf. for further reading
The Academic Standing Commission for Sealed Deposits
The Academic Standing Committee for Terminology and Neologisms
The Antoine Lavoisier Standing Committee
The Academic Standing Committee for Prospects in Energy Procurement
The Special Academic Working Party on Scientific Computing
The Special Academic Working Party on Material Sciences and Engineering
== Medals, awards and prizes ==
Each year, the Academy of Sciences distributes about 80 prizes. These include:
Marie Skłodowska-Curie and Pierre Curie Polish-French Science Award, created in 2022.
the Grande Médaille, awarded annually, in rotation, in the relevant disciplines of each division of the academy, to a French or foreign scholar who has contributed to the development of science in a decisive way.
the Lalande Prize, awarded from 1802 through 1970, for outstanding achievement in astronomy
the Valz Prize, awarded from 1877 through 1970, to honor advances in astronomy
the Richard Lounsbery Award, jointly with the National Academy of Sciences
the Prix Jacques Herbrand, for mathematics and physics
the Prix Paul Pascal, for chemistry
the Louis Bachelier Prize for major contributions to mathematical modeling in finance
the Prix Michel Montpetit for computer science and applied mathematics, awarded since 1977
the Leconte Prize, awarded annually since 1886, to recognize important discoveries in mathematics, physics, chemistry, natural history or medicine
the Prix Tchihatcheff (Tchihatchef; Chikhachev)
== People ==
The following are incomplete lists of the officers of the academy. See also Category:Officers of the French Academy of Sciences.
For a list of the academy's members past and present, see Category:Members of the French Academy of Sciences
=== Presidents ===
Source: French Academy of Sciences
=== Treasurers ===
?–1788 Georges-Louis Leclerc, Comte de Buffon
1788–1791 Mathieu Tillet
=== Permanent secretaries ===
==== General ====
==== Mathematical Sciences ====
==== Physical Sciences ====
==== Chemistry and Biology ====
== Publications ==
Publications of the French Academy of Sciences "Histoire de l'Académie royale des sciences" (1700–1790)
== See also ==
French art salons and academies
French Geodesic Mission
History of the metre
Seconds pendulum
Royal Commission on Animal Magnetism
== Notes ==
== References ==
== External links ==
Official website (in French) – English-language version
Complete listing of current members
Notes on the Académie des Sciences from the Scholarly Societies project (includes information on the society journals)
Search the Proceedings of the Académie des sciences in the French National Library (search item: Comptes Rendus)
Comptes rendus de l'Académie des sciences. Série 1, Mathématique in Gallica, the digital library of the BnF. | Wikipedia/French_Academy_of_Sciences |
A science festival is a festival that showcases science and technology with a similar atmosphere to an arts or music festival, and that primarily targets the general public. These public engagement events can be varied, including lectures, exhibitions, workshops, live demonstrations of experiments, guided tours, and panel discussions. There may also be events linking science to the arts or history, such as plays, dramatised readings, and musical productions. The core content is that of science and technology, but the style comes from the world of the arts.
== History ==
The modern concept of a science festival comes from the city of Edinburgh in 1989. The choice of Glasgow as European Capital of Culture for 1990 took Edinburgh by surprise and stimulated it to rebrand itself as a city of science, building on the success of a series of big urban developments led by its Economic Development Department. A senior member of the development team, Ian Wall, proposed that Edinburgh should highlight its new image by complementing its world-famous autumn arts festival with a new type of spring event for which he coined the phrase 'science festival'. Reaction was mixed, with some organisations doubting whether science could be packaged in an arts format. Even so, the city put resources behind the idea, appointing a director and project team, and in April 1989 the first Edinburgh International Science Festival took place.
Edinburgh's success led to the development of science festivals in many other parts of the world. The British Science Association restructured its annual meeting, originally established in 1831 as a discussion forum for scientists, to turn it into the British Science Festival of today. The town of Cheltenham—famous for its jazz, music, and literature festivals—added science to its portfolio with the creation of the Cheltenham Science Festival in 2002.
Realizing the key importance of science festivals science organizations and funding bodies put ever more emphasis on outreach to foster public understanding both of the results and the wider relevance of science. Recent years have seen the creation of a number of new science festivals as forms of public engagement. An umbrella organization for European science festivals and other science communication events, the European Science Events Association (EUSEA), was formed in 2001 and now has approximately 100 member organizations from 36 countries.
The concept spread to Sweden in 1997 with The International Science Festival in Gothenburg which is an annual festival in central Gothenburg, Sweden with thought provoking science activities for the public. The festival is visited by about 100,000 people each year. This makes it the largest popular science event in Sweden and one of the largest popular science events in Europe.
The spread of science festivals within the United States is relatively recent. One of the earliest examples is Wonderfest, an annual Bay Area science festival that began in 1998. Additionally, the annual meeting of the American Association for the Advancement of Science includes a number of public events. Focusing on one particular science, the physics festival "Mastering the Mysteries of the Universe", was held in Atlanta, Georgia, in 1999 in association with the centennial of the American Physical Society.
Since 2004, there has been a science festival in Pittsburgh (the SciTech festival; from 2005 on known as the SciTech Spectacular), and new science festivals have been held in Cambridge, Massachusetts (the Cambridge Science Festival, first held in April 2007); and in New York City (the World Science Festival held at the end of May 2008); and in March 2009, San Diego hosted the first west coast science festival, the San Diego Science Festival founded by Larry Bock.
As of 2009 the Science Festival Alliance, a consortium of major festivals formed with a 3-year NSF grant, has supported the growth of independent regional science festivals, with an initial emphasis on celebration in communities throughout the US.
In September 2010, the North Carolina Science Festival became the first statewide science festival in the United States, presenting more than 400 events across the state over a two-week span. The second NC Science Festival was held April 13–29, 2012, and the festival is now an annual event. Morehead Planetarium and Science Center at UNC-Chapel Hill founded the North Carolina Science Festival and continues to administer it.
In late October 2010, the USA Science and Engineering Festival was the "country’s first national science festival". This national emphasis was based partly on encouraging local events to coincide with the major event in Washington DC.
Festivals can vary greatly in size, scope, and their overall purpose. Involved partners may have different aims, methods, and motivations to participate and deliver such festivals. A university might stage a small festival in its hometown. On the other end of the scale, the 2006 British Association Festival of Science held on September 2–9 in Norwich, England, was attended by more than 174,000 visitors.
== Typical festival events ==
Science festivals feature a wide variety of events. As they offer an enjoyable setting with social interaction, visitors tend to develop increased interest in curiosity about science, and also value the opportunity to interact with scientific research through different forms of public engagement. Those can include conventional methods of science communication found in science museums and centres. Differing from them in their focus on current scientific research and their temporary nature. Because of this, science festivals have high amounts of volunteering scientists, university students, technologists and engineers.
Science festivals are also aimed at playing an important, if informal part in secondary science education. Many have events specifically aimed at students or teachers, such as workshops or offering curriculum-linked workshops, and science shows to regional schools throughout the year.
A typical format for a science festival is to have a series of lectures, with topics ranging from cutting-edge research to unusual perspectives on science. For instance, the 2007 Edinburgh festival "Big Ideas" series included talks on what makes racing cars fast, the molecular basis of food preparation, the neurobiology of love and beauty, and the properties of quarks. Most science festivals include hands-on activities similar to those found in science centers. Another popular theme is the interaction of science and culture, including the arts.
Generally speaking, science engagement can be separated into three orders of engagement. Irwin's conceptional 'third-order thinking' model defines 'first order' engagement to merely promote science learning, and the overall awareness and interest of science. The 'second order' of public engagement describes two-way 'dialogue', where both experts and laypeople can learn from each other by exchanging knowledge and valuable information. Connecting the wider social context of techno-scientific advancements to social needs in defining a 'third order' of engagement, involving pluralistic debates and discussions on how science can best serve societal needs. Science festivals are quite unique for the opportunity to combine diverse engagement formats, covering all of the previously mentioned orders of engagement in an informal setting.
== Strengths & Challenges ==
=== Strengths ===
The strengths of science festivals lie in their unique role of creating strong and memorable impressions due to their time-limited nature and the variety of different engagement forms. Compared to science broadcasting, festivals allow visitors to engage in discussions with experts about more complex topics. This enables visitors to dive deeper into science, benefitting from their immediacy and interactivity, while scientists get the chance to enthuse them about their work and connect to a non-expert audience.
Far beyond just conveying information, science festivals provide visitors with the conceptional tools to understand scientific development in different areas of science. In addition, festivals are often perceived to be more open and honest about uncertainties in the nature of scientific processes compared to the 'ready made' contents from some public relations end of science engagement.
=== Challenges ===
Existing research does not always focus enough on the need to complement impact evaluation research on the effectiveness of science festivals with insights about visitor perspectives. Most attendees already share a significant interest in science or self-report that they are culturally active in general. Jensen and Kennedy suggest that science festivals face challenges in terms of reaching out to as wide a public as possible, being much more inclusive to the actual population. To foster socio-economic inclusivity, science festivals should be brought to the public through new creative ways, such as school visits - reaching diverse audiences with increasingly diverse backgrounds and previous interest in science.
== List of science festivals ==
=== United Kingdom ===
British Association British Science Festival, England
British Science Festival, Newcastle, England
Caithness International Science Festival, Wick, Scotland
Cambridge Science Festival, Cambridge, England
Cheltenham Science Festival, Cheltenham, England
Edinburgh International Science Festival, Edinburgh, Scotland
Glasgow Science Festival, Glasgow, Scotland
Manchester Science Festival, Greater Manchester, England
Nottingham Festival of Science and Curiosity, Nottingham, England
Oxford Science and Ideas Festival, Oxford, England
Pint of Science, Bath, Birmingham, Bristol, Cambridge, Edinburgh, Exeter, Glasgow, Guildford, Hull, Leeds, London, Manchester, Newcastle, Norwich, Nottingham, Oxford, Portsmouth, Sheffield, Southampton, Teesside, York
=== Continental Europe ===
Science festival in Warsaw, Poland
Lower Silesian Science Festival, Wrocław, Poland
BergamoScienza, Bergamo, Italy
Copernicus Festival, Kraków, Poland
Festival della Scienza, Genoa, Italy
Highlights der Physik, various cities, Germany
The International Science Festival in Gothenburg, Sweden
Uchenye protiv mifov, Moscow and St Peterburg, Russia
=== United States ===
Bay Area Science Festival, San Francisco, California
Los Alamos ScienceFest, Los Alamos, New Mexico
Cambridge Science Festival, Cambridge, Massachusetts
North Carolina Science Festival
USA Science and Engineering Festival, Washington DC
World Science Festival, New York City
Michigan State University (MSU) Science Festival, East Lansing, Michigan
=== Canada ===
Science Rendezvous, Toronto, Ontario
Festival Eurêka!, Montréal, Québec
=== Australasia ===
New Zealand International Science Festival, Dunedin, New Zealand
World Science Festival Brisbane, Brisbane, Australia
Sydney Science Festival, Sydney, Australia
== See also ==
Science museum
Science outreach
Physics Outreach
Public science
== References ==
== External links ==
European Science Events Association
Mapping the World's Science Festivals - Nature Publishing Group's Team Blog
Science Festivals Linkedin Group
Science Festival Alliance | Wikipedia/Science_festival |
A correlation function is a function that gives the statistical correlation between random variables, contingent on the spatial or temporal distance between those variables. If one considers the correlation function between random variables representing the same quantity measured at two different points, then this is often referred to as an autocorrelation function, which is made up of autocorrelations. Correlation functions of different random variables are sometimes called cross-correlation functions to emphasize that different variables are being considered and because they are made up of cross-correlations.
Correlation functions are a useful indicator of dependencies as a function of distance in time or space, and they can be used to assess the distance required between sample points for the values to be effectively uncorrelated. In addition, they can form the basis of rules for interpolating values at points for which there are no observations.
Correlation functions used in astronomy, financial analysis, econometrics, and statistical mechanics differ only in the particular stochastic processes they are applied to. In quantum field theory there are correlation functions over quantum distributions.
== Definition ==
For possibly distinct random variables X(s) and Y(t) at different points s and t of some space, the correlation function is
C
(
s
,
t
)
=
corr
(
X
(
s
)
,
Y
(
t
)
)
,
{\displaystyle C(s,t)=\operatorname {corr} (X(s),Y(t)),}
where
corr
{\displaystyle \operatorname {corr} }
is described in the article on correlation. In this definition, it has been assumed that the stochastic variables are scalar-valued. If they are not, then more complicated correlation functions can be defined. For example, if X(s) is a random vector with n elements and Y(t) is a vector with q elements, then an n×q matrix of correlation functions is defined with
i
,
j
{\displaystyle i,j}
element
C
i
j
(
s
,
t
)
=
corr
(
X
i
(
s
)
,
Y
j
(
t
)
)
.
{\displaystyle C_{ij}(s,t)=\operatorname {corr} (X_{i}(s),Y_{j}(t)).}
When n=q, sometimes the trace of this matrix is focused on. If the probability distributions have any target space symmetries, i.e. symmetries in the value space of the stochastic variable (also called internal symmetries), then the correlation matrix will have induced symmetries. Similarly, if there are symmetries of the space (or time) domain in which the random variables exist (also called spacetime symmetries), then the correlation function will have corresponding space or time symmetries. Examples of important spacetime symmetries are —
translational symmetry yields C(s,s') = C(s − s') where s and s' are to be interpreted as vectors giving coordinates of the points
rotational symmetry in addition to the above gives C(s, s') = C(|s − s'|) where |x| denotes the norm of the vector x (for actual rotations this is the Euclidean or 2-norm).
Higher order correlation functions are often defined. A typical correlation function of order n is (the angle brackets represent the expectation value)
C
i
1
i
2
⋯
i
n
(
s
1
,
s
2
,
⋯
,
s
n
)
=
⟨
X
i
1
(
s
1
)
X
i
2
(
s
2
)
⋯
X
i
n
(
s
n
)
⟩
.
{\displaystyle C_{i_{1}i_{2}\cdots i_{n}}(s_{1},s_{2},\cdots ,s_{n})=\langle X_{i_{1}}(s_{1})X_{i_{2}}(s_{2})\cdots X_{i_{n}}(s_{n})\rangle .}
If the random vector has only one component variable, then the indices
i
,
j
{\displaystyle i,j}
are redundant. If there are symmetries, then the correlation function can be broken up into irreducible representations of the symmetries — both internal and spacetime.
== Properties of probability distributions ==
With these definitions, the study of correlation functions is similar to the study of probability distributions. Many stochastic processes can be completely characterized by their correlation functions; the most notable example is the class of Gaussian processes.
Probability distributions defined on a finite number of points can always be normalized, but when these are defined over continuous spaces, then extra care is called for. The study of such distributions started with the study of random walks and led to the notion of the Itō calculus.
The Feynman path integral in Euclidean space generalizes this to other problems of interest to statistical mechanics. Any probability distribution which obeys a condition on correlation functions called reflection positivity leads to a local quantum field theory after Wick rotation to Minkowski spacetime (see Osterwalder-Schrader axioms). The operation of renormalization is a specified set of mappings from the space of probability distributions to itself. A quantum field theory is called renormalizable if this mapping has a fixed point which gives a quantum field theory.
== See also ==
Autocorrelation – Correlation of a signal with a time-shifted copy of itself, as a function of shift
Correlation does not imply causation – Refutation of a logical fallacy
Correlogram – Chart of correlation statistics
Covariance function – Function in probability theory
Pearson product-moment correlation coefficient – Measure of linear correlationPages displaying short descriptions of redirect targets
Correlation function (astronomy) – Function describing the distribution of galaxies in the universe
Correlation function (statistical mechanics) – Measure of a system's order
Correlation function (quantum field theory) – Expectation value of time-ordered quantum operators
Mutual information – Measure of dependence between two variables
Rate distortion theory – Branch of information theory which provides the theoretical foundations for lossy data compressionPages displaying short descriptions of redirect targets
Radial distribution function – Description of particle density in statistical mechanics
== References == | Wikipedia/Correlation_function |
A science magazine is a periodical publication with news, opinions, and reports about science, generally written for a non-expert audience. In contrast, a periodical publication, usually including primary research and/or reviews, that is written by scientific experts is called a "scientific journal". Science magazines are read by non-scientists and scientists who want accessible information on fields outside their specialization.
Articles in science magazines are sometimes republished or summarized by the general press.
== Examples of general science magazines ==
=== Africa ===
=== Asia ===
==== Bangladesh ====
Byapon – Youth Science Magazine in Bengali
Bigganchinta[1]
BigganBarta – Free PDF Science Magazine in Bengali
Bangachi (ব্যাঙাচি) – Free Science Magazine in Bengali published by Banger Chhater Biggan
Biggan Ananda (বিজ্ঞান আনন্দ) - Published by Bangladesh Science Fiction Society (BSFS)
Zero to Infinity (জিরো টু ইনফিনিটি)
==== India ====
Resonance, published by Indian Academy of Sciences
Current Science
Dream 2047, published by Vigyan Prasar
Jnan o Bijnan, published by Bangiya Bijnan Parishad
Sandarbh
Science Reporter
Safari
==== Japan ====
Newton press
Nikkei Science
==== Kazakhstan ====
OYLA
==== Pakistan ====
Global Science
==== South Korea ====
Donga Science
==== Turkey ====
Bilim ve Teknik
=== Europe ===
EuroScientist
==== Austria ====
Universum
==== Czechia ====
Vesmír
==== Denmark ====
Aktuel Naturvidenskab
Illustreret Videnskab
==== Finland ====
Tiede
==== France ====
La Recherche
Pour la Science
Science & Vie
==== Germany ====
Laborjournal
Spektrum der Wissenschaft
Welt der Physik
Science Notes
==== Italy ====
Popular Science Italia
Airone
Focus
Le Scienze
==== Netherlands ====
Quest
Zenit
==== Poland ====
Wiedza i Życie
==== Russia ====
Nauka i Zhizn
Tekhnika Molodezhi
Kvant
Vokrug sveta
==== Serbia ====
SciTech
==== Sweden ====
Illustrerad Vetenskap
==== United Kingdom ====
All About Space
BBC Focus
BBC Science Focus
BBC Sky at Night
Laboratory News
New Scientist
Physics World
Scientific European
=== North America ===
==== United States ====
===== General =====
American Scientist
Behavioral Scientist
Discover
MIT Technology Review
Popular Mechanics
Knowable Magazine
Popular Science
Nautilus
New Scientist
Quanta Magazine
Science (1979–1986)
Science News
Scientific American
Seed
===== Astronomy/Aerospace =====
Air & Space
Astronomy
Mercury
Planetary Report
Sky & Telescope
Spinoff
===== Others =====
Physics Today
Scientific American Mind
The Scientist
Skeptic
Technologist
Weatherwise
=== Oceania ===
==== Australia ====
Australasian Science
Australian Geographic
Cosmos
New Scientist
=== South America ===
==== Brazil ====
Galileu
Superinteressante
Ciência Hoje
==== Chile ====
Argo Navis
== See also ==
Popular science
Science book
Science journalism
== References == | Wikipedia/Science_magazines |
Antiscience is a set of attitudes and a form of anti-intellectualism that involves a rejection of science and the scientific method. People holding antiscientific views do not accept science as an objective method that can generate universal knowledge. Antiscience commonly manifests through rejection of scientific ideas such as climate change and evolution. It also includes pseudoscience, methods that claim to be scientific but reject the scientific method. Antiscience leads to belief in false conspiracy theories and alternative medicine. Lack of trust in science has been linked to the promotion of political extremism and distrust in medical treatments.
== History ==
In the early days of the scientific revolution, scientists such as Robert Boyle (1627–1691) found themselves in conflict with those such as Thomas Hobbes (1588–1679), who were skeptical of whether science was a satisfactory way to obtain genuine knowledge about the world.
Hobbes' stance is regarded by Ian Shapiro as an antiscience position:
In his Six Lessons to the Professors of Mathematics,...[published in 1656, Hobbes] distinguished 'demonstrable' fields, as 'those the construction of the subject whereof is in the power of the artist himself,' from 'indemonstrable' ones 'where the causes are to seek for.' We can only know the causes of what we make. So geometry is demonstrable, because 'the lines and figures from which we reason are drawn and described by ourselves' and 'civil philosophy is demonstrable, because we make the commonwealth ourselves.' But we can only speculate about the natural world, because 'we know not the construction, but seek it from the effects.'
In his book Reductionism: Analysis and the Fullness of Reality, published in 2000, Richard H. Jones wrote that Hobbes "put forth the idea of the significance of the nonrational in human behaviour". Jones goes on to group Hobbes with others he classes as "antireductionists" and "individualists", including Wilhelm Dilthey (1833–1911), Karl Marx (1818–1883), Jeremy Bentham (1748–1832) and J S Mill (1806–1873), later adding Karl Popper (1902–1994), John Rawls (1921–2002), and E. O. Wilson (1929–2021) to the list.
Jean-Jacques Rousseau, in his Discourse on the Arts and Sciences (1750), claimed that science can lead to immorality. "Rousseau argues that the progression of the sciences and arts has caused the corruption of virtue and morality" and his "critique of science has much to teach us about the dangers involved in our political commitment to scientific progress, and about the ways in which the future happiness of mankind might be secured". Nevertheless, Rousseau does not state in his Discourses that sciences are necessarily bad, and states that figures like René Descartes, Francis Bacon, and Isaac Newton should be held in high regard.
In the conclusion to the Discourses, he says that these (aforementioned) can cultivate sciences to great benefit, and that morality's corruption is mostly because of society's bad influence on scientists.
William Blake (1757–1827) reacted strongly in his paintings and writings against the work of Isaac Newton (1642–1727), and is seen as being perhaps the earliest (and almost certainly the most prominent and enduring) example of what is seen by historians as the aesthetic or Romantic antiscience response. For example, in his 1795 poem "Auguries of Innocence", Blake describes the beautiful and natural robin redbreast imprisoned by what one might interpret as the materialistic cage of Newtonian mathematics and science.
Blake's painting of Newton depicts the scientist "as a misguided hero whose gaze was directed only at sterile geometrical diagrams drawn on the ground". Blake thought that "Newton, Bacon, and Locke with their emphasis on reason were nothing more than 'the three great teachers of atheism, or Satan's Doctrine'...the picture progresses from exuberance and colour on the left, to sterility and blackness on the right. In Blake's view Newton brings not light, but night". In a 1940 poem, W.H. Auden summarises Blake's anti-scientific views by saying that he "[broke] off relations in a curse, with the Newtonian Universe".
One recent biographer of Newton considers him more as a renaissance alchemist, natural philosopher, and magician rather than a true representative of scientific Enlightenment, as popularized by Voltaire (1694–1778) and other Newtonians.
Antiscience issues are seen as a fundamental consideration in the historical transition from "pre-science" or "protoscience" such as that evident in alchemy. Many disciplines that pre-date the widespread adoption and acceptance of the scientific method, such as geometry and astronomy, are not seen as anti-science. However, some of the orthodoxies within those disciplines that predate a scientific approach (such as those orthodoxies repudiated by the discoveries of Galileo (1564–1642)) are seen as being a product of an anti-scientific stance.
Friedrich Nietzsche in The Gay Science (1882) questions scientific dogmatism:
"[...] in Science, convictions have no rights of citizenship, as is said with good reason. Only when they decide to descend to the modesty of a hypothesis, of a provisional experimental point of view, of a regulative fiction, maybe they be granted admission and even a certain value within the realm of knowledge – though always with the restriction that they remain under police supervision, under the police of mistrust. But does this not mean, more precisely considered, that a conviction may obtain admission to science only when it ceases to be a conviction? Would not the discipline of the scientific spirit begin with this, no longer to permit oneself any convictions? Probably that is how it is. But one must still ask whether it is not the case that, in order that this discipline could begin, a conviction must have been there already, and even such a commanding and unconditional one that it sacrificed all other convictions for its own sake. It is clear that Science too rests on a faith; there is no Science 'without presuppositions.' The question whether truth is needed must not only have been affirmed in advance, but affirmed to the extent that the principle, the faith, the conviction is expressed: 'nothing is needed more than truth, and in relation to it, everything else has only second-rate value".
The term "scientism", originating in science studies, was adopted and is used by sociologists and philosophers of science to describe the views, beliefs and behavior of strong supporters of applying ostensibly scientific concepts beyond its traditional disciplines.
Specifically, scientism promotes science as the best or only objective means to determine normative and epistemological values. The term scientism is generally used critically, implying a cosmetic application of science in unwarranted situations considered not amenable to application of the scientific method or similar scientific standards. The word is commonly used in a pejorative sense, applying to individuals who seem to be treating science in a similar way to a religion. The term reductionism is occasionally used in a similarly pejorative way (as a more subtle attack on scientists). However, some scientists feel comfortable being labelled as reductionists, while agreeing that there might be conceptual and philosophical shortcomings of reductionism.
However, non-reductionist (see Emergentism) views of science have been formulated in varied forms in several scientific fields like statistical physics, chaos theory, complexity theory, cybernetics, systems theory, systems biology, ecology, information theory, etc. Such fields tend to assume that strong interactions between units produce new phenomena in "higher" levels that cannot be accounted for solely by reductionism. For example, it is not valuable (or currently possible) to describe a chess game or gene networks using quantum mechanics. The emergentist view of science ("More is Different", in the words of 1977 Nobel-laureate physicist Philip W. Anderson)
has been inspired in its methodology by the European social sciences (Durkheim, Marx) which tend to reject methodological individualism.
== Political ==
Elyse Amend and Darin Barney argue that while antiscience can be a descriptive label, it is often used as a rhetorical one, being effectively used to discredit one's political opponents. Thus, charges of antiscience are not necessarily warranted.
=== Left-wing ===
One expression of antiscience is the "denial of universality and... legitimisation of alternatives" and that the results of scientific findings do not always represent any underlying reality but can merely reflect the ideology of dominant groups within society. Alan Sokal states that this view associates science with the political right and is seen as a belief system that is conservative and conformist, that suppresses innovation, that resists change and that acts dictatorially. This includes the view, for example, that science has a "bourgeois and/or Eurocentric and/or masculinist world-view".
The anti-nuclear movement, often associated with the left, has been criticized for overstating the negative effects of nuclear power, and understating the environmental costs of non-nuclear sources that can be prevented through nuclear energy. Opposition to genetically modified organisms (GMOs) has also been associated with the left.
=== Right-wing ===
The origin of antiscience thinking may be traced back to the reaction of Romanticism to the Enlightenment, a movement often referred to as the Counter-Enlightenment. Romanticism emphasizes that intuition, passion, and organic links to nature are primal values and that rational thinking is merely a product of human life. Modern right-wing antiscience includes climate change denial, rejection of evolution, and misinformation about COVID-19 vaccines. While concentrated in areas of science that are seen as motivating government action, these attitudes are strong enough to make conservatives appreciate science less in general.
Characteristics of antiscience associated with the right include the appeal to conspiracy theories to explain why scientists believe what they believe, in an attempt to undermine the confidence or power usually associated to science (e.g., in global warming conspiracy theories). In modern times, it has been argued that right-wing politics carries an anti-science tendency. While some have suggested that this is innate to either rightists or their beliefs, others have argued it is a "quirk" of a historical and political context in which scientific findings happened to challenge or appeared to challenge the worldviews of rightists rather than leftists.
=== Religious ===
In this context, antiscience may be considered dependent on religious, moral, and cultural arguments. For this kind of religious antiscience philosophy, science is an anti-spiritual and materialistic force that undermines traditional values, ethnic identity, and accumulated historical wisdom in favor of reason and cosmopolitanism. In particular, the traditional and ethnic values emphasized are similar to those of white supremacist Christian Identity theology. Still, similar right-wing views have been developed by radically conservative sects of Islam, Judaism, Hinduism, and Buddhism. New religious movements such as the left-wing New Age and the far-right Falun Gong thinking also criticize the scientific worldview as favouring a reductionist, atheist, or materialist philosophy.
A frequent basis of antiscientific sentiment is religious theism with literal interpretations of sacred text. Here, scientific theories that conflict with divinely inspired knowledge are regarded as flawed. Over the centuries, religious institutions have been hesitant to embrace such ideas as heliocentrism and planetary motion because they contradict the dominant interpretation of various passages of scripture. More recently, the body of creation theologies known collectively as creationism, including the teleological theory of intelligent design, has been promoted by religious theists (primarily fundamentalists) in response to the process of evolution by natural selection. One of the more extreme creation theologies, young Earth creationism, also finds itself in conflict with research in cosmology, historical geology, and the origin of life. Young Earth creationism is predominantly exclusive to fundamentalist Protestant Christianity, though it is also present in Catholicism and Judaism, albeit to a lesser extent.
Studies suggest that a belief in spirituality rather than religion may better indicate an anti-science position.
To the extent that attempts to overcome antiscience sentiments have failed, some argue that a different approach to science advocacy is needed. One such approach says that it is important to develop a more accurate understanding of those who deny science (avoiding stereotyping them as backward and uneducated) and also to attempt outreach via those who share cultural values with target audiences, such as scientists who also hold religious beliefs.
== Areas ==
Historically, antiscience first arose as a reaction against scientific materialism. The 18th century Enlightenment had ushered in "the ideal of a unified system of all the sciences", but there were those fearful of this notion, who "felt that constrictions of reason and science, of a single all-embracing system... were in some way constricting, an obstacle to their vision of the world, chains on their imagination or feeling". Antiscience then is a rejection of "the scientific model [or paradigm]... with its strong implication that only that which was quantifiable, or at any rate, measurable... was real". In this sense, it comprises a "critical attack upon the total claim of the new scientific method to dominate the entire field of human knowledge". However, scientific positivism (logical positivism) does not deny the reality of non-measurable phenomena, only that those phenomena should not be adequate to scientific investigation. Moreover, positivism, as a philosophical basis for the scientific method, is not consensual or even dominant in the scientific community (see philosophy of science).
Recent developments and discussions around antiscience attitudes reveal how deeply intertwined these beliefs are with social, political, and psychological factors. A study published by Ohio State News on July 11, 2022, identified four primary bases that underpin antiscience beliefs: doubts about the credibility of scientific sources, identification with groups holding antiscience attitudes, conflicts between scientific messages and personal beliefs, and discrepancies between the presentation of scientific messages and individuals’ thinking styles. These factors are exacerbated in the current political climate, where ideology significantly influences people's acceptance of science, particularly on topics that have become politically polarized, such as vaccines and climate change. The politicization of science poses a significant challenge to public health and safety, particularly in managing global crises like the COVID-19 pandemic.
The following quotes explore this aspect of four major areas of antiscience: philosophy, sociology, ecology and political.
=== Philosophy ===
Philosophical objections against science are often objections about the role of reductionism. For example, in the field of psychology, "both reductionists and antireductionists accept that... non-molecular explanations may not be improved, corrected or grounded in molecular ones". Further, "epistemological antireductionism holds that, given our finite mental capacities, we would not be able to grasp the ultimate physical explanation of many complex phenomena even if we knew the laws governing their ultimate
constituents". Some see antiscience as "common...in academic settings...many people see that there are problems in demarcation between science, scientism, and pseudoscience resulting in an antiscience stance. Some argue that nothing can be known for sure".
Many philosophers are "divided as to whether reduction should be a central strategy for understanding the world". However, many agree that "there are, nevertheless, reasons why we want science to discover properties and explanations other than reductive physical ones". Such issues stem "from an antireductionist worry that there is no absolute conception of reality, that is, a characterization of reality such as... science claims to provide".
=== Sociology ===
Sociologist Thomas Gieryn refers to "some sociologists who might appear to be antiscience". Some "philosophers and antiscience types", he contends, may have presented "unreal images of science that threaten the believability of scientific knowledge", or appear to have gone "too far in their antiscience deconstructions". The question often lies in how much scientists conform to the standard ideal of "communalism, universalism, disinterestedness, originality, and... skepticism". "scientists don't always conform... scientists do get passionate about pet theories; they do rely on reputation in judging a scientist's work; they do pursue fame and gain via research". Thus, they may show inherent biases in their work. "[Many] scientists are not as rational and logical as the legend would have them, nor are they as illogical or irrational as some relativists might say".
=== Ecology and health sphere ===
Within the ecological and health spheres, Levins identifies a conflict "not between science and antiscience, but rather between different pathways for science and technology; between a commodified science-for-profit and a gentle science for humane goals; between the sciences of the smallest parts and the sciences of dynamic wholes... [he] offers proposals for a more holistic, integral approach to understanding and addressing environmental issues". These beliefs are also common within the scientific community, with for example, scientists being prominent in environmental campaigns warning of environmental dangers such as ozone depletion and the greenhouse effect. It can also be argued that this version of antiscience comes close to that found in the medical sphere, where patients and practitioners may choose to reject science and adopt a pseudoscientific approach to health problems. This can be both a practical and a conceptual shift and has attracted strong criticism: "therapeutic touch, a healing technique based upon the laying-on of hands, has found wide acceptance in the nursing profession despite its lack of scientific plausibility. Its acceptance is indicative of a broad antiscientific trend in nursing".
Glazer also criticises the therapists and patients, "for abandoning the biological underpinnings of nursing and for misreading philosophy in the service of an antiscientific world-view". In contrast, Brian Martin criticized Gross and Levitt by saying that "[their] basic approach is to attack constructivists for not being positivists," and that science is "presented as a unitary object, usually identified with scientific knowledge. It is portrayed as neutral and objective. Second, science is claimed to be under attack by 'antiscience' which is composed essentially of ideologues who are threats to the neutrality and objectivity that are fundamental to science. Third, a highly selective attack is made on the arguments of 'antiscience'". Such people allegedly then "routinely equate critique of scientific knowledge with hostility to science, a jump that is logically unsupportable and empirically dubious". Having then "constructed two artificial entities, a unitary 'science' and a unitary 'academic left', each reduced to epistemological essences, Gross and Levitt proceed to attack. They pick out figures in each of several areas – science studies, postmodernism, feminism, environmentalism, AIDS activism – and criticise their critiques of science".
The writings of Young serve to illustrate more antiscientific views: "The strength of the antiscience movement and of alternative technology is that their advocates have managed to retain Utopian vision while still trying to create concrete instances of it". "The real social, ideological and economic forces shaping science...[have] been opposed to the point of suppression in many quarters. Most scientists hate it and label it 'antiscience'. But it is urgently needed, because it makes science self-conscious and hopefully self-critical and accountable with respect to the forces which shape research priorities, criteria, goals".
Genetically modified foods also bring about antiscience sentiment. The general public has recently become more aware of the dangers of a poor diet, as there have been numerous studies that show that the two are inextricably linked. Anti-science dictates that science is untrustworthy, because it is never complete and always being revised, which would be a probable cause for the fear that the general public has of genetically modified foods despite scientific reassurance that such foods are safe.
Antivaccinationists rely on whatever comes to hand presenting some of their arguments as if scientific; however, a strain of antiscience is part of their approach.
=== Political ===
Political scientist Tom Nichols, from Harvard Extension School and the U.S. Naval War College, points out that skepticism towards scientific expertise has increasingly become a symbol of political identity, especially within conservative circles. This skepticism is not just a result of misinformation but also reflects a broader cultural shift towards diminishing trust in experts and authoritative sources. This trend challenges the traditional neutrality of science, positioning scientific beliefs and facts within the contentious arena of political ideology.
The COVID-19 pandemic, for example, conflicting responses to public health measures and vaccine acceptance have highlighted the extent to which science has been politicized. Such polarization suggests that for some, rejecting scientific consensus or public health guidance serves as an expression of political allegiance or skepticism towards perceived authority figures.
This politicization of science complicates efforts to address public health crises and undermines the broader social contract that underpins scientific research and its application for the public good. The challenge lies not only in combating misinformation but also in bridging ideological divides that affect public trust in science. Strategies to counteract antiscience attitudes may need to encompass more than just presenting factual information; they might also need to engage with the underlying social and psychological factors that contribute to these attitudes, fostering dialogue that acknowledges different viewpoints and seeks common ground.
== Antiscience media ==
Major antiscience media include portals Natural News, Global Revolution TV, TruthWiki.org, TheAntiMedia.org and GoodGopher. Antiscience views have also been supported on social media by organizations known to support fake news such as the web brigades.: 124
== See also ==
== References ==
== Bibliography ==
A Bullock & S Trombley [Eds.], The New Fontana Dictionary of Modern Thought, third edition, London: Harper Collins, 1999
Burger, P and Luckman, T, "The Social Construction of Reality: A Treatise" in the Sociology of Knowledge. Garden City, NY: Doubleday, 1966
Collins, Harry and Pinch, Trevor, The Golem. What everyone should know about science, Cambridge: Cambridge University Press, 1993
Gross, Paul R and Norman Levitt, Higher Superstition: The Academic Left and Its Quarrels with Science, Baltimore: Johns Hopkins University Press, 1994
Gerald Holton, Science and anti-science, Harvard University Press, 1993 ISBN 0674792998
Knorr-Cetina, Karin D, & Mulkay, Michael, Science Observed: Perspectives on the Social Study of Science, Sage Publications Ltd, 1983
Knorr-Cetina, Karin D, Epistemic Cultures: How the Sciences Make Knowledge, Harvard University Press, 1999
Levins, R. "Ten propositions on science and antiscience" in Social Text, 46/47:101–111, 1996.
Levins, R. "Touch Red," in Judy Kaplan an Linn Shapiro, eds., Red Diapers: Growing up in the Communist Left, U. of Illinois, 1998, pp. 257–266.
Levins, R. "Dialectics and systems theory" in Science and Society 62(3):373–399, 1998.
Levins, R. "The internal and external in explanatory theories", Science as Culture, 7(4):557–582, 1998.
Levins, R. and Lopez C. "Toward an ecosocial view of health", International Journal of Health Services 29(2):261–293, 1999.
Nye, Andrea, Words of Power: A Feminist Reading of the History of Logic, London: Routledge, 1990
Pepper, David, The Roots of Modern Environmentalism, London: Routledge, 1989
Ullica Segerstrale (Ed), Beyond the Science Wars: the missing discourse about science and society, Albany: State University of New York Press, 2000, ISBN 0791446182
Vining, Joseph, On the Future of Total Theory: Science, Antiscience, and Human Candor, Erasmus Institute papers, 1999
Leviathan and the Air Pump Schapin and Shaffer (covers the conflict between Hobbes and Boyle).
The Scientific Outlook by Bertrand Russell (sets out the limits of science from the perspective of a vehement campaigner against anti-science).
An Enquiry Concerning Human Understanding by David Hume (The first major work to point out the limits of inductive reasoning, the 'new tool of science').
Against Method by Paul Feyerabend (probably the individual most accused of reinvigorating anti-science, although some claim that he is in fact strengthening the scientific debate).
== External links ==
"What's wrong with relativism?", Physics World, by Harry Collins
The Postmodern Critique of Science
A Critique of Western Science by Alex Paterson
The Critique of Science Becomes Academic by Brian Martin
If They Believe That – Science by Reginald Firehammer
The Ontological Reversal: A Figure of Thought of Importance for Science Education by Bo Dahlin
Davidson, Donald, Essays on Actions and Events, OUP, 2001 ISBN 0199246270
Rosenberg, Alex; Kaplan, D. M. (2005). "How to Reconcile Physicalism and Antireductionism about Biology". Philosophy of Science. 72 (1): 43–68. doi:10.1086/428389. ISSN 1539-767X. JSTOR 10.1086/428389. S2CID 170840113.
Psychoneural Reduction The New Wave, John Bickle, Bradford Books, 1998, ISBN 0262024322
Dunning, Brian (8 November 2011). "Skeptoid #283: Top 10 Anti-Science Websites". Skeptoid. | Wikipedia/Antiscience |
A control variable (or scientific constant) in scientific experimentation is an experimental element which is constant (controlled) and unchanged throughout the course of the investigation. Control variables could strongly influence experimental results were they not held constant during the experiment in order to test the relative relationship of the dependent variable (DV) and independent variable (IV). The control variables themselves are not of primary interest to the experimenter.
"Good controls", also known as “confounders” or “deconfounders”, are variables which are theorized to be unaffected by the treatment and which are intended to eliminate omitted-variable bias. "Bad controls", on the other hand, are variables that could be affected by the treatment, might contribute to collider bias, and lead to erroneous results.
== Usage ==
A variable in an experiment which is held constant in order to assess the relationship between multiple variables, is a control variable. A control variable is an element that is not changed throughout an experiment because its unchanging state allows better understanding of the relationship between the other variables being tested.
In any system existing in a natural state, many variables may be interdependent, with each affecting the other. Scientific experiments test the relationship of an IV (or independent variable: that element that is manipulated by the experimenter) to the DV (or dependent variable: that element affected by the manipulation of the IV). Any additional independent variable can be a control variable.
A control variable is an experimental condition or element that is kept the same throughout the experiment, and it is not of primary concern in the experiment, nor will it influence the outcome of the experiment. Any unexpected (e.g.: uncontrolled) change in a control variable during an experiment would invalidate the correlation of dependent variables (DV) to the independent variable (IV), thus skewing the results, and invalidating the working hypothesis. This indicates the presence of a spurious relationship existing within experimental parameters. Unexpected results may result from the presence of a confounding variable, thus requiring a re-working of the initial experimental hypothesis. Confounding variables are a threat to the internal validity of an experiment. This situation may be resolved by first identifying the confounding variable and then redesigning the experiment taking that information into consideration. One way to this is to control the confounding variable, thus making it a control variable. If, however, the spurious relationship cannot be identified, the working hypothesis may have to be abandoned.
== Experimental examples ==
Take, for example, the well known combined gas law, which is stated mathematically as:
P
V
T
=
k
{\displaystyle \qquad {\frac {PV}{T}}=k}
where:
P is the pressure
V is the volume
T is the thermodynamic temperature measured in kelvins
k is a constant (with units of energy divided by temperature).
which shows that the ratio between the pressure-volume product and the temperature of a system remains constant.
In an experimental verification of parts of the combined gas law, (P * V = T), where Pressure, Temperature, and Volume are all variables, to test the resultant changes to any of these variables requires at least one to be kept constant. This is in order to see comparable experimental results in the remaining variables.
If Temperature is made the control variable and it is not allowed to change throughout the course of the experiment, the relationship between the dependent variables, Pressure, and Volume, can quickly be established by changing the value for one or the other, and this is Boyle's law. For instance, if the Pressure is raised then the Volume must decrease.
If, however, Volume is made the control variable and it is not allowed to change throughout the course of the experiment, the relationship between dependent variables, Pressure, and Temperature, can quickly be established by changing the value for one or the other, and this is Gay-Lussac's law. For instance, if the Pressure is raised then the Temperature must increase.
== Notes ==
== References ==
== External links ==
Definitions; Science Buddies – Science Fair Projects. | Wikipedia/Control_variable |
Annals of Science is a peer-reviewed academic journal covering the history of science and technology. It is published by Taylor & Francis and was established in 1936. The founding editor-in-chief was the Canadian historian of science Harcourt Brown.
== History ==
The journal was established after Brown visited Britain for a year and discussed where he could publish work on the history of science with Henry Robinson of the library of the Royal Society of London. They decided that aside from the Belgian Isis, there were few outlets for such work, and so founded the Annals of Science with Douglas McKie (University College London), who was the main editor. The aim was to publish faster than Isis and with a focus on the modern period. The editors chose to have a bright orange cover to make it stand out against the usual blue or grey of periodicals at the time.
Around the time of World War II, only three volumes were published over a period of 12 years. From 1956 to 1958, the Bulletin of the British Society for the History of Science was published as part of the Annals of Science. In 1974, then editor Ivor Grattan-Guinness moved the journal from 4 to 6 issues per year; 100 issues were published from 1936 to 1969 and a further hundred by 1986. Grattan-Guinness also redesigned the cover and changed the tagline from "The History of Science and Technology since the Renaissance" to "The History of Science and Technology from the Thirteenth Century".
== Reception ==
David M. Knight has said that "The major event of the first phase of the development of British journals [of the history of science] is the founding of Annals of Science in 1936." Gordon L. Miller called it a "respected scholarly journal". A review in Astrophysical Journal from the year of the launch noted approvingly that the policy of studying the history of science from the renaissance was "liberally interpreted" to accept papers studying earlier periods.
== Editors ==
Robinson was an editor until 1960 and McKie until 1967. Subsequent editors were:
Niels Hugh de Vaudrey Heathcote (1952–1974)
W.A. Smeaton (1960–1965)
F.W. Gibbs (1961–1965)
Trevor I. Williams (1966-?)
R.E.W Maddison (1966-?)
Harold J. Sharlin (1969-)
Hans Kangro (1969-)
Ivor Grattan-Guinness (1974–81, book review editor until 1987)
G.L.E. Turner (1981-?),
Trevor Levere (1999–2014)
Robert Iliffe (2011–present) and David Miller (2014–present).
Grattan-Guinness described his experience in taking on the editorship in an article in the journal in 2010. He had published a biographical article on Georg Cantor in the journal in 1971 and met the-then editor, Heathcote, during the process of publication. Heathcote was overloaded with work — "the journal seemed never to reject anything" — and he invited Grattan-Guinness to join the editorial board. He joined the board and met with the publishers in June 1974, when he told John Cheney, the house editor, that "the journal had acquired a poor reputation in recent years", which surprised Cheney. That same afternoon Cheney rang Heathcote only to find that he was in the process of writing his resignation letter recommending Grattan-Guinness as his successor — the younger man was immediately offered the post of editor. Taylor & Francis would otherwise have closed the journal.
== Abstracting and indexing ==
Annals of Science is abstracted and indexed in:
According to the Journal Citation Reports, the journal has a 2010 impact factor of 0.222.
== See also ==
List of history of science and technology journals and periodicals
== References ==
== External links ==
Official website | Wikipedia/Annals_of_Science |
Technology dynamics is broad and relatively new scientific field that has been developed in the framework of the postwar science and technology studies field. It studies the process of technological change. Under the field of Technology Dynamics the process of technological change is explained by taking into account influences from "internal factors" as well as from "external factors". Internal factors relate technological change to unsolved technical problems and the established modes of solving technological problems and external factors relate it to various (changing) characteristics of the social environment, in which a particular technology is embedded.
== Overview ==
For the last three decades, it has been argued that technology development is neither an autonomous process, determined by the "inherent progress" of human history, nor a process completely determined by external conditions like the prices of the resources that are needed to operate (develop) a technology, as it is theorized in neoclassical economic thinking. In mainstream neoclassical economic thinking, technology is seen as an exogenous factor: at the moment a technology is required, the most appropriate version can be taken down from the shelf based on costs of labor, capital and eventually raw materials.
Conversely, modern technology dynamics studies generally advocate that technologies are not "self-evident" or market-demanded, but are the upshot of a particular path of technology development and are shaped by social, economic and political factors. in this sense, technology dynamics aims at overcoming distinct "internal" and "external" points of views by presenting co-evolutionary approach regarding technology development.
In general, technology dynamics studies, besides giving a "thick description" of technology development, uses constructivist viewpoints emphasizing that technology is the outcome of particular social context. Accordingly, Technology Dynamics emphasizes the significance and possibility of regaining social control of technology, and also provides mechanisms needed to adapt to and steer the development of certain technologies. In that respect, it uses insights from retrospective studies to formulate hypotheses of a prospective nature on technology development of emerging technologies, besides formulating prescriptive policy recommendations.
An important feature of relevant theories of technological change therein is that they underline the quasi-evolutionary character of technological change: change based on technological variation and social selection in which technological knowledge, systems and institutions develop in interaction with each other. Processes of 'path dependence' are crucial in explaining technological change.
Following these lines, there have been different approaches and concepts used under the field of technology dynamics.
== Different frameworks to analyze the dynamics of technology ==
Social construction of technology
Actor–network theory
Systems theory
Normalization process theory
Quasi-evolutionary theories
Innovation system
Technological innovation system
Based on the analysis of the various perspectives, one can aim at developing interventions in the dynamics of a technology. Some approaches have been developed targeting on interventions in technological change:
Technology assessment
Backcasting
Strategic niche management
Transition management (governance)
== References ==
Wiebe E. Bijker, Thomas P. Hughes, Trevor J. Pinch (1987). The social construction of technological systems; new directions in the sociology and history of technology. Cambridge, Massachusetts, MIT Press.
Michel Callon, Philippe Larédo, et al. (1992). "The management and evaluation of technological programs and the dynamics of techno-economic networks: The case of the AFME." Research Policy 21(3): 215–236.
Geels, F. W. (2002). Understanding the dynamics of technological transitions : a co-evolutionary and socio-technical analysis. Enschede, Universiteit Twente.
Hekkert, M. P., R. A. A. Suurs, et al. "Functions of innovation systems: A new approach for analysing technological change." Technological Forecasting and Social Change In Press, Corrected Proof.
Nelson, R. R. and S. G. Winter (1982). An Evolutionary Theory of Economic Change. Cambridge MA., The Belknap Press of Harvard University Press.
Olmeda, Christopher J. (1998). Health Informatics: Concepts of Information Technology in Health and Human Services. Delfin Press. ISBN 0-9821442-1-0
Arie Rip, Misa, Thomas J., Schot, Johan (1995). Managing technology in society; the approach of constructive technology assessment. London, Pinter.
Rotmans, J., Kemp, R., Asselt, M. van (2001). "More revolution than evolution: transition management in public policy." Foresight 3(1): .015-.031.
Schot, J. W. (1992). "Constructive Technology Assessment and Technology Dynamics: The Case of Clean Technologies." Science, Technology, & Human Values 17(1): 36.
Smith, A., A. Stirling, et al. (2005). "The governance of sustainable socio-technical transitions." Research Policy 34(10): 1491–1510.
== External links ==
Technology Dynamics and sustainable Development | Wikipedia/Technology_dynamics |
The unity of science is a thesis in philosophy of science that says that all the sciences form a unified whole. The variants of the thesis can be classified as ontological (giving a unified account of the structure of reality) and/or as epistemic/pragmatic (giving a unified account of how the activities and products of science work). There are also philosophers who emphasize the disunity of science, which does not necessarily imply that there could be no unity in some sense but does emphasize pluralism in the ontology and/or practice of science.
Early versions of the unity of science thesis can be found in ancient Greek philosophers such as Aristotle, and in the later history of Western philosophy. For example, in the first half of the 20th century the thesis was associated with the unity of science movement led by Otto Neurath, and in the second half of the century the thesis was advocated by Ludwig von Bertalanffy in "General System Theory: A New Approach to Unity of Science" (1951) and by Paul Oppenheim and Hilary Putnam in "Unity of Science as a Working Hypothesis" (1958). It has been opposed by, for example, Jerry Fodor in "Special Sciences (Or: The Disunity of Science as a Working Hypothesis)" (1974), by Paul Feyerabend in Against Method (1975) and later works, by John Dupré in "The Disunity of Science" (1983) and The Disorder of Things: Metaphysical Foundations of the Disunity of Science (1993), by Nancy Cartwright in The Dappled World: A Study of the Boundaries of Science (1999) and other works, and by Evelyn Fox Keller in Making Sense of Life: Explaining Biological Development with Models, Metaphors, and Machines (2002) and other works.
Jean Piaget suggested, in his 1918 book Recherche and later works, that the unity of science can be considered in terms of a circle of the sciences, where logic is the foundation for mathematics, which is the foundation for mechanics and physics, and physics is the foundation for chemistry, which is the foundation for biology, which is the foundation for sociology, the moral sciences, psychology, and the theory of knowledge, and the theory of knowledge forms a basis for logic, completing the circle, without implying that any science could be reduced to any other. More recently, many complex systems are considered to be transdisciplinary objects of study. Such systems can be modeled as having emergent properties at different levels of organization, which do not neatly correspond to separate disciplines such as physics or biology, and which cannot be adequately modeled using a philosophy of extreme reductionism ("everything comes from the bottom", which does not fully account for emergent properties) or extreme holism ("everything comes from the top", which does not fully account for systems' components and interactions).
== See also ==
== Notes ==
== References ==
== Further reading ==
== External links ==
Unity of Science at PhilPapers
Guide to the Unity of Science Movement Records 1934–1968 at the University of Chicago Special Collections Research Center | Wikipedia/Unity_of_science |
The 19th century in science saw the birth of science as a profession; the term scientist was coined in 1833 by William Whewell, which soon replaced the older term of (natural) philosopher.
Among the most influential ideas of the 19th century were those of Charles Darwin (alongside the independent research of Alfred Russel Wallace), who in 1859 published the book On the Origin of Species, which introduced the idea of evolution by natural selection. Another important landmark in medicine and biology were the successful efforts to prove the germ theory of disease. Following this, Louis Pasteur made the first vaccine against rabies, and also made many discoveries in the field of chemistry, including the asymmetry of crystals. In chemistry, Dmitri Mendeleev, following the atomic theory of John Dalton, created the first periodic table of elements. In physics, the experiments, theories and discoveries of Michael Faraday, Andre-Marie Ampere, James Clerk Maxwell, and their contemporaries led to the creation of electromagnetism as a new branch of science. Thermodynamics led to an understanding of heat and the notion of energy was defined.
The discovery of new types of radiation and the simultaneous revelation of the nature of atomic structure and matter are two additional highlights. In astronomy, the planet Neptune was discovered. In mathematics, the notion of complex numbers finally matured and led to a subsequent analytical theory; they also began the use of hypercomplex numbers. Karl Weierstrass and others carried out the arithmetization of analysis for functions of real and complex variables. It also saw rise to new progress in geometry beyond those classical theories of Euclid, after a period of nearly two thousand years. The mathematical science of logic likewise had revolutionary breakthroughs after a similarly long period of stagnation. But the most important step in science at this time were the ideas formulated by the creators of electrical science. Their work changed the face of physics and made possible for new technology to come about such as electric power, electrical telegraphy, the telephone, and radio.
== Mathematics ==
Throughout the 19th century mathematics became increasingly abstract. Carl Friedrich Gauss (1777–1855) epitomizes this trend. He did revolutionary work on functions of complex variables, in geometry, and on the convergence of series, leaving aside his many contributions to science. He also gave the first satisfactory proofs of the fundamental theorem of algebra and of the quadratic reciprocity law. His 1801 volume Disquisitiones Arithmeticae laid the foundations of modern number theory.
This century saw the development of the two forms of non-Euclidean geometry, where the parallel postulate of Euclidean geometry no longer holds.
The Russian mathematician Nikolai Ivanovich Lobachevsky and his rival, the Hungarian mathematician János Bolyai, independently defined and studied hyperbolic geometry, where uniqueness of parallels no longer holds. In this geometry the sum of angles in a triangle add up to less than 180°. Elliptic geometry was developed later in the 19th century by the German mathematician Bernhard Riemann; here no parallel can be found and the angles in a triangle add up to more than 180°. Riemann also developed Riemannian geometry, which unifies and vastly generalizes the three types of geometry.
The 19th century saw the beginning of a great deal of abstract algebra. Hermann Grassmann in Germany gave a first version of vector spaces, William Rowan Hamilton in Ireland developed noncommutative algebra. The British mathematician George Boole devised an algebra that soon evolved into what is now called Boolean algebra, in which the only numbers were 0 and 1. Boolean algebra is the starting point of mathematical logic and has important applications in computer science.
Augustin-Louis Cauchy, Bernhard Riemann, and Karl Weierstrass reformulated the calculus in a more rigorous fashion.
Also, for the first time, the limits of mathematics were explored. Niels Henrik Abel, a Norwegian, and Évariste Galois, a Frenchman, proved that there is no general algebraic method for solving polynomial equations of degree greater than four (Abel–Ruffini theorem). Other 19th-century mathematicians utilized this in their proofs that straightedge and compass alone are not sufficient to trisect an arbitrary angle, to construct the side of a cube twice the volume of a given cube, nor to construct a square equal in area to a given circle. Mathematicians had vainly attempted to solve all of these problems since the time of the ancient Greeks. On the other hand, the limitation of three dimensions in geometry was surpassed in the 19th century through considerations of parameter space and hypercomplex numbers.
In the later 19th century, Georg Cantor established the first foundations of set theory, which enabled the rigorous treatment of the notion of infinity and has become the common language of nearly all mathematics. Cantor's set theory, and the rise of mathematical logic in the hands of Peano, L. E. J. Brouwer, David Hilbert, Bertrand Russell, and A.N. Whitehead, initiated a long running debate on the foundations of mathematics.
The 19th century saw the founding of a number of national mathematical societies: the London Mathematical Society in 1865, the Société Mathématique de France in 1872, the Edinburgh Mathematical Society in 1883, the Circolo Matematico di Palermo in 1884, and the American Mathematical Society in 1888. The first international, special-interest society, the Quaternion Society, was formed in 1899, in the context of a vector controversy.
== Physics ==
In 1800, Alessandro Volta invented the electric battery (known as the voltaic pile) and thus improved the way electric currents could also be studied. A year later, Thomas Young demonstrated the wave nature of light—which received strong experimental support from the work of Augustin-Jean Fresnel—and the principle of interference. In 1813, Peter Ewart supported the idea of the conservation of energy in his paper On the measure of moving force. In 1820, Hans Christian Ørsted found that a current-carrying conductor gives rise to a magnetic force surrounding it, and within a week after Ørsted's discovery reached France, André-Marie Ampère discovered that two parallel electric currents will exert forces on each other. In 1821, William Hamilton began his analysis of Hamilton's characteristic function. In 1821, Michael Faraday built an electricity-powered motor, while Georg Ohm stated his law of electrical resistance in 1826, expressing the relationship between voltage, current, and resistance in an electric circuit. A year later, botanist Robert Brown discovered Brownian motion: pollen grains in water undergoing movement resulting from their bombardment by the fast-moving atoms or molecules in the liquid. In 1829, Gaspard Coriolis introduced the terms of work (force times distance) and kinetic energy with the meanings they have today.
In 1831, Faraday (and independently Joseph Henry) discovered the reverse effect, the production of an electric potential or current through magnetism – known as electromagnetic induction; these two discoveries are the basis of the electric motor and the electric generator, respectively. In 1834, Carl Jacobi discovered his uniformly rotating self-gravitating ellipsoids (the Jacobi ellipsoid). In 1834, John Russell observed a nondecaying solitary water wave (soliton) in the Union Canal near Edinburgh and used a water tank to study the dependence of solitary water wave velocities on wave amplitude and water depth. In 1835, William Hamilton stated Hamilton's canonical equations of motion. In the same year, Gaspard Coriolis examined theoretically the mechanical efficiency of waterwheels, and deduced the Coriolis effect. In 1841, Julius Robert von Mayer, an amateur scientist, wrote a paper on the conservation of energy but his lack of academic training led to its rejection. In 1842, Christian Doppler proposed the Doppler effect. In 1847, Hermann von Helmholtz formally stated the law of conservation of energy. In 1851, Léon Foucault showed the Earth's rotation with a huge pendulum (Foucault pendulum).
There were important advances in continuum mechanics in the first half of the century, namely formulation of laws of elasticity for solids and discovery of Navier–Stokes equations for fluids.
=== Laws of thermodynamics ===
In the 19th century, the connection between heat and mechanical energy was established quantitatively by Julius Robert von Mayer and James Prescott Joule, who measured the mechanical equivalent of heat in the 1840s. In 1849, Joule published results from his series of experiments (including the paddlewheel experiment) which show that heat is a form of energy, a fact that was accepted in the 1850s. The relation between heat and energy was important for the development of steam engines, and in 1824 the experimental and theoretical work of Sadi Carnot was published. Carnot captured some of the ideas of thermodynamics in his discussion of the efficiency of an idealized engine. Sadi Carnot's work provided a basis for the formulation of the first law of thermodynamics—a restatement of the law of conservation of energy—which was stated around 1850 by William Thomson, later known as Lord Kelvin, and Rudolf Clausius. Lord Kelvin, who had extended the concept of absolute zero from gases to all substances in 1848, drew upon the engineering theory of Lazare Carnot, Sadi Carnot, and Émile Clapeyron–as well as the experimentation of James Prescott Joule on the interchangeability of mechanical, chemical, thermal, and electrical forms of work—to formulate the first law.
Kelvin and Clausius also stated the second law of thermodynamics, which was originally formulated in terms of the fact that heat does not spontaneously flow from a colder body to a hotter. Other formulations followed quickly (for example, the second law was expounded in Thomson and Peter Guthrie Tait's influential work Treatise on Natural Philosophy) and Kelvin in particular understood some of the law's general implications. The second Law was the idea that gases consist of molecules in motion had been discussed in some detail by Daniel Bernoulli in 1738, but had fallen out of favor, and was revived by Clausius in 1857. In 1850, Hippolyte Fizeau and Léon Foucault measured the speed of light in water and find that it is slower than in air, in support of the wave model of light. In 1852, Joule and Thomson demonstrated that a rapidly expanding gas cools, later named the Joule–Thomson effect or Joule–Kelvin effect. Hermann von Helmholtz puts forward the idea of the heat death of the universe in 1854, the same year that Clausius established the importance of dQ/T (Clausius's theorem) (though he did not yet name the quantity).
=== James Clerk Maxwell ===
In 1859, James Clerk Maxwell discovered the distribution law of molecular velocities. Maxwell showed that electric and magnetic fields are propagated outward from their source at a speed equal to that of light and that light is one of several kinds of electromagnetic radiation, differing only in frequency and wavelength from the others. In 1859, Maxwell worked out the mathematics of the distribution of velocities of the molecules of a gas. The wave theory of light was widely accepted by the time of Maxwell's work on the electromagnetic field, and afterward the study of light and that of electricity and magnetism were closely related. In 1864 James Maxwell published his papers on a dynamical theory of the electromagnetic field, and stated that light is an electromagnetic phenomenon in the 1873 publication of Maxwell's Treatise on Electricity and Magnetism. This work drew upon theoretical work by German theoreticians such as Carl Friedrich Gauss and Wilhelm Weber. The encapsulation of heat in particulate motion, and the addition of electromagnetic forces to Newtonian dynamics established an enormously robust theoretical underpinning to physical observations.
The prediction that light represented a transmission of energy in wave form through a "luminiferous ether", and the seeming confirmation of that prediction with Helmholtz student Heinrich Hertz's 1888 detection of electromagnetic radiation, was a major triumph for physical theory and raised the possibility that even more fundamental theories based on the field could soon be developed. Experimental confirmation of Maxwell's theory was provided by Hertz, who generated and detected electric waves in 1886 and verified their properties, at the same time foreshadowing their application in radio, television, and other devices. In 1887, Heinrich Hertz discovered the photoelectric effect. Research on the electromagnetic waves began soon after, with many scientists and inventors conducting experiments on their properties. In the mid to late 1890s Guglielmo Marconi developed a radio wave based wireless telegraphy system (see invention of radio).
The atomic theory of matter had been proposed again in the early 19th century by the chemist John Dalton and became one of the hypotheses of the kinetic-molecular theory of gases developed by Clausius and James Clerk Maxwell to explain the laws of thermodynamics. The kinetic theory in turn led to the statistical mechanics of Ludwig Boltzmann (1844–1906) and Josiah Willard Gibbs (1839–1903), which held that energy (including heat) was a measure of the speed of particles. Interrelating the statistical likelihood of certain states of organization of these particles with the energy of those states, Clausius reinterpreted the dissipation of energy to be the statistical tendency of molecular configurations to pass toward increasingly likely, increasingly disorganized states (coining the term "entropy" to describe the disorganization of a state). The statistical versus absolute interpretations of the second law of thermodynamics set up a dispute that would last for several decades (producing arguments such as "Maxwell's demon"), and that would not be held to be definitively resolved until the behavior of atoms was firmly established in the early 20th century. In 1902, James Jeans found the length scale required for gravitational perturbations to grow in a static nearly homogeneous medium.
== Chemistry ==
=== Synthesize of First Organic Compound ===
see more about this in Wöhler synthesis
In 1828, Friedrich Wöhler synthesized urea from certain inorganic compounds. He synthesized urea by slowly evaporating a water solution of ammonium cyanate, which he had prepared by adding silver cyanate to ammonium chloride. It has been previously believed that, the substances produced by plants and animals (by generally all living beings or organisms) can not be produced in lab and can only be produced by "life force". But this synthesize of urea had changed that concept. Which has led to many discoveries later.
=== Dalton's Atomic theory ===
See more about this in John DaltonIn 19th century, John Dalton proposed the idea of atoms as small indivisible particles which together can form compounds. Although the concept of the atom dates back to the ideas of Democritus, John Dalton formulated the first modern description of it as the fundamental building block of chemical structures. Dalton developed the law of multiple proportions (first presented in 1803) by studying and expanding upon the works of Antoine Lavoisier and Joseph Proust.
The main points of Dalton's atomic theory, as it eventually developed, are:
Elements are made of extremely small particles called atoms.
Atoms of a given element are identical in size, mass and other properties; atoms of different elements differ in size, mass and other properties.
Atoms cannot be subdivided, created or destroyed.
Atoms of different elements combine in simple whole-number ratios to form chemical compounds.
In chemical reactions, atoms are combined, separated or rearranged.
=== Periodic Table ===
see more about this in detail in History of the periodic table,
In 1869, Russian chemist Dmitri Mendeleev created the framework that became the modern periodic table, leaving gaps for elements that were yet to be discovered. While arranging the elements according to their atomic weight, if he found that they did not fit into the group he would rearrange them. Mendeleev predicted the properties of some undiscovered elements and gave them names such as "eka-aluminium" for an element with properties similar to aluminium. Later eka-aluminium was discovered as gallium. Some discrepancies remained; the position of certain elements, such as iodine and tellurium, could not be explained.
== Engineering and technology ==
1804: First steam locomotive begins operation.
1825: Erie Canal opened connecting the Great Lakes to the Atlantic Ocean.
1825: First isolation of aluminium.
1825: The Stockton and Darlington Railway, the first public railway in the world, is opened.
1826: Samuel Morey patents the internal combustion engine.
1829: First electric motor built.
1837: Telegraphy patented.
1841: The word "dinosaur" is coined by Richard Owen
1844: First publicly funded telegraph line in the world—between Baltimore and Washington—sends demonstration message on 24 May, ushering in the age of the telegraph. This message read "What hath God wrought?" (Bible, Numbers 23:23)
1849: The safety pin and the gas mask are invented.
1855: Bessemer process enables steel to be mass-produced.
1856: World's first oil refinery in Romania
1858: Invention of the phonautograph, the first true device for recording sound.
1863: First section of the London Underground opens.
1866: Successful transatlantic telegraph cable follows an earlier attempt in 1858.
1867: Alfred Nobel invents dynamite.
1869: First transcontinental railroad completed in United States on 10 May.
1870: Rasmus Malling-Hansen's invention the Hansen Writing Ball becomes the first commercially sold typewriter.
1873: Blue jeans and barbed wire are invented.
1877: Thomas Edison invents the phonograph
1878: First commercial telephone exchange in New Haven, Connecticut.
1879: Thomas Edison tests his first light bulb.
1881: First electrical power plant and grid in Godalming, Britain.
1884: Sir Hiram Maxim invents the first self-powered Machine gun.
1885: Singer begins production of the 'Vibrating Shuttle'. which would become the most popular model of sewing machine.
1886: Karl Benz sells the first commercial automobile.
1888: Galileo Ferraris and Nikola Tesla both introduce the idea of a rotating magnetic field induction motor.
1890: The cardboard box is invented.
1892: John Froelich develops and constructs the first gasoline/petrol-powered tractor.
1894: Karl Elsener invents the Swiss Army knife.
1894: First gramophone record.
1895: Wilhelm Röntgen identifies x-rays.
1896: Guglielmo Marconi applies for patent for the first radio wave base communication system.
== Biology and medicine ==
In 1859, Charles Darwin published the book The Origin of Species, which introduced the idea of evolution by natural selection.
Oscar Hertwig publishes his findings in reproductive and developmental biology. In 1875 he published his first work, being the first to correctly describe animal conception. In his later work in 1885, he described that the nucleus contained nuclein (now called nucleic acid) and that these nuclein were responsible for the transmission of hereditary characteristics.
=== Medicine ===
1804: Morphine first isolated.
1842: Anaesthesia used for the first time.
1855: Cocaine is isolated by Friedrich Gaedcke.
1885: Louis Pasteur creates the first successful vaccine against rabies for a young boy who had been bitten 14 times by a rabid dog.
1889: Aspirin patented.
== Social sciences ==
In 1871, William Stanley Jevons and Carl Menger, working independently, solved Adam Smith's paradox of value with the insight that people valued each additional unit of a good less than the previous unit. In 1874, Léon Walras independently came to a similar insight. Menger's student Friedrich von Wieser coined the term "marginal utility" to describe the new theory. Modern microeconomics is built on the insights of the Marginal Revolution.
=== Economics ===
1871: Marginalism introduced in economic theory.
1821: Comparative advantage in business was introduced by David Ricardo.
1824: The patronage of infant industries was explained by Friedrich List.
1828: The economic cooperative theory was stated by Charles Fourier.
1874: The law of general equilibrium was stated by Leon Walras from the Lausanne school.
== People ==
The list of important 19th-century scientists includes:
== References == | Wikipedia/19th_century_in_science |
On the Connexion of the Physical Sciences, by Mary Somerville, is one of the best-selling science books of the 19th century. The book went through many editions and was translated into several European languages. It is considered one of the first popular science books, containing few diagrams and very little mathematics. It describes astronomy, physics, chemistry, geography, meteorology and electromagnetism as they were scientifically understood at the time. In a review of the book in March 1834, William Whewell coined the word "scientist".
== See also ==
Letters to a German Princess
== References ==
== External links ==
On the connection of the physical sciences at the Internet Archive
On the Connexion of the Physical Sciences at Project Gutenberg | Wikipedia/On_the_Connexion_of_the_Physical_Sciences |
Creation science or scientific creationism is a pseudoscientific form of Young Earth creationism which claims to offer scientific arguments for certain literalist and inerrantist interpretations of the Bible. It is often presented without overt faith-based language, but instead relies on reinterpreting scientific results to argue that various myths in the Book of Genesis and other select biblical passages are scientifically valid. The most commonly advanced ideas of creation science include special creation based on the Genesis creation narrative and flood geology based on the Genesis flood narrative. Creationists also claim they can disprove or reexplain a variety of scientific facts, theories and paradigms of geology, cosmology, biological evolution, archaeology, history, and linguistics using creation science. Creation science was foundational to intelligent design.
The overwhelming consensus of the scientific community is that creation science fails to qualify as scientific because it lacks empirical support, supplies no testable hypotheses, and resolves to describe natural history in terms of scientifically untestable supernatural causes. Courts, most often in the United States where the question has been asked in the context of teaching the subject in public schools, have consistently ruled since the 1980s that creation science is a religious view rather than a scientific one. Historians, philosophers of science and skeptics have described creation science as a pseudoscientific attempt to map the Bible into scientific facts. Professional biologists have criticized creation science for being unscholarly, and even as a dishonest and misguided sham, with extremely harmful educational consequences.
== Beliefs and activities ==
=== Religious basis ===
Creation science is based largely upon chapters 1–11 of the Book of Genesis. These describe how God calls the world into existence through the power of speech ("And God said, Let there be light," etc.) in six days, calls all the animals and plants into existence, and molds the first man from clay and the first woman from a rib taken from the man's side; a worldwide flood destroys all life except for Noah and his family and representatives of the animals, and Noah becomes the ancestor of the 70 "nations" of the world; the nations live together until the incident of the Tower of Babel, when God disperses them and gives them their different languages. Creation science attempts to explain history and science within the span of Biblical chronology, which places the initial act of creation some six thousand years ago.
=== Modern religious affiliations ===
Most creation science proponents hold fundamentalist or Evangelical Christian beliefs in Biblical literalism or Biblical inerrancy, as opposed to the higher criticism supported by liberal Christianity in the Fundamentalist–Modernist Controversy. However, there are also examples of Islamic and Jewish scientific creationism that conform to the accounts of creation as recorded in their religious doctrines.
The Seventh-day Adventist Church has a history of support for creation science. This dates back to George McCready Price, an active Seventh-day Adventist who developed views of flood geology, which formed the basis of creation science. This work was continued by the Geoscience Research Institute, an official institute of the Seventh-day Adventist Church, located on its Loma Linda University campus in California.
Creation science is generally rejected by the Church of England as well as the Roman Catholic Church. The Pontifical Gregorian University has officially discussed intelligent design as a "cultural phenomenon" without scientific elements. The Church of England's official website cites Charles Darwin's local work assisting people in his religious parish.
=== Views on science ===
Creation science rejects evolution and the common descent of all living things on Earth. Instead, it asserts that the field of evolutionary biology is itself pseudoscientific or even a religion. Creationists argue instead for a system called baraminology, which considers the living world to be descended from uniquely created kinds or "baramins."
Creation science incorporates the concept of catastrophism to reconcile current landforms and fossil distributions with Biblical interpretations, proposing the remains resulted from successive cataclysmic events, such as a worldwide flood and subsequent ice age. It rejects one of the fundamental principles of modern geology (and of modern science generally), uniformitarianism, which applies the same physical and geological laws observed on the Earth today to interpret the Earth's geological history.
Sometimes creationists attack other scientific concepts, like the Big Bang cosmological model or methods of scientific dating based upon radioactive decay. Young Earth creationists also reject current estimates of the age of the universe and the age of the Earth, arguing for creationist cosmologies with timescales much shorter than those determined by modern physical cosmology and geological science, typically less than 10,000 years.
The scientific community has overwhelmingly rejected the ideas put forth in creation science as lying outside the boundaries of a legitimate science. The foundational premises underlying scientific creationism disqualify it as a science because the answers to all inquiry therein are preordained to conform to Bible doctrine, and because that inquiry is constructed upon theories which are not empirically testable in nature.
Scientists also deem creation science's attacks against biological evolution to be without scientific merit. The views of the scientific community were accepted in two significant court decisions in the 1980s, which found the field of creation science to be a religious mode of inquiry, not a scientific one.
== History ==
Creation science began in the 1960s, as a fundamentalist Christian effort in the United States to prove Biblical inerrancy and nullify the scientific evidence for evolution. It has since developed a sizable religious following in the United States, with creation science ministries branching worldwide. The main ideas in creation science are: the belief in creation ex nihilo (Latin: out of nothing); the conviction that the Earth was created within the last 6,000–10,000 years; the belief that humans and other life on Earth were created as distinct fixed "baraminological" kinds; and "flood geology" or the idea that fossils found in geological strata were deposited during a cataclysmic flood which completely covered the entire Earth. As a result, creationists also challenge the geologic and astrophysical measurements of the age of the Earth and the universe along with their origins, which creationists believe are irreconcilable with the account in the Book of Genesis. Creation science proponents often refer to the theory of evolution as "Darwinism" or as "Darwinian evolution."
The creation science texts and curricula that first emerged in the 1960s focused upon concepts derived from a literal interpretation of the Bible and were overtly religious in nature, most notably proposing Noah's flood in the Biblical Genesis account as an explanation for the geological and fossil record. These works attracted little notice beyond the schools and congregations of conservative fundamental and Evangelical Christians until the 1970s, when its followers challenged the teaching of evolution in the public schools and other venues in the United States, bringing it to the attention of the public-at-large and the scientific community. Many school boards and lawmakers were persuaded to include the teaching of creation science alongside evolution in the science curriculum. Creation science texts and curricula used in churches and Christian schools were revised to eliminate their Biblical and theological references, and less explicitly sectarian versions of creation science education were introduced in public schools in Louisiana, Arkansas, and other regions in the United States.
The 1982 ruling in McLean v. Arkansas found that creation science fails to meet the essential characteristics of science and that its chief intent is to advance a particular religious view. The teaching of creation science in public schools in the United States effectively ended in 1987 following the United States Supreme Court decision in Edwards v. Aguillard. The court affirmed that a statute requiring the teaching of creation science alongside evolution when evolution is taught in Louisiana public schools was unconstitutional because its sole true purpose was to advance a particular religious belief.
In response to this ruling, drafts of the creation science school textbook Of Pandas and People were edited to change references of creation to intelligent design before its publication in 1989. The intelligent design movement promoted this version. Requiring intelligent design to be taught in public school science classes was found to be unconstitutional in the 2005 Kitzmiller v. Dover Area School District federal court case.
=== Before 1960s ===
The teaching of evolution was gradually introduced into more and more public high school textbooks in the United States after 1900, but in the aftermath of the First World War the growth of fundamentalist Christianity gave rise to a creationist opposition to such teaching. Legislation prohibiting the teaching of evolution was passed in certain regions, most notably Tennessee's Butler Act of 1925.
The Soviet Union's successful launch of Sputnik 1 in 1957 sparked national concern that the science education in public schools was outdated. In 1958, the United States passed National Defense Education Act which introduced new education guidelines for science instruction. With federal grant funding, the Biological Sciences Curriculum Study (BSCS) drafted new standards for the public schools' science textbooks which included the teaching of evolution. Almost half the nation's high schools were using textbooks based on the guidelines of the BSCS soon after they were published in 1963.
The Tennessee legislature did not repeal the Butler Act until 1967.
Creation science (dubbed "scientific creationism" at the time) emerged as an organized movement during the 1960s. It was strongly influenced by the earlier work of armchair geologist George McCready Price who wrote works such as Illogical Geology: The Weakest Point in the Evolution Theory (1906) and The New Geology (1923) to advance what he termed "new catastrophism" and dispute the current geological time frames and explanations of geologic history. Price was cited at the Scopes Trial of 1925, but his writings had no credence among geologists and other scientists. Price's "new catastrophism" was also disputed by most other creationists until its revival with the 1961 publication of The Genesis Flood by John C. Whitcomb and Henry M. Morris, a work which quickly became an important text on the issue to fundamentalist Christians and expanded the field of creation science beyond critiques of geology into biology and cosmology as well. Soon after its publication, a movement was underway to have the subject taught in United States' public schools.
=== Court determinations ===
The various state laws prohibiting teaching of evolution were overturned in 1968 when the United States Supreme Court ruled in Epperson v. Arkansas such laws violated the Establishment Clause of the First Amendment to the United States Constitution. This ruling inspired a new creationist movement to promote laws requiring that schools give balanced treatment to creation science when evolution is taught. The 1981 Arkansas Act 590 was one such law that carefully detailed the principles of creation science that were to receive equal time in public schools alongside evolutionary principles. The act defined creation science as follows:
"'Creation-science' means the scientific evidences for creation and inferences from those evidences. Creation-science includes the scientific evidences and related inferences that indicate:
Sudden creation of the universe, and, in particular, life, from nothing;
The insufficiency of mutation and natural selection in bringing about development of all living kinds from a single organism;
Changes only with fixed limits of originally created kinds of plants and animals;
Separate ancestry for man and apes;
Explanation of the earth's geology by catastrophism, including the occurrence of worldwide flood; and
A relatively recent inception of the earth and living kinds."
This legislation was examined in McLean v. Arkansas, and the ruling handed down on January 5, 1982, concluded that creation-science as defined in the act "is simply not science". The judgement defined the following as essential characteristics of science:
It is guided by natural law;
It has to be explanatory by reference to nature law;
It is testable against the empirical world;
Its conclusions are tentative, i.e., are not necessarily the final word; and
It is falsifiable.
The court ruled that creation science failed to meet these essential characteristics and identified specific reasons. After examining the key concepts from creation science, the court found:
Sudden creation "from nothing" calls upon a supernatural intervention, not natural law, and is neither testable nor falsifiable
Objections in creation science that mutation and natural selection are insufficient to explain common origins was an incomplete negative generalization
'Kinds' are not scientific classifications, and creation science's claims of an outer limit to the evolutionary change possible of species are not explained scientifically or by natural law
The separate ancestry of man and apes is an assertion rather than a scientific explanation, and did not derive from any scientific fact or theory
Catastrophism, including its identification of the worldwide flood, failed as a science
"Relatively recent inception" was the product of religious readings and had no scientific meaning, and was neither the product of, nor explainable by, natural law; nor is it tentative
The court further noted that no recognized scientific journal had published any article espousing the creation science theory as described in the Arkansas law, and stated that the testimony presented by defense attributing the absence to censorship was not credible.
In its ruling, the court wrote that for any theory to qualify as scientific, the theory must be tentative, and open to revision or abandonment as new facts come to light. It wrote that any methodology which begins with an immutable conclusion that cannot be revised or rejected, regardless of the evidence, is not a scientific theory. The court found that creation science does not culminate in conclusions formed from scientific inquiry, but instead begins with the conclusion, one taken from a literal wording of the Book of Genesis, and seeks only scientific evidence to support it.
The law in Arkansas adopted the same two-model approach as that put forward by the Institute for Creation Research, one allowing only two possible explanations for the origins of life and existence of man, plants and animals: it was either the work of a creator or it was not. Scientific evidence that failed to support the theory of evolution was posed as necessarily scientific evidence in support of creationism, but in its judgment the court ruled this approach to be no more than a "contrived dualism which has not scientific factual basis or legitimate educational purpose."
The judge concluded that "Act 590 is a religious crusade, coupled with a desire to conceal this fact," and that it violated the First Amendment's Establishment Clause. The decision was not appealed to a higher court, but had a powerful influence on subsequent rulings. Louisiana's 1982 Balanced Treatment for Creation-Science and Evolution-Science Act, authored by State Senator Bill P. Keith, judged in the 1987 United States Supreme Court case Edwards v. Aguillard, and was handed a similar ruling. It found the law to require the balanced teaching of creation science with evolution had a particular religious purpose and was therefore unconstitutional.
=== Intelligent design splits off ===
In 1984, The Mystery of Life's Origin was first published. It was co-authored by chemist and creationist Charles B. Thaxton with Walter L. Bradley and Roger L. Olsen, the foreword written by Dean H. Kenyon, and sponsored by the Christian-based Foundation for Thought and Ethics (FTE). The work presented scientific arguments against current theories of abiogenesis and offered a hypothesis of special creation instead. While the focus of creation science had until that time centered primarily on the criticism of the fossil evidence for evolution and validation of the creation myth of the Bible, this new work posed the question whether science reveals that even the simplest living systems were far too complex to have developed by natural, unguided processes.
Kenyon later co-wrote with creationist Percival Davis a book intended as a "scientific brief for creationism" to use as a supplement to public high school biology textbooks. Thaxton was enlisted as the book's editor, and the book received publishing support from the FTE. Prior to its release, the 1987 Supreme Court ruling in Edwards v. Aguillard barred the teaching of creation science and creationism in public school classrooms. The book, originally titled Biology and Creation but renamed Of Pandas and People, was released in 1989 and became the first published work to promote the anti-evolutionist design argument under the name intelligent design. The contents of the book later became a focus of evidence in the federal court case, Kitzmiller v. Dover Area School District, when a group of parents filed suit to halt the teaching of intelligent design in Dover, Pennsylvania, public schools. School board officials there had attempted to include Of Pandas and People in their biology classrooms and testimony given during the trial revealed the book was originally written as a creationist text but following the adverse decision in the Supreme Court it underwent simple cosmetic editing to remove the explicit allusions to "creation" or "creator," and replace them instead with references to "design" or "designer."
By the mid-1990s, intelligent design had become a separate movement. The creation science movement is distinguished from the intelligent design movement, or neo-creationism, because most advocates of creation science accept scripture as a literal and inerrant historical account, and their primary goal is to corroborate the scriptural account through the use of science. In contrast, as a matter of principle, neo-creationism eschews references to scripture altogether in its polemics and stated goals (see Wedge strategy). By so doing, intelligent design proponents have attempted to succeed where creation science has failed in securing a place in public school science curricula. Carefully avoiding any reference to the identity of the intelligent designer as God in their public arguments, intelligent design proponents sought to reintroduce the creationist ideas into science classrooms while sidestepping the First Amendment's prohibition against religious infringement. However, the intelligent design curriculum was struck down as a violation of the Establishment Clause in Kitzmiller v. Dover Area School District, the judge in the case ruled "that ID is nothing less than the progeny of creationism."
Today, creation science as an organized movement is primarily centered within the United States. Creation science organizations are also known in other countries, most notably Creation Ministries International which was founded (under the name Creation Science Foundation) in Australia. Proponents are usually aligned with a Christian denomination, primarily with those characterized as evangelical, conservative, or fundamentalist. While creationist movements also exist in Islam and Judaism, these movements do not use the phrase creation science to describe their beliefs.
== Issues ==
Creation science has its roots in the work of young Earth creationist George McCready Price disputing modern science's account of natural history, focusing particularly on geology and its concept of uniformitarianism, and his efforts instead to furnish an alternative empirical explanation of observable phenomena which was compatible with strict Biblical literalism. Price's work was later discovered by civil engineer Henry M. Morris, who is now considered to be the father of creation science. Morris and later creationists expanded the scope with attacks against the broad spectrum scientific findings that point to the antiquity of the Universe and common ancestry among species, including growing body of evidence from the fossil record, absolute dating techniques, and cosmogony.
The proponents of creation science often say that they are concerned with religious and moral questions as well as natural observations and predictive hypotheses. Many state that their opposition to scientific evolution is primarily based on religion.
The overwhelming majority of scientists are in agreement that the claims of science are necessarily limited to those that develop from natural observations and experiments which can be replicated and substantiated by other scientists, and that claims made by creation science do not meet those criteria. Duane Gish, a prominent creation science proponent, has similarly claimed, "We do not know how the creator created, what processes He used, for He used processes which are not now operating anywhere in the natural universe. This is why we refer to creation as special creation. We cannot discover by scientific investigation anything about the creative processes used by the Creator." But he also makes the same claim against science's evolutionary theory, maintaining that on the subject of origins, scientific evolution is a religious theory which cannot be validated by science.
=== Metaphysical assumptions ===
Creation science makes the a priori metaphysical assumption that there exists a creator of the life whose origin is being examined. Christian creation science holds that the description of creation is given in the Bible, that the Bible is inerrant in this description (and elsewhere), and therefore empirical scientific evidence must correspond with that description. Creationists also view the preclusion of all supernatural explanations within the sciences as a doctrinaire commitment to exclude the supreme being and miracles. They claim this to be the motivating factor in science's acceptance of Darwinism, a term used in creation science to refer to evolutionary biology which is also often used as a disparagement. Critics argue that creation science is religious rather than scientific because it stems from faith in a religious text rather than by the application of the scientific method. The United States National Academy of Sciences (NAS) has stated unequivocally, "Evolution pervades all biological phenomena. To ignore that it occurred or to classify it as a form of dogma is to deprive the student of the most fundamental organizational concept in the biological sciences. No other biological concept has been more extensively tested and more thoroughly corroborated than the evolutionary history of organisms." Anthropologist Eugenie Scott has noted further, "Religious opposition to evolution propels antievolutionism. Although antievolutionists pay lip service to supposed scientific problems with evolution, what motivates them to battle its teaching is apprehension over the implications of evolution for religion."
Creation science advocates argue that scientific theories of the origins of the Universe, Earth, and life are rooted in a priori presumptions of methodological naturalism and uniformitarianism, each of which they reject. In some areas of science such as chemistry, meteorology or medicine, creation science proponents do not necessarily challenge the application of naturalistic or uniformitarian assumptions, but instead single out those scientific theories they judge to be in conflict with their religious beliefs, and it is against those theories that they concentrate their efforts.
=== Religious criticism ===
Many mainstream Christian churches criticize creation science on theological grounds, asserting either that religious faith alone should be a sufficient basis for belief in the truth of creation, or that efforts to prove the Genesis account of creation on scientific grounds are inherently futile because reason is subordinate to faith and cannot thus be used to prove it.
Many Christian theologies, including Liberal Christianity, consider the Genesis creation narrative to be a poetic and allegorical work rather than a literal history, and many Christian churches—including the Eastern Orthodox Church, the Roman Catholic, Anglican and the more liberal denominations of the Lutheran, Methodist, Congregationalist and Presbyterian faiths—have either rejected creation science outright or are ambivalent to it. Belief in non-literal interpretations of Genesis is often cited as going back to Saint Augustine.
Theistic evolution and evolutionary creationism are theologies that reconcile belief in a creator with biological evolution. Each holds the view that there is a creator but that this creator has employed the natural force of evolution to unfold a divine plan. Religious representatives from faiths compatible with theistic evolution and evolutionary creationism have challenged the growing perception that belief in a creator is inconsistent with the acceptance of evolutionary theory. Spokespersons from the Catholic Church have specifically criticized biblical creationism for relying upon literal interpretations of biblical scripture as the basis for determining scientific fact.
=== Scientific criticism ===
The National Academy of Sciences states that "the claims of creation science lack empirical support and cannot be meaningfully tested" and that "creation science is in fact not science and should not be presented as such in science classes." According to Joyce Arthur writing for Skeptic magazine, the "creation 'science' movement gains much of its strength through the use of distortion and scientifically unethical tactics" and "seriously misrepresents the theory of evolution."
Scientists have considered the hypotheses proposed by creation science and have rejected them because of a lack of evidence. Furthermore, the claims of creation science do not refer to natural causes and cannot be subject to meaningful tests, so they do not qualify as scientific hypotheses. In 1987, the United States Supreme Court ruled that creationism is religion, not science, and cannot be advocated in public school classrooms. Most mainline Christian denominations have concluded that the concept of evolution is not at odds with their descriptions of creation and human origins.
A summary of the objections to creation science by scientists follows:
Creation science is not falsifiable: An idea or hypothesis is generally not considered to be in the realm of science unless it can be potentially disproved with certain experiments, this is the concept of falsifiability in science. The act of creation as defined in creation science is not falsifiable because no testable bounds can be imposed on the creator. In creation science, the creator is defined as limitless, with the capacity to create (or not), through fiat alone, infinite universes, not just one, and endow each one with its own unique, unimaginable and incomparable character. It is impossible to disprove a claim when that claim as defined encompasses every conceivable contingency.
Creation science violates the principle of parsimony: Parsimony favours those explanations which rely on the fewest assumptions. Scientists prefer explanations that are consistent with known and supported facts and evidence and require the fewest assumptions to fill the remaining gaps. Many of the alternative claims made in creation science retreat from simpler scientific explanations and introduce more complications and conjecture into the equation.
Creation science is not, and cannot be, empirically or experimentally tested: Creationism posits supernatural causes which lie outside the realm of methodological naturalism and scientific experiment. Science can only test empirical, natural claims.
Creation science is not correctable, dynamic, tentative or progressive: Creation science adheres to a fixed and unchanging premise or "absolute truth," the "word of God," which is not open to change. Any evidence that runs contrary to that truth must be disregarded. In science, all claims are tentative, they are forever open to challenge, and must be discarded or adjusted when the weight of evidence demands it.
By invoking claims of "abrupt appearance" of species as a miraculous act, creation science is unsuited for the tools and methods demanded by science, and it cannot be considered scientific in the way that the term "science" is currently defined. Scientists and science writers commonly characterize creation science as a pseudoscience.
=== Historical, philosophical, and sociological criticism ===
Historically, the debate of whether creationism is compatible with science can be traced back to 1874, the year science historian John William Draper published his History of the Conflict between Religion and Science. In it Draper portrayed the entire history of scientific development as a war against religion. This presentation of history was propagated further by followers such as Andrew Dickson White in his two-volume A History of the Warfare of Science with Theology in Christendom (1896). Their conclusions have been disputed.
In the United States, the principal focus of creation science advocates is on the government-supported public school systems, which are prohibited by the Establishment Clause from promoting specific religions. Historical communities have argued that Biblical translations contain many translation errors and errata, and therefore that the use of biblical literalism in creation science is self-contradictory.
== Kinds of creation science ==
=== Biology ===
Creationist arguments in relation to biology center on an idea derived from Genesis that states that life was created by God, in a finite number of "created kinds," rather than through biological evolution from a common ancestor. Creationists contend that any observable speciation descends from these distinctly created kinds through inbreeding, deleterious mutations and other genetic mechanisms. Whereas evolutionary biologists and creationists share similar views of microevolution, creationists reject the fact that the process of macroevolution can explain common ancestry among organisms far beyond the level of common species. Creationists contend that there is no empirical evidence for new plant or animal species, and deny fossil evidence has ever been found documenting the process.
Popular arguments against evolution have changed since the publishing of Henry M. Morris' first book on the subject, Scientific Creationism (1974), but some consistent themes remain: that missing links or gaps in the fossil record are proof against evolution; that the increased complexity of organisms over time through evolution is not possible due to the law of increasing entropy; that it is impossible that the mechanism of natural selection could account for common ancestry; and that evolutionary theory is untestable. The origin of the human species is particularly hotly contested; the fossil remains of hominid ancestors are not considered by advocates of creation biology to be evidence for a speciation event involving Homo sapiens. Creationists also assert that early hominids, are either apes, or humans.
Richard Dawkins has explained evolution as "a theory of gradual, incremental change over millions of years, which starts with something very simple and works up along slow, gradual gradients to greater complexity," and described the existing fossil record as entirely consistent with that process. Biologists emphasize that transitional gaps between recovered fossils are to be expected, that the existence of any such gaps cannot be invoked to disprove evolution, and that instead the fossil evidence that could be used to disprove the theory would be those fossils which are found and which are entirely inconsistent with what can be predicted or anticipated by the evolutionary model. One example given by Dawkins was, "If there were a single hippo or rabbit in the Precambrian, that would completely blow evolution out of the water. None have ever been found."
=== Geology ===
==== Flood geology ====
Flood geology is a concept based on the belief that most of Earth's geological record was formed by the Great Flood described in the story of Noah's Ark. Fossils and fossil fuels are believed to have formed from animal and plant matter which was buried rapidly during this flood, while submarine canyons are explained as having formed during a rapid runoff from the continents at the end of the flood. Sedimentary strata are also claimed to have been predominantly laid down during or after Noah's flood and orogeny. Flood geology is a variant of catastrophism and is contrasted with geological science in that it rejects standard geological principles such as uniformitarianism and radiometric dating. For example, the Creation Research Society argues that "uniformitarianism is wishful thinking."
Geologists conclude that no evidence for such a flood is observed in the preserved rock layers and moreover that such a flood is physically impossible, given the current layout of land masses. For instance, since Mount Everest currently is approximately 8.8 kilometres in elevation and the Earth's surface area is 510,065,600 km2, the volume of water required to cover Mount Everest to a depth of 15 cubits (6.8 m), as indicated by Genesis 7:20, would be 4.6 billion cubic kilometres. Measurements of the amount of precipitable water vapor in the atmosphere have yielded results indicating that condensing all water vapor in a column of atmosphere would produce liquid water with a depth ranging between zero and approximately 70mm, depending on the date and the location of the column. Nevertheless, there continue to be adherents to the belief in flood geology, and in recent years new creationist models have been introduced such as catastrophic plate tectonics and catastrophic orogeny.
==== Radiometric dating ====
Creationists point to flawed experiments they have performed, which they claim demonstrate that 1.5 billion years of nuclear decay took place over a short period of time, from which they infer that "billion-fold speed-ups of nuclear decay" have occurred, a massive violation of the principle that radioisotope decay rates are constant, a core principle underlying nuclear physics generally, and radiometric dating in particular.
The scientific community points to numerous flaws in the creationists' experiments, to the fact that their results have not been accepted for publication by any peer-reviewed scientific journal, and to the fact that the creationist scientists conducting them were untrained in experimental geochronology. They have also been criticised for widely publicising the results of their research as successful despite their own admission of insurmountable problems with their hypothesis.
The constancy of the decay rates of isotopes is well supported in science. Evidence for this constancy includes the correspondences of date estimates taken from different radioactive isotopes as well as correspondences with non-radiometric dating techniques such as dendrochronology, ice core dating, and historical records. Although scientists have noted slight increases in the decay rate for isotopes subject to extreme pressures, those differences were too small to significantly impact date estimates. The constancy of the decay rates is also governed by first principles in quantum mechanics, wherein any deviation in the rate would require a change in the fundamental constants. According to these principles, a change in the fundamental constants could not influence different elements uniformly, and a comparison between each of the elements' resulting unique chronological timescales would then give inconsistent time estimates.
In refutation of young Earth claims of inconstant decay rates affecting the reliability of radiometric dating, Roger C. Wiens, a physicist specializing in isotope dating states:
There are only three quite technical instances where a half-life changes, and these do not affect the dating methods:
"Only one technical exception occurs under terrestrial conditions, and this is not for an isotope used for dating. ... The artificially-produced isotope, beryllium-7 has been shown to change by up to 1.5%, depending on its chemical environment. ... Heavier atoms are even less subject to these minute changes, so the dates of rocks made by electron-capture decays would only be off by at most a few hundredths of a percent."
"... Another case is material inside of stars, which is in a plasma state where electrons are not bound to atoms. In the extremely hot stellar environment, a completely different kind of decay can occur. 'Bound-state beta decay' occurs when the nucleus emits an electron into a bound electronic state close to the nucleus. ... All normal matter, such as everything on Earth, the Moon, meteorites, etc. has electrons in normal positions, so these instances never apply to rocks, or anything colder than several hundred thousand degrees."
"The last case also involves very fast-moving matter. It has been demonstrated by atomic clocks in very fast spacecraft. These atomic clocks slow down very slightly (only a second or so per year) as predicted by Einstein's theory of relativity. No rocks in our solar system are going fast enough to make a noticeable change in their dates."
==== Radiohaloes ====
In the 1970s, young Earth creationist Robert V. Gentry proposed that radiohaloes in certain granites represented evidence for the Earth being created instantaneously rather than gradually. This idea has been criticized by physicists and geologists on many grounds including that the rocks Gentry studied were not primordial and that the radionuclides in question need not have been in the rocks initially.
Thomas A. Baillieul, a geologist and retired senior environmental scientist with the United States Department of Energy, disputed Gentry's claims in an article entitled, "'Polonium Haloes' Refuted: A Review of 'Radioactive Halos in a Radio-Chronological and Cosmological Perspective' by Robert V. Gentry." Baillieul noted that Gentry was a physicist with no background in geology and given the absence of this background, Gentry had misrepresented the geological context from which the specimens were collected. Additionally, he noted that Gentry relied on research from the beginning of the 20th century, long before radioisotopes were thoroughly understood; that his assumption that a polonium isotope caused the rings was speculative; and that Gentry falsely argued that the half-life of radioactive elements varies with time. Gentry claimed that Baillieul could not publish his criticisms in a reputable scientific journal, although some of Baillieul's criticisms rested on work previously published in reputable scientific journals.
=== Astronomy and cosmology ===
==== Creationist cosmologies ====
Several attempts have been made by creationists to construct a cosmology consistent with a young Universe rather than the standard cosmological age of the universe, based on the belief that Genesis describes the creation of the Universe as well as the Earth. The primary challenge for young-universe cosmologies is that the accepted distances in the Universe require millions or billions of years for light to travel to Earth (the "starlight problem"). An older creationist idea, proposed by creationist astronomer Barry Setterfield, is that the speed of light has decayed in the history of the Universe. More recently, creationist physicist Russell Humphreys has proposed a hypothesis called "white hole cosmology", asserting that the Universe expanded out of a white hole less than 10,000 years ago; claiming that the age of the universe is illusory and results from relativistic effects. Humphreys' cosmology is advocated by creationist organisations such as Answers in Genesis; however because its predictions conflict with current observations, it is not accepted by the scientific community.
==== Planetology ====
Various claims are made by creationists concerning alleged evidence that the age of the Solar System is of the order of thousands of years, in contrast to the scientifically accepted age of 4.6 billion years. It is commonly argued that the number of comets in the Solar System is much higher than would be expected given its supposed age. Young Earth Creationists reject the existence of the Kuiper belt and Oort cloud. They also argue that the recession of the Moon from the Earth is incompatible with either the Moon or the Earth being billions of years old. These claims have been refuted by planetologists.
In response to increasing evidence suggesting that Mars once possessed a wetter climate, some creationists have proposed that the global flood affected not only the Earth but also Mars and other planets. People who support this claim include creationist astronomer Wayne Spencer and Russell Humphreys.
An ongoing problem for creationists is the presence of impact craters on nearly all Solar System objects, which is consistent with scientific explanations of solar system origins but creates insuperable problems for young Earth claims. Creationists Harold Slusher and Richard Mandock, along with Glenn Morton (who later repudiated this claim) asserted that impact craters on the Moon are subject to rock flow, and so cannot be more than a few thousand years old. While some creationist astronomers assert that different phases of meteoritic bombardment of the Solar System occurred during "creation week" and during the subsequent Great Flood, others regard this as unsupported by the evidence and call for further research.
== Groups ==
=== Proponents ===
Answers in Genesis
Creation Ministries International
Creation Research Society
Geoscience Research Institute
Institute for Creation Research
=== Critics ===
American Museum of Natural History
National Science Teachers Association
National Center for Science Education
No Answers in Genesis
National Academy of Sciences
Scientific American
The BioLogos Foundation
The Skeptic's Dictionary
Talk.reason
TalkOrigins Archive
== See also ==
Conflict thesis
Denialism
Ken Ham
Kent Hovind
International Conference on Creationism
Natural theology
Omphalos hypothesis
Adnan Oktar
Jonathan Sarfati
Scientific skepticism
== References ==
== Bibliography ==
== Further reading ==
=== Proponents ===
== External links ==
Notable creationist museums in the United States:
Creation Evidence Museum, located in Glen Rose, Texas
Creation Museum, located in Petersburg, Kentucky
Human Timeline (Interactive) – Smithsonian, National Museum of Natural History (August 2016). | Wikipedia/Creation_science |
The deductive-nomological model (DN model) of scientific explanation, also known as Hempel's model, the Hempel–Oppenheim model, the Popper–Hempel model, or the covering law model, is a formal view of scientifically answering questions asking, "Why...?". The DN model poses scientific explanation as a deductive structure, one where truth of its premises entails truth of its conclusion, hinged on accurate prediction or postdiction of the phenomenon to be explained.
Because of problems concerning humans' ability to define, discover, and know causality, this was omitted in initial formulations of the DN model. Causality was thought to be incidentally approximated by realistic selection of premises that derive the phenomenon of interest from observed starting conditions plus general laws. Still, the DN model formally permitted causally irrelevant factors. Also, derivability from observations and laws sometimes yielded absurd answers.
When logical empiricism fell out of favor in the 1960s, the DN model was widely seen as a flawed or greatly incomplete model of scientific explanation. Nonetheless, it remained an idealized version of scientific explanation, and one that was rather accurate when applied to modern physics. In the early 1980s, a revision to the DN model emphasized maximal specificity for relevance of the conditions and axioms stated. Together with Hempel's inductive-statistical model, the DN model forms scientific explanation's covering law model, which is also termed, from critical angle, subsumption theory.
== Form ==
The term deductive distinguishes the DN model's intended determinism from the probabilism of inductive inferences. The term nomological is derived from the Greek word νόμος or nomos, meaning "law". The DN model holds to a view of scientific explanation whose conditions of adequacy (CA)—semiformal but stated classically—are derivability (CA1), lawlikeness (CA2), empirical content (CA3), and truth (CA4).
In the DN model, a law axiomatizes an unrestricted generalization from antecedent A to consequent B by conditional proposition—If A, then B—and has empirical content testable. A law differs from mere true regularity—for instance, George always carries only $1 bills in his wallet—by supporting counterfactual claims and thus suggesting what must be true, while following from a scientific theory's axiomatic structure.
The phenomenon to be explained is the explanandum—an event, law, or theory—whereas the premises to explain it are explanans, true or highly confirmed, containing at least one universal law, and entailing the explanandum. Thus, given the explanans as initial, specific conditions C1, C2, ... Cn plus general laws L1, L2, ... Ln, the phenomenon E as explanandum is a deductive consequence, thereby scientifically explained.
== Roots ==
Aristotle's scientific explanation in Physics resembles the DN model, an idealized form of scientific explanation. The framework of Aristotelian physics—Aristotelian metaphysics—reflected the perspective of this principally biologist, who, amid living entities' undeniable purposiveness, formalized vitalism and teleology, an intrinsic morality in nature. With emergence of Copernicanism, however, Descartes introduced mechanical philosophy, then Newton rigorously posed lawlike explanation, both Descartes and especially Newton shunning teleology within natural philosophy. At 1740, David Hume staked Hume's fork, highlighted the problem of induction, and found humans ignorant of either necessary or sufficient causality. Hume also highlighted the fact/value gap, as what is does not itself reveal what ought.
Near 1780, countering Hume's ostensibly radical empiricism, Immanuel Kant highlighted extreme rationalism—as by Descartes or Spinoza—and sought middle ground. Inferring the mind to arrange experience of the world into substance, space, and time, Kant placed the mind as part of the causal constellation of experience and thereby found Newton's theory of motion universally true, yet knowledge of things in themselves impossible. Safeguarding science, then, Kant paradoxically stripped it of scientific realism. Aborting Francis Bacon's inductivist mission to dissolve the veil of appearance to uncover the noumena—metaphysical view of nature's ultimate truths—Kant's transcendental idealism tasked science with simply modeling patterns of phenomena. Safeguarding metaphysics, too, it found the mind's constants holding also universal moral truths, and launched German idealism.
Auguste Comte found the problem of induction rather irrelevant since enumerative induction is grounded on the empiricism available, while science's point is not metaphysical truth. Comte found human knowledge had evolved from theological to metaphysical to scientific—the ultimate stage—rejecting both theology and metaphysics as asking questions unanswerable and posing answers unverifiable. Comte in the 1830s expounded positivism—the first modern philosophy of science and simultaneously a political philosophy—rejecting conjectures about unobservables, thus rejecting search for causes. Positivism predicts observations, confirms the predictions, and states a law, thereupon applied to benefit human society. From late 19th century into the early 20th century, the influence of positivism spanned the globe. Meanwhile, evolutionary theory's natural selection brought the Copernican Revolution into biology and eventuated in the first conceptual alternative to vitalism and teleology.
== Growth ==
Whereas Comtean positivism posed science as description, logical positivism emerged in the late 1920s and posed science as explanation, perhaps to better unify empirical sciences by covering not only fundamental science—that is, fundamental physics—but special sciences, too, such as biology, psychology, economics, and anthropology. After defeat of National Socialism with World War II's close in 1945, logical positivism shifted to a milder variant, logical empiricism. All variants of the movement, which lasted until 1965, are neopositivism, sharing the quest of verificationism.
Neopositivists led emergence of the philosophy subdiscipline philosophy of science, researching such questions and aspects of scientific theory and knowledge. Scientific realism takes scientific theory's statements at face value, thus accorded either falsity or truth—probable or approximate or actual. Neopositivists held scientific antirealism as instrumentalism, holding scientific theory as simply a device to predict observations and their course, while statements on nature's unobservable aspects are elliptical at or metaphorical of its observable aspects, rather.
DN model received its most detailed, influential statement by Carl G Hempel, first in his 1942 article "The function of general laws in history", and more explicitly with Paul Oppenheim in their 1948 article "Studies in the logic of explanation". Leading logical empiricist, Hempel embraced the Humean empiricist view that humans observe sequence of sensory events, not cause and effect, as causal relations and casual mechanisms are unobservables. DN model bypasses causality beyond mere constant conjunction: first an event like A, then always an event like B.
Hempel held natural laws—empirically confirmed regularities—as satisfactory, and if included realistically to approximate causality. In later articles, Hempel defended DN model and proposed probabilistic explanation by inductive-statistical model (IS model). DN model and IS model—whereby the probability must be high, such as at least 50%—together form covering law model, as named by a critic, William Dray. Derivation of statistical laws from other statistical laws goes to the deductive-statistical model (DS model). Georg Henrik von Wright, another critic, named the totality subsumption theory.
== Decline ==
Amid failure of neopositivism's fundamental tenets, Hempel in 1965 abandoned verificationism, signaling neopositivism's demise. From 1930 onward, Karl Popper attacked positivism, although, paradoxically, Popper was commonly mistaken for a positivist. Even Popper's 1934 book embraces DN model, widely accepted as the model of scientific explanation for as long as physics remained the model of science examined by philosophers of science.
In the 1940s, filling the vast observational gap between cytology and biochemistry, cell biology arose and established existence of cell organelles besides the nucleus. Launched in the late 1930s, the molecular biology research program cracked a genetic code in the early 1960s and then converged with cell biology as cell and molecular biology, its breakthroughs and discoveries defying DN model by arriving in quest not of lawlike explanation but of causal mechanisms. Biology became a new model of science, while special sciences were no longer thought defective by lacking universal laws, as borne by physics.
In 1948, when explicating DN model and stating scientific explanation's semiformal conditions of adequacy, Hempel and Oppenheim acknowledged redundancy of the third, empirical content, implied by the other three—derivability, lawlikeness, and truth. In the early 1980s, upon widespread view that causality ensures the explanans' relevance, Wesley Salmon called for returning cause to because, and along with James Fetzer helped replace CA3 empirical content with CA3' strict maximal specificity.
Salmon introduced causal mechanical explanation, never clarifying how it proceeds, yet reviving philosophers' interest in such. Via shortcomings of Hempel's inductive-statistical model (IS model), Salmon introduced statistical-relevance model (SR model). Although DN model remained an idealized form of scientific explanation, especially in applied sciences, most philosophers of science consider DN model flawed by excluding many types of explanations generally accepted as scientific.
== Strengths ==
As theory of knowledge, epistemology differs from ontology, which is a subbranch of metaphysics, theory of reality. Ontology proposes categories of being—what sorts of things exist—and so, although a scientific theory's ontological commitment can be modified in light of experience, an ontological commitment inevitably precedes empirical inquiry.
Natural laws, so called, are statements of humans' observations, thus are epistemological—concerning human knowledge—the epistemic. Causal mechanisms and structures existing putatively independently of minds exist, or would exist, in the natural world's structure itself, and thus are ontological, the ontic. Blurring epistemic with ontic—as by incautiously presuming a natural law to refer to a causal mechanism, or to trace structures realistically during unobserved transitions, or to be true regularities always unvarying—tends to generate a category mistake.
Discarding ontic commitments, including causality per se, DN model permits a theory's laws to be reduced to—that is, subsumed by—a more fundamental theory's laws. The higher theory's laws are explained in DN model by the lower theory's laws. Thus, the epistemic success of Newtonian theory's law of universal gravitation is reduced to—thus explained by—Albert Einstein's general theory of relativity, although Einstein's discards Newton's ontic claim that universal gravitation's epistemic success predicting Kepler's laws of planetary motion is through a causal mechanism of a straightly attractive force instantly traversing absolute space despite absolute time.
Covering law model reflects neopositivism's vision of empirical science, a vision interpreting or presuming unity of science, whereby all empirical sciences are either fundamental science—that is, fundamental physics—or are special sciences, whether astrophysics, chemistry, biology, geology, psychology, economics, and so on. All special sciences would network via covering law model. And by stating boundary conditions while supplying bridge laws, any special law would reduce to a lower special law, ultimately reducing—theoretically although generally not practically—to fundamental science. (Boundary conditions are specified conditions whereby the phenomena of interest occur. Bridge laws translate terms in one science to terms in another science.)
== Weaknesses ==
By DN model, if one asks, "Why is that shadow 20 feet long?", another can answer, "Because that flagpole is 15 feet tall, the Sun is at x angle, and laws of electromagnetism". Yet by problem of symmetry, if one instead asked, "Why is that flagpole 15 feet tall?", another could answer, "Because that shadow is 20 feet long, the Sun is at x angle, and laws of electromagnetism", likewise a deduction from observed conditions and scientific laws, but an answer clearly incorrect. By the problem of irrelevance, if one asks, "Why did that man not get pregnant?", one could in part answer, among the explanans, "Because he took birth control pills"—if he factually took them, and the law of their preventing pregnancy—as covering law model poses no restriction to bar that observation from the explanans.
Many philosophers have concluded that causality is integral to scientific explanation. DN model offers a necessary condition of a causal explanation—successful prediction—but not sufficient conditions of causal explanation, as a universal regularity can include spurious relations or simple correlations, for instance Z always following Y, but not Z because of Y, instead Y and then Z as an effect of X. By relating temperature, pressure, and volume of gas within a container, Boyle's law permits prediction of an unknown variable—volume, pressure, or temperature—but does not explain why to expect that unless one adds, perhaps, the kinetic theory of gases.
Scientific explanations increasingly pose not determinism's universal laws, but probabilism's chance, ceteris paribus laws. Smoking's contribution to lung cancer fails even the inductive-statistical model (IS model), requiring probability over 0.5 (50%). (Probability standardly ranges from 0 (0%) to 1 (100%).) Epidemiology, an applied science that uses statistics in search of associations between events, cannot show causality, but consistently found higher incidence of lung cancer in smokers versus otherwise similar nonsmokers, although the proportion of smokers who develop lung cancer is modest. Versus nonsmokers, however, smokers as a group showed over 20 times the risk of lung cancer, and in conjunction with basic research, consensus followed that smoking had been scientifically explained as a cause of lung cancer, responsible for some cases that without smoking would not have occurred, a probabilistic counterfactual causality.
== Covering action ==
Through lawlike explanation, fundamental physics—often perceived as fundamental science—has proceeded through intertheory relation and theory reduction, thereby resolving experimental paradoxes to great historical success, resembling covering law model. In early 20th century, Ernst Mach as well as Wilhelm Ostwald had resisted Ludwig Boltzmann's reduction of thermodynamics—and thereby Boyle's law—to statistical mechanics partly because it rested on kinetic theory of gas, hinging on atomic/molecular theory of matter. Mach as well as Ostwald viewed matter as a variant of energy, and molecules as mathematical illusions, as even Boltzmann thought possible.
In 1905, via statistical mechanics, Albert Einstein predicted the phenomenon Brownian motion—unexplained since reported in 1827 by botanist Robert Brown. Soon, most physicists accepted that atoms and molecules were unobservable yet real. Also in 1905, Einstein explained the electromagnetic field's energy as distributed in particles, doubted until this helped resolve atomic theory in the 1910s and 1920s. Meanwhile, all known physical phenomena were gravitational or electromagnetic, whose two theories misaligned. Yet belief in aether as the source of all physical phenomena was virtually unanimous. At experimental paradoxes, physicists modified the aether's hypothetical properties.
Finding the luminiferous aether a useless hypothesis, Einstein in 1905 a priori unified all inertial reference frames to state special principle of relativity, which, by omitting aether, converted space and time into relative phenomena whose relativity aligned electrodynamics with the Newtonian principle Galilean relativity or invariance. Originally epistemic or instrumental, this was interpreted as ontic or realist—that is, a causal mechanical explanation—and the principle became a theory, refuting Newtonian gravitation. By predictive success in 1919, general relativity apparently overthrew Newton's theory, a revolution in science resisted by many yet fulfilled around 1930.
In 1925, Werner Heisenberg as well as Erwin Schrödinger independently formalized quantum mechanics (QM). Despite clashing explanations, the two theories made identical predictions. Paul Dirac's 1928 model of the electron was set to special relativity, launching QM into the first quantum field theory (QFT), quantum electrodynamics (QED). From it, Dirac interpreted and predicted the electron's antiparticle, soon discovered and termed positron, but the QED failed electrodynamics at high energies. Elsewhere and otherwise, strong nuclear force and weak nuclear force were discovered.
In 1941, Richard Feynman introduced QM's path integral formalism, which if taken toward interpretation as a causal mechanical model clashes with Heisenberg's matrix formalism and with Schrödinger's wave formalism, although all three are empirically identical, sharing predictions. Next, working on QED, Feynman sought to model particles without fields and find the vacuum truly empty. As each known fundamental force is apparently an effect of a field, Feynman failed. Louis de Broglie's waveparticle duality had rendered atomism—indivisible particles in a void—untenable, and highlighted the very notion of discontinuous particles as self-contradictory.
Meeting in 1947, Freeman Dyson, Richard Feynman, Julian Schwinger, and Sin-Itiro Tomonaga soon introduced renormalization, a procedure converting QED to physics' most predictively precise theory, subsuming chemistry, optics, and statistical mechanics. QED thus won physicists' general acceptance. Paul Dirac criticized its need for renormalization as showing its unnaturalness, and called for an aether. In 1947, Willis Lamb had found unexpected motion of electron orbitals, shifted since the vacuum is not truly empty. Yet emptiness was catchy, abolishing aether conceptually, and physics proceeded ostensibly without it, even suppressing it. Meanwhile, "sickened by untidy math, most philosophers of physics tend to neglect QED".
Physicists have feared even mentioning aether, renamed vacuum, which—as such—is nonexistent. General philosophers of science commonly believe that aether, rather, is fictitious, "relegated to the dustbin of scientific history ever since" 1905 brought special relativity. Einstein was noncommittal to aether's nonexistence, simply said it superfluous. Abolishing Newtonian motion for electrodynamic primacy, however, Einstein inadvertently reinforced aether, and to explain motion was led back to aether in general relativity. Yet resistance to relativity theory became associated with earlier theories of aether, whose word and concept became taboo. Einstein explained special relativity's compatibility with an aether, but Einstein aether, too, was opposed. Objects became conceived as pinned directly on space and time by abstract geometric relations lacking ghostly or fluid medium.
By 1970, QED along with weak nuclear field was reduced to electroweak theory (EWT), and the strong nuclear field was modeled as quantum chromodynamics (QCD). Comprised by EWT, QCD, and Higgs field, this Standard Model of particle physics is an "effective theory", not truly fundamental. As QCD's particles are considered nonexistent in the everyday world, QCD especially suggests an aether, routinely found by physics experiments to exist and to exhibit relativistic symmetry. Confirmation of the Higgs particle, modeled as a condensation within the Higgs field, corroborates aether, although physics need not state or even include aether. Organizing regularities of observations—as in the covering law model—physicists find superfluous the quest to discover aether.
In 1905, from special relativity, Einstein deduced mass–energy equivalence, particles being variant forms of distributed energy, how particles colliding at vast speed experience that energy's transformation into mass, producing heavier particles, although physicists' talk promotes confusion. As "the contemporary locus of metaphysical research", QFTs pose particles not as existing individually, yet as excitation modes of fields, the particles and their masses being states of aether, apparently unifying all physical phenomena as the more fundamental causal reality, as long ago foreseen. Yet a quantum field is an intricate abstraction—a mathematical field—virtually inconceivable as a classical field's physical properties. Nature's deeper aspects, still unknown, might elude any possible field theory.
Though discovery of causality is popularly thought science's aim, search for it was shunned by the Newtonian research program, even more Newtonian than was Isaac Newton. By now, most theoretical physicists infer that the four, known fundamental interactions would reduce to superstring theory, whereby atoms and molecules, after all, are energy vibrations holding mathematical, geometric forms. Given uncertainties of scientific realism, some conclude that the concept causality raises comprehensibility of scientific explanation and thus is key folk science, but compromises precision of scientific explanation and is dropped as a science matures. Even epidemiology is maturing to heed the severe difficulties with presumptions about causality. Covering law model is among Carl G Hempel's admired contributions to philosophy of science.
== See also ==
Types of inference
Deductive reasoning
Inductive reasoning
Abductive reasoning
Related subjects
Explanandum and explanans
Hypothetico-deductive model
Models of scientific inquiry
Philosophy of science
Scientific method
== Notes ==
== Sources ==
Avent, Ryan, "The Q&A: Brian Greene—life after the Higgs", The Economist blog: Babbage, 19 Jul 2012.
Ayala, Francisco J & Theodosius G Dobzhansky, eds, Studies in the Philosophy of Biology: Reduction and Related Problems (Berkeley & Los Angeles: University of California Press, 1974).
Bechtel, William, Discovering Cell Mechanisms: The Creation of Modern Cell Biology (New York: Cambridge University Press, 2006).
Bechtel, William, Philosophy of Science: An Overview for Cognitive Science (Hillsdale, NJ: Lawrence Erlbaum Associates, 1988).
Bem, Sacha & Huib L de Jong, Theoretical Issues in Psychology: An Introduction, 2nd edn (London: Sage Publications, 2006).
Ben-Menahem, Yemima, Conventionalism: From Poincaré to Quine (Cambridge: Cambridge University Press, 2006).
Blackmore, J T & R Itagaki, S Tanaka, eds, Ernst Mach's Vienna 1895–1930: Or Phenomenalism as Philosophy of Science (Dordrecht: Kluwer Academic Publishers, 2001).
Boffetta, Paolo, "Causation in the presence of weak associations", Critical Reviews in Food Science and Nutrition, 2010 Dec; 50(s1):13–16.
Bolotin, David, An Approach to Aristotle's Physics: With Particular Attention to the Role of His Manner of Writing (Albany: State University of New York Press, 1998).
Bourdeau, Michel, "Auguste Comte", in Edward N Zalta, ed, The Stanford Encyclopedia of Philosophy, Winter 2013 edn.
Braibant, Sylvie & Giorgio Giacomelli, Maurizio Spurio, Particles and Fundamental Interactions: An Introduction to Particle Physics (Dordrecht, Heidelberg, London, New York: Springer, 2012).
Buchen, Lizzie, "May 29, 1919: A major eclipse, relatively speaking", Wired, 29 May 2009.
Buckle, Stephen, Hume's Enlightenment Tract: The Unity and Purpose of An Enquiry Concerning Human Understanding (New York: Oxford University Press, 2001).
Burgess, Cliff & Guy Moore, The Standard Model: A Primer (New York: Cambridge University Press, 2007).
Chakraborti, Chhanda, Logic: Informal, Symbolic and Inductive (New Delhi: Prentice-Hall of India, 2007).
Chakravartty, Anjan, "Scientific realism", in Edward N Zalta, ed, The Stanford Encyclopedia of Philosophy, Summer 2013 edn.
Close, Frank, "Much ado about nothing", Nova: The Nature of Reality, PBS Online / WGBH Educational Foundation, 13 Jan 2012.
Comte, Auguste, auth, J. H. Bridges, trans, A General View of Positivism (London: Trübner and Co, 1865) [English translation from French as Comte's 2nd edn in 1851, after the 1st edn in 1848].
Cordero, Alberto, ch 3 "Rejected posits, realism, and the history of science", pp. 23–32, in Henk W de Regt, Stephan Hartmann & Samir Okasha, eds, EPSA Philosophy of Science: Amsterdam 2009 (New York: Springer, 2012).
Crelinsten, Jeffrey, Einstein's Jury: The Race to Test Relativity (Princeton: Princeton University Press, 2006).
Cushing, James T, Quantum Mechanics: Historical Contingency and the Copenhagen Hegemony (Chicago: University of Chicago Press, 1994).
Einstein, Albert, "Ether and the theory of relativity", pp. 3–24, Sidelights on Relativity (London: Methuen, 1922), the English trans of Einstein, "Äther und Relativitätstheorie" (Berlin: Verlag Julius, 1920), based on Einstein's 5 May 1920 address at University of Leyden, and collected in Jürgen Renn, ed, The Genesis of General Relativity, Volume 3 (Dordrecht: Springer, 2007).
Fetzer, James H, "Carl Hempel", in Edward N Zalta, ed, The Stanford Encyclopedia of Philosophy, Spring 2013 edn.
Fetzer, James H., ed, Science, Explanation, and Rationality: Aspects of the Philosophy of Carl G Hempel (New York: Oxford University Press, 2000).
Feynman, Richard P., QED: The Strange Theory of Light and Matter, w/new intro by A Zee (Princeton: Princeton University Press, 2006).
Flew, Antony G, A Dictionary of Philosophy, 2nd edn (New York: St Martin's Press, 1984), "Positivism", p. 283.
Friedman, Michael, Reconsidering Logical Positivism (New York: Cambridge University Press, 1999).
Gattei, Stefano, Karl Popper's Philosophy of Science: Rationality without Foundations (New York: Routledge, 2009), ch 2 "Science and philosophy".
Grandy, David A., Everyday Quantum Reality (Bloomington, Indiana : Indiana University Press, 2010).
Hacohen, Malachi H, Karl Popper—the Formative Years, 1902–1945: Politics and Philosophy in Interwar Vienna (Cambridge: Cambridge University Press, 2000).
Jegerlehner, Fred, "The Standard Model as a low-energy effective theory: What is triggering the Higgs mechanism?", arXiv (High Energy Physics—Phenomenology):1304.7813, 11 May 2013 (last revised).
Karhausen, Lucien R (2000). "Causation: The elusive grail of epidemiology". Medicine, Health Care and Philosophy. 3 (1): 59–67. doi:10.1023/A:1009970730507. PMID 11080970. S2CID 24260908.
Kay, Lily E, Molecular Vision of Life: Caltech, the Rockefeller Foundation, and the Rise of the New Biology (New York: Oxford University Press, 1993).
Khrennikov, K, ed, Proceedings of the Conference: Foundations of Probability and Physics (Singapore: World Scientific Publishing, 2001).
Kuhlmann, Meinard, "Physicists debate whether the world is made of particles or fields—or something else entirely", Scientific American, 24 July 2013.
Kundi, Michael (Jul 2006). "Causality and the interpretation of epidemiologic evidence". Environmental Health Perspectives. 114 (7): 969–74. doi:10.1289/ehp.8297. PMC 1513293. PMID 16835045.
Laudan, Larry, ed, Mind and Medicine: Problems of Explanation and Evaluation in Psychiatry and the Biomedical Sciences (Berkeley, Los Angeles, London: University of California Press, 1983).
Laughlin, Robert B, A Different Universe: Reinventing Physics from the Bottom Down (New York: Basic Books, 2005).
Lodge, Oliver, "The ether of space: A physical conception", Scientific American Supplement, 1909 Mar 27; 67(1734):202–03.
Manninen, Juha & Raimo Tuomela, eds, Essays on Explanation and Understanding: Studies in the Foundation of Humanities and Social Sciences (Dordrecht: D. Reidel, 1976).
Melia, Fulvio, The Black Hole at the Center of Our Galaxy (Princeton: Princeton University Press, 2003).
Montuschi, Eleonora, Objects in Social Science (London & New York: Continuum Books, 2003).
Morange, Michel, trans by Michael Cobb, A History of Molecular Biology (Cambridge MA: Harvard University Press, 2000).
Moyer, Donald F, "Revolution in science: The 1919 eclipse test of general relativity", in Arnold Perlmutter & Linda F Scott, eds, Studies in the Natural Sciences: On the Path of Einstein (New York: Springer, 1979).
Newburgh, Ronald & Joseph Peidle, Wolfgang Rueckner, "Einstein, Perrin, and the reality of atoms: 1905 revisited", American Journal of Physics, 2006 June; 74(6):478−481.
Norton, John D, "Causation as folk science", Philosopher's Imprint, 2003; 3(4), collected as ch 2 in Price & Corry, eds, Causation, Physics, and the Constitution of Reality (Oxford U P, 2007).
Ohanian, Hans C, Einstein's Mistakes: The Human Failings of Genius (New York: W W Norton & Company, 2008).
Okasha, Samir, Philosophy of Science: A Very Short Introduction (New York: Oxford University Press, 2002).
O'Shaughnessy, John, Explaining Buyer Behavior: Central Concepts and Philosophy of Science Issues (New York: Oxford University Press, 1992).
Parascandola, M; Weed, D L (Dec 2001). "Causation in epidemiology". Journal of Epidemiology and Community Health. 55 (12): 905–12. doi:10.1136/jech.55.12.905. PMC 1731812. PMID 11707485.
Pigliucci, Massimo, Answers for Aristotle: How Science and Philosophy Can Lead Us to a More Meaningful Life (New York: Basic Books, 2012).
Popper, Karl, "Against big words", In Search of a Better World: Lectures and Essays from Thirty Years (New York: Routledge, 1996).
Price, Huw & Richard Corry, eds, Causation, Physics, and the Constitution of Reality: Russell's Republic Revisited (New York: Oxford University Press, 2007).
Redman, Deborah A, The Rise of Political Economy as a Science: Methodology and the Classical Economists (Cambridge MA: MIT Press, 1997).
Reutlinger, Alexander & Gerhard Schurz, Andreas Hüttemann, "Ceteris paribus laws", in Edward N Zalta, ed, The Stanford Encyclopedia of Philosophy, Spring 2011 edn.
Riesselmann, Kurt, "Concept of ether in explaining forces", Inquiring Minds: Questions About Physics, US Department of Energy: Fermilab, 28 Nov 2008.
Rothman, Kenneth J; Greenland, Sander (2005). "Causation and causal inference in epidemiology". American Journal of Public Health. 95 (Suppl 1): S144–50. doi:10.2105/AJPH.2004.059204. hdl:10.2105/AJPH.2004.059204. PMID 16030331.
Rowlands, Peter, Oliver Lodge and the Liverpool Physical Society (Liverpool: Liverpool University Press, 1990).
Sarkar, Sahotra & Jessica Pfeifer, eds, The Philosophy of Science: An Encyclopedia, Volume 1: A–M (New York: Routledge, 2006).
Schwarz, John H (1998). "Recent developments in superstring theory". Proceedings of the National Academy of Sciences of the United States of America. 95 (6): 2750–7. Bibcode:1998PNAS...95.2750S. doi:10.1073/pnas.95.6.2750. PMC 19640. PMID 9501161.
Schweber, Silvan S, QED and the Men who Made it: Dyson, Feynman, Schwinger, and Tomonaga (Princeton: Princeton University Press, 1994).
Schliesser, Eric, "Hume's Newtonianism and anti-Newtonianism", in Edward N Zalta, ed, The Stanford Encyclopedia of Philosophy, Winter 2008 edn.
Spohn, Wolfgang, The Laws of Belief: Ranking Theory and Its Philosophical Applications (Oxford: Oxford University Press, 2012).
Suppe, Frederick, ed, The Structure of Scientific Theories, 2nd edn (Urbana, Illinois: University of Illinois Press, 1977).
Tavel, Morton, Contemporary Physics and the Limits of Knowledge (Piscataway, NJ: Rutgers University Press, 2002).
Torretti, Roberto, The Philosophy of Physics (New York: Cambridge University Press, 1999).
Vongehr, Sascha, "Higgs discovery rehabilitating despised Einstein Ether", Science 2.0: Alpha Meme website, 13 Dec 2011.
Vongehr, Sascha, "Supporting abstract relational space-time as fundamental without doctrinism against emergence, arXiv (History and Philosophy of Physics):0912.3069, 2 Oct 2011 (last revised).
von Wright, Georg Henrik, Explanation and Understanding (Ithaca, NY: Cornell University Press, 1971–2004).
Wells, James D, Effective Theories in Physics: From Planetary Orbits to Elementary Particle Masses (Heidelberg, New York, Dordrecht, London: Springer, 2012).
Wilczek, Frank, The Lightness of Being: Mass, Ether, and the Unification of Forces (New York: Basic Books, 2008).
Whittaker, Edmund T, A History of the Theories of Aether and Electricity: From the Age of Descartes to the Close of the Nineteenth Century (London, New York, Bombay, Calcutta: Longmans, Green, and Co, 1910 / Dublin: Hodges, Figgis, & Co, 1910).
Wilczek, Frank (Jan 1999). "The persistence of ether" (PDF). Physics Today. 52 (1): 11–13. Bibcode:1999PhT....52a..11W. doi:10.1063/1.882562.
Wolfson, Richard, Simply Einstein: Relativity Demystified (New York: W W Norton & Co, 2003).
Woodward, James, "Scientific explanation", in Edward N Zalta, ed, The Stanford Encyclopedia of Philosophy, Winter 2011 edn.
Wootton, David, ed, Modern Political Thought: Readings from Machiavelli to Nietzsche (Indianapolis: Hackett Publishing, 1996).
== Further reading ==
Carl G. Hempel, Aspects of Scientific Explanation and other Essays in the Philosophy of Science (New York: Free Press, 1965).
Randolph G. Mayes, "Theories of explanation", in Fieser Dowden, ed, Internet Encyclopedia of Philosophy, 2006.
Ilkka Niiniluoto, "Covering law model", in Robert Audi, ed., The Cambridge Dictionary of Philosophy, 2nd edn (New York: Cambridge University Press, 1996).
Wesley C. Salmon, Four Decades of Scientific Explanation (Minneapolis: University of Minnesota Press, 1990 / Pittsburgh: University of Pittsburgh Press, 2006). | Wikipedia/Deductive-nomological_model |
The branches of science, also referred to as sciences, scientific fields or scientific disciplines, are commonly divided into three major groups:
Formal sciences: the study of formal systems, such as those under the branches of logic and mathematics, which use an a priori, as opposed to empirical, methodology. They study abstract structures described by formal systems.
Natural sciences: the study of natural phenomena (including cosmological, geological, physical, chemical, and biological factors of the universe). Natural science can be divided into two main branches: physical science and life science (or biology).
Social sciences: the study of human behavior in its social and cultural aspects.
Scientific knowledge must be grounded in observable phenomena and must be capable of being verified by other researchers working under the same conditions.
Natural, social, and formal science make up the fundamental sciences, which form the basis of interdisciplinarity - and applied sciences such as engineering and medicine. Specialized scientific disciplines that exist in multiple categories may include parts of other scientific disciplines but often possess their own terminologies and expertises.
== Formal sciences ==
The formal sciences are the branches of science that are concerned with formal systems, such as logic, mathematics, theoretical computer science, information theory, systems theory, decision theory, statistics.
Unlike other branches, the formal sciences are not concerned with the validity of theories based on observations in the real world (empirical knowledge), but rather with the properties of formal systems based on definitions and rules. Hence there is disagreement on whether the formal sciences actually constitute as a science. Methods of the formal sciences are, however, essential to the construction and testing of scientific models dealing with observable reality, and major advances in formal sciences have often enabled major advances in the empirical sciences.
=== Logic ===
Logic (from Greek: λογική, logikḗ, 'possessed of reason, intellectual, dialectical, argumentative') is the systematic study of valid rules of inference, i.e. the relations that lead to the acceptance of one proposition (the conclusion) on the basis of a set of other propositions (premises). More broadly, logic is the analysis and appraisal of arguments.
It has traditionally included the classification of arguments; the systematic exposition of the logical forms; the validity and soundness of deductive reasoning; the strength of inductive reasoning; the study of formal proofs and inference (including paradoxes and fallacies); and the study of syntax and semantics.
Historically, logic has been studied in philosophy (since ancient times) and mathematics (since the mid-19th century). More recently, logic has been studied in cognitive science, which draws on computer science, linguistics, philosophy and psychology, among other disciplines.
=== Data science ===
=== Information science ===
Information science is an academic field which is primarily concerned with analysis, collection, classification, manipulation, storage, retrieval, movement, dissemination, and protection of information. Practitioners within and outside the field study the application and the usage of knowledge in organizations in addition to the interaction between people, organizations, and any existing information systems with the aim of creating, replacing, improving, or understanding the information systems.
=== Mathematics ===
Mathematics, in the broadest sense, is just a synonym of formal science; but traditionally mathematics means more specifically the coalition of four areas: arithmetic, algebra, geometry, and analysis, which are, to some degree, the study of quantity, structure, space, and change respectively.
=== Statistics ===
Statistics is the study of the collection, organization, and interpretation of data. It deals with all aspects of this, including the planning of data collection in terms of the design of surveys and experiments.
A statistician is someone who is particularly well versed in the ways of thinking necessary for the successful application of statistical analysis. Such people have often gained this experience through working in any of a wide number of fields. There is also a discipline called mathematical statistics, which is concerned with the theoretical basis of the subject.
The word statistics, when referring to the scientific discipline, is singular, as in "Statistics is an art." This should not be confused with the word statistic, referring to a quantity (such as mean or median) calculated from a set of data, whose plural is statistics ("this statistic seems wrong" or "these statistics are misleading").
=== Systems theory ===
Systems theory is the transdisciplinary study of systems in general, to elucidate principles that can be applied to all types of systems in all fields of research. The term does not yet have a well-established, precise meaning, but systems theory can reasonably be considered a specialization of systems thinking and a generalization of systems science. The term originates from Bertalanffy's General System Theory (GST) and is used in later efforts in other fields, such as the action theory of Talcott Parsons and the sociological autopoiesis of Niklas Luhmann.
In this context the word systems is used to refer specifically to self-regulating systems, i.e. that are self-correcting through feedback. Self-regulating systems are found in nature, including the physiological systems of the human body, in local and global ecosystems, and climate.
=== Decision theory ===
Decision theory (or the theory of choice not to be confused with choice theory) is the study of an agent's choices. Decision theory can be broken into two branches: normative decision theory, which analyzes the outcomes of decisions or determines the optimal decisions given constraints and assumptions, and descriptive decision theory, which analyzes how agents actually make the decisions they do.
Decision theory is closely related to the field of game theory and is an interdisciplinary topic, studied by economists, statisticians, psychologists, biologists, political and other social scientists, philosophers, and computer.
Empirical applications of this rich theory are usually done with the help of statistical and econometric methods.
=== Theoretical computer science ===
Theoretical computer science (TCS) is a subset of general computer science and mathematics that focuses on more mathematical topics of computing, and includes the theory of computation.
It is difficult to circumscribe the theoretical areas precisely. The ACM's (Association for Computing Theory) Special Interest Group on Algorithms and Computation Theory (SIGACT) provides the following description:
TCS covers a wide variety of topics including algorithms, data structures, computational complexity, parallel and distributed computation, probabilistic computation, quantum computation, automata theory, information theory, cryptography, program semantics and verification, machine learning, computational biology, computational economics, computational geometry, and computational number theory and algebra. Work in this field is often distinguished by its emphasis on mathematical technique and rigor.
== Natural sciences ==
Natural science is a branch of science concerned with the description, prediction, and understanding of natural phenomena, based on empirical evidence from observation and experimentation. Mechanisms such as peer review and repeatability of findings are used to try to ensure the validity of scientific advances.
Natural science can be divided into two main branches: life science and physical science. Life science is alternatively known as biology, and physical science is subdivided into branches: physics, chemistry, astronomy and Earth science. These branches of natural science may be further divided into more specialized branches (also known as fields).
=== Physical science ===
Physical science is an encompassing term for the branches of natural science that study non-living systems, in contrast to the life sciences. However, the term "physical" creates an unintended, somewhat arbitrary distinction, since many branches of physical science also study biological phenomena. There is a difference between physical science and physics.
==== Physics ====
Physics (from Ancient Greek: φύσις, romanized: physis, lit. 'nature') is a natural science that involves the study of matter and its motion through spacetime, along with related concepts such as energy and force. More broadly, it is the general analysis of nature, conducted in order to understand how the universe behaves.
Physics is one of the oldest academic disciplines, perhaps the oldest through its inclusion of astronomy. Over the last two millennia, physics was a part of natural philosophy along with chemistry, certain branches of mathematics, and biology, but during the Scientific Revolution in the 16th century, the natural sciences emerged as unique research programs in their own right. Certain research areas are interdisciplinary, such as biophysics and quantum chemistry, which means that the boundaries of physics are not rigidly defined. In the nineteenth and twentieth centuries physicalism emerged as a major unifying feature of the philosophy of science as physics provides fundamental explanations for every observed natural phenomenon. New ideas in physics often explain the fundamental mechanisms of other sciences, while opening to new research areas in mathematics and philosophy.
==== Chemistry ====
Chemistry (the etymology of the word has been much disputed) is the science of matter and the changes it undergoes. The science of matter is also addressed by physics, but while physics takes a more general and fundamental approach, chemistry is more specialized, being concerned by the composition, behavior (or reaction), structure, and properties of matter, as well as the changes it undergoes during chemical reactions. It is a physical science which studies various substances, atoms, molecules, and matter (especially carbon based). Example sub-disciplines of chemistry include: biochemistry, the study of substances found in biological organisms; physical chemistry, the study of chemical processes using physical concepts such as thermodynamics and quantum mechanics; and analytical chemistry, the analysis of material samples to gain an understanding of their chemical composition and structure. Many more specialized disciplines have emerged in recent years, e.g. neurochemistry the chemical study of the nervous system.
==== Earth science ====
Earth science (also known as geoscience, the geosciences or the Earth sciences) is an all-embracing term for the sciences related to the planet Earth. It is arguably a special case in planetary science, the Earth being the only known life-bearing planet. There are both reductionist and holistic approaches to Earth sciences. The formal discipline of Earth sciences may include the study of the atmosphere, hydrosphere, lithosphere, and biosphere, as well as the solid earth. Typically Earth scientists will use tools from physics, chemistry, biology, geography, chronology and mathematics to build a quantitative understanding of how the Earth system works, and how it evolved to its current state.
===== Geology =====
Geology (from the Ancient Greek γῆ, gē ("earth") and -λoγία, -logia, ("study of", "discourse")) is an Earth science concerned with the solid Earth, the rocks of which it is composed, and the processes by which they change over time. Geology can also include the study of the solid features of any terrestrial planet or natural satellite such as Mars or the Moon. Modern geology significantly overlaps all other Earth sciences, including hydrology and the atmospheric sciences, and so is treated as one major aspect of integrated Earth system science and planetary science.
===== Oceanography =====
Oceanography, or marine science, is the branch of Earth science that studies the ocean. It covers a wide range of topics, including marine organisms and ecosystem dynamics; ocean currents, waves, and geophysical fluid dynamics; plate tectonics and the geology of the seafloor; and fluxes of various chemical substances and physical properties within the ocean and across its boundaries. These diverse topics reflect multiple disciplines that oceanographers blend to further knowledge of the world ocean and understanding of processes within it: biology, chemistry, geology, meteorology, and physics as well as geography.
===== Meteorology =====
Meteorology is the interdisciplinary scientific study of the atmosphere. Studies in the field stretch back millennia, though significant progress in meteorology did not occur until the 17th century. The 19th century saw breakthroughs occur after observing networks developed across several countries. After the development of the computer in the latter half of the 20th century, breakthroughs in weather forecasting were achieved.
==== Astronomy ====
Space science is the study of everything in outer space. This has sometimes been called astronomy, but recently astronomy has come to be regarded as a division of broader space science, which has grown to include other related fields, such as studying issues related to space travel and space exploration (including space medicine), space archaeology and science performed in outer space (see space research).
=== Biological science ===
Life science, also known as biology, is the natural science that studies life such as microorganisms, plants, and animals including human beings, – including their physical structure, chemical processes, molecular interactions, physiological mechanisms, development, and evolution. Despite the complexity of the science, certain unifying concepts consolidate it into a single, coherent field. Biology recognizes the cell as the basic unit of life, genes as the basic unit of heredity, and evolution as the engine that propels the creation and extinction of species. Living organisms are open systems that survive by transforming energy and decreasing their local entropy to maintain a stable and vital condition defined as homeostasis.
==== Biochemistry ====
Biochemistry, or biological chemistry, is the study of chemical processes within and relating to living organisms. It is a sub-discipline of both biology and chemistry, and from a reductionist point of view it is fundamental in biology. Biochemistry is closely related to molecular biology, cell biology, genetics, and physiology.
==== Microbiology ====
Microbiology is the study of microorganisms, those being unicellular (single cell), multicellular (cell colony), or acellular (lacking cells). Microbiology encompasses numerous sub-disciplines including virology, bacteriology, protistology, mycology, immunology and parasitology.
==== Botany ====
Botany, also called plant science(s), plant biology or phytology, is the science of plant life and a branch of biology. Traditionally, botany has also included the study of fungi and algae by mycologists and phycologists respectively, with the study of these three groups of organisms remaining within the sphere of interest of the International Botanical Congress. Nowadays, botanists (in the strict sense) study approximately 410,000 species of land plants of which some 391,000 species are vascular plants (including approximately 369,000 species of flowering plants), and approximately 20,000 are bryophytes.
==== Zoology ====
Zoology () is the branch of biology that studies the animal kingdom, including the structure, embryology, evolution, classification, habits, and distribution of all animals, both living and extinct, and how they interact with their ecosystems. The term is derived from Ancient Greek ζῷον, zōion, i.e. "animal" and λόγος, logos, i.e. "knowledge, study". Some branches of zoology include: anthrozoology, arachnology, archaeozoology, cetology, embryology, entomology, helminthology, herpetology, histology, ichthyology, malacology, mammalogy, morphology, nematology, ornithology, palaeozoology, pathology, primatology, protozoology, taxonomy, and zoogeography.
==== Ecology ====
Ecology (from Greek: οἶκος, "house", or "environment"; -λογία, "study of") is a branch of biology concerning interactions among organisms and their biophysical environment, which includes both biotic and abiotic components. Topics of interest include the biodiversity, distribution, biomass, and populations of organisms, as well as cooperation and competition within and between species. Ecosystems are dynamically interacting systems of organisms, the communities they make up, and the non-living components of their environment. Ecosystem processes, such as primary production, pedogenesis, nutrient cycling, and niche construction, regulate the flux of energy and matter through an environment. Organisms with specific life history traits sustain these processes.
== Social sciences ==
Social science is the branch of science devoted to the study of societies and the relationships among individuals within those societies. The term was formerly used to refer to the field of sociology, the original "science of society", established in the 19th century. In addition to sociology, it now encompasses a wide array of academic disciplines, including anthropology, archaeology, economics, education, history, human geography, law, linguistics, political science, and psychology.
Positivist social scientists use methods resembling those of the natural sciences as tools for understanding society, and so define science in its stricter modern sense. Interpretivist social scientists, by contrast, may use social critique or symbolic interpretation rather than constructing empirically falsifiable theories. In modern academic practice, researchers are often eclectic, using multiple methodologies (for instance, by combining both quantitative and qualitative research). The term "social research" has also acquired a degree of autonomy as practitioners from various disciplines share in its aims and methods.
== Applied sciences ==
Applied science is the use of existing scientific knowledge to achieve practical goals, like technology or inventions.
Within natural science, disciplines that are basic science develop basic information to explain and perhaps predict phenomena in the natural world. Applied science is the use of scientific processes and knowledge as the means to achieve a particularly practical or useful result. This includes a broad range of applied science-related fields, including engineering and medicine.
Applied science can also apply formal science, such as statistics and probability theory, as in epidemiology. Genetic epidemiology is an applied science applying both biological and statistical methods.
== Relationships between the branches ==
The relationships between the branches of science are summarized by the table
== Visualizations and metascience ==
Metascience refers to or includes a field of science that is about science itself. OpenAlex and Scholia can be used to visualize and explore scientific fields and research topics.
== See also ==
Index of branches of science
List of words ending in ology
Outline of science
Exact sciences
Basic research
Hard and soft science
Branches of philosophy
Philosophy of science
Engineering physics
Human science
== Notes ==
== References ==
=== Footnotes ===
=== Works cited ===
== External links ==
Branches of Science, sciencemirror | Wikipedia/Branches_of_science |
Lists of publications in science cover publications in various fields of science that have introduced a major new topic, made a significant advance in knowledge or have significantly influenced the world.
== Mathematics ==
List of publications in mathematics
List of publications in statistics
List of publications in data science
== Medicine ==
List of publications in medicine
== Natural sciences ==
List of publications in biology
List of publications in chemistry
List of publications in physics
== Philosophy ==
List of publications in philosophy
== Social sciences ==
Bibliography of sociology
List of humor research publications
List of publications in anthropology
List of publications in economics | Wikipedia/Lists_of_important_publications_in_science |
In the philosophy of science, structuralism (also known as scientific structuralism or as the structuralistic theory-concept) asserts that all aspects of reality are best understood in terms of empirical scientific constructs of entities and their relations, rather than in terms of concrete entities in themselves.
== Overview ==
Structuralism is an active research program in the philosophy of science, which was first developed in the late 1960s and throughout the 1970s by several analytic philosophers.
As an instance of structuralism, the concept of matter should be interpreted not as an absolute property of nature in itself, but instead of how scientifically-grounded mathematical relations describe how the concept of matter interacts with other properties, whether that be in a broad sense such as the gravitational fields that mass produces or more empirically as how matter interacts with sense systems of the body to produce sensations such as weight.
Structuralism's aim is to comprise all important aspects of an empirical theory in one formal framework. The proponents of this meta-theoretic theory are Frederick Suppe, Patrick Suppes, Ronald Giere, Joseph D. Sneed, Wolfgang Stegmüller, Carlos Ulises Moulines, Wolfgang Balzer, John Worrall, Elie Georges Zahar, Pablo Lorenzano, Otávio Bueno, Anjan Chakravartty, Tian Yu Cao, Steven French, and Michael Redhead.
The term "structural realism" for the variation of scientific realism motivated by structuralist arguments, was coined by American philosopher Grover Maxwell in 1968. In 1998, the British structural realist philosopher James Ladyman distinguished epistemic and ontic forms of structural realism.
== Variations ==
=== Epistemic structural realism ===
The philosophical concept of (scientific) structuralism is related to that of epistemic structural realism (ESR). ESR, a position originally and independently held by Henri Poincaré (1902), Bertrand Russell (1927), and Rudolf Carnap (1928), was resurrected by John Worrall (1989), who proposes that there is retention of structure across theory change. Worrall, for example, argued that Fresnel's equations imply that light has a structure and that Maxwell's equations, which replaced Fresnel's, do also; both characterize light as vibrations. Fresnel postulated that the vibrations were in a mechanical medium called "ether"; Maxwell postulated that the vibrations were of electric and magnetic fields. The structure in both cases is the vibrations and it was retained when Maxwell's theories replaced Fresnel's. Because structure is retained, structural realism both (a) avoids pessimistic meta-induction and (b) does not make the success of science seem miraculous, i.e., it puts forward a no-miracles argument.
==== Newman problem ====
The so-called Newman problem (also Newman's problem, Newman objection, Newman's objection) refers to the critical notice of Russell's The Analysis of Matter (1927) published by Max Newman in 1928. Newman argued that the ESR claim that one can know only the abstract structure of the external world trivializes scientific knowledge. The basis of his argument is the realization that "[a]ny collection of things can be organized so as to have structure W, provided there are the right
number of them", where W is an arbitrary structure.
==== Response to the Newman problem ====
John Worrall (2000) advocates a version of ESR augmented by the Ramsey sentence reconstruction of physical theories (a Ramsey sentence aims at rendering propositions containing non-observable theoretical terms clear by substituting them with observable terms). John Worrall and Elie Georges Zahar (2001) claim that Newman's objection applies only if a distinction between observational and theoretical terms is not made.
Ramsey-style epistemic structural realism is distinct from and incompatible with the original Russellian epistemic structural realism (the difference between the two being that Ramsey-style ESR makes an epistemic commitment to Ramsey sentences, while Russellian ESR makes an epistemic commitment to abstract structures, that is, to (second-order) isomorphism classes of the observational structure of the world and not the (first-order) physical structure itself). Ioannis Votsis (2004) claims that Russellian ESR is also impervious to the Newman objection: Newman falsely attributed the trivial claim "there exists a relation with a particular abstract structure" to ESR, while ESR makes the non-trivial claim that there is a unique physical relation that is causally linked with a unique observational relation and the two are isomorphic.
==== Further criticism ====
The traditional scientific realist and notable critic of structural realism Stathis Psillos (1999) remarks that "structural realism is best understood as issuing an epistemic constraint on what can be known and on what scientific theories can reveal." He thinks that ESR faces a number of insurmountable objections. These include among others that ESR's only epistemic commitment is uninterpreted equations which are not by themselves enough to produce predictions and that the "structure versus nature" distinction that ESR appeals to cannot be sustained.
Votsis (2004) replies that the structural realist "does subscribe to interpreted equations, but attempts to distinguish between interpretations that link the terms to observations from those that do not" and he can appeal to the Russellian view that "nature" just means the non-isomorphically specifiable part of entities.
Psillos also defends David Lewis's descriptive-causal theory of reference (according to which the abandoned theoretical terms after a theory change are regarded as successfully referring "after all") and claims that it can adequately deal with referential continuity in conceptual transitions, during which theoretical terms are abandoned, thus rendering ESR redundant.
Votsis (2004) replies that a scientific realist needs not tie the approximate truth of a theory to referential success. Notably, structural realism initially did not dictate any particular theory of reference; however Votsis (2012) proposed a structuralist theory of reference according to which "scientific terms are able to refer to individual objects, i.e. in a term-by-term fashion, but that to fix this reference requires taking into account the relations these objects instantiate" (in this view, structural descriptions serve as reference determiners).
=== Ontic structural realism ===
While ESR claims that only the structure of reality is knowable, ontic structural realism (OSR) goes further to claim that structure is all there is. In this view, reality has no "nature" underlying its observed structure. Rather, reality is fundamentally structural, though variants of OSR disagree on precisely which aspects of structure are primitive. OSR is strongly motivated by modern physics, particularly quantum field theory, which undermines intuitive notions of identifiable objects with intrinsic properties. Some early quantum physicists held this view, including Hermann Weyl (1931), Ernst Cassirer (1936), and Arthur Eddington (1939). Recently, OSR has been called "the most fashionable ontological framework for modern physics".
Max Tegmark takes this concept even further with the mathematical universe hypothesis, which proposes that, if our universe is only a particular structure, then it is no more real than any other structure.
== Definition of structure ==
In mathematical logic, a mathematical structure is a standard concept. A mathematical structure is a set of abstract entities with relations between them. The natural numbers under arithmetic constitute a structure, with relations such as "is evenly divisible by" and "is greater than". Here the relation "is greater than" includes the element (3, 4), but not the element (4, 3). Points in space and the real numbers under Euclidean geometry are another structure, with relations such as "the distance between point P1 and point P2 is real number R1"; equivalently, the "distance" relation includes the element (P1, P2, R1). Other structures include the Riemann space of general relativity and the Hilbert space of quantum mechanics. The entities in a mathematical structure do not have any independent existence outside their participation in relations. Two descriptions of a structure are considered equivalent, and to be describing the same underlying structure, if there is a correspondence between the descriptions that preserves all relations.
Many proponents of structural realism formally or informally ascribe "properties" to the abstract objects; some argue that such properties, while they can perhaps be "shoehorned" into the formalism of relations, should instead be considered distinct from relations.
== Proposed structures ==
In quantum field theory (QFT), traditional proposals for "the most basic known structures" divide into "particle interpretations" such as ascribing reality to the Fock space of particles, and "field interpretations" such as considering the quantum wavefunction to be identical to the underlying reality. Varying interpretations of quantum mechanics provide one complication; another, perhaps minor, complication is that neither fields nor particles are completely localized in standard QFT. A third, less obvious, complication is that "unitarily inequivalent representations" are endemic in QFT; for example, the same patch of spacetime can be represented by a vacuum by an inertial observer, but as a thermal heat bath by an accelerating observer that perceives Unruh radiation, raising the difficult question of whether the vacuum structure or heat bath structure is the real structure, or whether both of these inequivalent structures are separately real. Another example, which does not require the complications of curved spacetime, is that in ferromagnetism, symmetry-breaking analysis results in inequivalent Hilbert spaces. More broadly, QFT's infinite degrees of freedom lead to inequivalent representations in the general case.
In general relativity, scholars often grant a "basic structure" status to the spacetime structure, sometimes via its metric.
== See also ==
Constructive empiricism, a rival yet related view
Semantic view of theories, a view often associated with structuralism
Structural-systematic philosophy, a particular form of structural realism
== Notes ==
^ α: Not to be confused with the distinct tradition of French (semiotic) structuralism.
^ β: So-called 'pessimistic meta-inductions' about theoretical knowledge have the following basic form: "Proposition p is widely believed by most contemporary experts, but p is like many other hypotheses that were widely believed by experts in the past and are disbelieved by most contemporary experts. We have as much reason to expect p to befall their fate as not, therefore we should at least suspend judgement about p if not actively disbelieve it."
== Citations ==
== References ==
W. Balzer, C. U. Moulines, J. D. Sneed, An Architectonic for Science: the Structuralist Approach. Reidel, Dordrecht, 1987.
C. M. Dawe, "The Structure of Genetics," PhD dissertation, University of London, 1982.
Humphreys, P., ed. (1994). Patrick Suppes: Scientific Philosopher, Vol. 2: Philosophy of Physics, Theory Structure and Measurement, and Action Theory, Synthese Library (Springer-Verlag).
J. D. Sneed, The Logical Structure of Mathematical Physics. Reidel, Dordrecht, 1971 (revised edition 1979).
Wolfgang Stegmüller, Probleme und Resultate der Wissenschafttheorie und Analytischen Philosophie: Die Entwicklung des neuen Strukturalismus seit 1973, 1986.
Frederick Suppe, ed., The Structure of Scientific Theories. Urbana: University of Illinois Press, 1977[1974].
John Worrall, "Structural Realism: the Best of Both Worlds" in: D. Papineau (ed.), The Philosophy of Science (Oxford, 1996).
T. Perrone, "Models, Theory Dislodgment, and Epistemic Non Asymptotic Enrichment", Idee, 7/2014, 211-230.
== External links ==
Stanford Encyclopedia of Philosophy: "Structuralism in Physics"
Ioannis Votsis – Structural Realism Bibliography (last updated on 29 June 2020) | Wikipedia/Structuralism_(philosophy_of_science) |
In the philosophy of science, the science wars were a series of scholarly and public discussions in the 1990s over the social place of science in making authoritative claims about the world.
Encyclopedia.com, citing the Encyclopedia of Science and Religion, describes the science wars as the
"complex of discussions about the way the sciences are related to or incarnated in culture, history, and practice. [...] [which] came to be called a 'war' in the mid 1990s because of a strong polarization over questions of legitimacy and authority. One side [...] is concerned with defending the authority of science as rooted in objective evidence and rational procedures. The other side argues that it is legitimate and fruitful to study the sciences as institutions and social-technical networks whose development is influenced by linguistics, economics, politics, and other factors surrounding formally rational procedures and isolated established facts."
The science wars took place principally in the United States in the 1990s in the academic and mainstream press. Scientific realists (such as Norman Levitt, Paul R. Gross, Jean Bricmont and Alan Sokal) accused many writers, whom they described as 'postmodernist', of having effectively rejected scientific objectivity, the scientific method, empiricism, and scientific knowledge.
Though much of the theory associated with 'postmodernism' (see post-structuralism) did not make any interventions into the natural sciences, the scientific realists took aim at its general influence. The scientific realists argued that large swathes of scholarship, amounting to a rejection of objectivity and realism, had been influenced by major 20th-century post-structuralist philosophers (such as Jacques Derrida, Gilles Deleuze, Jean-François Lyotard and others), whose work they declare to be incomprehensible or meaningless. They implicate a broad range of fields in this trend, including cultural studies, feminist studies, comparative literature, media studies, and especially science and technology studies, which does apply such methods to the study of science.
Physicist N. David Mermin understands the science wars as a series of exchanges between scientists and "sociologists, historians and literary critics" who the scientists "thought ...were ludicrously ignorant of science, making all kinds of nonsensical pronouncements. The other side dismissed these charges as naive, ill-informed and self-serving." Sociologist Harry Collins wrote that the "science wars" began "in the early 1990s with attacks by natural scientists or ex-natural scientists who had assumed the role of spokespersons for science. The subject of the attacks was the analysis of science coming out of literary studies and the social sciences."
== Historical background ==
Until the mid-20th century, the philosophy of science had concentrated on the viability of scientific method and knowledge, proposing justifications for the truth of scientific theories and observations and attempting to discover at a philosophical level why science worked.
Karl Popper, an early opponent of logical positivism in the 20th century, repudiated the classical observationalist/inductivist form of scientific method in favour of empirical falsification. He is also known for his opposition to the classical justificationist/verificationist account of knowledge which he replaced with critical rationalism, "the first non justificational philosophy of criticism in the history of philosophy".
His criticisms of scientific method were adopted by several postmodernist critiques.
A number of 20th-century philosophers maintained that logical models of pure science do not apply to actual scientific practice. It was the publication of Thomas Kuhn's The Structure of Scientific Revolutions in 1962, however, which fully opened the study of science to new disciplines by suggesting that the evolution of science was in part socially determined and that it did not operate under the simple logical laws put forward by the logical positivist school of philosophy.
Kuhn described the development of scientific knowledge not as a linear increase in truth and understanding, but as a series of periodic revolutions which overturned the old scientific order and replaced it with new orders (what he called "paradigms"). Kuhn attributed much of this process to the interactions and strategies of the human participants in science rather than its own innate logical structure. (See sociology of scientific knowledge).
Some interpreted Kuhn's ideas to mean that scientific theories were, either wholly or in part, social constructs, which many interpreted as diminishing the claim of science to representing objective reality, and that reality had a lesser or potentially irrelevant role in the formation of scientific theories. In 1971, Jerome Ravetz published Scientific knowledge and its social problems, a book describing the role that the scientific community, as a social construct, plays in accepting or rejecting objective scientific knowledge.
=== Postmodernism ===
A number of different philosophical and historical schools, often grouped together as "postmodernism", began reinterpreting scientific achievements of the past through the lens of the practitioners, often positing the influence of politics and economics in the development of scientific theories in addition to scientific observations. Rather than being presented as working entirely from positivistic observations, many scientists of the past were scrutinized for their connection to issues of gender, sexual orientation, race, and class. Some more radical philosophers, such as Paul Feyerabend, argued that scientific theories were themselves incoherent and that other forms of knowledge production (such as those used in religion) served the material and spiritual needs of their practitioners with equal validity as did scientific explanations.
Imre Lakatos advanced a midway view between the "postmodernist" and "realist" camps. For Lakatos, scientific knowledge is progressive; however, it progresses not by a strict linear path where every new element builds upon and incorporates every other, but by an approach where a "core" of a "research program" is established by auxiliary theories which can themselves be falsified or replaced without compromising the core. Social conditions and attitudes affect how strongly one attempts to resist falsification for the core of a program, but the program has an objective status based on its relative explanatory power. Resisting falsification only becomes ad-hoc and damaging to knowledge when an alternate program with greater explanatory power is rejected in favor of another with less. But because it is changing a theoretical core, which has broad ramifications for other areas of study, accepting a new program is also revolutionary as well as progressive. Thus, for Lakatos the character of science is that of being both revolutionary and progressive; both socially informed and objectively justified.
== The science wars ==
In Higher Superstition: The Academic Left and Its Quarrels With Science (1994), scientists Paul R. Gross and Norman Levitt accused postmodernists of anti-intellectualism, presented the shortcomings of relativism, and suggested that postmodernists knew little about the scientific theories they criticized and practiced poor scholarship for political reasons. The authors insist that the "science critics" misunderstood the theoretical approaches they criticized, given their "caricature, misreading, and condescension, [rather] than argument". The book sparked the so-called science wars. Higher Superstition inspired a New York Academy of Sciences conference titled The Flight from Science and Reason, organized by Gross, Levitt, and Gerald Holton. Attendees of the conference were critical of the polemical approach of Gross and Levitt, yet agreed upon the intellectual inconsistency of how laymen, non-scientist, and social studies intellectuals dealt with science.
=== Social Text ===
In 1996, Social Text, a left-wing Duke University publication of postmodern critical theory, compiled a "Science Wars" issue containing brief articles by postmodernist academics in the social sciences and the humanities, that emphasized the roles of society and politics in science. In the introduction to the issue, the Social Text editor, activist Andrew Ross, said that the attack upon science studies was a conservative reaction to reduced funding for scientific research. He characterized the Flight from Science and Reason conference as an attempted "linking together a host of dangerous threats: scientific creationism, New Age alternatives and cults, astrology, UFO-ism, the radical science movement, postmodernism, and critical science studies, alongside the ready-made historical specters of Aryan-Nazi science and the Soviet error of Lysenkoism" that "degenerated into name-calling".
In another Social Text article, the postmodern sociologist Dorothy Nelkin characterised Gross and Levitt's vigorous response as a "call to arms in response to the failed marriage of Science and the State"—in contrast to the scientists' historical tendency to avoid participating in perceived political threats, such as creation science, the animal rights movement, and anti-abortionists' attempts to curb fetal research. At the end of the Soviet–American Cold War (1945–91), military funding of science declined, while funding agencies demanded accountability, and research became directed by private interests. Nelkin suggested that postmodernist critics were "convenient scapegoats" who diverted attention from problems in science.
Also in 1996, physicist Alan Sokal had submitted an article to Social Text titled "Transgressing the Boundaries: Towards a Transformative Hermeneutics of Quantum Gravity", which proposed that quantum gravity is a linguistic and social construct and that quantum physics supports postmodernist criticisms of scientific objectivity. The staff published it in the "Science Wars" issue as a relevant contribution, later claiming that they held the article back from earlier issues due to Sokal's alleged refusal to consider revisions. Later, in the May 1996 issue of Lingua Franca, in the article "A Physicist Experiments With Cultural Studies", Sokal exposed his parody-article, "Transgressing the Boundaries" as an experiment testing the intellectual rigor of an academic journal that would "publish an article liberally salted with nonsense if (a) it sounded good and (b) it flattered the editors' ideological preconceptions". The matter became known as the "Sokal Affair" and brought greater public attention to the wider conflict.
Jacques Derrida, a frequent target of anti-relativist and anti-postmodern criticism in the wake of Sokal's article, responded to the hoax in "Sokal and Bricmont Aren't Serious", first published in Le Monde. He called Sokal's action sad (triste) for having overshadowed Sokal's mathematical work and ruined the chance to sort out controversies of scientific objectivity in a careful way. Derrida went on to fault him and co-author Jean Bricmont for what he considered an act of intellectual bad faith: they had accused him of scientific incompetence in the English edition of a follow-up book (an accusation several English reviewers noted), but deleted the accusation from the French edition and denied that it had ever existed. He concluded, as the title indicates, that Sokal was not serious in his approach, but had used the spectacle of a "quick practical joke" to displace the scholarship Derrida believed the public deserved.
=== Continued conflict ===
In the first few years after the 'Science Wars' edition of Social Text, the seriousness and volume of discussion increased significantly, much of it focused on reconciling the 'warring' camps of postmodernists and scientists. One significant event was the 'Science and Its Critics' conference in early 1997; it brought together scientists and scholars who study science and featured Alan Sokal and Steve Fuller as keynote speakers. The conference generated the final wave of substantial press coverage (in both news media and scientific journals), though by no means resolved the fundamental issues of social construction and objectivity in science.
Other attempts have been made to reconcile the two camps. Mike Nauenberg, a physicist at the University of California, Santa Cruz, organized a small conference in May 1997 that was attended by scientists and sociologists of science alike, among them Alan Sokal, N. David Mermin and Harry Collins. In the same year, Collins organized the Southampton Peace Workshop, which again brought together a broad range of scientists and sociologists. The Peace Workshop gave rise to the idea of a book that intended to map out some of the arguments between the disputing parties. The One Culture?: A Conversation about Science, edited by chemist Jay A. Labinger and sociologist Harry Collins, was eventually published in 2001. The book's title is a reference to C. P. Snow's The Two Cultures. It contains contributions from authors such as Alan Sokal, Jean Bricmont, Steven Weinberg, and Steven Shapin.
Other significant publications related to the science wars include Fashionable Nonsense by Sokal and Jean Bricmont (1998), The Social Construction of What? by Ian Hacking (1999) and Who Rules in Science by James Robert Brown (2004).
To John C. Baez, the Bogdanov Affair in 2002 served as the bookend to the Sokal controversy: the review, acceptance, and publication of papers, later alleged to be nonsense, in peer-reviewed physics journals. Cornell physics professor Paul Ginsparg, argued that the cases are not at all similar and that the fact that some journals and scientific institutions have low standards is "hardly a revelation". The new editor in chief of the journal Annals of Physics, who was appointed after the controversy along with a new editorial staff, had said that the standards of the journal had been poor leading up to the publication since the previous editor had become sick and died.
Interest in the science wars has waned considerably in recent years. Though the events of the science wars are still occasionally mentioned in the mainstream press, they have had little effect on either the scientific community or the community of critical theorists. Both sides continue to maintain that the other does not understand their theories, or mistakes constructive criticisms and scholarly investigations for attacks. In 1999, the French sociologist Bruno Latour—at the time believing that the natural sciences are socially constructivist—said, "Scientists always stomp around meetings talking about 'bridging the two-culture gap', but when scores of people from outside the sciences begin to build just that bridge, they recoil in horror and want to impose the strangest of all gags on free speech since Socrates: only scientists should speak about science!" Subsequently, Latour has suggested a re-evaluation of sociology's epistemology based on lessons learned from the Science Wars: "... scientists made us realize that there was not the slightest chance that the type of social forces we use as a cause could have objective facts as their effects".
Reviewing Sokal's Beyond the Hoax, Mermin stated that "As a sign that the science wars are over, I cite the 2008 election of Bruno Latour [...] to Foreign Honorary Membership in that bastion of the establishment, the American Academy of Arts and Sciences" and opined that "we are not only beyond Sokal's hoax, but beyond the science wars themselves".
However, more recently, some of the leading critical theorists have recognized that their critiques have, at times, been counter-productive and are providing intellectual ammunition for reactionary interests.
Writing about these developments in the context of global warming, Latour noted that "dangerous extremists are using the very same argument of social construction to destroy hard-won evidence that could save our lives. Was I wrong to participate in the invention of this field known as science studies? Is it enough to say that we did not really mean what we said?"
Kendrick Frazier notes that Latour is interested in helping to rebuild trust in science and that Latour has said that some of the authority of science needs to be regained.
In 2016, Shawn Lawrence Otto, in his book The War on Science: Who's Waging It, Why It Matters, and What We can Do About It, that the winners of the war on science "will chart the future of power, democracy, and freedom itself."
== See also ==
Chomsky–Foucault debate
Culture war
Deconstruction
Grievance studies affair
Historiography of science
Nature versus nurture
Normative science
Positivism
Positivism dispute
Science for the People
Scientific rationalism
Scientism
Searle–Derrida debate
Strong programme
Suppressed research in the Soviet Union
Teissier affair
== Notes ==
== References ==
Ashman, Keith M. and Barringer, Philip S. (ed.) (2001). After the science wars, Routledge, London. ISBN 0-415-21209-X
Gross, Paul R. and Levitt, Norman (1994). Higher Superstition: The Academic Left and Its Quarrels With Science, Johns Hopkins University Press, Baltimore, Maryland. ISBN 0-8018-4766-4
Sokal, Alan D. (1996). Transgressing the Boundaries: Towards a Transformative Hermeneutics of Quantum Gravity, Social Text 46/47, 217–252.
Callon, Michel (1999). Whose Impostures? Physicists at War with the Third Person, Social Studies of Science 29(2), 261–286.
Parsons, Keith (ed.) (2003). The Science Wars: Debating Scientific Knowledge and Technology, Prometheus Books, Amherst, NY, US. ISBN 1-57392-994-8
Labinger, Jay A. and Collins, Harry (eds.) (2001). The One Culture?: A Conversation About Science, University of Chicago Press, Chicago. ISBN 0-226-46723-6
Brown, James R. (2001). Who Rules in Science? An Opinionated Guide to the Wars, Harvard University Press, Cambridge, MA.
== External links ==
Papers by Alan Sokal on the "Social Text Affair"
Henriques, Gregg (1 June 2012). "Revisiting the Science Wars | Psychology Today". Psychology Today. Retrieved 3 June 2023. | Wikipedia/Science_wars |
"Surely You're Joking, Mr. Feynman!": Adventures of a Curious Character is an edited collection of reminiscences by the Nobel Prize–winning physicist Richard Feynman. The book, published in 1985, covers a variety of instances in Feynman's life. The anecdotes in the book are based on recorded audio conversations that Feynman had with his close friend and drumming partner Ralph Leighton.
== Summary ==
The book has many stories which are lighthearted in tone, such as his fascination with safe-cracking, studying various languages, participating with groups of people who share different interests (such as biology or philosophy), and ventures into art and samba music.
Other stories cover more serious material, including his work on the Manhattan Project (during which his first wife, Arline, died of tuberculosis) and his critique of the science education system in Brazil. The section "Monster Minds" describes his slightly nervous presentation of his graduate work on the Wheeler–Feynman absorber theory in front of Albert Einstein, Wolfgang Pauli, Henry Norris Russell, John von Neumann, and other major scientists of the time.
The anecdotes were edited from taped conversations that Feynman had with his close friend and drumming partner Ralph Leighton. Its surprise success led to a sequel, What Do You Care What Other People Think?, also taken from Leighton's taped conversations. Surely You're Joking, Mr. Feynman! became a national bestseller.
The book's title is taken from a comment made by a woman at Princeton University after Feynman asked for both cream and lemon in his tea, a combination that would just curdle the cream.: 60
=== Cargo Cult Science ===
The final chapter, "Cargo Cult Science", was adapted from Feynman's 1974 commencement address at the California Institute of Technology, in which he cautioned graduates not to minimize the weaknesses of their research in the pursuit of a preferred conclusion. He drew an analogy to the cargo cult phenomenon in the South Pacific Ocean in which, as he understood it, islanders built a mock airstrip to cause airplanes loaded with imported goods to land. The cargo cult islanders carved headphones from wood and wore them while sitting in handmade lashed-up control towers. They waved landing signals to conjure the cargo planes out of the sky.: 1h43m
Similarly, he argued, adopting the appearances of scientific investigation without a self-critical attitude will fail to produce reliable results.
Feynman used the term "cargo cult" to describe situations where people focus on superficial aspects of a process without understanding the underlying principles.: 338
== Reception ==
Feynman's "cargo cult" metaphor was used by Tomasz Witkowski in his criticism of social science and psychology in particular. In the first part of his book Psychology Led Astray, Witkowski asks "Is Psychology a Cargo Cult Science?", pointing out that the growth in the number of psychologists worldwide has been parallel with a decrease in mental health.: 25 He also points to other articles and applies the cargo cult metaphor to criticize social sciences.
Murray Gell-Mann was upset by Feynman's account in the book of the weak-interaction work and threatened to sue, resulting in a correction being inserted in later editions.
Feynman was criticized for a chapter titled "You Just Ask Them?" where he recounts attempting to pick up a woman, insulting her after she refuses his advances. Feynman states at the end of the chapter that this behavior was not typical.
== Publication data ==
Surely You're Joking, Mr. Feynman!: Adventures of a Curious Character, Richard Feynman, Ralph Leighton (contributor), Edward Hutchings (editor), 1985, W. W. Norton, ISBN 0-393-01921-7, 1997 paperback: ISBN 0-393-31604-1, 2002 Blackstone Audiobooks unabridged audio cassette: ISBN 0-7861-2218-8
== Citations ==
Gleick, James (1992). Genius: The Life and Science of Richard Feynman. Pantheon Books. ISBN 0679747044.
== External links ==
Quotations related to Richard Feynman at Wikiquote | Wikipedia/Cargo_cult_science |
Physical science is a branch of natural science that studies non-living systems, in contrast to life science. It in turn has many branches, each referred to as a "physical science", together is called the "physical sciences".
== Definition ==
Physical science can be described as all of the following:
A branch of science (a systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe).
A branch of natural science – natural science is a major branch of science that tries to explain and predict nature's phenomena, based on empirical evidence. In natural science, hypotheses must be verified scientifically to be regarded as scientific theory. Validity, accuracy, and social mechanisms ensuring quality control, such as peer review and repeatability of findings, are amongst the criteria and methods used for this purpose. Natural science can be broken into two main branches: life science (for example biology) and physical science. Each of these branches, and all of their sub-branches, are referred to as natural sciences.
A branch of applied science - the application of the scientific method and scientific knowledge to attain practical goals. It includes a broad range of disciplines, such as engineering and medicine., although medicine would not normally be considered a physical science. Applied science is often contrasted with basic science, which is focused on advancing scientific theories and laws that explain and predict natural or other phenomena.
== Branches ==
Physics – natural and physical science could involve the study of matter and its motion through space and time, along with related concepts such as energy and force. More broadly, it is the general analysis of nature, conducted in order to understand how the universe behaves.
Branches of physics
Astronomy – study of celestial objects (such as stars, galaxies, planets, moons, asteroids, comets and nebulae), the physics, chemistry, and evolution of such objects, and phenomena that originate outside the atmosphere of Earth, including supernovae explosions, gamma-ray bursts, and cosmic microwave background radiation.
Branches of astronomy
Chemistry – studies the composition, structure, properties and change of matter. In this realm, chemistry deals with such topics as the properties of individual atoms, the manner in which atoms form chemical bonds in the formation of compounds, the interactions of substances through intermolecular forces to give matter its general properties, and the interactions between substances through chemical reactions to form different substances.
Branches of chemistry
Earth science – all-embracing term referring to the fields of science dealing with planet Earth. Earth science is the study of how the natural environment (ecosphere or Earth system) works and how it evolved to its current state. It includes the study of the atmosphere, hydrosphere, lithosphere, and biosphere.
Materials science - an interdisciplinary field of researching and discovering materials. Materials scientists emphasize understanding how the history of a material (processing) influences its structure, and also the material's properties and performance. The understanding of processing structure properties relationships is called the materials paradigm. This paradigm is used for advanced understanding in a variety of research areas, including nanotechnology, biomaterials, and metallurgy.
Computer science - the study of computation, information, and automation. Computer science spans theoretical disciplines (such as algorithms, theory of computation, and information theory) to applied disciplines (including the design and implementation of hardware and software).
== History ==
History of physical science – history of the branch of natural science that studies non-living systems, in contrast to the life sciences. It in turn has many branches, each referred to as a "physical science", together called the "physical sciences". However, the term "physical" creates an unintended, somewhat arbitrary distinction, since many branches of physical science also study biological phenomena (organic chemistry, for example). The four main branches of physical science are astronomy, physics, chemistry, and the Earth sciences, which include meteorology and geology. There are also a number of others which have become important in the twenty-first such as materials science and computer science.
History of physics – history of the physical science that studies matter and its motion through space-time, and related concepts such as energy and force
History of acoustics – history of the study of mechanical waves in solids, liquids, and gases (such as vibration and sound)
History of agrophysics – history of the study of physics applied to agroecosystems
History of soil physics – history of the study of soil physical properties and processes.
History of astrophysics – history of the study of the physical aspects of celestial objects
History of astronomy – history of the study of the universe beyond Earth, including its formation and development, and the evolution, physics, chemistry, meteorology, and motion of celestial objects (such as galaxies, planets, etc.) and phenomena that originate outside the atmosphere of Earth (such as the cosmic background radiation).
History of astrodynamics – history of the application of ballistics and celestial mechanics to the practical problems concerning the motion of rockets and other spacecraft.
History of astrometry – history of the branch of astronomy that involves precise measurements of the positions and movements of stars and other celestial bodies.
History of cosmology – history of the discipline that deals with the nature of the Universe as a whole.
History of extragalactic astronomy – history of the branch of astronomy concerned with objects outside our own Milky Way Galaxy
History of galactic astronomy – history of the study of our own Milky Way galaxy and all its contents.
History of physical cosmology – history of the study of the largest-scale structures and dynamics of the universe and is concerned with fundamental questions about its formation and evolution.
History of planetary science – history of the scientific study of planets (including Earth), moons, and planetary systems, in particular those of the Solar System and the processes that form them.
History of stellar astronomy – history of the natural science that deals with the study of celestial objects (such as stars, planets, comets, nebulae, star clusters, and galaxies) and phenomena that originate outside the atmosphere of Earth (such as cosmic background radiation)
History of atmospheric physics – history of the study of the application of physics to the atmosphere
History of atomic, molecular, and optical physics – history of the study of how matter and light interact
History of biophysics – history of the study of physical processes relating to biology
History of medical physics – history of the application of physics concepts, theories and methods to medicine.
History of neurophysics – history of the branch of biophysics dealing with the nervous system.
History of chemical physics – history of the branch of physics that studies chemical processes from the point of view of physics.
History of computational physics – history of the study and implementation of numerical algorithms to solve problems in physics for which a quantitative theory already exists.
History of condensed matter physics – history of the study of the physical properties of condensed phases of matter.
History of cryogenics – history of cryogenics is the study of the production of very low temperature (below −150 °C, −238 °F or 123K) and the behavior of materials at those temperatures.
History of Dynamics – history of the study of the causes of motion and changes in motion
History of econophysics – history of the interdisciplinary research field, applying theories and methods originally developed by physicists in order to solve problems in economics
History of electromagnetism – history of the branch of science concerned with the forces that occur between electrically charged particles.
History of geophysics – history of the physics of the Earth and its environment in space; also the study of the Earth using quantitative physical methods
History of materials physics – history of the use of physics to describe materials in many different ways such as force, heat, light and mechanics.
History of mathematical physics – history of the application of mathematics to problems in physics and the development of mathematical methods for such applications and for the formulation of physical theories.
History of mechanics – history of the branch of physics concerned with the behavior of physical bodies when subjected to forces or displacements, and the subsequent effects of the bodies on their environment.
History of biomechanics – history of the study of the structure and function of biological systems such as humans, animals, plants, organs, and cells by means of the methods of mechanics.
History of classical mechanics – history of one of the two major sub-fields of mechanics, which is concerned with the set of physical laws describing the motion of bodies under the action of a system of forces.
History of continuum mechanics – history of the branch of mechanics that deals with the analysis of the kinematics and the mechanical behavior of materials modeled as a continuous mass rather than as discrete particles.
History of fluid mechanics – history of the study of fluids and the forces on them.
History of quantum mechanics – history of the branch of physics dealing with physical phenomena where the action is on the order of the Planck constant.
History of thermodynamics – history of the branch of physical science concerned with heat and its relation to other forms of energy and work.
History of nuclear physics – history of the field of physics that studies the building blocks and interactions of atomic nuclei.
History of optics – history of the branch of physics which involves the behavior and properties of light, including its interactions with matter and the construction of instruments that use or detect it.
History of particle physics – history of the branch of physics that studies the existence and interactions of particles that are the constituents of what is usually referred to as matter or radiation.
History of psychophysics – history of the quantitatively investigates the relationship between physical stimuli and the sensations and perceptions they affect.
History of plasma physics – history of the state of matter similar to gas in which a certain portion of the particles are ionized.
History of polymer physics – history of the field of physics that studies polymers, their fluctuations, mechanical properties, as well as the kinetics of reactions involving degradation and polymerization of polymers and monomers respectively.
History of quantum physics – history of the branch of physics dealing with physical phenomena where the action is on the order of the Planck constant.
History of theory of relativity –
History of statics – history of the branch of mechanics concerned with the analysis of loads (force, torque/moment) on physical systems in static equilibrium, that is, in a state where the relative positions of subsystems do not vary over time, or where components and structures are at a constant velocity.
History of solid state physics – history of the study of rigid matter, or solids, through methods such as quantum mechanics, crystallography, electromagnetism, and metallurgy.
History of vehicle dynamics – history of the dynamics of vehicles, here assumed to be ground vehicles.
History of chemistry – history of the physical science of atomic matter (matter that is composed of chemical elements), especially its chemical reactions, but also including its properties, structure, composition, behavior, and changes as they relate the chemical reactions
History of analytical chemistry – history of the study of the separation, identification, and quantification of the chemical components of natural and artificial materials.
History of astrochemistry – history of the study of the abundance and reactions of chemical elements and molecules in the universe, and their interaction with radiation.
History of cosmochemistry – history of the study of the chemical composition of matter in the universe and the processes that led to those compositions
History of atmospheric chemistry – history of the branch of atmospheric science in which the chemistry of the Earth's atmosphere and that of other planets is studied. It is a multidisciplinary field of research and draws on environmental chemistry, physics, meteorology, computer modeling, oceanography, geology and volcanology, and other disciplines
History of biochemistry – history of the study of chemical processes in living organisms, including, but not limited to, living matter. Biochemistry governs all living organisms and living processes.
History of agrochemistry – history of the study of both chemistry and biochemistry which are important in agricultural production, the processing of raw products into foods and beverages, and in environmental monitoring and remediation.
History of bioinorganic chemistry – history of the examines the role of metals in biology.
History of bioorganic chemistry – history of the rapidly growing scientific discipline that combines organic chemistry and biochemistry.
History of biophysical chemistry – history of the new branch of chemistry that covers a broad spectrum of research activities involving biological systems.
History of environmental chemistry – history of the scientific study of the chemical and biochemical phenomena that occur in natural places.
History of immunochemistry – history of the branch of chemistry that involves the study of the reactions and components on the immune system.
History of medicinal chemistry – history of the discipline at the intersection of chemistry, especially synthetic organic chemistry, and pharmacology and various other biological specialties, where they are involved with design, chemical synthesis, and development for market of pharmaceutical agents (drugs).
History of pharmacology – history of the branch of medicine and biology concerned with the study of drug action.
History of natural product chemistry – history of the chemical compound or substance produced by a living organism – history of the found in nature that usually has a pharmacological or biological activity for use in pharmaceutical drug discovery and drug design.
History of neurochemistry – history of the specific study of neurochemicals, which include neurotransmitters and other molecules such as neuro-active drugs that influence neuron function.
History of computational chemistry – history of the branch of chemistry that uses principles of computer science to assist in solving chemical problems.
History of chemo-informatics – history of the use of computer and informational techniques, applied to a range of problems in the field of chemistry.
History of molecular mechanics – history of the uses Newtonian mechanics to model molecular systems.
History of Flavor chemistry – history of someone who uses chemistry to engineer artificial and natural flavors.
History of Flow chemistry – history of the chemical reaction is run in a continuously flowing stream rather than in batch production.
History of geochemistry – history of the study of the mechanisms behind major geological systems using chemistry
History of aqueous geochemistry – history of the study of the role of various elements in watersheds, including copper, sulfur, mercury, and how elemental fluxes are exchanged through atmospheric-terrestrial-aquatic interactions
History of isotope geochemistry – history of the study of the relative and absolute concentrations of the elements and their isotopes using chemistry and geology
History of ocean chemistry – history of the study of the chemistry of marine environments including the influences of different variables.
History of organic geochemistry – history of the study of the impacts and processes that organisms have had on Earth
History of regional, environmental and exploration geochemistry – history of the study of the spatial variation in the chemical composition of materials at the surface of the Earth
History of inorganic chemistry – history of the branch of chemistry concerned with the properties and behavior of inorganic compounds.
History of nuclear chemistry – history of the subfield of chemistry dealing with radioactivity, nuclear processes, and nuclear properties.
History of radiochemistry – history of the chemistry of radioactive materials, where radioactive isotopes of elements are used to study the properties and chemical reactions of non-radioactive isotopes (often within radiochemistry the absence of radioactivity leads to a substance being described as being inactive as the isotopes are stable).
History of organic chemistry – history of the study of the structure, properties, composition, reactions, and preparation (by synthesis or by other means) of carbon-based compounds, hydrocarbons, and their derivatives.
History of petrochemistry – history of the branch of chemistry that studies the transformation of crude oil (petroleum) and natural gas into useful products or raw materials.
History of organometallic chemistry – history of the study of chemical compounds containing bonds between carbon and a metal.
History of photochemistry – history of the study of chemical reactions that proceed with the absorption of light by atoms or molecules..
History of physical chemistry – history of the study of macroscopic, atomic, subatomic, and particulate phenomena in chemical systems in terms of physical laws and concepts.
History of chemical kinetics – history of the study of rates of chemical processes.
History of chemical thermodynamics – history of the study of the interrelation of heat and work with chemical reactions or with physical changes of state within the confines of the laws of thermodynamics.
History of electrochemistry – history of the branch of chemistry that studies chemical reactions which take place in a solution at the interface of an electron conductor (a metal or a semiconductor) and an ionic conductor (the electrolyte), and which involve electron transfer between the electrode and the electrolyte or species in solution.
History of Femtochemistry – history of the Femtochemistry is the science that studies chemical reactions on extremely short timescales, approximately 10−15 seconds (one femtosecond, hence the name).
History of mathematical chemistry – history of the area of research engaged in novel applications of mathematics to chemistry; it concerns itself principally with the mathematical modeling of chemical phenomena.
History of mechanochemistry – history of the coupling of the mechanical and the chemical phenomena on a molecular scale and includes mechanical breakage, chemical behavior of mechanically stressed solids (e.g., stress-corrosion cracking), tribology, polymer degradation under shear, cavitation-related phenomena (e.g., sonochemistry and sonoluminescence), shock wave chemistry and physics, and even the burgeoning field of molecular machines.
History of physical organic chemistry – history of the study of the interrelationships between structure and reactivity in organic molecules.
History of quantum chemistry – history of the branch of chemistry whose primary focus is the application of quantum mechanics in physical models and experiments of chemical systems.
History of sonochemistry – history of the study of the effect of sonic waves and wave properties on chemical systems.
History of stereochemistry – history of the study of the relative spatial arrangement of atoms within molecules.
History of supramolecular chemistry – history of the area of chemistry beyond the molecules and focuses on the chemical systems made up of a discrete number of assembled molecular subunits or components.
History of thermochemistry – history of the study of the energy and heat associated with chemical reactions and/or physical transformations.
History of phytochemistry – history of the strict sense of the word the study of phytochemicals.
History of polymer chemistry – history of the multidisciplinary science that deals with the chemical synthesis and chemical properties of polymers or macromolecules.
History of solid-state chemistry – history of the study of the synthesis, structure, and properties of solid phase materials, particularly, but not necessarily exclusively of, non-molecular solids
Multidisciplinary fields involving chemistry
History of chemical biology – history of the scientific discipline spanning the fields of chemistry and biology that involves the application of chemical techniques and tools, often compounds produced through synthetic chemistry, to the study and manipulation of biological systems.
History of chemical engineering – history of the branch of engineering that deals with physical science (e.g., chemistry and physics), and life sciences (e.g., biology, microbiology and biochemistry) with mathematics and economics, to the process of converting raw materials or chemicals into more useful or valuable forms.
History of chemical oceanography – history of the study of the behavior of the chemical elements within the Earth's oceans.
History of chemical physics – history of the branch of physics that studies chemical processes from the point of view of physics.
History of materials science – history of the interdisciplinary field applying the properties of matter to various areas of science and engineering.
History of nanotechnology – history of the study of manipulating matter on an atomic and molecular scale
History of oenology – history of the science and study of all aspects of wine and winemaking except vine-growing and grape-harvesting, which is a subfield called viticulture.
History of spectroscopy – history of the study of the interaction between matter and radiated energy
History of surface science – history of the Surface science is the study of physical and chemical phenomena that occur at the interface of two phases, including solid–liquid interfaces, solid–gas interfaces, solid–vacuum interfaces, and liquid–gas interfaces.
History of Earth science – history of the all-embracing term for the sciences related to the planet Earth. Earth science, and all of its branches, are branches of physical science.
History of atmospheric sciences – history of the umbrella term for the study of the atmosphere, its processes, the effects other systems have on the atmosphere, and the effects of the atmosphere on these other systems.
History of climatology
History of meteorology
History of atmospheric chemistry
History of biogeography – history of the study of the distribution of species (biology), organisms, and ecosystems in geographic space and through geological time.
History of cartography – history of the study and practice of making maps or globes.
History of climatology – history of the study of climate, scientifically defined as weather conditions averaged over a period of time
History of coastal geography – history of the study of the dynamic interface between the ocean and the land, incorporating both the physical geography (i.e. coastal geomorphology, geology and oceanography) and the human geography (sociology and history) of the coast.
History of environmental science – history of an integrated, quantitative, and interdisciplinary approach to the study of environmental systems.
History of ecology – history of the scientific study of the distribution and abundance of living organisms and how the distribution and abundance are affected by interactions between the organisms and their environment.
History of Freshwater biology – history of the scientific biological study of freshwater ecosystems and is a branch of limnology
History of marine biology – history of the scientific study of organisms in the ocean or other marine or brackish bodies of water
History of parasitology – history of the Parasitology is the study of parasites, their hosts, and the relationship between them.
History of population dynamics – history of the Population dynamics is the branch of life sciences that studies short-term and long-term changes in the size and age composition of populations, and the biological and environmental processes influencing those changes.
History of environmental chemistry – history of the Environmental chemistry is the scientific study of the chemical and biochemical phenomena that occur in natural places.
History of environmental soil science – history of the Environmental soil science is the study of the interaction of humans with the pedosphere as well as critical aspects of the biosphere, the lithosphere, the hydrosphere, and the atmosphere.
History of environmental geology – history of the Environmental geology, like hydrogeology, is an applied science concerned with the practical application of the principles of geology in the solving of environmental problems.
History of toxicology – history of the branch of biology, chemistry, and medicine concerned with the study of the adverse effects of chemicals on living organisms.
History of geodesy – history of the scientific discipline that deals with the measurement and representation of the Earth, including its gravitational field, in a three-dimensional time-varying space
History of geography – history of the science that studies the lands, features, inhabitants, and phenomena of Earth
History of geoinformatics – history of the science and the technology which develops and uses information science infrastructure to address the problems of geography, geosciences and related branches of engineering.
History of geology – history of the study of the Earth, with the general exclusion of present-day life, flow within the ocean, and the atmosphere.
History of planetary geology – history of the planetary science discipline concerned with the geology of the celestial bodies such as the planets and their moons, asteroids, comets, and meteorites.
History of geomorphology – history of the scientific study of landforms and the processes that shape them
History of geostatistics – history of the branch of statistics focusing on spatial or spatiotemporal datasets
History of geophysics – history of the physics of the Earth and its environment in space; also the study of the Earth using quantitative physical methods.
History of glaciology – history of the study of glaciers, or more generally ice and natural phenomena that involve ice.
History of hydrology – history of the study of the movement, distribution, and quality of water on Earth and other planets, including the hydrologic cycle, water resources and environmental watershed sustainability.
History of hydrogeology – history of the area of geology that deals with the distribution and movement of groundwater in the soil and rocks of the Earth's crust (commonly in aquifers).
History of mineralogy – history of the study of chemistry, crystal structure, and physical (including optical) properties of minerals.
History of meteorology – history of the interdisciplinary scientific study of the atmosphere which explains and forecasts weather events.
History of oceanography – history of the branch of Earth science that studies the ocean
History of paleoclimatology – history of the study of changes in climate taken on the scale of the entire history of Earth
History of paleontology – history of the study of prehistoric life
History of petrology – history of the branch of geology that studies the origin, composition, distribution and structure of rocks.
History of limnology – history of the study of inland waters
History of seismology – history of the scientific study of earthquakes and the propagation of elastic waves through the Earth or through other planet-like bodies
History of soil science – history of the study of soil as a natural resource on the surface of the earth including soil formation, classification and mapping; physical, chemical, biological, and fertility properties of soils; and these properties in relation to the use and management of soils.
History of topography – history of the study of surface shape and features of the Earth and other observable astronomical objects including planets, moons, and asteroids.
History of volcanology – history of the study of volcanoes, lava, magma, and related geological, geophysical and geochemical phenomena.
== General principles ==
Principle – law or rule that has to be, or usually is to be followed, or can be desirably followed, or is an inevitable consequence of something, such as the laws observed in nature or the way that a system is constructed. The principles of such a system are understood by its users as the essential characteristics of the system, or reflecting system's designed purpose, and the effective operation or use of which would be impossible if any one of the principles was to be ignored.
=== Basic principles of physics ===
Physics – branch of science that studies matter and its motion through space and time, along with related concepts such as energy and force. Physics is one of the "fundamental sciences" because the other natural sciences (like biology, geology, etc.) deal with systems that seem to obey the laws of physics. According to physics, the physical laws of matter, energy, and the fundamental forces of nature govern the interactions between particles and physical entities (such as planets, molecules, atoms, or subatomic particles). Some of the basic pursuits of physics, which include some of the most prominent developments in modern science in the last millennium, include:
Describing the nature, measuring and quantifying of bodies and their motion, dynamics etc.
Newton's laws of motion
Mass, force and weight
Momentum and conservation of energy
Gravity, theories of gravity
Energy, work, and their relationship
Motion, position, and energy
Different forms of Energy, their interconversion and the inevitable loss of energy in the form of heat (Thermodynamics)
Energy conservation, conversion, and transfer.
Energy source the transfer of energy from one source to work in another.
Kinetic molecular theory
Phases of matter and phase transitions
Temperature and thermometers
Energy and heat
Heat flow: conduction, convection, and radiation
The four laws of thermodynamics
The principles of waves and sound
The principles of electricity, magnetism, and electromagnetism
The principles, sources, and properties of light
=== Basic principles of astronomy ===
Astronomy – science of celestial bodies and their interactions in space. Its studies include the following:
The life and characteristics of stars and galaxies
Origins of the universe. Physical science uses the Big Bang theory as the commonly accepted scientific theory of the origin of the universe.
A heliocentric Solar System. Ancient cultures saw the Earth as the centre of the Solar System or universe (geocentrism). In the 16th century, Nicolaus Copernicus advanced the ideas of heliocentrism, recognizing the Sun as the centre of the Solar System.
The structure of solar systems, planets, comets, asteroids, and meteors
The shape and structure of Earth (roughly spherical, see also Spherical Earth)
Earth in the Solar System
Time measurement
The composition and features of the Moon
Interactions of the Earth and Moon
(Note: Astronomy should not be confused with astrology, which assumes that people's destiny and human affairs in general correlate to the apparent positions of astronomical objects in the sky – although the two fields share a common origin, they are quite different; astronomers embrace the scientific method, while astrologers do not.)
=== Basic principles of chemistry ===
Chemistry – branch of science that studies the composition, structure, properties and change of matter. Chemistry is chiefly concerned with atoms and molecules and their interactions and transformations, for example, the properties of the chemical bonds formed between atoms to create chemical compounds. As such, chemistry studies the involvement of electrons and various forms of energy in photochemical reactions, oxidation-reduction reactions, changes in phases of matter, and separation of mixtures. Preparation and properties of complex substances, such as alloys, polymers, biological molecules, and pharmaceutical agents are considered in specialized fields of chemistry.
Physical chemistry
Chemical thermodynamics
Reaction kinetics
Molecular structure
Quantum chemistry
Spectroscopy
Theoretical chemistry
Electron configuration
Molecular modelling
Molecular dynamics
Statistical mechanics
Computational chemistry
Mathematical chemistry
Cheminformatics
Nuclear chemistry
The nature of the atomic nucleus
Characterization of radioactive decay
Nuclear reactions
Organic chemistry
Organic compounds
Organic reaction
Functional groups
Organic synthesis
Inorganic chemistry
Inorganic compounds
Crystal structure
Coordination chemistry
Solid-state chemistry
Biochemistry
Analytical chemistry
Instrumental analysis
Electroanalytical method
Wet chemistry
Electrochemistry
Redox reaction
Materials chemistry
=== Basic principles of Earth science ===
Earth science – the science of the planet Earth, as of 2018 the only identified life-bearing planet. Its studies include the following:
The water cycle and the process of transpiration
Freshwater
Oceanography
Weathering and erosion
Rocks
Agrophysics
Soil science
Pedogenesis
Soil fertility
Earth's tectonic structure
Geomorphology and geophysics
Physical geography
Seismology: stress, strain, and earthquakes
Characteristics of mountains and volcanoes
Characteristics and formation of fossils
Atmospheric sciences – the branches of science that study the atmosphere, its processes, the effects other systems have on the atmosphere, and the effects of the atmosphere on these other systems.
Atmosphere of Earth
Atmospheric pressure and winds
Evaporation, condensation, and humidity
Fog and clouds
Meteorology, weather, climatology, and climate
Hydrology, clouds and precipitation
Air masses and weather fronts
Major storms: thunderstorms, tornadoes, and hurricanes
Major climate groups
Speleology
Cave
== Notable physical scientists ==
List of physicists
List of astronomers
List of chemists
=== Earth scientists ===
List of Russian Earth scientists
== See also ==
Outline of science
Outline of natural science
Outline of physical science
Outline of earth science
Outline of formal science
Outline of social science
Outline of applied science
== Notes ==
== References ==
=== Works cited ===
Feynman, R.P.; Leighton, R.B.; Sands, M. (1963). The Feynman Lectures on Physics. Vol. 1. ISBN 0-201-02116-1. {{cite book}}: ISBN / Date incompatibility (help)
Holzner, S. (2006). Physics for Dummies. John Wiley & Sons. ISBN 0-470-61841-8. Physics is the study of your world and universe around you.
Maxwell, J.C. (1878). Matter and Motion. D. Van Nostrand. ISBN 0-486-66895-9. {{cite book}}: ISBN / Date incompatibility (help)
Young, H.D.; Freedman, R.A. (2014). Sears and Zemansky's University Physics with Modern Physics Technology Update (13th ed.). Pearson Education. ISBN 978-1-292-02063-1.
== External links ==
Physical science topics and articles for school curricula (grades K-12) | Wikipedia/Physical_science |
The hypothetico-deductive model or method is a proposed description of the scientific method. According to it, scientific inquiry proceeds by formulating a hypothesis in a form that can be falsifiable, using a test on observable data where the outcome is not yet known. A test outcome that could have and does run contrary to predictions of the hypothesis is taken as a falsification of the hypothesis. A test outcome that could have, but does not run contrary to the hypothesis corroborates the theory. It is then proposed to compare the explanatory value of competing hypotheses by testing how stringently they are corroborated by their predictions.
== Example ==
One example of an algorithmic statement of the hypothetico-deductive method is as follows:
One possible sequence in this model would be 1, 2, 3, 4. If the outcome of 4 holds, and 3 is not yet disproven, you may continue with 3, 4, 1, and so forth; but if the outcome of 4 shows 3 to be false, you will have to go back to 2 and try to invent a new 2, deduce a new 3, look for 4, and so forth.
Note that this method can never absolutely verify (prove the truth of) 2. It can only falsify 2. (This is what Einstein meant when he said, "No amount of experimentation can ever prove me right; a single experiment can prove me wrong.")
== Discussion ==
Additionally, as pointed out by Carl Hempel (1905–1997), this simple view of the scientific method is incomplete; a conjecture can also incorporate probabilities, e.g., the drug is effective about 70% of the time. Tests, in this case, must be repeated to substantiate the conjecture (in particular, the probabilities). In this and other cases, we can quantify a probability for our confidence in the conjecture itself and then apply a Bayesian analysis, with each experimental result shifting the probability either up or down. Bayes' theorem shows that the probability will never reach exactly 0 or 100% (no absolute certainty in either direction), but it can still get very close to either extreme. See also confirmation holism.
Qualification of corroborating evidence is sometimes raised as philosophically problematic. The raven paradox is a famous example. The hypothesis that 'all ravens are black' would appear to be corroborated by observations of only black ravens. However, 'all ravens are black' is logically equivalent to 'all non-black things are non-ravens' (this is the contrapositive form of the original implication). 'This is a green tree' is an observation of a non-black thing that is a non-raven and therefore corroborates 'all non-black things are non-ravens'. It appears to follow that the observation 'this is a green tree' is corroborating evidence for the hypothesis 'all ravens are black'.
Attempted resolutions may distinguish:
non-falsifying observations as to strong, moderate, or weak corroborations
investigations that do or do not provide a potentially falsifying test of the hypothesis.
Evidence contrary to a hypothesis is itself philosophically problematic. Such evidence is called a falsification of the hypothesis. However, under the theory of confirmation holism it is always possible to save a given hypothesis from falsification. This is so because any falsifying observation is embedded in a theoretical background, which can be modified in order to save the hypothesis. Karl Popper acknowledged this but maintained that a critical approach respecting methodological rules that avoided such immunizing stratagems is conducive to the progress of science.
Physicist Sean Carroll claims the model ignores underdetermination.
=== Versus other research models ===
The hypothetico-deductive approach contrasts with other research models such as the inductive approach or grounded theory. In the data percolation methodology,
the hypothetico-deductive approach is included in a paradigm of pragmatism by which four types of relations between the variables can exist: descriptive, of influence, longitudinal or causal. The variables are classified in two groups, structural and functional, a classification that drives the formulation of hypotheses and the statistical tests to be performed on the data so as to increase the efficiency of the research.
== See also ==
Confirmation bias
Deductive-nomological
Explanandum and explanans
Inquiry
Models of scientific inquiry
Philosophy of science
Pragmatism
Scientific method
Verifiability theory of meaning
Will to believe doctrine
=== Types of inference ===
Strong inference
Abductive reasoning
Deductive reasoning
Inductive reasoning
Analogy
== Citations ==
== References ==
Brody, Thomas A. (1993), The Philosophy Behind Physics, Springer Verlag, ISBN 0-387-55914-0. (Luis de la Peña and Peter E. Hodgson, eds.)
Bynum, W.F.; Porter, Roy (2005), Oxford Dictionary of Scientific Quotations, Oxford, ISBN 0-19-858409-1.
Godfrey-Smith, Peter (2003), Theory and Reality: An introduction to the philosophy of science, University of Chicago Press, ISBN 0-226-30063-3
Taleb, Nassim Nicholas (2007), The Black Swan, Random House, ISBN 978-1-4000-6351-2 | Wikipedia/Hypothetico-deductive_model |
A natural phenomenon is an observable event which is not man-made. Examples include: sunrise, weather, fog, thunder, tornadoes; biological processes, decomposition, germination; physical processes, wave propagation, erosion; tidal flow, and natural disasters such as electromagnetic pulses, volcanic eruptions, hurricanes and earthquakes.
== History ==
Over many intervals of time, natural phenomena have been observed by a series of countless events as a feature created by nature.
== Physical phenomena ==
The act of:
Freezing
Boiling
Gravity
Magnetism
=== Gallery ===
== Chemical phenomena ==
Oxidation
Fire
Rusting
== Biological phenomena ==
Metabolism
Catabolism
Anabolism
Decomposition – by which organic substances are broken down into a much simpler form of matter
Fermentation – converts sugar to acids, gases and/or alcohol.
Growth
Birth
Death
Population decrease
=== Gallery ===
== Astronomical phenomena ==
Supernova
Gamma ray bursts
Quasars
Blazars
Pulsars
Cosmic microwave background radiation
== Geological phenomena ==
Mineralogic phenomena
Lithologic phenomena
Rock types
Igneous rock
Igneous formation processes
Sedimentary rock
Sedimentary formation processes (sedimentation)
Quicksand
Metamorphic rock
Endogenic phenomena
Plate tectonics
Continental drift
Earthquake
Oceanic trench
Phenomena associated with igneous activity
Geysers and hot springs
Bradyseism
Volcanic eruption
Earth's magnetic field
Exogenic phenomena
Slope phenomena
Slump
Landslide
Weathering phenomena
Erosion
Glacial and peri-glacial phenomena
Glaciation
Moraines
Hanging valleys
Atmospheric phenomena
Impact phenomena
Impact crater
Coupled endogenic-exogenic phenomena
Orogeny
Drainage development
Stream capture
=== Gallery ===
== Meteorological phenomena ==
Violent meteorological phenomena are called storms. Regular, cyclical phenomena include seasons and atmospheric circulation. climate change is often semi-regular.
=== Atmospheric optical phenomena ===
=== Oceanographic ===
Oceanographic phenomena include tsunamis, ocean currents and breaking waves.
==== Gallery ====
== See also ==
== References == | Wikipedia/Natural_phenomena |
Pseudoscience consists of statements, beliefs, or practices that claim to be both scientific and factual but are incompatible with the scientific method. Pseudoscience is often characterized by contradictory, exaggerated or unfalsifiable claims; reliance on confirmation bias rather than rigorous attempts at refutation; lack of openness to evaluation by other experts; absence of systematic practices when developing hypotheses; and continued adherence long after the pseudoscientific hypotheses have been experimentally discredited. It is not the same as junk science.
The demarcation between science and pseudoscience has scientific, philosophical, and political implications. Philosophers debate the nature of science and the general criteria for drawing the line between scientific theories and pseudoscientific beliefs, but there is widespread agreement "that creationism, astrology, homeopathy, Kirlian photography, dowsing, ufology, ancient astronaut theory, Holocaust denialism, Velikovskian catastrophism, and climate change denialism are pseudosciences." There are implications for health care, the use of expert testimony, and weighing environmental policies. Recent empirical research has shown that individuals who indulge in pseudoscientific beliefs generally show lower evidential criteria, meaning they often require significantly less evidence before coming to conclusions. This can be coined as a 'jump-to-conclusions' bias that can increase the spread of pseudoscientific beliefs. Addressing pseudoscience is part of science education and developing scientific literacy.
Pseudoscience can have dangerous effects. For example, pseudoscientific anti-vaccine activism and promotion of homeopathic remedies as alternative disease treatments can result in people forgoing important medical treatments with demonstrable health benefits, leading to ill-health and deaths. Furthermore, people who refuse legitimate medical treatments for contagious diseases may put others at risk. Pseudoscientific theories about racial and ethnic classifications have led to racism and genocide.
The term pseudoscience is often considered pejorative, particularly by its purveyors, because it suggests something is being presented as science inaccurately or even deceptively. Therefore, practitioners and advocates of pseudoscience frequently dispute the characterization.
== Etymology ==
The word pseudoscience is derived from the Greek root pseudo meaning "false" and the English word science, from the Latin word scientia, meaning "knowledge". Although the term has been in use since at least the late 18th century (e.g., in 1796 by James Pettit Andrews in reference to alchemy), the concept of pseudoscience as distinct from real or proper science seems to have become more widespread during the mid-19th century. Among the earliest uses of "pseudo-science" was in an 1844 article in the Northern Journal of Medicine, issue 387:
That opposite kind of innovation which pronounces what has been recognized as a branch of science, to have been a pseudo-science, composed merely of so-called facts, connected together by misapprehensions under the disguise of principles.
An earlier use of the term was in 1843 by the French physiologist François Magendie, that refers to phrenology as "a pseudo-science of the present day". During the 20th century, the word was used pejoratively to describe explanations of phenomena which were claimed to be scientific, but which were not in fact supported by reliable experimental evidence.
Dismissing the separate issue of intentional fraud – such as the Fox sisters' "rappings" in the 1850s – the pejorative label pseudoscience distinguishes the scientific 'us', at one extreme, from the pseudo-scientific 'them', at the other, and asserts that 'our' beliefs, practices, theories, etc., by contrast with that of 'the others', are scientific. There are four criteria: (a) the 'pseudoscientific' group asserts that its beliefs, practices, theories, etc., are 'scientific'; (b) the 'pseudoscientific' group claims that its allegedly established facts are justified true beliefs; (c) the 'pseudoscientific' group asserts that its 'established facts' have been justified by genuine, rigorous, scientific method; and (d) this assertion is false or deceptive: "it is not simply that subsequent evidence overturns established conclusions, but rather that the conclusions were never warranted in the first place"
From time to time, however, the usage of the word occurred in a more formal, technical manner in response to a perceived threat to individual and institutional security in a social and cultural setting.
== Relationship to science ==
Pseudoscience is differentiated from science because – although it usually claims to be science – pseudoscience does not adhere to scientific standards, such as the scientific method, falsifiability of claims, and Mertonian norms.
=== Scientific method ===
A number of basic principles are accepted by scientists as standards for determining whether a body of knowledge, method, or practice is scientific. Experimental results should be reproducible and verified by other researchers. These principles are intended to ensure experiments can be reproduced measurably given the same conditions, allowing further investigation to determine whether a hypothesis or theory related to given phenomena is valid and reliable. Standards require the scientific method to be applied throughout, and bias to be controlled for or eliminated through randomization, fair sampling procedures, blinding of studies, and other methods. All gathered data, including the experimental or environmental conditions, are expected to be documented for scrutiny and made available for peer review, allowing further experiments or studies to be conducted to confirm or falsify results. Statistical quantification of significance, confidence, and error are also important tools for the scientific method.
=== Falsifiability ===
During the mid-20th century, the philosopher Karl Popper emphasized the criterion of falsifiability to distinguish science from non-science. Statements, hypotheses, or theories have falsifiability or refutability if there is the inherent possibility that they can be proven false, that is, if it is possible to conceive of an observation or an argument that negates them. Popper used astrology and psychoanalysis as examples of pseudoscience and Einstein's theory of relativity as an example of science. He subdivided non-science into philosophical, mathematical, mythological, religious and metaphysical formulations on one hand, and pseudoscientific formulations on the other.
Another example which shows the distinct need for a claim to be falsifiable was stated in Carl Sagan's publication The Demon-Haunted World when he discusses an invisible dragon that he has in his garage. The point is made that there is no physical test to refute the claim of the presence of this dragon. Whatever test one thinks can be devised, there is a reason why it does not apply to the invisible dragon, so one can never prove that the initial claim is wrong. Sagan concludes; "Now, what's the difference between an invisible, incorporeal, floating dragon who spits heatless fire and no dragon at all?". He states that "your inability to invalidate my hypothesis is not at all the same thing as proving it true", once again explaining that even if such a claim were true, it would be outside the realm of scientific inquiry.
=== Mertonian norms ===
During 1942, Robert K. Merton identified a set of five "norms" which characterize real science. If any of the norms were violated, Merton considered the enterprise to be non-science. His norms were:
Originality: The tests and research done must present something new to the scientific community.
Detachment: The scientists' reasons for practicing this science must be simply for the expansion of their knowledge. The scientists should not have personal reasons to expect certain results.
Universality: No person should be able to more easily obtain the information of a test than another person. Social class, religion, ethnicity, or any other personal factors should not be factors in someone's ability to receive or perform a type of science.
Skepticism: Scientific facts must not be based on faith. One should always question every case and argument and constantly check for errors or invalid claims.
Public accessibility: Any scientific knowledge one obtains should be made available to everyone. The results of any research should be published and shared with the scientific community.
=== Refusal to acknowledge problems ===
In 1978, Paul Thagard proposed that pseudoscience is primarily distinguishable from science when it is less progressive than alternative theories over a long period of time, and its proponents fail to acknowledge or address problems with the theory. In 1983, Mario Bunge suggested the categories of "belief fields" and "research fields" to help distinguish between pseudoscience and science, where the former is primarily personal and subjective and the latter involves a certain systematic method. The 2018 book about scientific skepticism by Steven Novella, et al. The Skeptics' Guide to the Universe lists hostility to criticism as one of the major features of pseudoscience.
=== Criticism of the term ===
Larry Laudan has suggested pseudoscience has no scientific meaning and is mostly used to describe human emotions: "If we would stand up and be counted on the side of reason, we ought to drop terms like 'pseudo-science' and 'unscientific' from our vocabulary; they are just hollow phrases which do only emotive work for us". Likewise, Richard McNally states, "The term 'pseudoscience' has become little more than an inflammatory buzzword for quickly dismissing one's opponents in media sound-bites" and "When therapeutic entrepreneurs make claims on behalf of their interventions, we should not waste our time trying to determine whether their interventions qualify as pseudoscientific. Rather, we should ask them: How do you know that your intervention works? What is your evidence?"
=== Alternative definition ===
For philosophers Silvio Funtowicz and Jerome R. Ravetz "pseudo-science may be defined as one where the uncertainty of its inputs must be suppressed, lest they render its outputs totally indeterminate". The definition, in the book Uncertainty and Quality in Science for Policy, alludes to the loss of craft skills in handling quantitative information, and to the bad practice of achieving precision in prediction (inference) only at the expenses of ignoring uncertainty in the input which was used to formulate the prediction. This use of the term is common among practitioners of post-normal science. Understood in this way, pseudoscience can be fought using good practices to assess uncertainty in quantitative information, such as NUSAP and – in the case of mathematical modelling – sensitivity auditing.
== History ==
The history of pseudoscience is the study of pseudoscientific theories over time. A pseudoscience is a set of ideas that presents itself as science, while it does not meet the criteria to be properly called such.
Distinguishing between proper science and pseudoscience is sometimes difficult. One proposal for demarcation between the two is the falsification criterion, attributed most notably to the philosopher Karl Popper. In the history of science and the history of pseudoscience it can be especially difficult to separate the two, because some sciences developed from pseudosciences. An example of this transformation is the science of chemistry, which traces its origins to the pseudoscientific or pre-scientific study of alchemy.
The vast diversity in pseudosciences further complicates the history of science. Some modern pseudosciences, such as astrology and acupuncture, originated before the scientific era. Others developed as part of an ideology, such as Lysenkoism, or as a response to perceived threats to an ideology. Examples of this ideological process are creation science and intelligent design, which were developed in response to the scientific theory of evolution.
== Indicators of possible pseudoscience ==
A topic, practice, or body of knowledge might reasonably be termed pseudoscientific when it is presented as consistent with the norms of scientific research, but it demonstrably fails to meet these norms.
=== Use of vague, exaggerated or untestable claims ===
Assertion of scientific claims that are vague rather than precise, and that lack specific measurements.
Assertion of a claim with little or no explanatory power.
Failure to make use of operational definitions (i.e., publicly accessible definitions of the variables, terms, or objects of interest so that persons other than the definer can measure or test them independently) (See also: Reproducibility).
Failure to make reasonable use of the principle of parsimony, i.e., failing to seek an explanation that requires the fewest possible additional assumptions when multiple viable explanations are possible (See: Occam's razor).
Lack of boundary conditions: Most well-supported scientific theories possess well-articulated limitations under which the predicted phenomena do and do not apply.
Lack of effective controls in experimental design, such as the use of placebos and double-blinding.
Lack of understanding of basic and established principles of physics and engineering.
=== Improper collection of evidence ===
Assertions that do not allow the logical possibility that they can be shown to be false by observation or physical experiment (See also: Falsifiability).
Assertion of claims that a theory predicts something that it has not been shown to predict. Scientific claims that do not confer any predictive power are considered at best "conjectures", or at worst "pseudoscience" (e.g., ignoratio elenchi).
Assertion that claims which have not been proven false must therefore be true, and vice versa (See: Argument from ignorance).
Over-reliance on testimonial, anecdotal evidence, or personal experience: This evidence may be useful for the context of discovery (i.e., hypothesis generation), but should not be used in the context of justification (e.g., statistical hypothesis testing).
Use of myths and religious texts as if they were fact, or basing evidence on readings of such texts.
Use of concepts and scenarios from science fiction as if they were fact. This technique appeals to the familiarity that many people already have with science fiction tropes through the popular media.
Presentation of data that seems to support claims while suppressing or refusing to consider data that conflict with those claims. This is an example of selection bias or cherry picking, a distortion of evidence or data that arises from the way that the data are collected. It is sometimes referred to as the selection effect.
Repeating excessive or untested claims that have been previously published elsewhere, and promoting those claims as if they were facts; an accumulation of such uncritical secondary reports, which do not otherwise contribute their own empirical investigation, is called the Woozle effect.
Reversed burden of proof: science places the burden of proof on those making a claim, not on the critic. "Pseudoscientific" arguments may neglect this principle and demand that skeptics demonstrate beyond a reasonable doubt that a claim (e.g., an assertion regarding the efficacy of a novel therapeutic technique) is false. It is essentially impossible to prove a universal negative, so this tactic incorrectly places the burden of proof on the skeptic rather than on the claimant.
Appeals to holism as opposed to reductionism to dismiss negative findings: proponents of pseudoscientific claims, especially in organic medicine, alternative medicine, naturopathy and mental health, often resort to the "mantra of holism" .
=== Lack of openness to testing by other experts ===
Evasion of peer review before publicizing results (termed "science by press conference"): Some proponents of ideas that contradict accepted scientific theories avoid subjecting their ideas to peer review, sometimes on the grounds that peer review is biased towards established paradigms, and sometimes on the grounds that assertions cannot be evaluated adequately using standard scientific methods. By remaining insulated from the peer review process, these proponents forgo the opportunity of corrective feedback from informed colleagues.
Some agencies, institutions, and publications that fund scientific research require authors to share data so others can evaluate a paper independently. Failure to provide adequate information for other researchers to reproduce the claims contributes to a lack of openness.
Appealing to the need for secrecy or proprietary knowledge when an independent review of data or methodology is requested.
Substantive debate on the evidence by knowledgeable proponents of all viewpoints is not encouraged.
=== Absence of progress ===
Failure to progress towards additional evidence of its claims. Terence Hines has identified astrology as a subject that has changed very little in the past two millennia.
Lack of self-correction: scientific research programmes make mistakes, but they tend to reduce these errors over time. By contrast, ideas may be regarded as pseudoscientific because they have remained unaltered despite contradictory evidence. The work Scientists Confront Velikovsky (1976) Cornell University, also delves into these features in some detail, as does the work of Thomas Kuhn, e.g., The Structure of Scientific Revolutions (1962) which also discusses some of the items on the list of characteristics of pseudoscience.
Statistical significance of supporting experimental results does not improve over time and are usually close to the cutoff for statistical significance. Normally, experimental techniques improve or the experiments are repeated, and this gives ever stronger evidence. If statistical significance does not improve, this typically shows the experiments have just been repeated until a success occurs due to chance variations.
=== Personalization of issues ===
Tight social groups and authoritarian personality, suppression of dissent and groupthink can enhance the adoption of beliefs that have no rational basis. In attempting to confirm their beliefs, the group tends to identify their critics as enemies.
Assertion of a conspiracy on the part of the mainstream scientific community, government, or educational facilities to suppress pseudoscientific information. People who make these accusations often compare themselves to Galileo Galilei and his persecution by the Roman Catholic Church; this comparison is commonly known as the Galileo gambit.
Attacking the motives, character, morality, or competence of critics, rather than their arguments (see ad hominem)
=== Use of misleading language ===
Creating scientific-sounding terms to persuade non-experts to believe statements that may be false or meaningless: for example, a long-standing hoax refers to water by the rarely used formal name "dihydrogen monoxide" and describes it as the main constituent in most poisonous solutions to show how easily the general public can be misled.
Using established terms in idiosyncratic ways, thereby demonstrating unfamiliarity with mainstream work in the discipline.
== Prevalence of pseudoscientific beliefs ==
=== Countries ===
The Ministry of AYUSH in the Government of India is purposed with developing education, research and propagation of indigenous alternative medicine systems in India. The ministry has faced significant criticism for funding systems that lack biological plausibility and are either untested or conclusively proven as ineffective. Quality of research has been poor, and drugs have been launched without any rigorous pharmacological studies and meaningful clinical trials on Ayurveda or other alternative healthcare systems. There is no credible efficacy or scientific basis of any of these forms of treatment.
In his book The Demon-Haunted World, Carl Sagan discusses the government of China and the Chinese Communist Party's concern about Western pseudoscience developments and certain ancient Chinese practices in China. He sees pseudoscience occurring in the United States as part of a worldwide trend and suggests its causes, dangers, diagnosis and treatment may be universal.
A large percentage of the United States population lacks scientific literacy, not adequately understanding scientific principles and method. In the Journal of College Science Teaching, Art Hobson writes, "Pseudoscientific beliefs are surprisingly widespread in our culture even among public school science teachers and newspaper editors, and are closely related to scientific illiteracy." However, a 10,000-student study in the same journal concluded there was no strong correlation between science knowledge and belief in pseudoscience.
During 2006, the U.S. National Science Foundation (NSF) issued an executive summary of a paper on science and engineering which briefly discussed the prevalence of pseudoscience in modern times. It said, "belief in pseudoscience is widespread" and, referencing a Gallup Poll, stated that belief in the 10 commonly believed examples of paranormal phenomena listed in the poll were "pseudoscientific beliefs". The items were "extrasensory perception (ESP), that houses can be haunted, ghosts, telepathy, clairvoyance, astrology, that people can mentally communicate with the dead, witches, reincarnation, and channelling". Such beliefs in pseudoscience represent a lack of knowledge of how science works. The scientific community may attempt to communicate information about science out of concern for the public's susceptibility to unproven claims. The NSF stated that pseudoscientific beliefs in the U.S. became more widespread during the 1990s, peaked about 2001, and then decreased slightly since with pseudoscientific beliefs remaining common. According to the NSF report, there is a lack of knowledge of pseudoscientific issues in society and pseudoscientific practices are commonly followed. Surveys indicate about a third of adult Americans consider astrology to be scientific.
In Russia, in the late 20th and early 21st century, significant budgetary funds were spent on programs for the experimental study of "torsion fields", the extraction of energy from granite, the study of "cold nuclear fusion", and astrological and extrasensory "research" by the Ministry of Defense, the Ministry of Emergency Situations, the Ministry of Internal Affairs, and the State Duma (see Military Unit 10003). In 2006, Deputy Chairman of the Security Council of the Russian Federation Nikolai Spassky published an article in Rossiyskaya Gazeta, where among the priority areas for the development of the Russian energy sector, the task of extracting energy from a vacuum was in the first place. The Clean Water project was adopted as a United Russia party project; in the version submitted to the government, the program budget for 2010–2017 exceeded $14 billion.
=== Racism ===
There have been many connections between pseudoscientific writers and researchers and their anti-semitic, racist and neo-Nazi backgrounds. They often use pseudoscience to reinforce their beliefs. One of the most predominant pseudoscientific writers is Frank Collin, a self-proclaimed Nazi who goes by Frank Joseph in his writings. The majority of his works include the topics of Atlantis, extraterrestrial encounters, and Lemuria as well as other ancient civilizations, often with white supremacist undertones. For example, he posited that European peoples migrated to North America before Columbus, and that all Native American civilizations were initiated by descendants of white people.
The Alt-Right using pseudoscience to base their ideologies on is not a new issue. The entire foundation of anti-semitism is based on pseudoscience, or scientific racism. In an article from Newsweek by Sander Gilman, Gilman describes the pseudoscience community's anti-semitic views. "Jews as they appear in this world of pseudoscience are an invented group of ill, stupid or stupidly smart people who use science to their own nefarious ends. Other groups, too, are painted similarly in 'race science', as it used to call itself: African-Americans, the Irish, the Chinese and, well, any and all groups that you want to prove inferior to yourself". Neo-Nazis and white supremacist often try to support their claims with studies that "prove" that their claims are more than just harmful stereotypes. For example Bret Stephens published a column in The New York Times where he claimed that Ashkenazi Jews had the highest IQ among any ethnic group. However, the scientific methodology and conclusions reached by the article Stephens cited has been called into question repeatedly since its publication. It has been found that at least one of that study's authors has been identified by the Southern Poverty Law Center as a white nationalist.
The journal Nature has published a number of editorials in the last few years warning researchers about extremists looking to abuse their work, particularly population geneticists and those working with ancient DNA. One article in Nature, titled "Racism in Science: The Taint That Lingers" notes that early-twentieth-century eugenic pseudoscience has been used to influence public policy, such as the Immigration Act of 1924 in the United States, which sought to prevent immigration from Asia and parts of Europe.
== Explanations ==
In a 1981 report Singer and Benassi wrote that pseudoscientific beliefs have their origin from at least four sources:
Common cognitive errors from personal experience
Erroneous sensationalistic mass media coverage
Sociocultural factors
Poor or erroneous science education
A 1990 study by Eve and Dunn supported the findings of Singer and Benassi and found pseudoscientific belief being promoted by high school life science and biology teachers.
=== Psychology ===
The psychology of pseudoscience attempts to explore and analyze pseudoscientific thinking by means of thorough clarification on making the distinction of what is considered scientific vs. pseudoscientific. The human proclivity for seeking confirmation rather than refutation (confirmation bias), the tendency to hold comforting beliefs, and the tendency to overgeneralize have been proposed as reasons for pseudoscientific thinking. According to Beyerstein, humans are prone to associations based on resemblances only, and often prone to misattribution in cause-effect thinking.
Michael Shermer's theory of belief-dependent realism is driven by the idea that the brain is essentially a "belief engine" which scans data perceived by the senses and looks for patterns and meaning. There is also the tendency for the brain to create cognitive biases, as a result of inferences and assumptions made without logic and based on instinct – usually resulting in patterns in cognition. These tendencies of patternicity and agenticity are also driven "by a meta-bias called the bias blind spot, or the tendency to recognize the power of cognitive biases in other people but to be blind to their influence on our own beliefs".
Lindeman states that social motives (i.e., "to comprehend self and the world, to have a sense of control over outcomes, to belong, to find the world benevolent and to maintain one's self-esteem") are often "more easily" fulfilled by pseudoscience than by scientific information. Furthermore, pseudoscientific explanations are generally not analyzed rationally, but instead experientially. Operating within a different set of rules compared to rational thinking, experiential thinking regards an explanation as valid if the explanation is "personally functional, satisfying and sufficient", offering a description of the world that may be more personal than can be provided by science and reducing the amount of potential work involved in understanding complex events and outcomes.
Anyone searching for psychological help that is based in science should seek a licensed therapist whose techniques are not based in pseudoscience. Hupp and Santa Maria provide a complete explanation of what that person should look for.
=== Education and scientific literacy ===
There is a trend to believe in pseudoscience more than scientific evidence. Some people believe the prevalence of pseudoscientific beliefs is due to widespread scientific illiteracy. Individuals lacking scientific literacy are more susceptible to wishful thinking, since they are likely to turn to immediate gratification powered by System 1, our default operating system which requires little to no effort. This system encourages one to accept the conclusions they believe, and reject the ones they do not. Further analysis of complex pseudoscientific phenomena require System 2, which follows rules, compares objects along multiple dimensions and weighs options. These two systems have several other differences which are further discussed in the dual-process theory. The scientific and secular systems of morality and meaning are generally unsatisfying to most people. Humans are, by nature, a forward-minded species pursuing greater avenues of happiness and satisfaction, but we are all too frequently willing to grasp at unrealistic promises of a better life.
Psychology has much to discuss about pseudoscience thinking, as it is the illusory perceptions of causality and effectiveness of numerous individuals that needs to be illuminated. Research suggests that illusionary thinking happens in most people when exposed to certain circumstances such as reading a book, an advertisement or the testimony of others are the basis of pseudoscience beliefs. It is assumed that illusions are not unusual, and given the right conditions, illusions are able to occur systematically even in normal emotional situations. One of the things pseudoscience believers quibble most about is that academic science usually treats them as fools. Minimizing these illusions in the real world is not simple. To this aim, designing evidence-based educational programs can be effective to help people identify and reduce their own illusions.
== Boundaries with science ==
=== Classification ===
Philosophers classify types of knowledge. In English, the word science is used to indicate specifically the natural sciences and related fields, which are called the social sciences. Different philosophers of science may disagree on the exact limits – for example, is mathematics a formal science that is closer to the empirical ones, or is pure mathematics closer to the philosophical study of logic and therefore not a science? – but all agree that all of the ideas that are not scientific are non-scientific. The large category of non-science includes all matters outside the natural and social sciences, such as the study of history, metaphysics, religion, art, and the humanities. Dividing the category again, unscientific claims are a subset of the large category of non-scientific claims. This category specifically includes all matters that are directly opposed to good science. Un-science includes both "bad science" (such as an error made in a good-faith attempt at learning something about the natural world) and pseudoscience. Thus pseudoscience is a subset of un-science, and un-science, in turn, is subset of non-science.
Science is also distinguishable from revelation, theology, or spirituality in that it offers insight into the physical world obtained by empirical research and testing. The most notable disputes concern the evolution of living organisms, the idea of common descent, the geologic history of the Earth, the formation of the Solar System, and the origin of the universe. Systems of belief that derive from divine or inspired knowledge are not considered pseudoscience if they do not claim either to be scientific or to overturn well-established science. Moreover, some specific religious claims, such as the power of intercessory prayer to heal the sick, although they may be based on untestable beliefs, can be tested by the scientific method.
Some statements and common beliefs of popular science may not meet the criteria of science. "Pop" science may blur the divide between science and pseudoscience among the general public, and may also involve science fiction. Indeed, pop science is disseminated to, and can also easily emanate from, persons not accountable to scientific methodology and expert peer review.
If claims of a given field can be tested experimentally and standards are upheld, it is not pseudoscience, regardless of how odd, astonishing, or counterintuitive those claims are. If claims made are inconsistent with existing experimental results or established theory, but the method is sound, caution should be used, since science consists of testing hypotheses which may turn out to be false. In such a case, the work may be better described as ideas that are "not yet generally accepted". Protoscience is a term sometimes used to describe a hypothesis that has not yet been tested adequately by the scientific method, but which is otherwise consistent with existing science or which, where inconsistent, offers reasonable account of the inconsistency. It may also describe the transition from a body of practical knowledge into a scientific field.
=== Philosophy ===
Karl Popper stated it is insufficient to distinguish science from pseudoscience, or from metaphysics (such as the philosophical question of what existence means), by the criterion of rigorous adherence to the empirical method, which is essentially inductive, based on observation or experimentation. He proposed a method to distinguish between genuine empirical, nonempirical or even pseudoempirical methods. The latter case was exemplified by astrology, which appeals to observation and experimentation. While it had empirical evidence based on observation, on horoscopes and biographies, it crucially failed to use acceptable scientific standards. Popper proposed falsifiability as an important criterion in distinguishing science from pseudoscience.
To demonstrate this point, Popper gave two cases of human behavior and typical explanations from Sigmund Freud and Alfred Adler's theories: "that of a man who pushes a child into the water with the intention of drowning it; and that of a man who sacrifices his life in an attempt to save the child." From Freud's perspective, the first man would have suffered from psychological repression, probably originating from an Oedipus complex, whereas the second man had attained sublimation. From Adler's perspective, the first and second man suffered from feelings of inferiority and had to prove himself, which drove him to commit the crime or, in the second case, drove him to rescue the child. Popper was not able to find any counterexamples of human behavior in which the behavior could not be explained in the terms of Adler's or Freud's theory. Popper argued it was that the observation always fitted or confirmed the theory which, rather than being its strength, was actually its weakness. In contrast, Popper gave the example of Einstein's gravitational theory, which predicted "light must be attracted by heavy bodies (such as the Sun), precisely as material bodies were attracted." Following from this, stars closer to the Sun would appear to have moved a small distance away from the Sun, and away from each other. This prediction was particularly striking to Popper because it involved considerable risk. The brightness of the Sun prevented this effect from being observed under normal circumstances, so photographs had to be taken during an eclipse and compared to photographs taken at night. Popper states, "If observation shows that the predicted effect is definitely absent, then the theory is simply refuted." Popper summed up his criterion for the scientific status of a theory as depending on its falsifiability, refutability, or testability.
Paul R. Thagard used astrology as a case study to distinguish science from pseudoscience and proposed principles and criteria to delineate them. First, astrology has not progressed in that it has not been updated nor added any explanatory power since Ptolemy. Second, it has ignored outstanding problems such as the precession of equinoxes in astronomy. Third, alternative theories of personality and behavior have grown progressively to encompass explanations of phenomena which astrology statically attributes to heavenly forces. Fourth, astrologers have remained uninterested in furthering the theory to deal with outstanding problems or in critically evaluating the theory in relation to other theories. Thagard intended this criterion to be extended to areas other than astrology. He believed it would delineate as pseudoscientific such practices as witchcraft and pyramidology, while leaving physics, chemistry, astronomy, geoscience, biology, and archaeology in the realm of science.
In the philosophy and history of science, Imre Lakatos stresses the social and political importance of the demarcation problem, the normative methodological problem of distinguishing between science and pseudoscience. His distinctive historical analysis of scientific methodology based on research programmes suggests: "scientists regard the successful theoretical prediction of stunning novel facts – such as the return of Halley's comet or the gravitational bending of light rays – as what demarcates good scientific theories from pseudo-scientific and degenerate theories, and in spite of all scientific theories being forever confronted by 'an ocean of counterexamples'". Lakatos offers a "novel fallibilist analysis of the development of Newton's celestial dynamics, [his] favourite historical example of his methodology" and argues in light of this historical turn, that his account answers for certain inadequacies in those of Karl Popper and Thomas Kuhn. "Nonetheless, Lakatos did recognize the force of Kuhn's historical criticism of Popper – all important theories have been surrounded by an 'ocean of anomalies', which on a falsificationist view would require the rejection of the theory outright...Lakatos sought to reconcile the rationalism of Popperian falsificationism with what seemed to be its own refutation by history".
Many philosophers have tried to solve the problem of demarcation in the following terms: a statement constitutes knowledge if sufficiently many people believe it sufficiently strongly. But the history of thought shows us that many people were totally committed to absurd beliefs. If the strengths of beliefs were a hallmark of knowledge, we should have to rank some tales about demons, angels, devils, and of heaven and hell as knowledge. Scientists, on the other hand, are very sceptical even of their best theories. Newton's is the most powerful theory science has yet produced, but Newton himself never believed that bodies attract each other at a distance. So no degree of commitment to beliefs makes them knowledge. Indeed, the hallmark of scientific behaviour is a certain scepticism even towards one's most cherished theories. Blind commitment to a theory is not an intellectual virtue: it is an intellectual crime.
Thus a statement may be pseudoscientific even if it is eminently 'plausible' and everybody believes in it, and it may be scientifically valuable even if it is unbelievable and nobody believes in it. A theory may even be of supreme scientific value even if no one understands it, let alone believes in it.
The boundary between science and pseudoscience is disputed and difficult to determine analytically, even after more than a century of study by philosophers of science and scientists, and despite some basic agreements on the fundamentals of the scientific method. The concept of pseudoscience rests on an understanding that the scientific method has been misrepresented or misapplied with respect to a given theory, but many philosophers of science maintain that different kinds of methods are held as appropriate across different fields and different eras of human history. According to Lakatos, the typical descriptive unit of great scientific achievements is not an isolated hypothesis but "a powerful problem-solving machinery, which, with the help of sophisticated mathematical techniques, digests anomalies and even turns them into positive evidence".
To Popper, pseudoscience uses induction to generate theories, and only performs experiments to seek to verify them. To Popper, falsifiability is what determines the scientific status of a theory. Taking a historical approach, Kuhn observed that scientists did not follow Popper's rule, and might ignore falsifying data, unless overwhelming. To Kuhn, puzzle-solving within a paradigm is science. Lakatos attempted to resolve this debate, by suggesting history shows that science occurs in research programmes, competing according to how progressive they are. The leading idea of a programme could evolve, driven by its heuristic to make predictions that can be supported by evidence. Feyerabend claimed that Lakatos was selective in his examples, and the whole history of science shows there is no universal rule of scientific method, and imposing one on the scientific community impedes progress. Laudan maintained that the demarcation between science and non-science was a pseudo-problem, preferring to focus on the more general distinction between reliable and unreliable knowledge.
[Feyerabend] regards Lakatos's view as being closet anarchism disguised as methodological rationalism. Feyerabend's claim was not that standard methodological rules should never be obeyed, but rather that sometimes progress is made by abandoning them. In the absence of a generally accepted rule, there is a need for alternative methods of persuasion. According to Feyerabend, Galileo employed stylistic and rhetorical techniques to convince his reader, while he also wrote in Italian rather than Latin and directed his arguments to those already temperamentally inclined to accept them.
== Politics, health, and education ==
=== Political implications ===
The demarcation problem between science and pseudoscience brings up debate in the realms of science, philosophy and politics. Imre Lakatos, for instance, points out that the Communist Party of the Soviet Union at one point declared that Mendelian genetics was pseudoscientific and had its advocates, including well-established scientists such as Nikolai Vavilov, sent to a Gulag and that the "liberal Establishment of the West" denies freedom of speech to topics it regards as pseudoscience, particularly where they run up against social mores.
Something becomes pseudoscientific when science cannot be separated from ideology, scientists misrepresent scientific findings to promote or draw attention for publicity, when politicians, journalists and a nation's intellectual elite distort the facts of science for short-term political gain, or when powerful individuals of the public conflate causation and cofactors by clever wordplay. These ideas reduce the authority, value, integrity and independence of science in society.
=== Health and education implications ===
Distinguishing science from pseudoscience has practical implications in the case of health care, expert testimony, environmental policies, and science education. Treatments with a patina of scientific authority which have not actually been subjected to actual scientific testing may be ineffective, expensive and dangerous to patients and confuse health providers, insurers, government decision makers and the public as to what treatments are appropriate. Claims advanced by pseudoscience may result in government officials and educators making bad decisions in selecting curricula.
The extent to which students acquire a range of social and cognitive thinking skills related to the proper usage of science and technology determines whether they are scientifically literate. Education in the sciences encounters new dimensions with the changing landscape of science and technology, a fast-changing culture and a knowledge-driven era. A reinvention of the school science curriculum is one that shapes students to contend with its changing influence on human welfare. Scientific literacy, which allows a person to distinguish science from pseudosciences such as astrology, is among the attributes that enable students to adapt to the changing world. Its characteristics are embedded in a curriculum where students are engaged in resolving problems, conducting investigations, or developing projects.
Alan J. Friedman mentions why most scientists avoid educating about pseudoscience, including that paying undue attention to pseudoscience could dignify it.
On the other hand, Robert L. Park emphasizes how pseudoscience can be a threat to society and considers that scientists have a responsibility to teach how to distinguish science from pseudoscience.
Pseudosciences such as homeopathy, even if generally benign, are used by charlatans. This poses a serious issue because it enables incompetent practitioners to administer health care. True-believing zealots may pose a more serious threat than typical con men because of their delusion to homeopathy's ideology. Irrational health care is not harmless and it is careless to create patient confidence in pseudomedicine.
On 8 December 2016, journalist Michael V. LeVine pointed out the dangers posed by the Natural News website: "Snake-oil salesmen have pushed false cures since the dawn of medicine, and now websites like Natural News flood social media with dangerous anti-pharmaceutical, anti-vaccination and anti-GMO pseudoscience that puts millions at risk of contracting preventable illnesses."
The anti-vaccine movement has persuaded large numbers of parents not to vaccinate their children, citing pseudoscientific research that links childhood vaccines with the onset of autism. These include the study by Andrew Wakefield, which claimed that a combination of gastrointestinal disease and developmental regression, which are often seen in children with ASD, occurred within two weeks of receiving vaccines. The study was eventually retracted by its publisher, and Wakefield was stripped of his license to practice medicine.
Alkaline water is water that has a pH of higher than 7, purported to host numerous health benefits, with no empirical backing. A practitioner known as Robert O. Young who promoted alkaline water and an "Alkaline diet" was sent to jail for 3 years in 2017 for practicing medicine without a license.
== See also ==
Antiscience – Attitudes that reject science and the scientific method
Credulity – Willingness or ability to believe that a statement is true
Factoid – Invented claim or trivial fact
Fringe theory – Idea which departs from accepted scholarship in the field
List of topics characterized as pseudoscience
Magical thinking – Belief in the connection of unrelated events
Not even wrong – English phrase
Normative science – Aspect of science
Pseudo-scholarship – Pretended but not actual scholarship
Pseudolaw – Falsehood or trickery presented as law
Pseudomathematics – Work of mathematical cranks
Synergetic theory – Pseudoscientific theory.
== Notes ==
== References ==
== Bibliography ==
=== Works cited ===
=== Further reading === | Wikipedia/Pseudoscience |
The presence of women in science spans the earliest times of the history of science wherein they have made substantial contributions. Historians with an interest in gender and science have researched the scientific endeavors and accomplishments of women, the barriers they have faced, and the strategies implemented to have their work peer-reviewed and accepted in major scientific journals and other publications. The historical, critical, and sociological study of these issues has become an academic discipline in its own right.
The involvement of women in medicine occurred in several early Western civilizations, and the study of natural philosophy in ancient Greece was open to women. Women contributed to the proto-science of alchemy in the first or second centuries CE During the Middle Ages, religious convents were an important place of education for women, and some of these communities provided opportunities for women to contribute to scholarly research. The 11th century saw the emergence of the first universities; women were, for the most part, excluded from university education. Outside academia, botany was the science that benefitted most from the contributions of women in early modern times. The attitude toward educating women in medical fields appears to have been more liberal in Italy than elsewhere. The first known woman to earn a university chair in a scientific field of studies was eighteenth-century Italian scientist Laura Bassi.
Gender roles were largely deterministic in the eighteenth century and women made substantial advances in science. During the nineteenth century, women were excluded from most formal scientific education, but they began to be admitted into learned societies during this period. In the later nineteenth century, the rise of the women's college provided jobs for women scientists and opportunities for education. Marie Curie paved the way for scientists to study radioactive decay and discovered the elements radium and polonium. Working as a physicist and chemist, she conducted pioneering research on radioactive decay and was the first woman to receive a Nobel Prize in Physics and became the first person to receive a second Nobel Prize in Chemistry. Sixty women have been awarded the Nobel Prize between 1901 and 2022. Twenty-four women have been awarded the Nobel Prize in physics, chemistry, physiology or medicine.
== Cross-cultural perspectives ==
In the 1970s and 1980s, many books and articles about women scientists were appearing; virtually all of the published sources ignored women of color and women outside of Europe and North America. The formation of the Kovalevskaia Fund in 1985 and the Organization for Women in Science for the Developing World in 1993 gave more visibility to previously marginalized women scientists, but even today there is a dearth of information about current and historical women in science in developing countries. According to academic Ann Hibner Koblitz:
Most work on women scientists has focused on the personalities and scientific subcultures of Western Europe and North America, and historians of women in science have implicitly or explicitly assumed that the observations made for those
regions will hold true for the rest of the world.
Koblitz has said that these generalizations about women in science often do not hold up cross-culturally:
A scientific or technical field that might be considered 'unwomanly' in one country in a given period may enjoy the participation of many women in a different historical period or in another country. An example is engineering, which in many countries is considered the exclusive domain of men, especially in usually prestigious subfields such as electrical or mechanical engineering. There are exceptions to this, however. In the former Soviet Union all subspecialties of engineering had high percentages of women, and at the Universidad Nacional de Ingeniería of Nicaragua, women made up 70% of engineering students in 1990.
== Historical examples ==
=== Ancient history ===
The involvement of women in the field of medicine has been recorded in several early civilizations. An ancient Egyptian physician, Peseshet (c. 2600–2500 B.C.E.), described in an inscription as "lady overseer of the female physicians", is the earliest known female physician named in the history of science. Agamede was cited by Homer as a healer in ancient Greece before the Trojan War (c. 1194–1184 BCE). According to one late antique legend, Agnodice was the first female physician to practice legally in fourth century BCE Athens.
The study of natural philosophy in ancient Greece was open to women. Recorded examples include Aglaonike, who predicted eclipses; and Theano, mathematician and physician, who was a pupil (possibly also wife) of Pythagoras, and one of a school in Crotone founded by Pythagoras, which included many other women. A passage in Pollux speaks about those who invented the process of coining money mentioning Pheidon and Demodike from Cyme, wife of the Phrygian king, Midas, and daughter of King Agamemnon of Cyme. A daughter of a certain Agamemnon, king of Aeolian Cyme, married a Phrygian king called Midas. This link may have facilitated the Greeks "borrowing" their alphabet from the Phrygians because the Phrygian letter shapes are closest to the inscriptions from Aeolis.
During the period of the Babylonian civilization, around 1200 BCE, two perfumeresses named Tapputi-Belatekallim and -ninu (first half of her name unknown) were able to obtain the essences from plants by using extraction and distillation procedures. During the Egyptian dynasty, women were involved in applied chemistry, such as the making of beer and the preparation of medicinal compounds. Women have been recorded to have made major contributions to alchemy. Many of which lived in Alexandria around the 1st or 2nd centuries C.E., where the gnostic tradition led to female contributions being valued. The most famous of the women alchemist, Mary the Jewess, is credited with inventing several chemical instruments, including the double boiler (bain-marie); the improvement or creation of distillation equipment of that time. Such distillation equipment were called kerotakis (simple still) and the tribikos (a complex distillation device).
Hypatia of Alexandria (c. 350–415 CE), daughter of Theon of Alexandria, was a philosopher, mathematician, and astronomer. She is the earliest female mathematician about whom detailed information has survived. Hypatia is credited with writing several important commentaries on geometry, algebra and astronomy. Hypatia was the head of a philosophical school and taught many students. In 415 CE, she became entangled in a political dispute between Cyril, the bishop of Alexandria, and Orestes, the Roman governor, which resulted in a mob of Cyril's supporters stripping her, dismembering her, and burning the pieces of her body.
=== Medieval Europe ===
The early parts of the European Middle Ages, also known as the Dark Ages, were marked by the decline of the Roman Empire. The Latin West was left with great difficulties that affected the continent's intellectual production dramatically. Although nature was still seen as a system that could be comprehended in the light of reason, there was little innovative scientific inquiry. The Arabic world deserves credit for preserving scientific advancements. Arabic scholars produced original scholarly work and generated copies of manuscripts from Classical periods. During this period, Christianity underwent a period of resurgence, and Western civilization was bolstered as a result. This phenomenon was, in part, due to monasteries and nunneries that nurtured the skills of reading and writing, and the monks and nuns who collected and copied important writings produced by scholars of the past.
As it mentioned before, convents were an important place of education for women during this period, for the monasteries and nunneries encourage the skills of reading and writing, and some of these communities provided opportunities for women to contribute to scholarly research. An example is the German abbess Hildegard of Bingen (1098–1179 A.D), a famous philosopher and botanist, whose prolific writings include treatments of various scientific subjects, including medicine, botany and natural history (c. 1151–58). Another famous German abbess was Hroswitha of Gandersheim (935–1000 A.D.) that also helped encourage women to be intellectual. However, with the growth in number and power of nunneries, the all-male clerical hierarchy was not welcomed toward it, and thus it stirred up conflict by having backlash against women's advancement. That impacted many religious orders closed on women and disbanded their nunneries, and overall excluding women from the ability to learn to read and write. With that, the world of science became closed off to women, limiting women's influence in science.
Entering the 11th century, the first universities emerged. Women were, for the most part, excluded from university education. However, there were some exceptions. The Italian University of Bologna allowed women to attend lectures from its inception, in 1088.
The attitude to educating women in medical fields in Italy appears to have been more liberal than in other places. The physician, Trotula di Ruggiero, is supposed to have held a chair at the Medical School of Salerno in the 11th century, where she taught many noble Italian women, a group sometimes referred to as the "ladies of Salerno". Several influential texts on women's medicine, dealing with obstetrics and gynecology, among other topics, are also often attributed to Trotula.
Dorotea Bucca was another distinguished Italian physician. She held a chair of philosophy and medicine at the University of Bologna for over forty years from 1390. Other Italian women whose contributions in medicine have been recorded include Abella, Jacobina Félicie, Alessandra Giliani, Rebecca de Guarna, Margarita, Mercuriade (14th century), Constance Calenda, Calrice di Durisio (15th century), Constanza, Maria Incarnata and Thomasia de Mattio.
Despite the success of some women, cultural biases affecting their education and participation in science were prominent in the Middle Ages. For example, Saint Thomas Aquinas, a Christian scholar, wrote, referring to women, "She is mentally incapable of holding a position of authority."
=== Scientific Revolutions of 1600s and 1700s ===
Margaret Cavendish, a seventeenth-century aristocrat, took part in some of the most important scientific debates of that time. She was, however, not inducted into the English Royal Society, although she was once allowed to attend a meeting. She wrote a number of works on scientific matters, including Observations upon Experimental Philosophy (1666) and Grounds of Natural Philosophy. In these works she was especially critical of the growing belief that humans, through science, were the masters of nature. The 1666 work attempted to heighten female interest in science. The observations provided a critique of the experimental science of Bacon and criticized microscopes as imperfect machines.
Isabella Cortese, an Italian alchemist, is most known for her book I secreti della signora Isabella Cortese or The Secrets of Isabella Cortese. Cortese was able to manipulate nature in order to create several medicinal, alchemy and cosmetic "secrets" or experiments. Isabella's book of secrets belongs to a larger book of secrets that became extremely popular among the elite during the 16th century. Despite the low percentage of literate women during Cortese's era, the majority of alchemical and cosmetic "secrets" in the book of secrets were geared towards women. This included but was not limited to pregnancy, fertility, and childbirth.
Sophia Brahe, sister of Tycho Brahe, was a Danish Horticulturalist. Brahe was trained by her older brother in chemistry and horticulture but taught herself astronomy by studying books in German. Sophia visited her brother in the Uranienborg on numerous occasions and assisted on his project the De nova stella. Her observations lead to the discovery of the Supernova SN 1572 which helped refute the geocentric model of the universe.
Tycho Wrote the Urania Titani about his sister Sophia and her husband Erik. The Urania presented Sophia and the Titan represented Erik. Tycho used this poem in order to show his appreciation for his sister and all of her work.
In Germany, the tradition of female participation in craft production enabled some women to become involved in observational science, especially astronomy. Between 1650 and 1710, women were 14% of German astronomers. The most famous female astronomer in Germany was Maria Winkelmann. She was educated by her father and uncle and received training in astronomy from a nearby self-taught astronomer. Her chance to be a practising astronomer came when she married Gottfried Kirch, Prussia's foremost astronomer. She became his assistant at the astronomical observatory operated in Berlin by the Academy of Science. She made original contributions, including the discovery of a comet. When her husband died, Winkelmann applied for a position as assistant astronomer at the Berlin Academy – for which she had experience. As a woman – with no university degree – she was denied the post. Members of the Berlin Academy feared that they would establish a bad example by hiring a woman. "Mouths would gape", they said.
Winkelmann's problems with the Berlin Academy reflect the obstacles women faced in being accepted in scientific work, which was considered to be chiefly for men. No woman was invited to either the Royal Society of London nor the French Academy of Sciences until the twentieth century. Most people in the seventeenth century viewed a life devoted to any kind of scholarship as being at odds with the domestic duties women were expected to perform.
A founder of modern botany and zoology, the German Maria Sibylla Merian (1647–1717), spent her life investigating nature. When she was thirteen, Sibylla began growing caterpillars and studying their metamorphosis into butterflies. She kept a "Study Book" which recorded her investigations into natural philosophy. In her first publication, The New Book of Flowers, she used imagery to catalog the lives of plants and insects. After her husband died, and her brief stint of living in Siewert, she and her daughter journeyed to Paramaribo for two years to observe insects, birds, reptiles, and amphibians. She returned to Amsterdam and published The Metamorphosis of the Insects of Suriname, which "revealed to Europeans for the first time the astonishing diversity of the rain forest." She was a botanist and entomologist who was known for her artistic illustrations of plants and insects. Uncommon for that era, she traveled to South America and Surinam, where, assisted by her daughters, she illustrated the plant and animal life of those regions.
Overall, the Scientific Revolution did little to change people's ideas about the nature of women – more specifically – their capacity to contribute to science just as men do. According to Jackson Spielvogel, 'Male scientists used the new science to spread the view that women were by nature inferior and subordinate to men and suited to play a domestic role as nurturing mothers. The widespread distribution of books ensured the continuation of these ideas'.
=== Eighteenth century ===
Although women excelled in many scientific areas during the eighteenth century, they were discouraged from learning about plant reproduction. Carl Linnaeus' system of plant classification based on sexual characteristics drew attention to botanical licentiousness, and people feared that women would learn immoral lessons from nature's example. Women were often depicted as both innately emotional and incapable of objective reasoning, or as natural mothers reproducing a natural, moral society.
The eighteenth century was characterized by three divergent views towards women: that women were mentally and socially inferior to men, that they were equal but different, and that women were potentially equal in both mental ability and contribution to society. While individuals such as Jean-Jacques Rousseau believed women's roles were confined to motherhood and service to their male partners, the Enlightenment was a period in which women experienced expanded roles in the sciences.
The rise of salon culture in Europe brought philosophers and their conversation to an intimate setting where men and women met to discuss contemporary political, social, and scientific topics. While Jean-Jacques Rousseau attacked women-dominated salons as producing 'effeminate men' that stifled serious discourse, salons were characterized in this era by the mixing of the sexes.
Lady Mary Wortley Montagu defied convention by introducing smallpox inoculation through variolation to Western medicine after witnessing it during her travels in the Ottoman Empire. In 1718 Wortley Montague had her son inoculated and when in 1721 a smallpox epidemic struck England, she had her daughter inoculated. This was the first such operation done in Britain. She persuaded Caroline of Ansbach to test the treatment on prisoners. Princess Caroline subsequently inoculated her two daughters in 1722. Under a pseudonym, Wortley Montague published an article describing and advocating in favor of inoculation in September 1722.
After publicly defending forty nine theses in the Palazzo Pubblico, Laura Bassi was awarded a doctorate of philosophy in 1732 at the University of Bologna. Thus, Bassi became the second woman in the world to earn a philosophy doctorate after Elena Cornaro Piscopia in 1678, 54 years prior. She subsequently defended twelve additional theses at the Archiginnasio, the main building of the University of Bologna which allowed her to petition for a teaching position at the university. In 1732 the university granted Bassi's professorship in philosophy, making her a member of the Academy of the Sciences and the first woman to earn a professorship in physics at a university in Europe But the university held the value that women were to lead a private life and from 1746 to 1777 she gave only one formal dissertation per year ranging in topic from the problem of gravity to electricity. Because she could not lecture publicly at the university regularly, she began conducting private lessons and experiments from home in the year of 1749. However, due to her increase in responsibilities and public appearances on behalf of the university, Bassi was able to petition for regular pay increases, which in turn was used to pay for her advanced equipment. Bassi earned the highest salary paid by the University of Bologna of 1,200 lire. In 1776, at the age of 65, she was appointed to the chair in experimental physics by the Bologna Institute of Sciences with her husband as a teaching assistant.
According to Britannica, Maria Gaetana Agnesi is "considered to be the first woman in the Western world to have achieved a reputation in mathematics." She is credited as the first woman to write a mathematics handbook, the Instituzioni analitiche ad uso della gioventù italiana, (Analytical Institutions for the Use of Italian Youth). Published in 1748 it "was regarded as the best introduction extant to the works of Euler." The goal of this work was, according to Agnesi herself, to give a systematic illustration of the different results and theorems of infinitesimal calculus. In 1750 she became the second woman to be granted a professorship at a European university. Also appointed to the University of Bologna she never taught there.
The German Dorothea Erxleben was instructed in medicine by her father from an early age and Bassi's university professorship inspired Erxleben to fight for her right to practise medicine. In 1742 she published a tract arguing that women should be allowed to attend university. After being admitted to study by a dispensation of Frederick the Great, Erxleben received her M.D. from the University of Halle in 1754. She went on to analyse the obstacles preventing women from studying, among them housekeeping and children. She became the first female medical doctor in Germany.
In 1741–42 Charlotta Frölich became the first woman to be published by the Royal Swedish Academy of Sciences with three books in agricultural science. In 1748 Eva Ekeblad became the first woman inducted into that academy. In 1746 Ekeblad had written to the academy about her discoveries of how to make flour and alcohol out of potatoes. Potatoes had been introduced into Sweden in 1658 but had been cultivated only in the greenhouses of the aristocracy. Ekeblad's work turned potatoes into a staple food in Sweden, and increased the supply of wheat, rye and barley available for making bread, since potatoes could be used instead to make alcohol. This greatly improved the country's eating habits and reduced the frequency of famines. Ekeblad also discovered a method of bleaching cotton textile and yarn with soap in 1751, and of replacing the dangerous ingredients in cosmetics of the time by using potato flour in 1752.
Émilie du Châtelet, a close friend of Voltaire, was the first scientist to appreciate the significance of kinetic energy, as opposed to momentum. She repeated and described the importance of an experiment originally devised by Willem 's Gravesande showing the impact of falling objects is proportional not to their velocity, but to the velocity squared. This understanding is considered to have made a profound contribution to Newtonian mechanics. In 1749 she completed the French translation of Newton's Philosophiae Naturalis Principia Mathematica (the Principia), including her derivation of the notion of conservation of energy from its principles of mechanics. Published ten years after her death, her translation and commentary of the Principia contributed to the completion of the scientific revolution in France and to its acceptance in Europe.
Marie-Anne Pierrette Paulze and her husband Antoine Lavoisier rebuilt the field of chemistry, which had its roots in alchemy and at the time was a convoluted science dominated by George Stahl's theory of phlogiston. Paulze accompanied Lavoisier in his lab, making entries into lab notebooks and sketching diagrams of his experimental designs. The training she had received allowed her to accurately and precisely draw experimental apparatuses, which ultimately helped many of Lavoisier's contemporaries to understand his methods and results. Paulze translated various works about phlogiston into French. One of her most important translation was that of Richard Kirwan's Essay on Phlogiston and the Constitution of Acids, which she both translated and critiqued, adding footnotes as she went along and pointing out errors in the chemistry made throughout the paper. Paulze was instrumental in the 1789 publication of Lavoisier's Elementary Treatise on Chemistry, which presented a unified view of chemistry as a field. This work proved pivotal in the progression of chemistry, as it presented the idea of conservation of mass as well as a list of elements and a new system for chemical nomenclature. She also kept strict records of the procedures followed, lending validity to the findings Lavoisier published.
The astronomer Caroline Herschel was born in Hanover but moved to England where she acted as an assistant to her brother, William Herschel. Throughout her writings, she repeatedly made it clear that she desired to earn an independent wage and be able to support herself. When the crown began paying her for her assistance to her brother in 1787, she became the first woman to do so at a time when even men rarely received wages for scientific enterprises – to receive a salary for services to science. During 1786–97 she discovered eight comets, the first on 1 August 1786. She had unquestioned priority as discoverer of five of the comets and rediscovered Comet Encke in 1795. Five of her comets were published in Philosophical Transactions, a packet of paper bearing the superscription, "This is what I call the Bills and Receipts of my Comets" contains some data connected with the discovery of each of these objects. William was summoned to Windsor Castle to demonstrate Caroline's comet to the royal family. Caroline Herschel is often credited as the first woman to discover a comet; however, Maria Kirch discovered a comet in the early 1700s, but is often overlooked because at the time, the discovery was attributed to her husband, Gottfried Kirch.
=== Nineteenth century ===
==== Early nineteenth century ====
Science remained a largely amateur profession during the early part of the nineteenth century. Botany was considered a popular and fashionable activity, and one particularly suitable to women. In the later eighteenth and early nineteenth centuries, it was one of the most accessible areas of science for women in both England and North America.
However, as the nineteenth century progressed, botany and other sciences became increasingly professionalized, and women were increasingly excluded. Women's contributions were limited by their exclusion from most formal scientific education, but began to be recognized through their occasional admittance into learned societies during this period.
Scottish scientist Mary Fairfax Somerville carried out experiments in magnetism, presenting a paper entitled 'The Magnetic Properties of the Violet Rays of the Solar Spectrum' to the Royal Society in 1826, the second woman to do so. She also wrote several mathematical, astronomical, physical and geographical texts, and was a strong advocate for women's education. In 1835, she and Caroline Herschel were the first two women elected as Honorary Members of the Royal Astronomical Society.
English mathematician Ada, Lady Lovelace, a pupil of Somerville, corresponded with Charles Babbage about applications for his analytical engine. In her notes (1842–43) appended to her translation of Luigi Menabrea's article on the engine, she foresaw wide applications for it as a general-purpose computer, including composing music. She has been credited as writing the first computer program, though this has been disputed.
In Germany, institutes for "higher" education of women (Höhere Mädchenschule, in some regions called Lyzeum) were founded at the beginning of the century. The Deaconess Institute at Kaiserswerth was established in 1836 to instruct women in nursing. Elizabeth Fry visited the institute in 1840 and was inspired to found the London Institute of Nursing, and Florence Nightingale studied there in 1851.
In the US, Maria Mitchell made her name by discovering a comet in 1847, but also contributed calculations to the Nautical Almanac produced by the United States Naval Observatory. She became the first woman member of the American Academy of Arts and Sciences in 1848 and of the American Association for the Advancement of Science in 1850.
Other notable female scientists during this period include:
in Britain, Mary Anning (paleontologist), Anna Atkins (botanist), Janet Taylor (astronomer)
in France, Marie-Sophie Germain (mathematician), Jeanne Villepreux-Power (marine biologist)
==== Late 19th century in western Europe ====
The latter part of the 19th century saw a rise in educational opportunities for women. Schools aiming to provide education for girls similar to that afforded to boys were founded in the UK, including the North London Collegiate School (1850), Cheltenham Ladies' College (1853) and the Girls' Public Day School Trust schools (from 1872). The first UK women's university college, Girton, was founded in 1869, and others soon followed: Newnham (1871) and Somerville (1879).
The Crimean War (1854–1856) contributed to establishing nursing as a profession, making Florence Nightingale a household name. A public subscription allowed Nightingale to establish a school of nursing in London in 1860, and schools following her principles were established throughout the UK. Nightingale was also a pioneer in public health as well as a statistician.
James Barry became the first British woman to gain a medical qualification in 1812, passing as a man. Elizabeth Garrett Anderson was the first openly female Briton to qualify medically, in 1865. With Sophia Jex-Blake, American Elizabeth Blackwell and others, Garret Anderson founded the first UK medical school to train women, the London School of Medicine for Women, in 1874.
Annie Scott Dill Maunder was a pioneer in astronomical photography, especially of sunspots. A mathematics graduate of Girton College, Cambridge, she was first hired (in 1890) to be an assistant to Edward Walter Maunder, discoverer of the Maunder Minimum, the head of the solar department at Greenwich Observatory. They worked together to observe sunspots and to refine the techniques of solar photography. They married in 1895. Annie's mathematical skills made it possible to analyse the years of sunspot data that Maunder had been collecting at Greenwich. She also designed a small, portable wide-angle camera with a 1.5-inch-diameter (38 mm) lens. In 1898, the Maunders traveled to India, where Annie took the first photographs of the Sun's corona during a solar eclipse. By analysing the Cambridge records for both sunspots and geomagnetic storm, they were able to show that specific regions of the Sun's surface were the source of geomagnetic storms and that the Sun did not radiate its energy uniformly into space, as William Thomson, 1st Baron Kelvin had declared.
In Prussia women could go to university from 1894 and were allowed to receive a PhD. In 1908 all remaining restrictions for women were terminated.
Alphonse Rebière published a book in 1897, in France, entitled Les Femmes dans la science (Women in Science) which listed the contributions and publications of women in science.
Other notable female scientists during this period include:
in Britain, Hertha Marks Ayrton (mathematician, engineer), Margaret Huggins (astronomer), Beatrix Potter (mycologist)
in France, Dorothea Klumpke-Roberts (American-born astronomer)
in Germany, Amalie Dietrich (naturalist), Agnes Pockels (physicist)
in Russia and Sweden, Sofia Kovalevskaya (mathematician)
==== Late nineteenth-century Russians ====
In the second half of the 19th century, a large proportion of the most successful women in the STEM fields were Russians. Although many women received advanced training in medicine in the 1870s, in other fields women were barred and had to go to western Europe – mainly Switzerland – in order to pursue scientific studies. In her book about these "women of the [eighteen] sixties" (шестидесятницы), as they were called, Ann Hibner Koblitz writes:: 11
To a large extent, women's higher education in continental Europe was pioneered by this first generation of Russian women. They were the first students in Zürich, Heidelberg, Leipzig, and elsewhere. Theirs were the first doctorates in medicine, chemistry, mathematics, and biology.
Among the successful scientists were Nadezhda Suslova (1843–1918), the first woman in the world to obtain a medical doctorate fully equivalent to men's degrees; Maria Bokova-Sechenova (1839–1929), a pioneer of women's medical education who received two doctoral degrees, one in medicine in Zürich and one in physiology in Vienna; Iulia Lermontova (1846–1919), the first woman in the world to receive a doctoral degree in chemistry; the marine biologist Sofia Pereiaslavtseva (1849–1903), director of the Sevastopol Biological Station and winner of the Kessler Prize of the Russian Society of Natural Scientists; and the mathematician Sofia Kovalevskaia (1850–1891), the first woman in 19th century Europe to receive a doctorate in mathematics and the first to become a university professor in any field.
==== Late nineteenth century in the United States ====
In the later nineteenth century the rise of the women's college provided jobs for women scientists, and opportunities for education.
Women's colleges produced a disproportionate number of women who went on for PhDs in science.
Many coeducational colleges and universities also opened or started to admit women during this period; such institutions included just over 3000 women in 1875, by 1900 numbered almost 20,000.
An example is Elizabeth Blackwell, who became the first certified female doctor in the US when she graduated from Geneva Medical College in 1849. With her sister, Emily Blackwell, and Marie Zakrzewska, Blackwell founded the New York Infirmary for Women and Children in 1857 and the first women's medical college in 1868, providing both training and clinical experience for women doctors. She also published several books on medical education for women.
In 1876, Elizabeth Bragg became the first woman to graduate with a civil engineering degree in the United States, from the University of California, Berkeley.
=== Early twentieth century ===
==== Europe before World War II ====
Marie Skłodowska-Curie, the first woman to win a Nobel prize in 1903 (physics), went on to become a double Nobel prize winner in 1911, both for her work on radiation. She was the first person to win two Nobel prizes, a feat accomplished by only three others since then. She also was the first woman to teach at Sorbonne University in Paris.
Alice Perry is understood to be the first woman to graduate with a degree in civil engineering in the then United Kingdom of Great Britain and Ireland, in 1906 at Queen's College, Galway, Ireland.
Lise Meitner played a major role in the discovery of nuclear fission. As head of the physics section at the Kaiser Wilhelm Institute in Berlin she collaborated closely with the head of chemistry Otto Hahn on atomic physics until forced to flee Berlin in 1938. In 1939, in collaboration with her nephew Otto Frisch, Meitner derived the theoretical explanation for an experiment performed by Hahn and Fritz Strassman in Berlin, thereby demonstrating the occurrence of nuclear fission. The possibility that Fermi's bombardment of uranium with neutrons in 1934 had instead produced fission by breaking up the nucleus into lighter elements, had actually first been raised in print in 1934, by chemist Ida Noddack (co-discover of the element rhenium), but this suggestion had been ignored at the time, as no group made a concerted effort to find any of these light radioactive fission products.
Maria Montessori was the first woman in Southern Europe to qualify as a physician. She developed an interest in the diseases of children and believed in the necessity of educating those recognized to be ineducable. In the case of the latter she argued for the development of training for teachers along Froebelian lines and developed the principle that was also to inform her general educational program, which is the first the education of the senses, then the education of the intellect. Montessori introduced a teaching program that allowed defective children to read and write. She sought to teach skills not by having children repeatedly try it, but by developing exercises that prepare them.
Emmy Noether revolutionized abstract algebra, filled in gaps in relativity, and was responsible for a critical theorem about conserved quantities in physics. One notes that the Erlangen program attempted to identify invariants under a group of transformations. On 16 July 1918, before a scientific organization in Göttingen, Felix Klein read a paper written by Emmy Noether, because she was not allowed to present the paper herself. In particular, in what is referred to in physics as Noether's theorem, this paper identified the conditions under which the Poincaré group of transformations (now called a gauge group) for general relativity defines conservation laws. Noether's papers made the requirements for the conservation laws precise. Among mathematicians, Noether is best known for her fundamental contributions to abstract algebra, where the adjective noetherian is nowadays commonly used on many sorts of objects.
Mary Cartwright was a British mathematician who was the first to analyze a dynamical system with chaos. Inge Lehmann, a Danish seismologist, first suggested in 1936 that inside the Earth's molten core there may be a solid inner core. Women such as Margaret Fountaine continued to contribute detailed observations and illustrations in botany, entomology, and related observational fields. Joan Beauchamp Procter, an outstanding herpetologist, was the first woman Curator of Reptiles for the Zoological Society of London at London Zoo.
Florence Sabin was an American medical scientist. Sabin was the first woman faculty member at Johns Hopkins in 1902, and the first woman full-time professor there in 1917. Her scientific and research experience is notable. Sabin published over 100 scientific papers and multiple books.
==== United States before and during World War II ====
Women moved into science in significant numbers by 1900, helped by the women's colleges and by opportunities at some of the new universities. Margaret Rossiter's books Women Scientists in America: Struggles and Strategies to 1940 and Women Scientists in America: Before Affirmative Action 1940–1972 provide an overview of this period, stressing the opportunities women found in separate women's work in science.
In 1892, Ellen Swallow Richards called for the "christening of a new science" – "oekology" (ecology) in a Boston lecture. This new science included the study of "consumer nutrition" and environmental education. This interdisciplinary branch of science was later specialized into what is currently known as ecology, while the consumer nutrition focus split off and was eventually relabeled as home economics, which provided another avenue for women to study science. Richards helped to form the American Home Economics Association, which published a journal, the Journal of Home Economics, and hosted conferences. Home economics departments were formed at many colleges, especially at land grant institutions. In her work at MIT, Ellen Richards also introduced the first biology course in its history as well as the focus area of sanitary engineering.
Women also found opportunities in botany and embryology. In psychology, women earned doctorates but were encouraged to specialize in educational and child psychology and to take jobs in clinical settings, such as hospitals and social welfare agencies.
In 1901, Annie Jump Cannon first noticed that it was a star's temperature that was the principal distinguishing feature among different spectra. This led to re-ordering of the ABC types by temperature instead of hydrogen absorption-line strength. Due to Cannon's work, most of the then-existing classes of stars were thrown out as redundant. Afterward, astronomy was left with the seven primary classes recognized today, in order: O, B, A, F, G, K, M; that has since been extended.
Henrietta Swan Leavitt first published her study of variable stars in 1908. This discovery became known as the "period-luminosity relationship" of Cepheid variables. Our picture of the universe was changed forever, largely because of Leavitt's discovery.
The accomplishments of Edwin Hubble, renowned American astronomer, were made possible by Leavitt's groundbreaking research and Leavitt's Law. "If Henrietta Leavitt had provided the key to determine the size of the cosmos, then it was Edwin Powell Hubble who inserted it in the lock and provided the observations that allowed it to be turned", wrote David H. and Matthew D.H. Clark in their book Measuring the Cosmos.
Hubble often said that Leavitt deserved the Nobel for her work. Gösta Mittag-Leffler of the Swedish Academy of Sciences had begun paperwork on her nomination in 1924, only to learn that she had died of cancer three years earlier (the Nobel prize cannot be awarded posthumously).
In 1925, Harvard graduate student Cecilia Payne-Gaposchkin demonstrated for the first time from existing evidence on the spectra of stars that stars were made up almost exclusively of hydrogen and helium, one of the most fundamental theories in stellar astrophysics.
Canadian-born Maud Menten worked in the US and Germany. Her most famous work was on enzyme kinetics together with Leonor Michaelis, based on earlier findings of Victor Henri. This resulted in the Michaelis–Menten equations. Menten also invented the azo-dye coupling reaction for alkaline phosphatase, which is still used in histochemistry. She characterised bacterial toxins from B. paratyphosus, Streptococcus scarlatina and Salmonella ssp., and conducted the first electrophoretic separation of proteins in 1944. She worked on the properties of hemoglobin, regulation of blood sugar level, and kidney function.
World War II brought some new opportunities. The Office of Scientific Research and Development, under Vannevar Bush, began in 1941 to keep a registry of men and women trained in the sciences. Because there was a shortage of workers, some women were able to work in jobs they might not otherwise have accessed. Many women worked on the Manhattan Project or on scientific projects for the United States military services. Women who worked on the Manhattan Project included Leona Woods Marshall, Katharine Way, and Chien-Shiung Wu. It was actually Wu who confirmed Enrico Fermi's hypothesis through her earlier draft that Xe-135 impeded the B reactor from working. The adjustments made would quickly let the project resume its course.
Wu would later also confirm Albert Einstein's EPR Paradox in the first experimental corroboration, and prove the first violation of Parity and Charge Conjugate Symmetry, thereby laying the conceptual basis for the future Standard model of Particle Physics, and the rapid development of the new field.
Women in other disciplines looked for ways to apply their expertise to the war effort. Three nutritionists, Lydia J. Roberts, Hazel K. Stiebeling, and Helen S. Mitchell, developed the Recommended Dietary Allowance in 1941 to help military and civilian groups make plans for group feeding situations. The RDAs proved necessary, especially, once foods began to be rationed. Rachel Carson worked for the United States Bureau of Fisheries, writing brochures to encourage Americans to consume a wider variety of fish and seafood. She also contributed to research to assist the Navy in developing techniques and equipment for submarine detection.
Women in psychology formed the National Council of Women Psychologists, which organized projects related to the war effort. The NCWP elected Florence Laura Goodenough president. In the social sciences, several women contributed to the Japanese Evacuation and Resettlement Study, based at the University of California. This study was led by sociologist Dorothy Swaine Thomas, who directed the project and synthesized information from her informants, mostly graduate students in anthropology. These included Tamie Tsuchiyama, the only Japanese-American woman to contribute to the study, and Rosalie Hankey Wax.
In the United States Navy, female scientists conducted a wide range of research. Mary Sears, a planktonologist, researched military oceanographic techniques as head of the Hydgrographic Office's Oceanographic Unit. Florence van Straten, a chemist, worked as an aerological engineer. She studied the effects of weather on military combat. Grace Hopper, a mathematician, became one of the first computer programmers for the Mark I computer. Mina Spiegel Rees, also a mathematician, was the chief technical aide for the Applied Mathematics Panel of the National Defense Research Committee.
Gerty Cori was a biochemist who discovered the mechanism by which glycogen, a derivative of glucose, is transformed in the muscles to form lactic acid, and is later reformed as a way to store energy. For this discovery she and her colleagues were awarded the Nobel prize in 1947, making her the third woman and the first American woman to win a Nobel Prize in science. She was the first woman ever to be awarded the Nobel Prize in Physiology or Medicine. Cori is among several scientists whose works are commemorated by a U.S. postage stamp.
=== Late 20th century to early 21st century ===
Nina Byers notes that before 1976, fundamental contributions of women to physics were rarely acknowledged. Women worked unpaid or in positions lacking the status they deserved. That imbalance is gradually being redressed.
In the early 1980s, Margaret Rossiter presented two concepts for understanding the statistics behind women in science as well as the disadvantages women continued to suffer. She coined the terms "hierarchical segregation" and "territorial segregation." The former term describes the phenomenon in which the further one goes up the chain of command in the field, the smaller the presence of women. The latter describes the phenomenon in which women "cluster in scientific disciplines.": 33–34
A recent book titled Athena Unbound provides a life-course analysis (based on interviews and surveys) of women in science from early childhood interest, through university, graduate school and the academic workplace. The thesis of this book is that "Women face a special series of gender related barriers to entry and success in scientific careers that persist, despite recent advances".
The L'Oréal-UNESCO Awards for Women in Science were set up in 1998, with prizes alternating each year between the materials science and life sciences. One award is given for each geographical region of Africa and the Middle East, Asia-Pacific, Europe, Latin America and the Caribbean, and North America. By 2017, these awards had recognised almost 100 laureates from 30 countries. Two of the laureates have gone on to win the Nobel Prize, Ada Yonath (2008) and Elizabeth Blackburn (2009). Fifteen promising young researchers also receive an International Rising Talent fellowship each year within this programme.
==== Europe after World War II ====
South-African born physicist and radiobiologist Tikvah Alper(1909–95), working in the UK, developed many fundamental insights into biological mechanisms, including the (negative) discovery that the infective agent in scrapie could not be a virus or other eukaryotic structure.
French virologist Françoise Barré-Sinoussi performed some of the fundamental work in the identification of the human immunodeficiency virus (HIV) as the cause of AIDS, for which she shared the 2008 Nobel Prize in Physiology or Medicine.
In July 1967, Jocelyn Bell Burnell discovered evidence for the first known radio pulsar, which resulted in the 1974 Nobel Prize in Physics for her supervisor. She was president of the Institute of Physics from October 2008 until October 2010.
Astrophysicist Margaret Burbidge was a member of the B2FH group responsible for originating the theory of stellar nucleosynthesis, which explains how elements are formed in stars. She has held a number of prestigious posts, including the directorship of the Royal Greenwich Observatory.
Mary Cartwright was a mathematician and student of G. H. Hardy. Her work on nonlinear differential equations was influential in the field of dynamical systems.
Rosalind Franklin was a crystallographer, whose work helped to elucidate the fine structures of coal, graphite, DNA and viruses. In 1953, the work she did on DNA allowed Watson and Crick to conceive their model of the structure of DNA. Her photograph of DNA gave Watson and Crick a basis for their DNA research, and they were awarded the Nobel Prize without giving due credit to Franklin, who had died of cancer in 1958.
Jane Goodall is a British primatologist considered to be the world's foremost expert on chimpanzees and is best known for her over 55-year study of social and family interactions of wild chimpanzees. She is the founder of the Jane Goodall Institute and the Roots & Shoots programme.
Dorothy Hodgkin analyzed the molecular structure of complex chemicals by studying diffraction patterns caused by passing X-rays through crystals. She won the 1964 Nobel prize for chemistry for discovering the structure of vitamin B12, becoming the third woman to win the prize for chemistry.
Irène Joliot-Curie, daughter of Marie Curie, won the 1935 Nobel Prize for chemistry with her husband Frédéric Joliot for their work in radioactive isotopes leading to nuclear fission. This made the Curies the family with the most Nobel laureates to date.
Palaeoanthropologist Mary Leakey discovered the first skull of a fossil ape on Rusinga Island and also a noted robust Australopithecine.
Italian neurologist Rita Levi-Montalcini received the 1986 Nobel Prize in Physiology or Medicine for the discovery of Nerve growth factor (NGF). Her work allowed for a further potential understanding of different diseases such as tumors, delayed healing, malformations, and others. This research led to her winning the Nobel Prize for Physiology or Medicine alongside Stanley Cohen in 1986. While making advancements in medicine and science, Rita Levi-Montalcini was also active politically throughout her life. She was appointed a Senator for Life in the Italian Senate in 2001 and is the oldest Nobel laureate ever to have lived.
Zoologist Anne McLaren conducted studied in genetics which led to advances in in vitro fertilization. She became the first female officer of the Royal Society in 331 years.
Christiane Nüsslein-Volhard received the Nobel Prize in Physiology or Medicine in 1995 for research on the genetic control of embryonic development. She also started the Christiane Nüsslein-Volhard Foundation (Christiane Nüsslein-Volhard Stiftung), to aid promising young female German scientists with children.
Bertha Swirles was a theoretical physicist who made a number of contributions to early quantum theory. She co-authored the well-known textbook Methods of Mathematical Physics with her husband Sir Harold Jeffreys.
==== United States after World War II ====
Kay McNulty, Betty Jennings, Betty Snyder, Marlyn Wescoff, Fran Bilas and Ruth Lichterman were six of the original programmers for the ENIAC, the first general purpose electronic computer.
Linda B. Buck is a neurobiologist who was awarded the 2004 Nobel Prize in Physiology or Medicine along with Richard Axel for their work on olfactory receptors.
Rachel Carson was a marine biologist from the United States. She is credited with being the founder of the environmental movement. The biologist and activist published Silent Spring, a work on the dangers of pesticides, in 1962. The publishing of her environmental science book led to the questioning of usage of harmful pesticides and other chemicals in agricultural settings. This led to a campaign to attempt to ultimately discredit Carson. However, the federal government called for a review of DDT which concluded with DDT being banned. Carson later died from cancer in 1964 at 57 years old.
Eugenie Clark, popularly known as The Shark Lady, was an American ichthyologist known for her research on poisonous fish of the tropical seas and on the behavior of sharks.
Ann Druyan is an American writer, lecturer and producer specializing in cosmology and popular science. Druyan has credited her knowledge of science to the 20 years she spent studying with her late husband, Carl Sagan, rather than formal academic training. She was responsible for the selection of music on the Voyager Golden Record for the Voyager 1 and Voyager 2 exploratory missions. Druyan also sponsored the Cosmos 1 spacecraft.
Gertrude B. Elion was an American biochemist and pharmacologist, awarded the Nobel Prize in Physiology or Medicine in 1988 for her work on the differences in biochemistry between normal human cells and pathogens.
Sandra Moore Faber, with Robert Jackson, discovered the Faber–Jackson relation between luminosity and stellar dispersion velocity in elliptical galaxies. She also headed the team which discovered the Great Attractor, a large concentration of mass which is pulling a number of nearby galaxies in its direction.
Zoologist Dian Fossey worked with gorillas in Africa from 1967 until her murder in 1985.
Astronomer Andrea Ghez received a MacArthur "genius grant" in 2008 for her work in surmounting the limitations of earthbound telescopes.
Maria Goeppert Mayer was the second female Nobel Prize winner in Physics, for proposing the nuclear shell model of the atomic nucleus. Earlier in her career, she had worked in unofficial or volunteer positions at the university where her husband was a professor. Goeppert Mayer is one of several scientists whose works are commemorated by a U.S. postage stamp.
Sulamith Low Goldhaber and her husband Gerson Goldhaber formed a research team on the K meson and other high-energy particles in the 1950s.
Carol Greider and the Australian born Elizabeth Blackburn, along with Jack W. Szostak, received the 2009 Nobel Prize in Physiology or Medicine for the discovery of how chromosomes are protected by telomeres and the enzyme telomerase.
Rear Admiral Grace Murray Hopper developed the first computer compiler while working for the Eckert Mauchly Computer Corporation, released in 1952.
Deborah S. Jin's team at JILA, in Boulder, Colorado, in 2003 produced the first fermionic condensate, a new state of matter.
Stephanie Kwolek, a researcher at DuPont, invented poly-paraphenylene terephthalamide – better known as Kevlar.
Lynn Margulis is a biologist best known for her work on endosymbiotic theory, which is now generally accepted for how certain organelles were formed.
Barbara McClintock's studies of maize genetics demonstrated genetic transposition in the 1940s and 1950s. Before then, McClintock obtained her PhD from Cornell University in 1927. Her discovery of transposition provided a greater understanding of mobile loci within chromosomes and the ability for genetics to be fluid. She dedicated her life to her research, and she was awarded the Nobel Prize in Physiology or Medicine in 1983. McClintock was the first American woman to receive a Nobel Prize that was not shared by anyone else. McClintock is one of several scientists whose works are commemorated by a U.S. postage stamp.
Nita Ahuja is a renowned surgeon-scientist known for her work on CIMP in cancer, she is currently the Chief of surgical oncology at Johns Hopkins Hospital. First woman ever to be the Chief of this prestigious department.
Carolyn Porco is a planetary scientist best known for her work on the Voyager program and the Cassini–Huygens mission to Saturn. She is also known for her popularization of science, in particular space exploration.
Physicist Helen Quinn, with Roberto Peccei, postulated Peccei-Quinn symmetry. One consequence is a particle known as the axion, a candidate for the dark matter that pervades the universe. Quinn was the first woman to receive the Dirac Medal by the International Centre for Theoretical Physics (ICTP) and the first to receive the Oskar Klein Medal.
Lisa Randall is a theoretical physicist and cosmologist, best known for her work on the Randall–Sundrum model. She was the first tenured female physics professor at Princeton University.
Sally Ride was an astrophysicist and the first American woman, and then-youngest American, to travel to outer space. Ride wrote or co-wrote several books on space aimed at children, with the goal of encouraging them to study science. Ride participated in the Gravity Probe B (GP-B) project, which provided more evidence that the predictions of Albert Einstein's general theory of relativity are correct.
Through her observations of galaxy rotation curves, astronomer Vera Rubin discovered the Galaxy rotation problem, now taken to be one of the key pieces of evidence for the existence of dark matter. She was the first female allowed to observe at the Palomar Observatory.
Sara Seager is a Canadian-American astronomer who is currently a professor at the Massachusetts Institute of Technology and known for her work on extrasolar planets.
Astronomer Jill Tarter is best known for her work on the search for extraterrestrial intelligence. Tarter was named one of the 100 most influential people in the world by Time Magazine in 2004. She is the former director of SETI.
Rosalyn Yalow was the co-winner of the 1977 Nobel Prize in Physiology or Medicine (together with Roger Guillemin and Andrew Schally) for development of the radioimmunoassay (RIA) technique.
==== Australia after World War II ====
Amanda Barnard, an Australia-based theoretical physicist specializing in nanomaterials, winner of the Malcolm McIntosh Prize for Physical Scientist of the Year.
Isobel Bennett, was one of the first women to go to Macquarie Island with the Australian National Antarctic Research Expeditions (ANARE). She is one of Australia's best known marine biologists.
Dorothy Hill, an Australian geologist who became the first female Professor at an Australian university.
Ruby Payne-Scott, was an Australian who was an early leader in the fields of radio astronomy and radiophysics. She was one of the first radio astronomers and the first woman in the field.
Penny Sackett, an astronomer who became the first female Chief Scientist of Australia in 2008. She is a US-born Australian citizen.
Fiona Stanley, winner of the 2003 Australian of the Year award, is an epidemiologist noted for her research into child and maternal health, birth disorders, and her work in the public health field.
Michelle Simmons, winner of the 2018 Australian of the Year award, is a quantum physicist known for her research and leadership on atomic-scale silicon quantum devices.
==== Israel after World War II ====
Ada Yonath, the first woman from the Middle East to win a Nobel prize in the sciences, was awarded the Nobel Prize in Chemistry in 2009 for her studies on the structure and function of the ribosome.
Latin America
Maria Nieves Garcia-Casal, the first scientist and nutritionist woman from Latin America to lead the Latin America Society of Nutrition.
Angela Restrepo Moreno is a microbiologist from Colombia. She first gained interest in tiny organisms when she had the opportunity to view them through a microscope that belonged to her grandfather. While Restrepo has a variety of research, her main area of research is fungi and their causes of diseases. Her work led her to develop research on a disease caused by fungi that has only been diagnosed in Latin America but was originally found in Brazil: Paracoccidioidomycosis. Research groups also developed by Restrepo have begun studying two routes: the relationship between humans, fungi, and the environment and also how the cells within the fungi work.
Along with her research, Restrepo co-founded a non-profit that is devoted to scientific research named Corporation for Biological Research (CIB). Angela Restrepo Moreno was awarded the SCOPUS Prize in 2007 for her numerous publications. She currently resides in Colombia and continues her research.
Susana López Charretón was born in Mexico City, Mexico in 1957. She is a virologist whose area of study focused on the rotavirus. When she initially began studying rotavirus, it had only been discovered four years earlier. Charretón's main job was to study how the virus entered cells and its ways of multiplying. Because of her, and several others, work other scientists were able to learn about more details of the virus. Now, her research focuses on the virus's ability to recognize the cells it infects. Along with her husband, Charretón was awarded the Carlos J. Finlay Prize for Microbiology in 2001. She also received the Loreal-UNESCO prize titled "Woman in Science" in 2012. Charretón has also received several other awards for her research.
Liliana Quintanar Vera is a Mexican chemist. Currently a researcher at the Department of Chemistry of the Center of Investigation and Advanced Studies, Vera's research currently focuses on neurodegenerative diseases like Parkinson's, Alzheimer's, and prion disease and also on degenerative diseases like diabetes and cataracts. For this research she focused on how copper interacts with the proteins of the neurodegenerative diseases mentioned before.
Liliana's awards include the Mexican Academy of Sciences Research Prize for Science in 2017, the Marcos Moshinsky Chair award in 2016, the Fulbright Scholarship in 2014, and the L'Oréal-UNESCO For Women in Science Award in 2007.
== Nobel laureates ==
The Nobel Prize and Prize in Economic Sciences have been awarded to women 61 times between 1901 and 2022. One woman, Marie Sklodowska-Curie, has been honored twice, with the 1903 Nobel Prize in Physics and the 1911 Nobel Prize in Chemistry. This means that 60 women in total have been awarded the Nobel Prize between 1901 and 2022. 25 women have been awarded the Nobel Prize in physics, chemistry, physiology or medicine.
=== Chemistry ===
2022 – Carolyn Bertozzi
2020 – Emmanuelle Charpentier, Jennifer Doudna
2018 – Frances Arnold
2009 – Ada E. Yonath
1964 – Dorothy Crowfoot Hodgkin
1935 – Irène Joliot-Curie
1911 – Marie Sklodowska-Curie
=== Physics ===
2023 – Anne L'Huillier
2020 – Andrea Ghez
2018 – Donna Strickland
1963 – Maria Goeppert-Mayer
1903 – Marie Sklodowska-Curie
=== Physiology or Medicine ===
2023 – Katalin Karikó
2015 – Youyou Tu
2014 – May-Britt Moser
2009 – Elizabeth H. Blackburn
2009 – Carol W. Greider
2008 – Françoise Barré-Sinoussi
2004 – Linda B. Buck
1995 – Christiane Nüsslein-Volhard
1988 – Gertrude B. Elion
1986 – Rita Levi-Montalcini
1983 – Barbara McClintock
1977 – Rosalyn Yalow
1947 – Gerty Cori
== Fields Medal ==
2014 – Maryam Mirzakhani (1977–2017), the first woman to have won the prize, was an Iranian mathematician and a professor of mathematics at Stanford University.
2022 – Maryna Viazovska
== Statistics ==
Statistics are used to indicate disadvantages faced by women in science, and also to track positive changes of employment opportunities and incomes for women in science.: 33
=== Situation in the 1990s ===
Women appear to do less well than men (in terms of degree, rank, and salary) in the fields that have been traditionally dominated by women, such as nursing. In 1991 women attributed 91% of the PhDs in nursing, and men held 4% of full professorships in nursing. In the field of psychology, where women earn the majority of PhDs, women do not fill the majority of high rank positions in that field.
Women's lower salaries in the scientific community are also reflected in statistics. According to the data provided in 1993, the median salaries of female scientists and engineers with doctoral degrees were 20% less than men.: 35 This data can be explained as there was less participation of women in high rank scientific fields/positions and a female majority in low-paid fields/positions. However, even with men and women in the same scientific community field, women are typically paid 15–17% less than men. In addition to the gender gap, there were also salary differences between ethnicity: African-American women with more years of experiences earn 3.4% less than European-American women with similar skills, while Asian women engineers out-earn both Africans and Europeans.
Women are also under-represented in the sciences as compared to their numbers in the overall working population. Within 11% of African-American women in the workforce, 3% are employed as scientists and engineers. Hispanics made up 8% of the total workers in the US, 3% of that number are scientists and engineers. Native Americans participation cannot be statistically measured.
Women tend to earn less than men in almost all industries, including government and academia. Women are less likely to be hired in highest-paid positions. The data showing the differences in salaries, ranks, and overall success between the genders is often claimed to be a result of women's lack of professional experience. The rate of women's professional achievement is increasing. In 1996, the salaries for women in professional fields increased from 85% to 95% relative to men with similar skills and jobs. Young women between the age of 27 and 33 earned 98%, nearly as much as their male peers. In the total workforce of the United States, women earn 74% as much as their male counterparts (in the 1970s they made 59% as much as their male counterparts).: 33–37
Claudia Goldin, Harvard concludes in A Grand Gender Convergence: Its Last Chapter – "The gender gap in pay would be considerably reduced and might vanish altogether if firms did not have an incentive to disproportionately reward individuals who labored long hours and worked particular hours."
Research on women's participation in the "hard" sciences such as physics and computer science speaks of the "leaky pipeline" model, in which the proportion of women "on track" to potentially becoming top scientists fall off at every step of the way, from getting interested in science and maths in elementary school, through doctorate, postdoctoral, and career steps. The leaky pipeline also applies in other fields. In biology, for instance, women in the United States have been getting Masters degrees in the same numbers as men for two decades, yet fewer women get PhDs; and the numbers of women principal investigators have not risen.
What may be the cause of this "leaky pipeline" of women in the sciences? It is important to look at factors outside of academia that are occurring in women's lives at the same time they are pursuing their continued education and career search. The most outstanding factor that is occurring at this crucial time is family formation. As women are continuing their academic careers, they are also stepping into their new role as a wife and mother. These traditionally require at large time commitment and presence outside work. These new commitments do not fare well for the person looking to attain tenure. That is why women entering the family formation period of their life are 35% less likely to pursue tenure positions after receiving their PhD's than their male counterparts.
In the UK, women occupied over half the places in science-related higher education courses (science, medicine, maths, computer science and engineering) in 2004–05. However, gender differences varied from subject to subject: women substantially outnumbered men in biology and medicine, especially nursing, while men predominated in maths, physical sciences, computer science and engineering.
In the US, women with science or engineering doctoral degrees were predominantly employed in the education sector in 2001, with substantially fewer employed in business or industry than men. According to salary figures reported in 1991, women earn anywhere between 83.6 percent to 87.5 percent that of a man's salary. An even greater disparity between men and women is the ongoing trend that women scientists with more experience are not as well-compensated as their male counterparts. The salary of a male engineer continues to experience growth as he gains experience whereas the female engineer sees her salary reach a plateau.
Women, in the United States and many European countries, who succeed in science tend to be graduates of single-sex schools.: Chapter 3 Women earn 54% of all bachelor's degrees in the United States and 50% of those are in science. 9% of US physicists are women.: Chapter 2
=== Overview of situation in 2013 ===
In 2013, women accounted for 53% of the world's graduates at the bachelor's and master's level and 43% of successful PhD candidates but just 28% of researchers. Women graduates are consistently highly represented in the life sciences, often at over 50%. However, their representation in the other fields is inconsistent. In North America and much of Europe, few women graduate in physics, mathematics and computer science but, in other regions, the proportion of women may be close to parity in physics or mathematics. In engineering and computer sciences, women consistently trail men, a situation that is particularly acute in many high-income countries.
==== In decision-making ====
As of 2015, each step up the ladder of the scientific research system saw a drop in female participation until, at the highest echelons of scientific research and decision-making, there were very few women left. In 2015, the EU Commissioner for Research, Science and Innovation Carlos Moedas called attention to this phenomenon, adding that the majority of entrepreneurs in science and engineering tended to be men. In 2013, the German government coalition agreement introduced a 30% quota for women on company boards of directors.
In 2010, women made up 14% of university chancellors and vice-chancellors at Brazilian public universities and 17% of those in South Africa in 2011. As of 2015, in Argentina, women made up 16% of directors and vice-directors of national research centres and, in Mexico, 10% of directors of scientific research institutes at the National Autonomous University of Mexico. In the US, numbers are slightly higher at 23%. In the EU, less than 16% of tertiary institutions were headed by a woman in 2010 and just 10% of universities. In 2011, at the main tertiary institution for the English-speaking Caribbean, the University of the West Indies, women represented 51% of lecturers but only 32% of senior lecturers and 26% of full professors . A 2018 review of the Royal Society of Britain by historians Aileen Fyfe and Camilla Mørk Røstvik produced similarly low numbers, with women accounting for more than 25% of members in only a handful of countries, including Cuba, Panama and South Africa. As of 2015, the figure for Indonesia was 17%.
==== Women in life sciences ====
In life sciences, women researchers have achieved parity (45–55% of researchers) in many countries. In some, the balance even now tips in their favour. Six out of ten researchers are women in both medical and agricultural sciences in Belarus and New Zealand, for instance. More than two-thirds of researchers in medical sciences are women in El Salvador, Estonia, Kazakhstan, Latvia, the Philippines, Tajikistan, Ukraine and Venezuela.
There has been a steady increase in female graduates in agricultural sciences since the turn of the century. In sub-Saharan Africa, for instance, numbers of female graduates in agricultural science have been increasing steadily, with eight countries reporting a share of women graduates of 40% or more: Lesotho, Madagascar, Mozambique, Namibia, Sierra Leone, South Africa, Swaziland and Zimbabwe. The reasons for this surge are unclear, although one explanation may lie in the growing emphasis on national food security and the food industry. Another possible explanation is that women are highly represented in biotechnology. For example, in South Africa, women were underrepresented in engineering (16%) in 2004 and in 'natural scientific professions' (16%) in 2006 but made up 52% of employees working in biotechnology-related companies.
Women play an increasing role in environmental sciences and conservation biology. In fact, women played a foremost role in the development of these disciplines. Silent Spring by Rachel Carson proved an important impetus to the conservation movement and the later banning of chemical pesticides. Women played an important role in conservation biology including the famous work of Dian Fossey, who published the famous Gorillas in the Mist and Jane Goodall who studied primates in East Africa. Today women make up an increasing proportion of roles in the active conservation sector. A recent survey of those working in the Wildlife Trusts in the U.K., the leading conservation organisation in England, found that there are nearly as many women as men in practical conservation roles.
==== In engineering and related fields ====
Women are consistently underrepresented in engineering and related fields. In Israel, for instance, where 28% of senior academic staff are women, there are proportionately many fewer in engineering (14%), physical sciences (11%), mathematics and computer sciences (10%) but dominate education (52%) and paramedical occupations (63%). In Japan and the Republic of Korea, women represent just 5% and 10% of engineers.
For women who are pursuing STEM major careers, these individuals often face gender disparities in the work field, especially in regards to science and engineering. It has become more common for women to pursue undergraduate degrees in science, but are continuously discredited in salary rates and higher ranking positions. For example, men show a greater likelihood of being selected for an employment position than a woman.
In Europe and North America, the number of female graduates in engineering, physics, mathematics and computer science is generally low. Women make up just 19% of engineers in Canada, Germany and the US and 22% in Finland, for example. However, 50% of engineering graduates are women in Cyprus, 38% in Denmark and 36% in the Russian Federation, for instance.
In many cases, engineering has lost ground to other sciences, including agriculture. The case of New Zealand is fairly typical. Here, women jumped from representing 39% to 70% of agricultural graduates between 2000 and 2012, continued to dominate health (80–78%) but ceded ground in science (43–39%) and engineering (33–27%).
In a number of developing countries, there is a sizable proportion of women engineers. At least three out of ten engineers are women, for instance, in Costa Rica, Vietnam and the United Arab Emirates (31%), Algeria (32%), Mozambique (34%), Tunisia (41%) and Brunei Darussalam (42%). In Malaysia (50%) and Oman (53%), women are on a par with men. Of the 13 sub-Saharan countries reporting data, seven have observed substantial increases (more than 5%) in women engineers since 2000, namely: Benin, Burundi, Eritrea, Ethiopia, Madagascar, Mozambique and Namibia.
Of the seven Arab countries reporting data, four observe a steady percentage or an increase in female engineers (Morocco, Oman, Palestine and Saudi Arabia). In the United Arab Emirates, the government has made it a priority to develop a knowledge economy, having recognized the need for a strong human resource base in science, technology and engineering. With just 1% of the labour force being Emirati, it is also concerned about the low percentage of Emirati citizens employed in key industries. As a result, it has introduced policies promoting the training and employment of Emirati citizens, as well as a greater participation of Emirati women in the labour force. Emirati female engineering students have said that they are attracted to a career in engineering for reasons of financial independence, the high social status associated with this field, the opportunity to engage in creative and challenging projects and the wide range of career opportunities.
An analysis of computer science shows a steady decrease in female graduates since 2000 that is particularly marked in high-income countries. Between 2000 and 2012, the share of women graduates in computer science slipped in Australia, New Zealand, the Republic of Korea and US. In Latin America and the Caribbean, the share of women graduates in computer science dropped by between 2 and 13 percentage points over this period for all countries reporting data.
There are exceptions. In Denmark, the proportion of female graduates in computer science increased from 15% to 24% between 2000 and 2012 and Germany saw an increase from 10% to 17%. These are still very low levels. Figures are higher in many emerging economies. In Turkey, for instance, the proportion of women graduating in computer science rose from a relatively high 29% to 33% between 2000 and 2012.
The Malaysian information technology (IT) sector is made up equally of women and men, with large numbers of women employed as university professors and in the private sector. This is a product of two historical trends: the predominance of women in the Malay electronics industry, the precursor to the IT industry, and the national push to achieve a 'pan-Malayan' culture beyond the three ethnic groups of Indian, Chinese and Malay. Government support for the education of all three groups is available on a quota basis and, since few Malay men are interested in IT, this leaves more room for women. Additionally, families tend to be supportive of their daughters' entry into this prestigious and highly remunerated industry, in the interests of upward social mobility. Malaysia's push to develop an endogenous research culture should deepen this trend.
In India, the substantial increase in women undergraduates in engineering may be indicative of a change in the 'masculine' perception of engineering in the country. It is also a product of interest on the part of parents, since their daughters will be assured of employment as the field expands, as well as an advantageous marriage. Other factors include the 'friendly' image of engineering in India and the easy access to engineering education resulting from the increase in the number of women's engineering colleges over the last two decades.
==== In space ====
While women have made huge strides in the STEM fields, it is obvious that they are still underrepresented. One of the areas where women are most underrepresented in science is space flight. Out of the 556 people who have traveled to space, only 65 of them were women. This means that only 11% of astronauts have been women.
In the 1960s, the American space program was taking off. However, women were not allowed to be considered for the space program because at the time astronauts were required to be military pilots – a profession that women were not allowed to be a part of. There were other "practical" reasons as well. According to General Don Flickinger of the United States Air Force, there was difficulty "designing and fitting a space suit to accommodate their particular biological needs and functions."
During the early 1960s, the first American astronauts, nicknamed the Mercury Seven, were training. At the same time, William Randolph Lovelace II was interested to see if women could manage to go through the same training that the Mercury 7 undergoing at the time. Lovelace recruited thirteen female pilots, called the "Mercury 13", and put them through the same tests that the male astronauts took. As a result, the women actually performed better on these tests than the men of the Mercury 7 did. However, this did not convince NASA officials to allow women in space. In response, congressional hearings were held to investigate discrimination against women in the program. One of the women who testified at the hearing was Jerrie Cobb, the first woman to pass Lovelace's tests. During her testimony, Cobb said:I find it a little ridiculous when I read in a newspaper that there is a place called Chimp College in New Mexico where they are training chimpanzees for space flight, one a female named Glenda. I think it would be at least as important to let the women undergo this training for space flight.NASA officials also had representatives present, notably astronauts John Glenn and Scott Carpenter, to testify that women are not suited for the space program. Ultimately, no action came from the hearings, and NASA did not put a woman in space until 1983.
Even though the United States did not allow women in space during the 60s or 70s, other countries did. Valentina Tereshkova, a cosmonaut from the Soviet Union, was the first woman to fly in space. Although she had no piloting experience, she flew on the Vostok 6 in 1963. Before going to space, Tereshkova was a textile worker. Although she successfully orbited the Earth 48 times, the next woman to go to space did not fly until almost twenty years later.
Sally Ride was the third woman to go to space and the first American woman in space. In 1978, Ride and five other women were accepted into the first class of astronauts that allowed women. In 1983, Ride became the first American woman in space when she flew on the Challenger for the STS-7 mission.
NASA has been more inclusive in recent years. The number of women in NASA's astronaut classes has steadily risen since the first class that allowed women in 1978. The most recent class was 45% women, and the class before was 50%. In 2019, the first all-female spacewalk was completed at the International Space Station.
=== Regional trends as of 2013 ===
The global figures mask wide disparities from one region to another. In Southeast Europe, for instance, women researchers have obtained parity and, at 44%, are on the verge of doing so in Central Asia and Latin America and the Caribbean. In the European Union, on the other hand, just one in three (33%) researchers is a woman, compared to 37% in the Arab world. Women are also better represented in sub-Saharan Africa (30%) than in South Asia (17%).
There are also wide intraregional disparities. Women make up 52% of researchers in the Philippines and Thailand, for instance, and are close to parity in Malaysia and Vietnam, yet only one in three researchers is a woman in Indonesia and Singapore. In Japan and the Republic of Korea, two countries characterized by high researcher densities and technological sophistication, as few as 15% and 18% of researchers respectively are women. These are the lowest ratios among members of the Organisation for Economic Co-operation and Development. The Republic of Korea also has the widest gap among OECD members in remuneration between men and women researchers (39%). There is also a yawning gap in Japan (29%).
==== Latin America and the Caribbean ====
Latin America has some of the world's highest rates of women studying scientific fields; it also shares with the Caribbean one of the highest proportions of female researchers: 44%. Of the 12 countries reporting data for the years 2010–2013, seven have achieved gender parity, or even dominate research: Bolivia (63%), Venezuela (56%), Argentina (53%), Paraguay (52%), Uruguay (49%), Brazil (48%) and Guatemala (45%). Costa Rica is on the cusp (43%). Chile has the lowest score among countries for which there are recent data (31%). The Caribbean paints a similar picture, with Cuba having achieved gender parity (47%) and Trinidad and Tobago on 44%. Recent data on women's participation in industrial research are available for those countries with the most developed national innovation systems, with the exception of Brazil and Cuba: Uruguay (47%), Argentina (29%), Colombia and Chile (26%).
As in most other regions, the great majority of health graduates are women (60–85%). Women are also strongly represented in science. More than 40% of science graduates are women in each of Argentina, Colombia, Ecuador, El Salvador, Mexico, Panama and Uruguay. The Caribbean paints a similar picture, with women graduates in science being on a par with men or dominating this field in Barbados, Cuba, Dominican Republic and Trinidad and Tobago.
In engineering, women make up over 30% of the graduate population in seven Latin American countries (Argentina, Colombia, Costa Rica, Honduras, Panama and Uruguay) and one Caribbean country, the Dominican Republic. There has been a decrease in the number of women engineering graduates in Argentina, Chile and Honduras.
The participation of women in science has consistently dropped since the turn of the century. This trend has been observed in all sectors of the larger economies: Argentina, Brazil, Chile and Colombia. Mexico is a notable exception, having recorded a slight increase. Some of the decrease may be attributed to women transferring to agricultural sciences in these countries. Another negative trend is the drop in female doctoral students and in the labour force. Of those countries reporting data, the majority signal a significant drop of 10–20 percentage points in the transition from master's to doctoral graduates.
A study at UNICAMP (2019-2023) reveals female underrepresentation in publications, particularly in STEM fields and first/last authorship positions. While UNICAMP's 42% female participation is comparable to USP's historical average (38.28%), both fall below the Brazilian average (49%), contrasting with higher female representation in science in some Latin American countries (UNESCO). Despite gender equity policies, female participation at UNICAMP declined after 2021, potentially due to the pandemic, and Field-Weighted Citation Impact (FWCI) was lower in areas like Social Sciences and Life Sciences, highlighting the need for stronger gender equality policies in science.
==== Eastern Europe, West and Central Asia ====
Most countries in Eastern Europe, West and Central Asia have attained gender parity in research (Armenia, Azerbaijan, Georgia, Kazakhstan, Mongolia and Ukraine) or are on the brink of doing so (Kyrgyzstan and Uzbekistan). This trend is reflected in tertiary education, with some exceptions in engineering and computer science. Although Belarus and the Russian Federation have seen a drop over the past decade, women still represented 41% of researchers in 2013. In the former Soviet states, women are also very present in the business enterprise sector: Bosnia and Herzegovina (59%), Azerbaijan (57%), Kazakhstan (50%), Mongolia (48%), Latvia (48%), Serbia (46%), Croatia and Bulgaria (43%), Ukraine and Uzbekistan (40%), Romania and Montenegro (38%), Belarus (37%), Russian Federation (37%).
One in three researchers is a woman in Turkey (36%) and Tajikistan (34%). Participation rates are lower in Iran (26%) and Israel (21%), although Israeli women represent 28% of senior academic staff. At university, Israeli women dominate medical sciences (63%) but only a minority study engineering (14%), physical sciences (11%), mathematics and computer science (10%). There has been an interesting evolution in Iran. Whereas the share of female PhD graduates in health remained stable at 38–39% between 2007 and 2012, it rose in all three other broad fields. Most spectacular was the leap in female PhD graduates in agricultural sciences from 4% to 33% but there was also a marked progression in science (from 28% to 39%) and engineering (from 8% to 16%).
==== Southeast Europe ====
With the exception of Greece, all the countries of Southeast Europe were once part of the Soviet bloc. Some 49% of researchers in these countries are women (compared to 37% in Greece in 2011). This high proportion is considered a legacy of the consistent investment in education by the Socialist governments in place until the early 1990s, including that of the former Yugoslavia. Moreover, the participation of female researchers is holding steady or increasing in much of the region, with representation broadly even across the four sectors of government, business, higher education and non-profit. In most countries, women tend to be on a par with men among tertiary graduates in science. Between 70% and 85% of graduates are women in health, less than 40% in agriculture and between 20% and 30% in engineering. Albania has seen a considerable increase in the share of its women graduates in engineering and agriculture.
==== European Union ====
Women make up 33% of researchers overall in the European Union (EU), slightly more than their representation in science (32%). Women constitute 40% of researchers in higher education, 40% in government and 19% in the private sector, with the number of female researchers increasing faster than that of male researchers. The proportion of female researchers has been increasing over the last decade, at a faster rate than men (5.1% annually over 2002–2009 compared with 3.3% for men), which is also true for their participation among scientists and engineers (up 5.4% annually between 2002 and 2010, compared with 3.1% for men).
Despite these gains, women's academic careers in Europe remain characterized by strong vertical and horizontal segregation. In 2010, although female students (55%) and graduates (59%) outnumbered male students, men outnumbered women at the PhD and graduate levels (albeit by a small margin). Further along in the research career, women represented 44% of grade C academic staff, 37% of grade B academic staff and 20% of grade A academic staff.11 These trends are intensified in science, with women making up 31% of the student population at the tertiary level to 38% of PhD students and 35% of PhD graduates. At the faculty level, they make up 32% of academic grade C personnel, 23% of grade B and 11% of grade A. The proportion of women among full professors is lowest in engineering and technology, at 7.9%. With respect to representation in science decision-making, in 2010 15.5% of higher education institutions were headed by women and 10% of universities had a female rector.
Membership on science boards remained predominantly male as well, with women making up 36% of board members. The EU has engaged in a major effort to integrate female researchers and gender research into its research and innovation strategy since the mid-2000s. Increases in women's representation in all of the scientific fields overall indicates that this effort has met with some success; however, the continued lack of representation of women at the top level of faculties, management and science decision making indicate that more work needs to be done. The EU is addressing this through a gender equality strategy and crosscutting mandate in Horizon 2020, its research and innovation funding programme for 2014–2020.
==== Australia, New Zealand and USA ====
In 2013, women made up the majority of PhD graduates in fields related to health in Australia (63%), New Zealand (58%) and the United States of America (73%). The same can be said of agriculture, in New Zealand's case (73%). Women have also achieved parity in agriculture in Australia (50%) and the United States (44%). Just one in five women graduate in engineering in the latter two countries, a situation that has not changed over the past decade. In New Zealand, women jumped from constituting 39% to 70% of agricultural graduates (all levels) between 2000 and 2012 but ceded ground in science (43–39%), engineering (33–27%) and health (80–78%). As for Canada, it has not reported sex-disaggregated data for women graduates in science and engineering in recent years. Moreover, none of the four countries mentioned here have reported recent data on the share of female researchers.
==== South Asia ====
South Asia is the region where women make up the smallest proportion of researchers: 17%. This is 13 percentage points below sub-Saharan Africa. Of those countries in South Asia reporting data for 2009–2013, Nepal has the lowest representation of all (in head counts), at 8% (2010), a substantial drop from 15% in 2002. In 2013, only 14% of researchers (in full-time equivalents) were women in the region's most populous country, India, down slightly from 15% in 2009. The percentage of female researchers is highest in Sri Lanka (39%), followed by Pakistan: 24% in 2009, 31% in 2013. There are no recent data available for Afghanistan or Bangladesh.
Women are most present in the private non-profit sector – they make up 60% of employees in Sri Lanka – followed by the academic sector: 30% of Pakistani and 42% of Sri Lankan female researchers. Women tend to be less present in the government sector and least likely to be employed in the business sector, accounting for 23% of employees in Sri Lanka, 11% in India and just 5% in Nepal. Women have achieved parity in science in both Sri Lanka and Bangladesh but are less likely to undertake research in engineering. They represent 17% of the research pool in Bangladesh and 29% in Sri Lanka. Many Sri Lankan women have followed the global trend of opting for a career in agricultural sciences (54%) and they have also achieved parity in health and welfare. In Bangladesh, just over 30% choose agricultural sciences and health, which goes against the global trend. Although Bangladesh still has progress to make, the share of women in each scientific field has increased steadily over the past decade.
==== Southeast Asia ====
Southeast Asia presents a different picture entirely, with women basically on a par with men in some countries: they make up 52% of researchers in the Philippines and Thailand, for example. Other countries are close to parity, such as Malaysia and Vietnam, whereas Indonesia and Singapore are still around the 30% mark. Cambodia trails its neighbours at 20%. Female researchers in the region are spread fairly equally across the sectors of participation, with the exception of the private sector, where they make up 30% or less of researchers in most countries.
The proportion of women tertiary graduates reflects these trends, with high percentages of women in science in Brunei Darussalam, Malaysia, Myanmar and the Philippines (around 60%) and a low of 10% in Cambodia. Women make up the majority of graduates in health sciences, from 60% in Laos to 81% in Myanmar – Vietnam being an exception at 42%. Women graduates are on a par with men in agriculture but less present in engineering: Vietnam (31%), the Philippines (30%) and Malaysia (39%); here, the exception is Myanmar, at 65%. In the Republic of Korea, women make up about 40% of graduates in science and agriculture and 71% of graduates in health sciences but only 18% of female researchers overall. This represents a loss in the investment made in educating girls and women up through tertiary education, a result of traditional views of women's role in society and in the home. Kim and Moon (2011) remark on the tendency of Korean women to withdraw from the labour force to take care of children and assume family responsibilities, calling it a 'domestic brain drain'.
Women remain very much a minority in Japanese science (15% in 2013), although the situation has improved slightly (13% in 2008) since the government fixed a target in 2006 of raising the ratio of female researchers to 25%. Calculated on the basis of the current number of doctoral students, the government hopes to obtain a 20% share of women in science, 15% in engineering and 30% in agriculture and health by the end of the current Basic Plan for Science and Technology in 2016. In 2013, Japanese female researchers were most common in the public sector in health and agriculture, where they represented 29% of academics and 20% of government researchers. In the business sector, just 8% of researchers were women (in head counts), compared to 25% in the academic sector. In other public research institutions, women accounted for 16% of researchers. One of the main thrusts of Abenomics, Japan's current growth strategy, is to enhance the socio-economic role of women. Consequently, the selection criteria for most large university grants now take into account the proportion of women among teaching staff and researchers.
The low ratio of women researchers in Japan and the Republic of Korea, which both have some of the highest researcher densities in the world, brings down Southeast Asia's average to 22.5% for the share of women among researchers in the region.
==== Arab States ====
At 37%, the share of female researchers in the Arab States compares well with other regions. The countries with the highest proportion of female researchers are Bahrain and Sudan at around 40%. Jordan, Libya, Oman, Palestine and Qatar have percentage shares in the low twenties. The country with the lowest participation of female researchers is Saudi Arabia, even though they make up the majority of tertiary graduates, but the figure of 1.4% covers only the King Abdulaziz City for Science and Technology. Female researchers in the region are primarily employed in government research institutes, with some countries also seeing a high participation of women in private nonprofit organizations and universities. With the exception of Sudan (40%) and Palestine (35%), fewer than one in four researchers in the business enterprise sector is a woman; for half of the countries reporting data, there are barely any women at all employed in this sector.
Despite these variable numbers, the percentage of female tertiary-level graduates in science and engineering is very high across the region, which indicates there is a substantial drop between graduation and employment and research. Women make up half or more than half of science graduates in all but Sudan and over 45% in agriculture in eight out of the 15 countries reporting data, namely Algeria, Egypt, Jordan, Lebanon, Sudan, Syria, Tunisia and the United Arab Emirates. In engineering, women make up over 70% of graduates in Oman, with rates of 25–38% in the majority of the other countries, which is high in comparison to other regions.
The participation of women is somewhat lower in health than in other regions, possibly on account of cultural norms restricting interactions between males and females. Iraq and Oman have the lowest percentages (mid-30s), whereas Iran, Jordan, Kuwait, Palestine and Saudi Arabia are at gender parity in this field. The United Arab Emirates and Bahrain have the highest rates of all: 83% and 84%.
Once Arab women scientists and engineers graduate, they may come up against barriers to finding gainful employment. These include a misalignment between university programmes and labour market demand – a phenomenon which also affects men –, a lack of awareness about what a career in their chosen field entails, family bias against working in mixed-gender environments and a lack of female role models.
One of the countries with the smallest female labour force is developing technical and vocational education for girls as part of a wider scheme to reduce dependence on foreign labour. By 2017, the Technical and Vocational Training Corporation of Saudi Arabia is to have constructed 50 technical colleges, 50 girls' higher technical institutes and 180 industrial secondary institutes. The plan is to create training placements for about 500 000 students, half of them girls. Boys and girls will be trained in vocational professions that include information technology, medical equipment handling, plumbing, electricity and mechanics.
==== Sub-Saharan Africa ====
Just under one in three (30%) researchers in sub-Saharan Africa is a woman. Much of sub-Saharan Africa is seeing solid gains in the share of women among tertiary graduates in scientific fields. In two of the top four countries for women's representation in science, women graduates are part of very small cohorts, however: they make up 54% of Lesotho's 47 tertiary graduates in science and 60% of those in Namibia's graduating class of 149. South Africa and Zimbabwe, which have larger graduate populations in science, have achieved parity, with 49% and 47% respectively. The next grouping clusters seven countries poised at around 35–40% (Angola, Burundi, Eritrea, Liberia, Madagascar, Mozambique and Rwanda). The rest are grouped around 30% or below (Benin, Ethiopia, Ghana, Swaziland and Uganda). Burkina Faso ranks lowest, with women making up 18% of its science graduates.
Female representation in engineering is fairly high in sub-Saharan Africa in comparison with other regions. In Mozambique and South Africa, for instance, women make up more than 34% and 28% of engineering graduates, respectively. Numbers of female graduates in agricultural science have been increasing steadily across the continent, with eight countries reporting the share of women graduates of 40% or more (Lesotho, Madagascar, Mozambique, Namibia, Sierra Leone, South Africa, Swaziland and Zimbabwe). In health, this rate ranges from 26% and 27% in Benin and Eritrea to 94% in Namibia.
Of note is that women account for a relatively high proportion of researchers employed in the business enterprise sector in South Africa (35%), Kenya (34%), Botswana and Namibia (33%) and Zambia (31%). Female participation in industrial research is lower in Uganda (21%), Ethiopia (15%) and Mali (12%).
== Lack of agency and representation ==
=== Social pressures to both conform to femininity and which punish femininity ===
Beginning in the twentieth century to present day, more and more women are becoming acknowledged for their work in science. However, women often find themselves at odds with expectations held towards them in relation to their scientific studies. For example, in 1968 James Watson questioned scientist Rosalind Franklin's place in the industry. He claimed that "the best place for a feminist was in another person's lab".: 76–77 Women were and still are often critiqued of their overall presentation. In Franklin's situation, she was seen as lacking femininity for she failed to wear lipstick or revealing clothing.: 76–77
Since on average most of a woman's colleagues in science are men who do not see her as a true social peer, she will also find herself left out of opportunities to discuss possible research opportunities outside of the laboratory. In Londa Schiebinger's book, Has Feminism Changed Science?, she mentions that men would have discussed their research outside of the lab, but this conversation is preceded by culturally "masculine" small-talk topics that, whether intentionally or not, excluded women influenced by their culture's feminine gender role from the conversation.: 81–91 Consequently, this act of excluding many women from the after-hours work discussions produced a more separate work environment between the men and the women in science; as women then would converse with other women in science about their current findings and theories. Ultimately, the women's work was devalued as a male scientist was not involved in the overall research and analysis.
According to Oxford University Press, the inequality toward women is "endorsed within cultures and entrenched within institutions [that] hold power to reproduce that inequality". There are various gendered barriers in social networks that prevent women from working in male-dominated fields and top management jobs. Social networks are based on the cultural beliefs such as schemas and stereotypes. According to social psychology studies, top management jobs are more likely to have incumbent schemas that favor "an achievement-oriented aggressiveness and emotional toughness that is distinctly male in character". Gender stereotypes of feminine style assume women to be conforming and submissive to male culture creating a sense of unqualified women for top management jobs. In attempting to demonstrate competence and power, women can still be seen as unlikeable and untrustworthy, even if they excel at traditionally "masculine" tasks. In addition, women's achievements are likely to be dismissed or discredited. These "untrustworthy, dislikable women" could have very well been denied achievement from the fear men held of a woman overtaking his management position. Social networks and gender stereotypes produce many injustices that women have to experience in their workplace, as well as, the various obstacles they encounter when trying to advance in male-dominated and top management jobs. Women in professions like science, technology, and other related industries are likely to encounter these gendered barriers in their careers.
=== Underrepresentation of homosexual and bi women, and gender nonconformists in STEM ===
While there has been a push to encourage more women to participate in science, there is less outreach to lesbian, bi, or gender nonconforming women, and gender nonconforming people more broadly. Due to the lack of data and statistics of LGBTQ members involvement in the STEM field, it is unknown to what exact degree lesbian and bisexual women, gender non-conformers (transgender, nonbinary/agender, or anti-gender gender abolitionists who eschew the system altogether) are potentially even more repressed and underrepresented than their straight peers. But a general lack of out lesbian and bi women in STEM has been noted. Reasons for under-representation of same-sex attracted women and anyone gender nonconforming in STEM fields include lack of role models in K–12, the desire of some transgender girls and women to adopt traditional heteronormative gender roles as gender is a cultural performance and socially-determined subjective internal experience, employment discrimination, and the possibility of sexual harassment in the workplace. Historically, women who have accepted STEM research positions for the government or the military remained in the closet due to lack of federal protections or the fact that homosexual or gender nonconforming expression was criminalized in their country. A notable example is Sally Ride, a physicist, the first American female astronaut, and a lesbian. Sally Ride chose not to reveal her sexuality until after her death in 2012; she purposefully revealed her sexual orientation in her obituary. She has been known as the first female (and youngest) American to enter space, as well as, starting her own company, Sally Ride Science, that encourages young girls to enter the STEM field. She chose to keep her sexuality to herself because she was familiar with "the male-dominated" NASA's anti-homosexual policies at the time of her space travel. Sally Ride's legacy continues as her company is still working to increase young girls and women's participation in the STEM fields.
In a nationwide study of LGBTQA employees in STEM fields in the United States, same-sex attracted and gender nonconforming women in engineering, earth sciences, and mathematics reported that they were less likely to be out in the workplace. In general, LGBTQA people in this survey reported that, when more female or feminine gender role-identified people worked in their labs, the more accepting and safe the work environment. In another study of over 30,000 LGBT employees in STEM-related federal agencies in the United States, queer women in these agencies reported feeling isolated in the workplace and having to work harder than their gender conforming male colleagues. This isolation and overachievement remained constant as they earned supervisory positions and worked their way up the ladder. Gender nonconforming people in physics, particularly those identified as trans women in physics programs and labs, felt the most isolated and perceived the most hostility.
Organizations such as Lesbians Who Tech, Out to Innovate, Out in Science, Technology, Engineering and Mathematics (OSTEM), Pride in STEM, and House of STEM provide networking and mentoring opportunities for lesbian girls and women and LGBT people interested in or currently working in STEM fields. These organizations also advocate for the rights of lesbian and bi women and gender nonconformists in STEM in education and the workplace.
== Reasons for disadvantages ==
Margaret Rossiter, an American historian of science, offered three concepts to explain the reasons behind the data in statistics and how these reasons disadvantaged women in the science industry. The first concept is hierarchical segregation. This is a well-known phenomenon in society, that the higher the level and rank of power and prestige, the smaller the population of females participating. The hierarchical differences point out that there are fewer women participating at higher levels of both academia and industry. Based on data collected in 1982, women earn 54 percent of all bachelor's degrees in the United States, with 50 percent of these in science. The source also indicated that this number increased almost every year. As of 2020, women were earning 57.3 percent of all bachelor's degrees, with 38.6 percent of these in a STEM field.
The second concept included in Rossiter's explanation of women in science is territorial segregation.: 34–35 The term refers to how female employment is often clustered in specific industries or categories in industries. Women stayed at home or took employment in feminine fields while men left the home to work. Although nearly half of the civilian work force is female, women still comprise the majority of low-paid jobs or jobs that society considered feminine. Statistics show that 60 percent of white professional women are nurses, daycare workers, or schoolteachers.
Researchers collected the data on many differences between women and men in science. Rossiter found that in 1966, thirty-eight percent of female scientists held master's degrees compared to twenty-six percent of male scientists; but large proportions of female scientists were in environmental and nonprofit organizations. During the late 1960s and 1970s, equal-rights legislation made the number of female scientists rise dramatically. The number of science degrees awarded to woman rose from seven percent in 1970 to twenty-four percent in 1985. In 1975 only 385 women received bachelor's degrees in engineering compared to 11,000 women in 1985. Elizabeth Finkel claims that even if the number of women participating in scientific fields increases, the opportunities are still limited. Another researcher, Harriet Zuckerman, claims that when woman and man have similar abilities for a job, the probability of the woman getting the job is lower. Finkel agrees, saying, "In general, while woman and men seem to be completing doctorate with similar credentials and experience, the opposition and rewards they find are not comparable. Women tend to be treated with less salary and status, many policy makers notice this phenomenon and try to rectify the unfair situation for women participating in scientific fields."
=== Societal disadvantages ===
Despite women's tendency to perform better than men academically, there are flaws involving stereotyping, lack of information, and family influence that have been found to affect women's involvement in science. Stereotyping has an effect, because people associate characteristics such as nurturing, kind, and warm or characteristics like strong and powerful with a particular gender. These character associations lead people to stereotype that certain jobs are more suitable to a particular gender. Lack of information is something that many institutions have worked hard over the years to improve by making programs such as the IFAC project (Information for a choice: empowering women through learning for scientific and technological career paths) which investigated low women participation in science and technology fields at high school to university level. However, not all efforts were as successful, "Science: it's a girl thing" campaign, which has since been removed, received backlash for further encouraging women that they must partake in "girly" or "feminine" activities. The idea being that if women are fully informed of their career choices and employability, they will be more inclined to pursue STEM field jobs. Women also struggle in the sense of lacking role models of women in science. Family influence is dependent on education level, economic status, and belief system. Education level of a student's parent matters, because oftentimes people who have higher education have a different opinion on education's importance than someone that does not. A parent can also be an influence in the sense that they want their children to follow in their footsteps and pursue a similar occupation, especially in women, it's been found that the mother's line of work tends to correlate with their daughters. Economic status can influence what kind of higher education a student might get. Economic status may influence their education depending on whether they are a work bound student or a college bound student. A work bound student may choose a shorter career path to quickly begin making money or due to lack of time. The belief system of a household can also have a big impact on women depending on their family's religious or cultural viewpoints. There are still some countries that have certain regulations on women's occupation, clothing, and curfew that limit career choices for women. Parental influence is also relevant because people tend to want to fulfill what they could not have as a child. Unfortunately, women are at such a disadvantage because not only must they overcome societal norms but then they also have to outperform men for the same recognition, studies show.
That sexism is alive and well in science is known. ...Even in the life sciences, where men and women start careers in fairly equal numbers, the number of women drops off rapidly at professorial level.On average, fewer than one in five science professors are female. Science punishes career breaks, and women who take time off to have children are immediately disadvantaged. "The flashpoint is when you're about 35 and trying to get tenure. That can be when you're trying to have kids, and it can play a major role in why you see so much attrition at that stage," said Jennifer Rohn, a cell biologist at University College London. A grant may give a woman a year's grace if she has a baby, but it takes longer to get back into research projects than that.
== Contemporary advocacy and developments ==
=== Efforts to increase participation ===
A number of organizations have been set up to combat the stereotyping that may encourage girls away from careers in these areas. In the UK The WISE Campaign (Women into Science, Engineering and Construction) and the UKRC (The UK Resource Centre for Women in SET) are collaborating to ensure industry, academia and education are all aware of the importance of challenging the traditional approaches to careers advice and recruitment that mean some of the best brains in the country are lost to science. The UKRC and other women's networks provide female role models, resources and support for activities that promote science to girls and women. The Women's Engineering Society, a professional association in the UK, has been supporting women in engineering and science since 1919. In computing, the British Computer Society group BCSWomen is active in encouraging girls to consider computing careers, and in supporting women in the computing workforce.
In the United States, the Association for Women in Science is one of the most prominent organization for professional women in science. In 2011, the Scientista Foundation was created to empower pre-professional college and graduate women in science, technology, engineering and mathematics (STEM), to stay in the career track. There are also several organizations focused on increasing mentorship from a younger age. One of the best known groups is Science Club for Girls, which pairs undergraduate mentors with high school and middle school mentees. The model of that pairs undergraduate college mentors with younger students is quite popular. In addition, many young women are creating programs to boost participation in STEM at a younger level, either through conferences or competitions.
In efforts to make women scientists more visible to the general public, the Grolier Club in New York hosted a "landmark exhibition" titled "Extraordinary Women in Science & Medicine: Four Centuries of Achievement", showcasing the lives and works of 32 women scientists in 2003. The National Institute for Occupational Safety and Health (NIOSH) developed a video series highlighting the stories of female researchers at NIOSH. Each of the women featured in the videos share their journey into science, technology, engineering, or math (STEM), and offers encouragement to aspiring scientists. NIOSH also partners with external organizations in efforts to introduce individuals to scientific disciplines and funds several science-based training programs across the country.
Creative Resilience: Art by Women in Science is a multi–media exhibition and accompanying publication, produced in 2021 by the Gender Section of the United Nations Educational, Scientific and Cultural Organization (UNESCO). The project aims to give visibility to women, both professionals and university students, working in science, technology, engineering and mathematics (STEM). With short biographical information and graphic reproductions of their artworks dealing with the Covid-19 pandemic and accessible online, the project provides a platform for women scientists to express their experiences, insights, and creative responses to the pandemic.
==== In the media ====
In 2013, journalist Christie Aschwanden noted that a type of media coverage of women scientists that "treats its subject's sex as her most defining detail" was still prevalent. She proposed a checklist, the "Finkbeiner test", to help avoid this approach. It was cited in the coverage of a much-criticized 2013 New York Times obituary of rocket scientist Yvonne Brill that began with the words: "She made a mean beef stroganoff". Women are often poorly portrayed in film. The misrepresentation of women scientists in film, television and books can influence children to engage in gender stereotyping. This was seen in a 2007 meta-analysis conducted by Jocelyn Steinke and colleagues from Western Michigan University where, after engaging elementary school students in a Draw-a-Scientist Test, out of 4,000 participants only 28 girls drew female scientists.
=== Notable controversies and developments ===
A study conducted at Lund University in 2010 and 2011 analysed the genders of invited contributors to News & Views in Nature and Perspectives in Science. It found that 3.8% of the Earth and environmental science contributions to News & Views were written by women even while the field was estimated to be 16–20% female in the United States. Nature responded by suggesting that, worldwide, a significantly lower number of Earth scientists were women, but nevertheless committed to address any disparity.
In 2012, a journal article published in Proceedings of the National Academy of Sciences (PNAS) reported a gender bias among science faculty. Faculty were asked to review a resume from a hypothetical student and report how likely they would be to hire or mentor that student, as well as what they would offer as starting salary. Two resumes were distributed randomly to the faculty, only differing in the names at the top of the resume (John or Jennifer). The male student was rated as significantly more competent, more likely to be hired, and more likely to be mentored. The median starting salary offered to the male student was greater than $3,000 over the starting salary offered to the female student. Both male and female faculty exhibited this gender bias. This study suggests bias may partly explain the persistent deficit in the number of women at the highest levels of scientific fields. Another study reported that men are favored in some domains, such as biology tenure rates, but that the majority of domains were gender-fair; the authors interpreted this to suggest that the under-representation of women in the professorial ranks was not solely caused by sexist hiring, promotion, and remuneration. In April 2015 Williams and Ceci published a set of five national experiments showing that hypothetical female applicants were favored by faculty for assistant professorships over identically qualified men by a ratio of 2 to 1.
In 2014, a controversy over the depiction of pinup women on Rosetta project scientist Matt Taylor's shirt during a press conference raised questions of sexism within the European Space Agency. The shirt, which featured cartoon women with firearms, led to an outpouring of criticism and an apology after which Taylor "broke down in tears."
In 2015, stereotypes about women in science were directed at Fiona Ingleby, research fellow in evolution, behavior, and environment at the University of Sussex, and Megan Head, postdoctoral researcher at the Australian National University, when they submitted a paper analyzing the progression of PhD graduates to postdoctoral positions in the life sciences to the journal PLOS ONE. The authors received an email on 27 March informing them that their paper had been rejected due to its poor quality. The email included comments from an anonymous reviewer, which included the suggestion that male authors be added in order to improve the quality of the science and serve as a means of ensuring that incorrect interpretations of the data are not included. Ingleby posted excerpts from the email on Twitter on 29 April bringing the incident to the attention of the public and media. The editor was dismissed from the journal and the reviewer was removed from the list of potential reviewers. A spokesman from PLOS apologized to the authors and said they would be given the opportunity to have the paper reviewed again.
On 9 June 2015, Nobel prize winning biochemist Tim Hunt spoke at the World Conference of Science Journalists in Seoul. Prior to applauding the work of women scientists, he described emotional tension, saying "you fall in love with them, they fall in love with you, and when you criticise them they cry." Initially, his remarks were widely condemned and he was forced to resign from his position at University College London. However, multiple conference attendees gave accounts, including a partial transcript and a partial recording, maintaining that his comments were understood to be satirical before being taken out of context by the media.
In 2016, an article published in JAMA Dermatology reported a significant and dramatic downward trend in the number of NIH-funded woman investigators in the field of dermatology and that the gender gap between male and female NIH-funded dermatology investigators was widening. The article concluded that this disparity was likely due to a lack of institutional support for women investigators.
==== Problematic public statements ====
In January 2005, Harvard University President Lawrence Summers sparked controversy at a National Bureau of Economic Research (NBER) Conference on Diversifying the Science & Engineering Workforce. Dr. Summers offered his explanation for the shortage of women in senior posts in science and engineering. He made comments suggesting the lower numbers of women in high-level science positions may in part be due to innate differences in abilities or preferences between men and women. Making references to the field and behavioral genetics, he noted the generally greater variability among men (compared to women) on tests of cognitive abilities, leading to proportionally more men than women at both the lower and upper tails of the test score distributions. In his discussion of this, Summers said that "even small differences in the standard deviation [between genders] will translate into very large differences in the available pool substantially out [from the mean]". Summers concluded his discussion by saying:So my best guess, to provoke you, of what's behind all of this is that the largest phenomenon, by far, is the general clash between people's legitimate family desires and employers' current desire for high power and high intensity, that in the special case of science and engineering, there are issues of intrinsic aptitude, and particularly of the variability of aptitude, and that those considerations are reinforced by what are in fact lesser factors involving socialization and continuing discrimination.Despite his protégée, Sheryl Sandberg, defending Summers' actions and Summers offering his own apology repeatedly, the Harvard Graduate School of Arts and Sciences passed a motion of "lack of confidence" in the leadership of Summers who had allowed tenure offers to women plummet after taking office in 2001. The year before he became president, Harvard extended 13 of its 36 tenure offers to women and by 2004 those numbers had dropped to 4 of 32 with several departments lacking even a single tenured female professor. This controversy is speculated to have significantly contributed to Summers resignation from his position at Harvard the following year.
== See also ==
== References ==
== Sources ==
This article incorporates text from a free content work. Licensed under CC-BY-SA IGO 3.0. Text taken from UNESCO Science Report: towards 2030, 85–103, UNESCO, UNESCO Publishing.
== Further reading ==
== External links ==
Science Speaks: A Focus on NIOSH Women in Science Short, personal stories of females working in fields of science. A video series developed by the National Institute for Occupational Safety and Health (NIOSH)
Gender tutorials on women in science from Hunter College and the Graduate Center of the City University of New York (CUNY)
Statistics on women at science conferences from the American Astronomical Society, Committee on the Status of Women in Astronomy
The Library of Congress Selected Internet Resources Women in Science and Medicine
Women in Science at the Encyclopædia Britannica | Wikipedia/Women_in_science |
Science outreach, also called education and public outreach (EPO or E/PO) or simply public outreach, is an umbrella term for a variety of activities by research institutes, universities, and institutions such as science museums, aimed at promoting public awareness (and understanding) of science and making informal contributions to science education.
== Scope and history ==
While there have always been individual scientists interested in educating the public, science outreach has recently become more organized. For example, the National Aeronautics and Space Administration (NASA) now requires all of its projects to organize suitable outreach activities. Also working to inform the public are organizations such as Communicating Astronomy to the Public and the Washington Declaration on Communicating Astronomy to the Public that organize conferences for the public on science issues and make efforts to put outreach on a more general institutional footing.
Recently, an increasing number of projects have hired designated outreach scientists (part-time or full-time) that handle public relations for their project. There are also specialized outreach providers such as the Education branch of the Space Science Institute in Boulder, Colorado and the Education and Public Outreach Group at Sonoma State University which offer to organize a project's outreach activities on a contractual basis.
In addition to outreach by research institutions, an important part of informal science education are outreach programs such as science museums and science festivals.
== Activities ==
Science outreach can take on a variety of forms.
=== Public talks, lectures, and discussions ===
Lectures are probably the oldest form of science outreach, dating back to the 1820s when Michael Faraday organized the first of the Royal Institution's Christmas Lectures.
Public talks can be part of a lecture series, given at a science festival or in cooperation with a special interest group such as a local astronomy club. Public presentations can have a variety of formats, including straightforward lecture formats with or without experimental demonstrations, guided live interviews, and discussions with several participants and a moderator. There are also less formal initiatives such as Café Scientifique, in which a café or bar is the venue for regular meetings involving guest scientists that come to talk about their work or take part in discussions with members of the public, and collaborations with museums
=== Visiting primary and secondary schools ===
School students and teachers are an important target group for science outreach. Outreach activities can include scientists visiting schools, giving talks at assemblies, discussions with students, or participation in events such as career fairs and science and technology camps. One organization that focuses on this kind of science outreach is Robogals. Many universities also have science outreach programs that are dedicated to building relationships between high school students, university scientists, and K–12 teachers. A few of the most prominent university science outreach programs include Carolina Science Outreach, the Vanderbilt Student Volunteers for Science, the Rockefeller University Science Outreach Program, the Present Your Ph.D. thesis to a 12-Year Old Outreach Project at University of Texas at Austin in Austin, Texas, the Present Your PhD graduate organization at Baylor University in Waco, Texas, the Discover STEM Polymer Day and Energy and U at the University of Minnesota, and the Stanford University Office of Science Outreach. Using Canada as an example, it has been estimated that with sufficient organization, every classroom from kindergarten through graduation could in practice receive a visit from one or more scientists annually with participation from only 10-15% of the scientific enterprise. Some examples of science outreach programs in Canada include: Let's Talk Science, Actua, The Chemical Institute of Canada, and Science Rendezvous.
=== Workshops and schools for teachers or students ===
Inviting groups of school students to a research institution for a workshop is another popular form of outreach. Formats range from a one-day visit to more involved week-long events such as Perimeter Institute's International Summer School for Young Physicists, a two-week-long program for a total of a hundred Canadian and international students from grade 11.
Another method of science outreach invites school teachers to participate in workshops where they are able to learn effective strategies to engage students in science. This approach was especially embraced by the Canadian Space Agency (CSA) which held an annual "Space Educators" conference up until 2012 to provides teachers with access to resources to educate their students in space-related science.
=== Supporting science fairs and similar events ===
Besides organizing independent events, many outreach organizations sponsor existing events that promote sciences awareness. A notable examples are science fairs, public science events in which working scientists can participate both as judges and as sponsors of student projects.
=== Online aggregation of science activities, resources, and programs ===
The internet is a rich source of science activities, resources, and programs. For example, research laboratories often maintain educational outreach projects aimed at translating their science into something meaningful for the general public, often K–12 students, as an effort to increase research broader impacts required by funding agencies such as the National Science Foundation (NSF). These may include activities using fast-growing plants that exhibit distinctive mutants with unique phenotypes useful to teach K–12 students about both Mendelian and molecular genetics. Some institutions and organizations maintain large or small aggregations of their activity resources, outreach programs, upcoming events calendars, and partnering programs.
== Awards ==
A number of awards honor commitment to science outreach. Examples include:
Award for Public Understanding of Science and Technology, American Association for the Advancement of Science
Descartes Prize for Excellence in Science Communication, European Commission
Michael Faraday Prize for communicating science to a UK audience (Royal Society)
Communicator award, Deutsche Forschungsgemeinschaft
Synapse Mentorship Awards, often given for exceptional contributions to science outreach, Canadian Institutes of Health Research
Nicholson Medal for Human Outreach, American Physical Society
Charles A. Black Award, for exemplary contributions to public understanding of food and agricultural science
Kalinga Prize for popularisation of science is an award given by UNESCO since 1952 for exceptional skill in presenting scientific ideas to lay people
== See also ==
List of Astronomy Outreach Resources in Europe
Science Communication Observatory
Science festival
Science museum
Scientific literacy
Physics Outreach
Popular science
Public science
== References ==
== External links ==
NASA Science | Wikipedia/Science_outreach |
Feminist technoscience is a transdisciplinary branch of science studies which emerged from decades of feminist critique on the way gender and other identity markers are entangled in the combined fields of science and technology. The term technoscience, especially in regard to the field of feminist technoscience studies, seeks to remove the distinction between scientific research and development with applied applications of technology while assuming science is entwined with the common interests of society. As a result, science is suggested to be held to the same level of political and ethical accountability as the technologies which develop from it. Feminist technoscience studies continue to develop new theories on how politics of gender and other identity markers are interconnected to resulting processes of technical change, and power relations of the globalized, material world.
Feminist technoscience focuses less on intrapersonal relationships between men and women, and more on broader issues concerning knowledge production and how bodies manifest and are acknowledged in societies.
Feminist technoscience studies are inspired by social constructionist approaches to gender, sex, intersectionalities, and science, technology and society (STS). It can also be referred to as feminist science studies, feminist STS, feminist cultural studies of science, feminist studies of science and technology, and gender and science.
== History ==
According to Judy Wajcman, the concept of technology has historically been bound to indigenous women. The roles of harvesters, or caretakers of the domestic economy taken up by these women lead Wajcman to conclude they would have created tools such as the sickle and the pestle, making them the first technologists.: 15 During the eighteenth century, industrial engineering began to constitute the modern definition of technology. This transformed the meaning from including useful arts technology – such as needlework, metalwork, weaving, and mining – to strictly applied science.: 16 As a result, "male machines" replaced the "female fabrics" as identifiers of modern technology when engineering was considered a masculine profession.: 16 Due to political movements of the 1960s and early 70s, science and technology were considered as industrial, governmental, and/or militaristic based practices, which were associated with masculinity, thus resulting in a lack of feminist discourse. Feminist scholarship identified the absence of women's presence in technological and scientific spheres, due to the use of sex stereotyping in education and sexual discrimination in the workforce, as well as the development of technology as a masculine construct.: 16 Examples of masculine-coded technologies under these categories included ARPANET, a precursor to the internet developed by the United States Department of Defence, and the Manhattan Project.
The women's health movements of the 1970s in the United States and the United Kingdom provided momentum to the emergence of feminist politics around scientific knowledge. During the early states of second-wave feminism, campaigns for improved birth control and abortion rights were at the forefront in challenging the consolidation of male dominated sciences and technologies at the expense of women's health. After the first successful birth of a child using in vitro fertilization technology, critiques of reproductive technologies rapidly grew. In the 1970s and 1980s, there were fears that oppressive population policies would be enacted, since men could use technology to appropriate the reproductive abilities of women. For many feminist activists, such as Gena Corea and Maria Mies, such technologies changed women's bodies into industrialized factories for the production of more human beings, which these feminist activists viewed as another way of continuing the subjugation of women in society. Others viewed the act of regaining knowledge and control over women's bodies as a crucial component to women's liberation.: 17 Further advances in reproductive technologies allowed the possibility to allow new family types and lifestyles to form, beyond the heterosexual family unit.
Science was originally seen as an alien entity opposed to women's interests. Sciences and technologies developed under the misconception that women's needs were universal and inferior to the needs of men, forcing women into rigid, determined sex roles.: 18 A shift happened in the 1980s – Sandra Harding proposed "the female question in science" to raise "the question of the science in feminism", claiming that science is involved in projects that are not only neutral and objective, but that are strongly linked to male interests.: 18 The conceptualization of science and technology was expanded to reflect the all-pervasive ways in which technology is encountered in daily life, gaining attention of feminists out of concern for female positions in science and technological professions. Rather than asking how women can be better treated within and by science, feminist critics instead chose to focus on how a science deeply involved in masculinity and masculine projects could be used for the emancipation of women.: 18
Today's feminist critique often uses the former demonology of technology as a point of departure to tell a story of progress from liberal to postmodern feminism. According to Judy Wajcman, both liberal and Marxist feminists failed in the analysis of science and technology, because they considered the technology as neutral and did not pay attention to the symbolic dimension of technoscience.
== Feminist technologies and technoscience studies ==
Feminist technoscience studies have become intrinsically linked with practices of Technofeminism and the development of feminist technologies in cultural and critical vernacular. Feminist technoscience studies explore the coded social and historical implications of science and technology on the development of society, including how identity constructs and is constructed by these technologies. Technofeminism emerged in the early 1980s, leaning on the different feminist movements. Feminist scholars reanalyzed the Scientific Revolution, and stated that the resulting science was based on the masculine ideology of exploiting the Earth and control. During this time, nature and scientific inquiry were modelled after misogynous relationships to women. Femininity was associated with nature and considered as something passive to be objectified. This was in contrast to culture, which was represented by objectifying masculinity. This analysis depended on the use of gender imagery to conceptualize the nature of technoscientific masculine ideology.: 85
Judy Wajcman draws parallels between Judith Butler's theory of gender performativity and the construction of technology. Butler conceives gender as a performative act as opposed to a naturalized condition one is born into. Through a fluctuating process achieved in daily social interaction, gender identity is acted and constructed through relational behaviours – it is a fluid concept. Drawing from the work of Butler and Donna Haraway, Amade M'charek analyzes how objects, when linked to another object or signifier, construct identity through the use of human imagination:
Differences and similarities may be stable or not, depending on the maintenance work that goes into the relations that help to produce them. They are neither fundaments nor qualities that are always embodied… Differences are relational. They do not always materialize in bodies (in the flesh, genes, hormones, brains, or the skin). Rather they materialize in the very relations that help to enact them.
In this theory, identity is not the byproduct of genes, but the constant upholding of hierarchical difference relations. Differences in identity are the effect of interferences, performing and enacting and being enacted upon. Technology too, as proposed by Wajcman, is a product of mutual alliances, not objectively given but collectively created in a process of reiteration. To this end, technology exists as both a source and a concurrence of identity relations.
Western technology and science is deeply implicated in the masculine projection and patriarchal domination of women and nature.: 85 After the shift of feminist theory to focus more on technoscience, there was a call for new technology to be based on the needs and values of women, rather than masculine dominated technological development. The differences between female and male needs were asserted by feminist movements, drawing attention to the exclusion of women being served by current technologies.: 22 Reproductive technologies in particular were influenced by this movement. During this time, household technologies, new media, and new technosciences were, for the most part, disregarded.
=== Feminist technologies ===
Feminist technologies are ones that are formed from feminist social relations, but varied definitions and layers of feminism complicate the definition. Deborah Johnson proposes four candidates for feminist technologies:
Technologies that are good for women
Technologies that constitute gender-equitable social relations
Technologies that favor women
Technologies that constitute social relations that are more equitable than those that were constituted by a prior technology or than those that prevail in the wider society
The successes of certain technologies, such as the pap smear for cervical cancer testing, relied on the feminization of technician jobs. The intervention of women outside the technological sphere, like from members of the women's health movement, and public health activists also aided in the tool's development. However, other feminist technologies, such as birth control serve as an example of a feminist technology also shaped in part by dominant masculinity.
Combined oral contraceptive pills were first approved for use in the United States in 1960, during the time of the women's liberation movement. The birth control pill helped make it possible for more women to enter the workforce by giving them the ability to control their own fertility. Decades prior to this, activists such as Margaret Sanger and Katharine McCormick fought for female contraceptives, seeing it as a necessity for the emancipation of women. However, in the 1970s feminists raised critique on male control of the medical and pharmaceutical industry. The male domination of these fields led technologies such as oral contraceptives to be developed around what men considered to be universal, defining characteristics of women (these being their sex and reproductive capabilities). Birth control pills themselves also succeeded in perpetrating and creating this universality – shaped by moral considerations of the natural body, the length of the menstrual cycle was able to be engineered.
Feminist work in design including fields like industrial design, graphic design and fashion design parallels work on feminist technoscience and feminist technology. Isabel Prochner examines feminist design processes and the development of feminist artefacts and technology, stressing that the process should:
Emphasize human life and flourishing over output and growth
Follow best practices in labor, international production and trade
Take place in an empowering workspace
Involve non-hierarchical, interdisciplinary and collaborative work
Address user needs at multiple levels, including support for pleasure, fun and happiness
Create thoughtful products for female users
Create good jobs through production, execution and sale of the design solution
=== Bioethics and capitalism ===
The development of reproductive technologies blur the lines between nature and technology, allowing for the reconfiguration of life itself. Through the advances of genetic technologies, the controlling of pregnancy, childbirth, and motherhood has become increasingly possible through intrusive means. These advances in biotechnology are serving to develop life as a commodity and deepen monetary inequality - a link made by feminist theorists such as Donna Haraway. Genetic engineering also brings about questions in eugenics, leading early radical feminist analysis to declare and attempt to reclaim motherhood as a foundation of female identity.: 79 The idea of a green, natural motherhood was popularized by ecofeminists who celebrated the identification of women with nature, and natural life.: 79
Haraway instead chooses to embrace technology as feminist instead of reverting to this idea of naturalized femininity. By embracing the image of the cyborg, an amalgamation that is neither human/animal nor machine, Haraway explores the ideas of technoscience and gender, conceptualizing a space where gender is an arbitrary, unnecessary construct.: 80
The corporatization of biology through the alteration of nature through technology is also a theme explored by Haraway. The OncoMouse is a laboratory mouse genetically modified to carry a specific gene which increases the creature's chance of developing cancer. Until 2005, American conglomerate DuPoint owned the patent to the OncoMouse, reconfiguring and relegating life to a commodity.: 89 This development in genetic engineering brings up questions about lab animal treatment, as well as ethical questions around class and race. Increasing breast cancer rates in Black women are discussed in ecofeminist analysis of the modification of lab animals from breast cancer research to being the discussion into an ethically ambiguous space. Haraway in particular raises the question of whether modifying and expending a live commodity like OncoMouse is ethical if it leads to the development of a cure for breast cancer.: 91
The reconfiguring of life in biotechnologies and genetic engineering allow for a precedence to be set, leading to capitalist cultural consequences. Through these technologies technoscience becomes naturalized, and also becomes increasingly subject to the process of commodification and capital accumulation in transnational capitalist corporations.: 89 Similar to Marxist and Neo-Marxist analyses of sciences, biotechnologies allow for the concept of commodity to become fetishized as genes are reified to have a monetary value outside of use value. This also positions life and nature as things to be exploited by capitalism.: 90
== See also ==
Cyberfeminism
Digital rhetoric
Annemarie Mol
Donna Haraway
Evelyn Fox Keller
John Law
Judy Wajcman
Karen Barad
Lucy Suchman
Nina Lykke
Sandra Harding
TechnoFeminism
== Further reading ==
Faulkner, Wendy (January 2001). "The technology question in feminism". Women's Studies International Forum. 24 (1): 79–95. doi:10.1016/S0277-5395(00)00166-7.
Giordano, Sara (2017). "Feminists increasing public understandings of science: a feminist approach to developing critical science literacy skills". Frontiers: A Journal of Women Studies. 38 (1): 100–123. doi:10.5250/fronjwomestud.38.1.0100. JSTOR 10.5250/fronjwomestud.38.1.0100. S2CID 152248924.
Xavier, Mínguez Alcaide (January 2015). "Métodos de Diálogo con Grandes Grupos. Herramientas para afrontar la complejidad". Revista de Estudios Sociales (51): 186–197. doi:10.7440/res51.2015.14.
== Notes ==
== References ==
Booth, Shirley (2010). Gender Issues in Learning and Working with Technology: Social Contexts and Cultural Contexts. Hershey, PA: Information Science Reference. p. 69. ISBN 978-1-61520-813-5.
Whelan, Emma (2001). "Politics by Other Means: Feminism and Mainstream Science Studies". The Canadian Journal of Sociology. 26 (4): 535–581. doi:10.2307/3341492. JSTOR 3341492.
Wajcman, Judy (2004). Technofeminism (Reprint ed.). Cambridge, United Kingdom: Polity. ISBN 978-0-7456-3043-4.
Elovaara, Pirjo; Mörtberg, Christina (2010). Travelling thoughtfulness: feminist technoscience stories. Umeå: Department of Informatics, Umeå University. ISBN 978-91-7459-094-4.
Weber, Jutta Davis, Kathy; Evans, Mary; Lorber, Judith (2006). From Science and Technology to Feminist Technoscience (PDF). pp. 397–414. ISBN 9780761943907. In: Handbook of Gender and Women's Studies; Davis K, Evans M, Lorber J
Åsberg, Cecilia; Lykke, Nina (5 November 2010). "Feminist technoscience studies". European Journal of Women's Studies. 17 (4): 299–305. doi:10.1177/1350506810377692. S2CID 146433213.
Gill, Rosalind (March 2005). "Technofeminism". Science as Culture. 14 (1): 97–101. doi:10.1080/09505430500042130. S2CID 219715620.
== External links ==
Feminist Epistemology and Philosophy of Science, Stanford Encyclopedia of Philosophy
van der Velden, Maja; Mörtberg, Christina (November 2012). "Between Need and Desire: Exploring Strategies for Gendering Design". Science, Technology, & Human Values. 37 (6): 663–683. doi:10.1177/0162243911401632. S2CID 146481731.
Review of “Technofeminism” of Judy Wajcman, Universitat Oberta de Catalunya (Spanish)
Norma (Nordic Journal for Masculinity Studies)
International Journal of Feminist Technoscience
Kvinder, Køn & Forskning
Tidsskrift för genusvetenskap
Tidsskrift for kjønnsforskning
Centre for Gender and Women's Studies | Wikipedia/Feminist_technoscience |
Science studies is an interdisciplinary research area that seeks to situate scientific expertise in broad social, historical, and philosophical contexts. It uses various methods to analyze the production, representation and reception of scientific knowledge and its epistemic and semiotic role.
Similarly to cultural studies, science studies are defined by the subject of their research and encompass a large range of different theoretical and methodological perspectives and practices. The interdisciplinary approach may include and borrow methods from the humanities, natural and formal sciences, from scientometrics to ethnomethodology or cognitive science.
Science studies have a certain importance for evaluation and science policy. Overlapping with the field of science, technology and society, practitioners study the relationship between science and technology, and the interaction of expert and lay knowledge in the public realm.
== Scope ==
The field started with a tendency toward navel-gazing: it was extremely self-conscious in its genesis and applications. From early concerns with scientific discourse, practitioners soon started to deal with the relation of scientific expertise to politics and lay people. Practical examples include bioethics, bovine spongiform encephalopathy (BSE), pollution, global warming, biomedical sciences, physical sciences, natural hazard predictions, the (alleged) impact of the Chernobyl disaster in the UK, generation and review of science policy and risk governance and its historical and geographic contexts. While staying a discipline with multiple metanarratives, the fundamental concern is about the role of the perceived expert in providing governments and local authorities with information from which they can make decisions.
The approach poses various important questions about what makes an expert and how experts and their authority are to be distinguished from the lay population and interacts with the values and policy making process in liberal democratic societies.
Practitioners examine the forces within and through which scientists investigate specific phenomena such as
technological milieus, epistemic instruments and cultures and laboratory life (compare Karin Knorr-Cetina, Bruno Latour, Hans-Jörg Rheinberger)
science and technology (e.g. Wiebe Bijker, Trevor Pinch, Thomas P. Hughes)
science, technology and society (e.g. Peter Weingart, Ulrike Felt, Helga Nowotny and Reiner Grundmann)
language and rhetoric of science (e.g. Charles Bazerman, Alan G. Gross, Greg Myers)
aesthetics of science and visual culture in science (u.a. Peter Geimer), the role of aesthetic criteria in scientific practice (compare mathematical beauty) and the relation between emotion, cognition and rationality in the development of science.
semiotic studies of creative processes, as in the discovery, conceptualization, and realization of new ideas. or the interaction and management of different forms of knowledge in cooperative research.
large-scale research and research institutions, e.g. particle colliders (Sharon Traweek)
research ethics, science policy, and the role of the university.
== History of the field ==
In 1935, in a celebrated paper, the Polish sociologist couple Maria Ossowska and Stanisław Ossowski proposed the founding of a "science of science" to study the scientific enterprise, its practitioners, and the factors influencing their work. Earlier, in 1923, the Polish sociologist Florian Znaniecki had made a similar proposal.
Fifty years before Znaniecki, in 1873, Aleksander Głowacki, better known in Poland by his pen name "Bolesław Prus", had delivered a public lecture – later published as a booklet – On Discoveries and Inventions, in which he said:
Until now there has been no science that describes the means for making discoveries and inventions, and the generality of people, as well as many people of learning, believe that there never will be. This is an error. Someday a science of making discoveries and inventions will exist and will render services. It will arise not all at once; first only its general outline will appear, which subsequent researchers will correct and elaborate, and which still later researchers will apply to individual branches of knowledge.
It is striking that, while early 20th-century sociologist proponents of a discipline to study science and its practitioners wrote in general theoretical terms, Prus had already half a century earlier described, with many specific examples, the scope and methods of such a discipline.
Thomas Kuhn's Structure of Scientific Revolutions (1962) increased interest both in the history of science and in science's philosophical underpinnings. Kuhn posited that the history of science was less a linear succession of discoveries than a succession of paradigms within the philosophy of science. Paradigms are broader, socio-intellectual constructs that determine which types of truth claims are permissible.
Science studies seeks to identify key dichotomies – such as those between science and technology, nature and culture, theory and experiment, and science and fine art – leading to the differentiation of scientific fields and practices.
The sociology of scientific knowledge arose at the University of Edinburgh, where David Bloor and his colleagues developed what has been termed "the strong programme". It proposed that both "true" and "false" scientific theories should be treated the same way. Both are informed by social factors such as cultural context and self-interest.
Human knowledge, abiding as it does within human cognition, is ineluctably influenced by social factors.
It proved difficult, however, to address natural-science topics with sociological methods, as was abundantly evidenced by the US science wars. Use of a deconstructive approach (as in relation to works on arts or religion) to the natural sciences risked endangering not only the "hard facts" of the natural sciences, but the objectivity and positivist tradition of sociology itself. The view on scientific knowledge production as a (at least partial) social construct was not easily accepted. Latour and others identified a dichotomy crucial for modernity, the division between nature (things, objects) as being transcendent, allowing to detect them, and society (the subject, the state) as immanent as being artificial, constructed. The dichotomy allowed for mass production of things (technical-natural hybrids) and large-scale global issues that endangered the distinction as such. E.g. We Have Never Been Modern asks to reconnect the social and natural worlds, returning to the pre-modern use of "thing"—addressing objects as hybrids made and scrutinized by the public interaction of people, things, and concepts.
Science studies scholars such as Trevor Pinch and Steve Woolgar started already in the 1980s to involve "technology", and called their field "science, technology and society". This "turn to technology" brought science studies into communication with academics in science, technology, and society programs.
More recently, a novel approach known as mapping controversies has been gaining momentum among science studies practitioners, and was introduced as a course for students in engineering, and architecture schools. In 2002 Harry Collins and Robert Evans asked for a third wave of science studies (a pun on The Third Wave), namely studies of expertise and experience answering to recent tendencies to dissolve the boundary between experts and the public.
== Application to natural and man-made hazards ==
=== Sheepfarming after Chernobyl ===
A showcase of the rather complex problems of scientific information and its interaction with lay persons is Brian Wynne's study of Sheepfarming in Cumbria after the Chernobyl disaster. He elaborated on the responses of sheep farmers in Cumbria, who had been subjected to administrative restrictions because of radioactive contamination, allegedly caused by the nuclear accident at Chernobyl in 1986. The sheep farmers suffered economic losses, and their resistance against the imposed regulation was being deemed irrational and inadequate. It turned out that the source of radioactivity was actually the Sellafield nuclear reprocessing complex; thus, the experts who were responsible for the duration of the restrictions were completely mistaken. The example led to attempts to better involve local knowledge and lay-persons' experience and to assess its often highly geographically and historically defined background.
=== Science studies on volcanology ===
Donovan et al. (2012) used social studies of volcanology to investigate the generation of knowledge and expert advice on various active volcanoes. It contains a survey of volcanologists carried out during 2008 and 2009 and interviews with scientists in the UK, Montserrat, Italy and Iceland during fieldwork seasons. Donovan et al. (2012) asked the experts about the felt purpose of volcanology and what they considered the most important eruptions in historical time. The survey tries to identify eruptions that had an influence on volcanology as a science and to assess the role of scientists in policymaking.
A main focus was on the impact of the Montserrat eruption 1997. The eruption, a classical example of the black swan theory directly killed (only) 19 persons. However the outbreak had major impacts on the local society and destroyed important infrastructure, as the island's airport. About 7,000 people, or two-thirds of the population, left Montserrat; 4,000 to the United Kingdom.
The Montserrat case put immense pressure on volcanologists, as their expertise suddenly became the primary driver of various public policy approaches. The science studies approach provided valuable insights in that situation. There were various miscommunications among scientists. Matching scientific uncertainty (typical of volcanic unrest) and the request for a single unified voice for political advice was a challenge. The Montserrat Volcanologists began to use statistical elicitation models to estimate the probabilities of particular events, a rather subjective method, but allowing to synthesizing consensus and experience-based expertise step by step. It involved as well local knowledge and experience.
Volcanology as a science currently faces a shift of its epistemological foundations of volcanology. The science started to involve more research into risk assessment and risk management. It requires new, integrated methodologies for knowledge collection that transcend scientific disciplinary boundaries but combine qualitative and quantitative outcomes in a structured whole.
== Experts and democracy ==
Science has become a major force in Western democratic societies, which depend on innovation and technology (compare Risk society) to address its risks. Beliefs about science can be very different from those of the scientists themselves, for reasons of e.g. moral values, epistemology or political motivations. The designation of expertise as authoritative in the interaction with lay people and decision makers of all kind is nevertheless challenged in contemporary risk societies, as suggested by scholars who follow Ulrich Beck's theorisation. The role of expertise in contemporary democracies is an important theme for debate among science studies scholars. Some argue for a more widely distributed, pluralist understanding of expertise (Sheila Jasanoff and Brian Wynne, for example), while others argue for a more nuanced understanding of the idea of expertise and its social functions (Collins and Evans, for example).
== See also ==
Logology (study of science)
Merton thesis
Public awareness of science
Science and technology studies
Science and technology studies in India
Social construction of technology
Sociology of scientific knowledge
Sokal affair
== References ==
== Bibliography ==
Science studies, general
Bauchspies, W., Jennifer Croissant and Sal Restivo: Science, Technology, and Society: A Sociological Perspective (Oxford: Blackwell, 2005).
Biagioli, Mario, ed. The Science Studies Reader (New York: Routledge, 1999).
Bloor, David; Barnes, Barry & Henry, John, Scientific knowledge: a sociological analysis (Chicago: University Press, 1996).
Gross, Alan. Starring the Text: The Place of Rhetoric in Science Studies. Carbondale: SIU Press, 2006.
Fuller, Steve, The Philosophy of Science and Technology Studies (New York: Routledge, 2006).
Hess, David J. Science Studies: An Advanced Introduction (New York: NYU Press, 1997).
Jasanoff, Sheila, ed. Handbook of science and technology studies (Thousand Oaks, Calif.: SAGE Publications, 1995).
Latour, Bruno, "The Last Critique," Harper's Magazine (April 2004): 15–20.
Latour, Bruno. Science in Action. Cambridge. 1987.
Latour, Bruno, "Do You Believe in Reality: News from the Trenches of the Science Wars," in Pandora's Hope (Cambridge: Harvard University Press, 1999)
Vinck, Dominique. The Sociology of Scientific Work. The Fundamental Relationship between Science and Society (Cheltenham: Edward Elgar, 2010).
Wyer, Mary; Donna Cookmeyer; Mary Barbercheck, eds. Women, Science and Technology: A Reader in Feminist Science Studies, Routledge 200
Haraway, Donna J. "Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective," in Simians, Cyborgs, and Women: the Reinvention of Nature (New York: Routledge, 1991), 183–201. Originally published in Feminist Studies, Vol. 14, No. 3 (Autumn, 1988), pp. 575–599. (available online)
Foucault, Michel, "Truth and Power," in Power/Knowledge (New York: Pantheon Books, 1997), 109–133.
Porter, Theodore M. Trust in Numbers: The Pursuit of Objectivity in Science and Public Life (Princeton: Princeton University Press, 1995).
Restivo, Sal: "Science, Society, and Values: Toward a Sociology of Objectivity" (Lehigh PA: Lehigh University Press, 1994).
Medicine and biology
Dumit, Joseph (2003). Picturing Personhood: Brain Scans and Biomedical Identity. Princeton: Princeton University Press. ISBN 9780691113982.
Fadiman, Anne (1997). The Spirit Catches You and You Fall Down. New York: Farrar, Straus and Giroux.
Martin, Emily (1999). "Toward an Anthropology of Immunology: The Body as Nation State". In Biagioli, Mario (ed.). The Science Studies Reader. New York: Routledge. pp. 358–71.
Media, culture, society and technology
Hancock, Jeff. Deception and design: the impact of communication technology on lying behavior
Lessig, Lawrence. Free Culture. Penguin USA, 2004. ISBN 1-59420-006-8
MacKenzie, Donald. The Social Shaping of Technology Open University Press: 2nd ed. 1999. ISBN 0-335-19913-5
Mitchell, William J. Rethinking Media Change Thorburn and Jennings eds. Cambridge, Massachusetts : MIT Press, 2003.
Postman, Neil. Amusing Ourselves to Death: Public Discourse in the Age of Show Business. Penguin USA, 1985. ISBN 0-670-80454-1
Rheingold, Howard. Smart Mobs: The Next Social Revolution. Cambridge: Mass., Perseus Publishing. 2002.
== External links ==
Sociology of Science, an introductory article by Joseph Ben-David & Teresa A. Sullivan, Annual Review of Sociology, 1975
The Incommensurability of Scientific and Poetic Knowledge
University of Washington Science Studies Network | Wikipedia/Science_studies |
Science policy is concerned with the allocation of resources for the conduct of science towards the goal of best serving the public interest. Topics include the funding of science, the careers of scientists, and the translation of scientific discoveries into technological innovation to promote commercial product development, competitiveness, economic growth and economic development. Science policy focuses on knowledge production and role of knowledge networks, collaborations, and the complex distributions of expertise, equipment, and know-how. Understanding the processes and organizational context of generating novel and innovative science and engineering ideas is a core concern of science policy. Science policy topics include weapons development, health care and environmental monitoring.
Science policy thus deals with the entire domain of issues that involve science. A large and complex web of factors influences the development of science and engineering that includes government science policymakers, private firms (including both national and multi-national firms), social movements, media, non-governmental organizations, universities, and other research institutions. In addition, science policy is increasingly international as defined by the global operations of firms and research institutions as well as by the collaborative networks of non-governmental organizations and of the nature of scientific inquiry itself.
== History ==
State policy has influenced the funding of public works and science for thousands of years, dating at least from the time of the Mohists, who inspired the study of logic during the period of the Hundred Schools of Thought, and the study of defensive fortifications during the Warring States period in China. General levies of labor and grain were collected to fund great public works in China, including the accumulation of grain for distribution in times of famine, for the building of levees to control flooding by the great rivers of China, for the building of canals and locks to connect rivers of China, some of which flowed in opposite directions to each other, and for the building of bridges across these rivers. These projects required a civil service, the scholars, some of whom demonstrated great mastery of hydraulics.
In Italy, Galileo noted that individual taxation of minute amounts could fund large sums to the State, which could then fund his research on the trajectory of cannonballs, noting that "each individual soldier was being paid from coin collected by a general tax of pennies and farthings, while even a million of gold would not suffice to pay the entire army."
In Great Britain, Lord Chancellor Sir Francis Bacon had a formative effect on science policy with his identification of "experiments of ... light, more penetrating into nature [than what others know]", which today we call the crucial experiment. Governmental approval of the Royal Society recognized a scientific community which exists to this day. British prizes for research spurred the development of an accurate, portable chronometer, which directly enabled reliable navigation and sailing on the high seas, and also funded Babbage's computer.
The professionalization of science, begun in the nineteenth century, was partly enabled by the creation of scientific organizations such as the National Academy of Sciences, the Kaiser Wilhelm Institute, and State funding of universities of their respective nations. In the United States, a member of the National Academy of Sciences can sponsor a Direct Submission for publication in the Proceedings of the National Academy of Sciences. PNAS serves as a channel to recognize research of importance to at least one member of the National Academy of Sciences.
Public policy can directly affect the funding of capital equipment, intellectual infrastructure for industrial research, by providing tax incentives to those organizations who fund research. Vannevar Bush, director of the office of scientific research and development for the U.S. government in July 1945, wrote "Science is a proper concern of government" Vannevar Bush directed the forerunner of the National Science Foundation, and his writings directly inspired researchers to invent the hyperlink and the computer mouse. The DARPA initiative to support computing was the impetus for the Internet Protocol stack. In the same way that scientific consortiums like CERN for high-energy physics have a commitment to public knowledge, access to this public knowledge in physics led directly to CERN's sponsorship of development of the World Wide Web and standard Internet access for all.
== Philosophies of science policy ==
=== Basic versus applied research ===
The programs that are funded are often divided into four basic categories: basic research, applied research, development, and facilities and equipment. Translational research is a newer concept that seeks to bridge the gap between basic science and practical applications.
Basic science attempts to stimulate breakthroughs. Breakthroughs often lead to an explosion of new technologies and approaches. Once the basic result is developed, it is widely published; however conversion into a practical product is left for the free market. However, many governments have developed risk-taking research and development organizations to take basic theoretical research over the edge into practical engineering. In the U.S., this function is performed by DARPA.
In contrast, technology development is a policy in which engineering, the application of science, is supported rather than basic science. The emphasis is usually given to projects that increase important strategic or commercial engineering knowledge. The most extreme success story is undoubtedly the Manhattan Project that developed nuclear weapons. Another remarkable success story was the "X-vehicle" studies that gave the US a lasting lead in aerospace technologies.
These exemplify two disparate approaches: The Manhattan Project was huge, and spent freely on the most risky alternative approaches. The project members believed that failure would result in their enslavement or destruction by Nazi Germany. Each X-project built an aircraft whose only purpose was to develop a particular technology. The plan was to build a few cheap aircraft of each type, fly a test series, often to the destruction of an aircraft, and never design an aircraft for a practical mission. The only mission was technology development.
A number of high-profile technology developments have failed. The US Space Shuttle failed to meet its cost or flight schedule goals. Most observers explain the project as over constrained: the cost goals too aggressive, the technology and mission too underpowered and undefined.
The Japanese fifth generation computer systems project met every technological goal, but failed to produce commercially important artificial intelligence. Many observers believe that the Japanese tried to force engineering beyond available science by brute investment. Half the amount spent on basic research rather might have produced ten times the result.
=== Utilitarian versus monumental science policy ===
Utilitarian policies prioritize scientific projects that significantly reduce suffering for larger numbers of people. This approach would mainly consider the numbers of people that can be helped by a research policy. Research is more likely to be supported when it costs less and has greater benefits. Utilitarian research often pursues incremental improvements rather than dramatic advancements in knowledge, or break-through solutions, which are more commercially viable.
In contrast, monumental science is a policy in which science is supported for the sake of a greater understanding of the universe, rather than for specific short-term practical goals. This designation covers both large projects, often with large facilities, and smaller research that does not have obvious practical applications and are often overlooked. While these projects may not always have obvious practical outcomes, they provide education of future scientists, and advancement of scientific knowledge of lasting worth about the basic building blocks of science.
Practical outcomes do result from many of these "monumental" science programs. Sometimes these practical outcomes are foreseeable and sometimes they are not. A classic example of a monumental science program focused towards a practical outcome is the Manhattan project. An example of a monumental science program that produces unexpected practical outcome is the laser. Coherent light, the principle behind lasing, was first predicted by Einstein in 1916, but not created until 1954 by Charles H. Townes with the maser. The breakthrough with the maser led to the creation of the laser in 1960 by Theodore Maiman. The delay between the theory of coherent light and the production of the laser was partially due to the assumption that it would be of no practical use.
=== Scholastic conservation ===
This policy approach prioritizes efficiently teaching all available science to those who can use it, rather than investing in new science. In particular, the goal is not to lose any existing knowledge, and to find new practical ways to apply the available knowledge. The classic success stories of this method occurred in the 19th century U.S. land-grant universities, which established a strong tradition of research in practical agricultural and engineering methods. More recently, the Green Revolution prevented mass famine over the last thirty years. The focus, unsurprisingly, is usually on developing a robust curriculum and inexpensive practical methods to meet local needs.
== By country ==
Most developed countries usually have a specific national body overseeing national science (including technology and innovation) policy. Many developing countries follow the same fashion. Many governments of developed countries provide considerable funds (primarily to universities) for scientific research (in fields such as physics and geology) as well as social science research (in fields such as economics and history). Much of this is not intended to provide concrete results that may be commercialisable, although research in scientific fields may lead to results that have such potential. Most university research is aimed at gaining publication in peer reviewed academic journals.
A funding body is an organisation that provides research funding in the form of research grants or scholarships. Research councils are funding bodies that are government-funded agencies engaged in the support of research in different disciplines and postgraduate funding. Funding from research councils is typically competitive. As a general rule, more funding is available in science and engineering disciplines than in the arts and social sciences.
=== Australia ===
In Australia, the two main research councils are the Australian Research Council and the National Health and Medical Research Council.
=== Canada ===
In Canada, the three main research councils ("Tri-Council") are the Social Sciences and Humanities Research Council (SSHRC) the Natural Sciences and Engineering Research Council (NSERC) and the Canadian Institutes of Health Research (CIHR). Additional research funding agencies include the Canada Foundation for Innovation, Genome Canada, Sustainable Development Technology Canada, Mitacs and several Tri-Council supported Networks of Centres of Excellence.
=== Brazil ===
In Brazil, two important research agencies are the National Council for Scientific and Technological Development (CNPq, Portuguese: Conselho Nacional de Desenvolvimento Científico e Tecnológico), an organization of the Brazilian federal government under the Ministry of Science and Technology, and São Paulo Research Foundation (FAPESP, Portuguese: Fundação de Amparo à Pesquisa do Estado de São Paulo), a public foundation located in the state of São Paulo, Brazil.
=== European Union ===
The science policy of the European Union is carried out through the European Research Area, a system which integrates the scientific resources of member nations and acts as a "common market" for research and innovation. The European Union's executive body, the European Commission, has a Directorate-General for Research, which is responsible for the Union's science policy. In addition, the Joint Research Centre provides independent scientific and technical advice to the European Commission and Member States of the European Union (EU) in support of EU policies. There is also the recently established European Research Council, the first European Union funding body set up to support investigator-driven research.
There are also European science agencies that operate independently of the European Union, such as the European Science Foundation, European Space Agency, and the European Higher Education Area, created by the Bologna process.
The European environmental research and innovation policy addresses global challenges of pivotal importance for the well-being of European citizens within the context of sustainable development and environmental protection. Research and innovation in Europe is financially supported by the programme Horizon 2020, which is also open to participation worldwide.
=== Germany ===
German research funding agencies include the Deutsche Forschungsgemeinschaft, which covers both science and humanities.
=== India ===
Research funding by the Government of India comes from a number of sources. For basic science and technology research, these include the Council for Scientific and Industrial Research (CSIR), Department of Science and Technology (DST), and University Grants Commission (UGC). For medical research, these include the Indian Council for Medical Research (ICMR), CSIR, DST and Department of Biotechnology (DBT). For applied research, these include the CSIR, DBT and Science and Engineering Research Council (SERC).
Other funding authorities are the Defence Research Development Organisation (DRDO), the Indian Council of Agricultural Research (ICAR), the Indian Space Research Organisation (ISRO), the Department of Ocean Development (DOD), the Indian Council for Social Science Research (ICSSR), and the Ministry of Environment and Forests (MEF) etc.
=== Ireland ===
Irish funding councils include the Irish Research Council (IRC) and the Science Foundation Ireland. The prior Irish Research Council for Science, Engineering and Technology (IRCSET) and the Irish Research Council for the Humanities and Social Sciences (IRCHSS) were merged to form the IRC in March 2012.
=== The Netherlands ===
Dutch research funding agencies include Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO) [1] and Agentschap NL [2]. In 2016, the Netherlands began trials for Self-Organized Funding Allocation (SOFA), a novel method of distributing research funds which proponents believe may have advantages compared to the grant system.
=== Pakistan ===
The Government of Pakistan has mandated that a certain percentage of gross revenue generated by all telecom service providers be allocated to development and research of information and communication technologies. The National ICT R&D Fund was established in January 2007.
=== Russia ===
Under the Soviet Union, much research was routinely suppressed.
Now science in Russia is supported by state and private funds. From the state: the Russian Humanitarian Scientific Foundation (http://www.rfh.ru), the Russian Foundation for Basic Research (www.rfbr.ru), the Russian Science Foundation (http://rscf.ru)
=== Sri Lanka ===
Science and Technology Policy Research Division (STPRD) of the National Science Foundation (NSF), which was established as a statutory body, through an Act of the Parliament of Sri Lanka, is engaged in providing evidence based policy recommendations for policy formulation on science, technology and other fields ensuring the research/innovation eco-system of the country. Accordingly, the Division undertake science, technology and innovation policy research in the areas of importance to make recommendations for policy formulation.
Besides NSF, the national experts, researchers, public universities and non-governmental bodies like National Academy of Sciences of Sri Lanka (NASSL), also provides expert advice on policy matters to the Government.
=== Switzerland ===
Swiss research funding agencies include the Swiss National Science Foundation (SNSF), the innovation promotion agency CTI (CTI/KTI), Ressortforschung des Bundes [3], and Eidgenössische Stiftungsaufsicht [4].
=== United Kingdom ===
In the United Kingdom, the Haldane principle, that decisions about what to spend research funds on should be made by researchers rather than politicians, is still influential in research policy. There are several university departments with a focus on science policy, such as the Science Policy Research Unit. There are seven grant-awarding Research Councils:
Arts and Humanities Research Council (AHRC)
Biotechnology and Biological Sciences Research Council (BBSRC)
Economic and Social Research Council (ESRC)
Engineering and Physical Sciences Research Council (EPSRC)
Medical Research Council (MRC)
Natural Environment Research Council (NERC)
Science and Technology Facilities Council (STFC)
=== United States ===
The United States has a long history of government support for science and technology. Science policy in the United States is the responsibility of many organizations throughout the federal government. Much of the large-scale policy is made through the legislative budget process of enacting the yearly federal budget. Further decisions are made by the various federal agencies which spend the funds allocated by Congress, either on in-house research or by granting funds to outside organizations and researchers.
Research funding agencies in the United States are spread among many different departments, which include:
Defense Advanced Research Projects Agency (DARPA)
United States Department of Energy Office of Science
National Institutes of Health: biomedical research
National Science Foundation: fundamental research and education in all the non-medical fields of science and engineering.
Office of Naval Research
== See also ==
Big Science
Evidence-based policy
Funding bias
Funding of science
History of military science
History of science policy
List of books about the politics of science
List of funding opportunity databases
Metascience
Open access
Operations research
Office of Science and Technology Policy
Patent
Politicization of science
Right to science and culture
Science of science policy
Small Science
Self-Organized Funding Allocation
Intellectual property policy
== Further reading ==
=== Books ===
Science the Endless Frontier.
Pasteur's Quadrant: Basic Science and Technological Innovation
Beyond Sputnik: U.S. Science Policy in the 21st Century
The Honest Broker: Making Sense of Science in Policy and Politics
How Economics Shapes Science
Frontiers Of Illusion: Science, Technology, and the Politics of Progress
Science Policy Up Close
Dangerous Science: Science Policy and Risk Analysis for Scientists and Engineers
=== Journals ===
Issues in Science and Technology
Science and Public Policy
Research Policy
Journal of Science Policy and Governance
== References ==
== External links ==
Media related to Science policy at Wikimedia Commons | Wikipedia/Science_policy |
Science of Team Science (SciTS) is a field of scientific philosophy and methodology focused on understanding and improving cross-disciplinary collaboration in research. The field encompasses conceptual and methodological strategies to understand how scientific teams can be organized to work more effectively. SciTS initiatives are concerned with understanding and managing factors that facilitate or hinder the effectiveness of collaborative science, as well as evaluating its outcomes.
== History ==
Since the 1990s, interest in and large-scale funding for team-based research initiatives has increased, driven by efforts to address complex problems through cross-disciplinary collaboration. Some argue that this trend reflects the growing recognition that addressing multifaceted challenges—such as climate change and public health issues—benefits from partnerships among scientists and practitioners from diverse fields. A systematic review of SciTS literature highlighted it as essential to interprofessional collaborative research and called for its integration into health professions education and clinical practice at the University of Minnesota's NCIPE.
The interdisciplinary nature of SciTS initially emerged from practical concerns raised by funding agencies, which sought to assess the performance of team science, understand its added value, evaluate the return on investment in large research initiatives, and inform scientific policy. The term "science of team science" was first introduced in October 2006 at a conference called The Science of Team Science: Assessing the Value of Transdisciplinary Research, hosted by the National Cancer Institute in Bethesda, Maryland. The SciTS field was further developed in a supplement to the American Journal of Preventive Medicine, published in July 2008. Two years later, the First Annual International Science of Team Science (SciTS) Conference was held on April 22–24, 2010, in Chicago, Illinois, organized by the Northwestern University Clinical and Translational Sciences (NUCATS) Institute.
In 2013, the National Academy of Sciences established a National Research Council Committee on the Science of Team Science to evaluate the current state of knowledge and practice in SciTS. A committee report was later published in 2015.
In 2023, Patrick Forscher and colleagues published a review identifying the benefits of big team science, noting that innovations facilitate the collection of larger samples and support efforts toward reproducibility and generalizability. However, concerns exist that team science could increasingly influence funding priorities, potentially shifting emphasis from applied to more theoretical research areas, as well as leading to unsuccessful large-scale projects. Forscher's recommendations included creating an advisory board and structured bylaws, formalizing feedback mechanisms from contributors, engaging in mentoring, and separating idea generation from project implementation.
== Methods ==
The definition of a successful team may differ depending on the stakeholder. SciTS uses both qualitative and quantitative methods to evaluate the antecedent conditions, collaborative processes, and outcomes associated with team science, as well as the organizational, social, and political context that influences team science.
A 2018 review of literature on SciTS published between 2006 and 2016 identified 109 articles. It reported that 75% of these articles used pre-existing data (e.g., archival data), 62% used bibliometrics, over 40% used surveys, and over 10% used interview and observational data.
== See also ==
Integrative learning
Interactional expertise
Interdisciplinarity
Multidisciplinarity
Multidimensional network
Transdisciplinarity
Global brain
== References ==
== Further reading ==
Azoulay P, Joshua S, Zivin JW (2010). "Superstar Extinction". The Quarterly Journal of Economics. 125 (2): 549–589.
Bennett LM, Gadlin H, Levine-Finley S (2010). "Collaboration and team science: a field guide" (PDF). Bethesda, Maryland: National Institutes of Health. Accessed May 28, 2010.
Börner, Katy; Dall'Asta, Luca; Ke, Weimao; Vespignani, Alessandro (2005). "Studying the emerging global brain: Analyzing and visualizing the impact of co-authorship teams" (PDF). Complexity. 10 (4): 57–67. arXiv:cond-mat/0502147. Bibcode:2005Cmplx..10d..57B. doi:10.1002/cplx.20078. ISSN 1076-2787. S2CID 2190589.
Contractor, Noshir (2009). "The Emergence of Multidimensional Networks". Journal of Computer-Mediated Communication. 14 (3): 743–747. doi:10.1111/j.1083-6101.2009.01465.x. ISSN 1083-6101.
Cummings JN. "A socio-technical framework for identifying team science collaborations that could benefit from cyberinfrastructure". VOSS: National Science Foundation; 2009.
Stokols D, Taylor B, Hall K, Moser R (2006). "The science of team science: an overview of the field" (PDF). Bethesda, Maryland: National Cancer Institute. Accessed May 28, 2010.
Rhoten D (2007). The dawn of networked science. The Chronicle Review. 54. Accessed May 28, 2010.
== External links ==
Annual International Science of Team Science Conference
National Cancer Institute Science of Team Science website | Wikipedia/Science_of_team_science |
The Theory of Forms or Theory of Ideas, also known as Platonic idealism or Platonic realism, is a philosophical theory credited to the Classical Greek philosopher Plato.
A major concept in metaphysics, the theory suggests that the physical world is not as real or true as Forms. According to this theory, Forms—conventionally capitalized and also commonly translated as Ideas—are the timeless, absolute, non-physical, and unchangeable essences of all things, which objects and matter in the physical world merely participate in, imitate, or resemble. In other words, Forms are various abstract ideals that exist even outside of human minds and that constitute the basis of reality. Thus, Plato's Theory of Forms is a type of philosophical realism, asserting that certain ideas are literally real, and a type of idealism, asserting that reality is fundamentally composed of ideas, or abstract objects.
Plato describes these entities only through the characters (primarily Socrates) in his dialogues who sometimes suggest that these Forms are the only objects of study that can provide knowledge. The theory itself is contested by characters within the dialogues, and it remains a general point of controversy in philosophy. Nonetheless, the theory is considered to be a classical solution to the problem of universals.
== Etymology ==
Referring to Forms, Plato used a number of Ancient Greek terms that mainly relate to vision, sight, and appearance, including ἰδέα (idéā; from a root meaning to see), a word that precedes attested philosophical usage. Plato uses these aspects of sight and appearance in his dialogues to explain his Forms, including the supreme one: the Form of the Good. Other terms include εἶδος (eîdos) meaning "visible form", and the related terms μορφή (morphḗ) meaning "shape", and φαινόμενα (phainómena) meaning "appearances", from φαίνω (phaínō) meaning "shine", ultimately from Indo-European *bʰeh₂- or *bhā-. The original meanings of these terms remained stable over the centuries before the beginning of Western philosophy, at which time they became equivocal, acquiring additional specialized philosophic meanings. Plato used the terms eidos and idea interchangeably.
== Pre-Socratic philosophy ==
The pre-Socratic philosophers, ancient Greek thinkers born before Plato, noted that appearances change, and they began to ask what the thing that changes "really" is. If something changes, what component or essence of it remains "real"? The answer was substance, which stands under the changes and is the actually existing thing being seen. The status of appearances now came into question, including how the appearance is related to the substance. For instance, the earliest known pre-Socratic philosopher, Thales, argued that the fundamental substance all things are made of is water.
Scriptures written by Pythagoras, another pre-Socratic philosopher, suggest that he developed an earlier theory similar to Plato's Forms. For Pythagoras, like Plato, the substance or essence of all things was not something physical (like water) but rather something abstract. However, Pythagoras's theory was much narrower than Plato's, proposing that the non-physical and timeless essences that compose the physical world are specifically numbers, whereas Plato conceived of his Forms as a vast array of intangible ideals.
== Plato's Forms ==
The Forms are expounded upon in Plato's dialogues and general speech, in that every object or quality in reality—dogs, human beings, mountains, colors, courage, love, and goodness—has a Form. Form answers the question, "What is that?" Plato was going a step further and asking what Form itself is. He supposed that the object was essentially or "really" the Form and that the phenomena were mere shadows mimicking the Form; that is, momentary portrayals of the Form under different circumstances. The problem of universals – how can one thing in general be many things in particular – was solved by presuming that Form was a distinct singular thing but caused plural representations of itself in particular objects. For example, in the dialogue Parmenides, Socrates states: "Nor, again, if a person were to show that all is one by partaking of one, and at the same time many by partaking of many, would that be very astonishing. But if he were to show me that the absolute one was many, or the absolute many one, I should be truly amazed.": 129 Matter is considered particular in itself. For Plato, Forms, such as beauty, are more real than any objects that imitate them. Though the Forms are timeless and unchanging, physical things are in a constant change of existence. Where Forms are unqualified perfection, physical things are qualified and conditioned.
These Forms are the essences of various objects: they are that without which a thing would not be the kind of thing it is. For example, there are countless tables in the world but the Form of tableness is at the core; it is the essence of all of them. Plato's Socrates held that the world of Forms is transcendent to our own world (the world of substances) and also is the essential basis of reality. Super-ordinate to matter, Forms are the most pure of all things. Furthermore, he believed that true knowledge/intelligence is the ability to grasp the world of Forms with one's mind.
A Form is aspatial (transcendent to space) and atemporal (transcendent to time). In the world of Plato, atemporal means that it does not exist within any time period, rather it provides the formal basis for time. It therefore formally grounds beginning, persisting and ending. It is neither eternal in the sense of existing forever, nor mortal, of limited duration. It exists transcendent to time altogether. Forms are aspatial in that they have no spatial dimensions, and thus no orientation in space, nor do they even (like the point) have a location. They are non-physical, but they are not in the mind. Forms are extra-mental (i.e. real in the strictest sense of the word).
A Form is an objective "blueprint" of perfection. The Forms are perfect and unchanging representations of objects and qualities. For example, the Form of beauty or the Form of a triangle. For the form of a triangle say there is a triangle drawn on a blackboard. A triangle is a polygon with 3 sides. The triangle as it is on the blackboard is far from perfect. However, it is only the intelligibility of the Form "triangle" that allows us to know the drawing on the chalkboard is a triangle, and the Form "triangle" is perfect and unchanging. It is exactly the same whenever anyone chooses to consider it; however, time only affects the observer and not the triangle. It follows that the same attributes would exist for the Form of beauty and for all Forms.
Plato explains how we are always many steps away from the idea or Form. The idea of a perfect circle can have us defining, speaking, writing, and drawing about particular circles that are always steps away from the actual being. The perfect circle, partly represented by a curved line, and a precise definition, cannot be drawn. The idea of the perfect circle is discovered, not invented.
=== Intelligible realm and separation of the Forms ===
Plato often invokes, particularly in his dialogues Phaedo, Republic and Phaedrus, poetic language to illustrate the mode in which the Forms are said to exist. Near the end of the Phaedo, for example, Plato describes the world of Forms as a pristine region of the physical universe located above the surface of the Earth (Phd. 109a–111c). In the Phaedrus the Forms are in a "place beyond heaven" (hyperouranios topos) (Phdr. 247c ff); and in the Republic the sensible world is contrasted with the intelligible realm (noēton topon) in the famous Allegory of the Cave.
It would be a mistake to take Plato's imagery as positing the intelligible world as a literal physical space apart from this one. Plato emphasizes that the Forms are not beings that extend in space (or time), but subsist apart from any physical space whatsoever. Thus we read in the Symposium of the Form of Beauty: "It is not anywhere in another thing, as in an animal, or in earth, or in heaven, or in anything else, but itself by itself with itself," (211b). And in the Timaeus Plato writes: "Since these things are so, we must agree that that which keeps its own form unchangingly, which has not been brought into being and is not destroyed, which neither receives into itself anything else from anywhere else, nor itself enters into anything anywhere, is one thing," (52a, emphasis added).
=== Ambiguities of the theory ===
Plato's conception of Forms actually differs from dialogue to dialogue, and in certain respects it is never fully explained, so many aspects of the theory are open to interpretation. Forms are first introduced in the Phaedo, but in that dialogue the concept is simply referred to as something the participants are already familiar with, and the theory itself is not developed. Similarly, in the Republic, Plato relies on the concept of Forms as the basis of many of his arguments but feels no need to argue for the validity of the theory itself or to explain precisely what Forms are. Commentators have been left with the task of explaining what Forms are and how visible objects participate in them, and there has been no shortage of disagreement. Some scholars advance the view that Forms are paradigms, perfect examples on which the imperfect world is modeled. Others interpret Forms as universals, so that the Form of Beauty, for example, is that quality that all beautiful things share. Yet others interpret Forms as "stuffs," the conglomeration of all instances of a quality in the visible world. Under this interpretation, we could say there is a little beauty in one person, a little beauty in another – all the beauty in the world put together is the Form of Beauty. Plato himself was aware of the ambiguities and inconsistencies in his Theory of Forms, as is evident from the incisive criticism he makes of his own theory in the Parmenides.
== Evidence of Forms ==
=== Human perception ===
In Cratylus, Plato writes:But if the very nature of knowledge changes, at the time when the change occurs there will be no knowledge, and, according to this view, there will be no one to know and nothing to be known: but if that which knows and that which is known exist ever, and the beautiful and the good and every other thing also exist, then I do not think that they can resemble a process of flux, as we were just now supposing.
Plato believed that long before our bodies ever existed, our souls existed and inhabited heaven, where they became directly acquainted with the forms themselves. Real knowledge, to him, was knowledge of the forms. But knowledge of the forms cannot be gained through sensory experience because the forms are not in the physical world. Therefore, our real knowledge of the forms must be the memory of our initial acquaintance with the forms in heaven. Therefore, what we seem to learn is in fact just remembering.
=== Perfection ===
No one has ever seen a perfect circle, nor a perfectly straight line, yet everyone knows what a circle and a straight line are. Plato uses the tool-maker's blueprint as evidence that Forms are real:... when a man has discovered the instrument which is naturally adapted to each work, he must express this natural form, and not others which he fancies, in the material ....
Perceived circles or lines are not exactly circular or straight, and true circles and lines could never be detected since by definition they are sets of infinitely small points. But if the perfect ones were not real, how could they direct the manufacturer?
== Criticisms of Platonic Forms ==
=== Self-criticism ===
One difficulty lies in the conceptualization of the "participation" of an object in a form (or Form). The young Socrates conceives of his solution to the problem of the universals in another metaphor:
Nay, but the idea may be like the day which is one and the same in many places at once, and yet continuous with itself; in this way each idea may be one and the same in all at the same time.
But exactly how is a Form like the day in being everywhere at once? The solution calls for a distinct form, in which the particular instances, which are not identical to the form, participate; i.e., the form is shared out somehow like the day to many places. The concept of "participate", represented in Greek by more than one word, is as obscure in Greek as it is in English. Plato hypothesized that distinctness meant existence as an independent being, thus opening himself to the famous third man argument of Parmenides, which proves that forms cannot independently exist and be participated.
If universal and particulars – say man or greatness – all exist and are the same then the Form is not one but is multiple. If they are only like each other then they contain a form that is the same and others that are different. Thus if we presume that the Form and a particular are alike then there must be another, or third Form, man or greatness by possession of which they are alike. An infinite regression would then result; that is, an endless series of third men. The ultimate participant, greatness, rendering the entire series great, is missing. Moreover, any Form is not unitary but is composed of infinite parts, none of which is the proper Form.
The young Socrates did not give up the Theory of Forms over the Third Man but took another tack, that the particulars do not exist as such. Whatever they are, they "mime" the Forms, appearing to be particulars. This is a clear dip into representationalism, that we cannot observe the objects as they are in themselves but only their representations. That view has the weakness that if only the mimes can be observed then the real Forms cannot be known at all and the observer can have no idea of what the representations are supposed to represent or that they are representations.
Socrates' later answer would be that men already know the Forms because they were in the world of Forms before birth. The mimes only recall these Forms to memory.
=== Aristotelian criticism ===
The topic of Aristotle's criticism of Plato's Theory of Forms is a large one and continues to expand. Rather than quote Plato, Aristotle often summarized. Classical commentaries thus recommended Aristotle as an introduction to Plato, even when in disagreement; the Platonist Syrianus used Aristotelian critiques to further refine the Platonic position on forms in use in his school, a position handed down to his student Proclus. As a historian of prior thought, Aristotle was invaluable, however this was secondary to his own dialectic and in some cases he treats purported implications as if Plato had actually mentioned them, or even defended them. In examining Aristotle's criticism of The Forms, it is helpful to understand Aristotle's own hylomorphic forms, by which he intends to salvage much of Plato's theory.
Plato distinguished between real and non-real "existing things", where the latter term is used of substance. The figures that the artificer places in the gold are not substance, but gold is. Aristotle stated that, for Plato, all things studied by the sciences have Form and asserted that Plato considered only substance to have Form. Uncharitably, this leads him to something like a contradiction: Forms existing as the objects of science, but not-existing as substance. Scottish philosopher W.D. Ross objects to this as a mischaracterization of Plato.
Plato did not claim to know where the line between Form and non-Form is to be drawn. As Cornford points out, those things about which the young Socrates (and Plato) asserted "I have often been puzzled about these things" (in reference to Man, Fire and Water), appear as Forms in later works. However, others do not, such as Hair, Mud, Dirt. Of these, Socrates is made to assert, "it would be too absurd to suppose that they have a Form."
Ross also objects to Aristotle's criticism that Form Otherness accounts for the differences between Forms and purportedly leads to contradictory forms: the Not-tall, the Not-beautiful, etc. That particulars participate in a Form is for Aristotle much too vague to permit analysis. By one way in which he unpacks the concept, the Forms would cease to be of one essence due to any multiple participation. As Ross indicates, Plato didn't make that leap from "A is not B" to "A is Not-B." Otherness would only apply to its own particulars and not to those of other Forms. For example, there is no Form Not-Greek, only particulars of Form Otherness that somehow suppress Form Greek.
Regardless of whether Socrates meant the particulars of Otherness yield Not-Greek, Not-tall, Not-beautiful, etc., the particulars would operate specifically rather than generally, each somehow yielding only one exclusion.
Plato had postulated that we know Forms through a remembrance of the soul's past lives and Aristotle's arguments against this treatment of epistemology are compelling. For Plato, particulars somehow do not exist, and, on the face of it, "that which is non-existent cannot be known". See Metaphysics III 3–4.
=== Scholastic criticism ===
Nominalism (from Latin nomen, "name") says that ideal universals are mere names, human creations; the blueness shared by sky and blue jeans is a shared concept, communicated by our word "blueness". Blueness is held not to have any existence beyond that which it has in instances of blue things. This concept arose in the Middle Ages, as part of Scholasticism.
Scholasticism was a highly multinational, polyglottal school of philosophy, and the nominalist argument may be more obvious if an example is given in more than one language. For instance, colour terms are strongly variable by language; some languages consider blue and green the same colour, others have monolexemic terms for several shades of blue, which are considered different; other languages, like the Mandarin qing denote both blue and black. The German word "Stift" means a pen or a pencil, and also anything of the same shape. The English "pencil" originally meant "small paintbrush"; the term later included the silver rod used for silverpoint. The German "Bleistift" and "Silberstift" can both be called "Stift", but this term also includes felt-tip pens, which are clearly not pencils.
The shifting and overlapping nature of these concepts makes it easy to imagine them as mere names, with meanings not rigidly defined, but specific enough to be useful for communication. Given a group of objects, how is one to decide if it contains only instances of a single Form, or several mutually exclusive Forms?
== See also ==
== Notes ==
== Primary sources ==
Dialogues that discuss Forms
The theory is presented in the following dialogues:
== Bibliography ==
Alican, Necip Fikri; Thesleff, Holger (2013). "Rethinking Plato's Forms". Arctos: Acta Philologica Fennica. 47: 11–47. ISSN 0570-734X.
Alican, Necip Fikri (2014). "Rethought Forms: How Do They Work?". Arctos: Acta Philologica Fennica. 48: 25–55. ISSN 0570-734X.
Cornford, Francis MacDonald (1957). Plato and Parmenides. New York: The Liberal Arts Press.
Dancy, Russell (2004). Plato's Introduction of Forms. Cambridge: Cambridge University Press. ISBN 978-0-521037-18-1.{{cite book}}: CS1 maint: publisher location (link)
Fine, Gail (1993). On Ideas: Aristotle's Criticism of Plato's Theory of Forms. Oxford: Oxford University Press. ISBN 978-0-198235-49-1. OCLC 191827006.{{cite book}}: CS1 maint: publisher location (link) Reviewed by Gerson, Lloyd P (1993). "Gail Fine, On Ideas. Aristotle's Criticism of Plato's Theory of Forms". Bryn Mawr Classical Review.
Fine, Gail (2003). Plato on Knowledge and Forms: Selected Essays. Oxford: Clarendon Press. ISBN 978-0-199245-59-8.{{cite book}}: CS1 maint: publisher location (link)
Grabowski, Francis A. III (2008). Plato, Metaphysics and the Forms. Continuum Studies in Ancient Philosophy. Continuum.
Matía Cubillo, Gerardo Óscar (2021). "Suggestions on How to Combine the Platonic Forms to Overcome the Interpretative Difficulties of the Parmenides Dialogue", Revista de Filosofía de la Universidad de Costa Rica, vol. 60, 156: 157–171.
Patterson, Richard (1985). Image and Reality in Plato's Metaphysics. Indianapolis: Hackett Publishing Company. ISBN 978-0-915145-72-0.{{cite book}}: CS1 maint: publisher location (link)
Rodziewicz, Artur (2012). IDEA AND FORM. ΙΔΕΑ ΚΑΙ ΕΙΔΟΣ. On the Foundations of the Philosophy of Plato and the Presocratics (IDEA I FORMA. ΙΔΕΑ ΚΑΙ ΕΙΔΟΣ. O fundamentach filozofii Platona i presokratyków). Wroclaw: WUWR.
Ross, William David (1951). Plato's Theory of Ideas. Oxford: Clarendon Press. ISBN 978-0-837186-35-1. {{cite book}}: ISBN / Date incompatibility (help)CS1 maint: publisher location (link)
Thesleff, Holger (2009). Platonic Patterns: A Collection of Studies by Holger Thesleff. Las Vegas: Parmenides Publishing. ISBN 978-1-930972-29-2.{{cite book}}: CS1 maint: publisher location (link)
Welton, William A., ed. (2002). Plato's Forms: Varieties of Interpretation. Lanham: Rowman & Littlefield. ISBN 978-0-7391-0514-6.
== External links ==
"Form" . Encyclopædia Britannica (11th ed.). 1911.
Cohen, Marc (2006). "Theory of Forms". Philosophy 320: History of Ancient Philosophy. University of Washington Philosophy Department.
"Lesson Three: Plato's Theory of Forms". International Catholic University.
Ruggiero, Tim (July 2002). "Plato And The Theory of Forms". philosophical society.com.
Silverman, Allan. "Plato's Middle Period Metaphysics and Epistemology". In Zalta, Edward N. (ed.). Stanford Encyclopedia of Philosophy.
Balaguer, Mark. "Platonism in Metaphysics". In Zalta, Edward N. (ed.). Stanford Encyclopedia of Philosophy. | Wikipedia/Theory_of_forms |
An academy of sciences is a type of learned society or academy (as special scientific institution) dedicated to sciences that may or may not be state funded. Some state funded academies are national, or royal (i.e. United Kingdom's Royal Society of London for Improving Natural Knowledge) as a form of honor.
The other type of academies are Academy of Arts or combination of both (e.g., American Academy of Arts and Sciences).
Academy of Letters is another related expression, encompassing literature.
In non-English-speaking countries, the range of academic fields of the members of a national Academy of Science often includes scholarly disciplines which would not normally be classed as "science" in English. Many languages use a broad term for systematized learning which includes both natural sciences and social sciences and fields such as literary studies, linguistics, history, or art history. (Often these terms are calques from Latin scientia (the etymological source of English science) and, accordingly, derivatives of the verb 'know', such as German Wissenschaft, Swedish vetenskap, Hungarian tudomány, Estonian teadus or Finnish tiede.) Accordingly, for example the Austrian Academy of Sciences (Österreichische Akademie der Wissenschaften), the Hungarian Academy of Sciences (Magyar Tudományos Akadémia), or the Estonian Academy of Sciences (Eesti Teaduste Akadeemia) also cover the areas of social sciences and humanities.
As the engineering sciences have become more varied and advanced, there is a recent trend in many advanced countries to organize the National Academy of Engineering (or National Academy of Engineering Sciences), separate from the national academy of sciences.
Academies of science play an important role in science diplomacy efforts.
Academies are increasingly organized in regional or even international academies. The Interacademy Partnership for example is a global network consisting of over 140 national, regional and global member academies of science, engineering and medicine. Pan-Europe academies include the Academia Europaea and the European Academy of Sciences and Arts. Additionally, there are many regional associations such as ALLEA in Europe, NASAC as the Network of African Science Academies, IANAS in Latin America, and AASSA in Asia.
The International Science Council brings together international scientific unions and associations as well as national and regional scientific organizations such as academies and research councils from the natural sciences, social sciences and the humanities.
Apart from national academies of science, there are now increasingly also national young academies. National young academies usually select members for a limited term, normally 4–5 years, after which members become academy alumni. Young academies typically engage with issues important to young scientists. These include, for example, science education or the dialog between science and society. Most young academies are affiliated with a senior Academy of Sciences or with a network of senior academies. The Global Young Academy, which itself is a science academy (e.g. full member of Interacademy Partnership) often serves as a facilitator of the growing global network of young academies. Since its creation, more than 35 national young academies have been established. In 2019, there were 41 national young academies.
== List ==
World
Developing world – The World Academy of Sciences (TWAS)
Academy – World Academy of Art and Science
International Science Council
Europe
Academia Europaea
European Academy of Sciences and Arts
ASEAN – ASEAN Academy of Engineering and Technology
Afghanistan – Academy of Sciences of Afghanistan
Albania – Academy of Sciences of Albania
Argentina – National Academy of Sciences of Argentina
Armenia – National Academy of Sciences of Armenia
Austria – Austrian Academy of Sciences
Australia – Australian Academy of Science
Azerbaijan – National Academy of Sciences of Azerbaijan
Bangladesh – Bangladesh Academy of Sciences
Belarus – National Academy of Sciences of Belarus
Belgium – Royal Academies for Science and the Arts of Belgium
Brazil – Brazilian Academy of Sciences
Bulgaria – Bulgarian Academy of Sciences
Canada
Royal Society of Canada
Canadian Academy of Engineering
China
Chinese Academy of Sciences
Chinese Academy of Engineering
Chinese Academy of Social Sciences
Costa Rica – Academia Nacional de Ciencias (Costa Rica)
Croatia – Croatian Academy of Sciences and Arts
Czech Republic – Czech Academy of Sciences
Denmark – Royal Danish Academy of Sciences and Letters
Estonia – Estonian Academy of Sciences
Finland
Finnish Society of Sciences and Letters
Finnish Academy of Science and Letters
France – French Academy of Sciences
Georgia
Georgian National Academy of Sciences
Abkhazian Regional Academy of Sciences
Germany
German National Academy of Sciences Leopoldina
Union of Regional German Academies of Sciences and Humanities:
Akademie der Wissenschaften und der Literatur
Academy of Sciences and Humanities in Hamburg
Bavarian Academy of Sciences and Humanities
Berlin-Brandenburg Academy of Sciences and Humanities
Göttingen Academy of Sciences and Humanities
Heidelberg Academy for Sciences and Humanities
Saxon Academy of Sciences and Humanities
acatech
Ghana – Ghana Academy of Arts and Sciences
Greece – Academy of Athens
Hong Kong
Hong Kong Academy of Sciences
Hong Kong Academy of Engineering
Hong Kong Academy of the Humanities
Hungary – Hungarian Academy of Sciences
India
Indian Academy of Sciences
Indian National Science Academy
National Academy of Sciences, India
Indonesia
Indonesian Institute of Sciences
Indonesian Academy of Sciences
Iran – Academy of Sciences of Iran
Italy
Lincean Academy
Accademia Pontaniana
Accademia Cosentina
Accademia Nazionale delle Scienze (detta dei XL)
Accademia Nazionale Virgiliana di Scienze Lettere ed Arti
Istituto Lombardo Accademia di Scienze e Lettere
Israel – Israel Academy of Sciences and Humanities
Japan
Science Council of Japan
Japan Academy
Kazakhstan – National Academy of Sciences of the Republic of Kazakhstan
Kyrgyzstan – National Academy of Sciences of the Kyrgyz Republic
Latvia – Latvian Academy of Sciences
Lebanon – Lebanese Academy of Sciences
Liechtenstein - Naturwissenschaftliches Forum
Lithuania – Lithuanian Academy of Sciences
Malaysia – Akademi Sains Malaysia
Mexico – Mexican Academy of Sciences
Moldova – Academy of Sciences of Moldova
Mongolia – Mongolian Academy of Sciences
Montenegro
Montenegrin Academy of Sciences and Arts
Doclean Academy of Sciences and Arts
Morocco – Hassan II Academy of Sciences and Technologies
Netherlands – Royal Netherlands Academy of Sciences
New Zealand – Royal Society of New Zealand
Nigeria – Nigerian Academy of Science
North Korea – Academy of Sciences of the Democratic People's Republic of Korea
North Macedonia – Macedonian Academy of Sciences and Arts
Norway
Norwegian Academy of Science and Letters
Royal Norwegian Society of Science and Letters
Norwegian Academy of Technological Sciences
Pakistan – Pakistan Academy of Sciences
Philippines - National Academy of Science and Technology
Poland
Polish Academy of Sciences
Polish Academy of Learning
Portugal
Lisbon Academy of Sciences
Lisbon Geographic Society
Romania – Romanian Academy
Russia – Russian Academy of Sciences
San Marino – International Academy of Sciences San Marino
Serbia – Serbian Academy of Sciences and Arts
Singapore – Singapore National Academy of Science
Slovakia – Slovak Academy of Sciences
Slovenia – Slovenian Academy of Sciences and Arts
South Africa
Academy of Science of South Africa
Royal Society of South Africa
Suid-Afrikaanse Akademie vir Wetenskap en Kuns
South Korea – National Academy of Sciences, Republic of Korea
Soviet Union – Soviet Academy of Sciences
Spain – Spanish Royal Academy of Sciences
Sri Lanka – National Academy of Sciences of Sri Lanka
Sweden – Royal Swedish Academy of Sciences
Switzerland – Swiss Academies of Arts and Sciences
Taiwan – Academia Sinica
Thailand – Royal Institute of Thailand
Turkey – Turkish Academy of Sciences
Ukraine – National Academy of Sciences of Ukraine
United Kingdom
Royal Society
Royal Academy of Engineering
Academy of Medical Sciences
British Academy
Scotland – Royal Society of Edinburgh
United States
National Academies
U.S. National Academy of Sciences
U.S. National Academy of Engineering
U.S. National Academy of Medicine formerly the Institute of Medicine
National Research Council
American Academy of Arts and Sciences
State-specific
California – California Academy of Sciences
Missouri – Academy of Science, St. Louis
New York – New York Academy of Sciences
Pennsylvania - Pennsylvania Academy of Science
Vatican City – Pontifical Academy of Sciences
Jordan and the Islamic world – Islamic World Academy of Sciences (IAS)
== See also ==
National academy
== References == | Wikipedia/Academy_of_sciences |
Criticism of science addresses problems within science in order to improve science as a whole and its role in society. Criticisms come from philosophy, from social movements like feminism, and from within science itself.
The emerging field of metascience seeks to increase the quality of and efficiency of scientific research by improving the scientific process.
== Philosophical critiques ==
Philosopher of science Paul Feyerabend advanced the idea of epistemological anarchism, which holds that there are no useful and exception-free methodological rules governing the progress of science or the growth of knowledge, and that the idea that science can or should operate according to universal and fixed rules is unrealistic, pernicious and detrimental to science itself. Feyerabend advocates a democratic society where science is treated as equal to other ideologies or social institutions such as religion, and education, or magic and mythology, and considers the dominance of science in society authoritarian and unjustified. He also contended (along with Imre Lakatos) that the demarcation problem of distinguishing science from pseudoscience on objective grounds is not possible and thus fatal to the notion of science running according to fixed, universal rules.
Feyerabend also criticized science for not having evidence for its own philosophical precepts. Particularly the notion of Uniformity of Law and the Uniformity of Process across time and space, or Uniformitarianism in short, as noted by Stephen Jay Gould. "We have to realize that a unified theory of the physical world simply does not exist" says Feyerabend, "We have theories that work in restricted regions, we have purely formal attempts to condense them into a single formula, we have lots of unfounded claims (such as the claim that all of chemistry can be reduced to physics), phenomena that do not fit into the accepted framework are suppressed; in physics, which many scientists regard as the one really basic science, we have now at least three different points of view...without a promise of conceptual (and not only formal) unification". In other words, science is begging the question when it presupposes that there is a universal truth with no proof thereof.
Historian Jacques Barzun termed science "a faith as fanatical as any in history" and warned against the use of scientific thought to suppress considerations of meaning as integral to human existence.
Sociologist Stanley Aronowitz scrutinized science for operating with the presumption that the only acceptable criticisms of science are those conducted within the methodological framework that science has set up for itself. That science insists that only those who have been inducted into its community, through means of training and credentials, are qualified to make these criticisms. Aronowitz also alleged that while scientists consider it absurd that Fundamentalist Christianity uses biblical references to bolster their claim that the Bible is true, scientists pull the same tactic by using the tools of science to settle disputes concerning its own validity.
New-age writer Alan Watts criticized science for operating under a materialist model of the world that he posited is simply a modified version of the Abrahamic worldview, that "the universe is constructed and maintained by a Lawmaker" (commonly identified as God or the Logos). Watts asserts that during the rise of secularism through the 18th to 20th century when scientific philosophers got rid of the notion of a lawmaker they kept the notion of law, and that the idea that the world is a material machine run by law is a presumption just as unscientific as religious doctrines that affirm it is a material machine made and run by a lawmaker.
=== Epistemology ===
David Parkin compared the epistemological stance of science to that of divination. He suggested that, to the degree that divination is an epistemologically specific means of gaining insight into a given question, science itself can be considered a form of divination that is framed from a Western view of the nature (and thus possible applications) of knowledge.
Author and Episkopos of Discordianism Robert Anton Wilson stresses that the instruments used in scientific investigation produce meaningful answers relevant only to the instrument, and that there is no objective vantage point from which science could verify its findings since all findings are relative to begin with.
=== Ethics ===
Several academics have offered critiques concerning ethics in science. In Science and Ethics, for example, the professor of philosophy Bernard Rollin examines the relevance of ethics to science, and argues in favor of making education in ethics part and parcel of scientific training.
Social science scholars, like social anthropologist Tim Ingold, and scholars from philosophy and the humanities, like critical theorist Adorno, have criticized modern science for subservience to economic and technological interests. A related criticism is the debate on positivism. While before the 19th century science was perceived to be in opposition to religion, in contemporary society science is often defined as the antithesis of the humanities and the arts.
Many thinkers, such as Carolyn Merchant, Theodor Adorno and E. F. Schumacher considered that the 17th century Scientific Revolution shifted science from a focus on understanding nature, or wisdom, to a focus on manipulating nature, i.e. power, and that science's emphasis on manipulating nature leads it inevitably to manipulate people, as well. Science's focus on quantitative measures has led to critiques that it is unable to recognize important qualitative aspects of the world.
== Critiques from within science ==
Metascience is the use of scientific methodology to study science itself, with the goal of increasing the quality of research while reducing waste. Meta-research has identified methodological weaknesses in many areas of science. Critics argue that reforms are needed to address these weaknesses.
=== Reproducibility ===
The social sciences, such as social psychology, have long suffered from the problem of their studies being largely not reproducible. Now, medicine has come under similar pressures. In a phenomenon known as the replication crisis, journals are less likely to publish straight replication studies so it may be difficult to disprove results. Another result of publication bias is the Proteus phenomenon: early attempts to replicate results tend to contradict them. However, there are claims that this bias may be beneficial, allowing accurate meta-analysis with fewer publications.
=== Cognitive biases ===
Critics argue that the biggest bias within science is motivated reasoning, whereby scientists are more likely to accept evidence that supports their hypothesis and more likely to scrutinize findings that do not. Scientists do not practice pure induction but instead often come into science with preconceived ideas and often will, unconsciously or consciously, interpret observations to support their own hypotheses through confirmation bias. For example, scientists may re-run trials when they do not support a hypothesis but use results from the first trial when they do support their hypothesis. It is often argued that while each individual has cognitive biases, these biases are corrected for when scientific evidence converges. However, systematic issues in the publication system of academic journals can often compound these biases. Issues like publication bias, where studies with non-significant results are less likely to be published, and selective outcome reporting bias, where only the significant outcomes out of a variety of outcomes are likely to be published, are common within academic literature. These biases have widespread implications, such as the distortion of meta-analyses where only studies that include positive results are likely to be included. Statistical outcomes can be manipulated as well, for example large numbers of participants can be used and trials overpowered so that small difference cause significant effects or inclusion criteria can be changed to include those are most likely to respond to a treatment. Whether produced on purpose or not, all of these issues need to be taken into consideration within scientific research, and peer-reviewed published evidence should not be assumed to be outside of the realm of bias and error; some critics are now claiming that many results in scientific journals are false or exaggerated.
Science has been criticized for being too conformist, and for becoming on average less disruptive.
== Feminist critiques ==
Feminist scholars and women scientists such as Emily Martin, Evelyn Fox Keller, Ruth Hubbard, Londa Schiebinger and Bonnie Spanier have critiqued science because they believe it presents itself as objective and neutral while ignoring its inherent gender bias. They assert that gender bias exists in the language and practice of science, as well as in the expected appearance and social acceptance of who can be scientists within society.
Sandra Harding says that the "moral and political insights of the women's movement have inspired social scientists and biologists to raise critical questions about the ways traditional researchers have explained gender, sex, and relations within and between the social and natural worlds." Anne Fausto-Sterling is a prominent example of this kind of feminist work within biological science. Some feminists, such as Ruth Hubbard and Evelyn Fox Keller, criticize traditional scientific discourse as being historically biased towards a male perspective. A part of the feminist research agenda is the examination of the ways in which power inequities are created and/or reinforced in scientific and academic institutions.
Other feminist scholars, such as Ann Hibner Koblitz, Lenore Blum, Mary Gray, Mary Beth Ruskai, and Pnina Abir-Am and Dorinda Outram, have criticized some gender and science theories for ignoring the diverse nature of scientific research and the tremendous variation in women's experiences in different cultures and historical periods. For example, the first generation of women to receive advanced university degrees in Europe were almost entirely in the natural sciences and medicine—in part because those fields at the time were much more welcoming of women than were the humanities. Koblitz and others who are interested in increasing the number of women in science have expressed concern that some of the statements by feminist critics of science could undermine those efforts, notably the following assertion by Keller:
Just as surely as inauthenticity is the cost a woman suffers by joining men in misogynist jokes, so it is, equally, the cost suffered by a woman who identifies with an image of the scientist modeled on the patriarchal husband. Only if she undergoes a radical disidentification from self can she share masculine pleasure in mastering a nature cast in the image of woman as passive, inert, and blind.
=== Language in science ===
Emily Martin examines the metaphors used in science to support her claim that science reinforces socially constructed ideas about gender rather than objective views of nature. In her study about the fertilization process, Martin describes several cases when gender-biased perception skewed the descriptions of biological processes during fertilization and even possibly hampered the research. She asserts that classic metaphors of the strong dominant sperm racing to an idle egg are products of gendered stereotyping rather than a faithful portrayal of human fertilization. The notion that women are passive and men are active are socially constructed attributes of gender which, according to Martin, scientists have projected onto the events of fertilization and so obscuring the fact that eggs do play an active role. For example, she wrote that "even after having revealed...the egg to be a chemically active sperm catcher, even after discussing the egg's role in tethering the sperm, the research team continued for another three years to describe the sperm's role as actively penetrating the egg." Scott Gilbert, a developmental biologist at Swarthmore College supports her position: "if you don't have an interpretation of fertilization that allows you to look at the egg as active, you won't look for the molecules that can prove it. You simply won't find activities that you don't visualize."
== Media and politics ==
The mass media face a number of pressures that can prevent them from accurately depicting competing scientific claims in terms of their credibility within the scientific community as a whole. Determining how much weight to give different sides in a scientific debate requires considerable expertise regarding the matter. Few journalists have real scientific knowledge, and even beat reporters who know a great deal about certain scientific issues may know little about other ones they are suddenly asked to cover.
Many issues damage the relationship of science to the media and the use of science and scientific arguments by politicians. As a very broad generalisation, many politicians seek certainties and facts whilst scientists typically offer probabilities and caveats. However, politicians' ability to be heard in the mass media frequently distorts the scientific understanding by the public. Examples in Britain include the controversy over the MMR inoculation, and the 1988 forced resignation of a government minister, Edwina Currie, for revealing the high probability that battery eggs were contaminated with Salmonella.
Some scientists and philosophers suggest that scientific theories are more or less shaped by the dominant political, economic, or cultural models of the time, even though the scientific community may claim to be exempt from social influences and historical conditions. For example, the Russian philosopher, socialist, and zoologist Peter Kropotkin thought that the Darwinian theory of evolution overstressed a painful "we must struggle to survive" way of life, which he said was influenced by capitalism and the struggling lifestyles people lived within it. Karl Marx also thought that science was largely driven by and used as capital.
Robert Anton Wilson, Stanley Aronowitz, and Paul Feyerabend all thought that the military-industrial complex, large corporations, and the grants that came from them had an immense influence over the research and even results of scientific experiments. Aronowitz even went as far as to say "It does not matter that the scientific community ritualistically denies its alliance with economic/industrial and military power. The evidence is overwhelming that such is the case. Thus, every major power has a national science policy; the United States Military appropriates billions each year for 'basic' as well as 'applied' research".
== See also ==
Academic bias
Anti-intellectualism
Antiscience
Criticism of college and university rankings in North America
Intellectual inbreeding
Postmodernism
Pseudoscience
Pseudoskepticism
Research paper mill
Scientific misconduct
Empirical limits in science
== Notes and references ==
== Further reading == | Wikipedia/Criticism_of_science |
In its most common sense, methodology is the study of research methods. However, the term can also refer to the methods themselves or to the philosophical discussion of associated background assumptions. A method is a structured procedure for bringing about a certain goal, like acquiring knowledge or verifying knowledge claims. This normally involves various steps, like choosing a sample, collecting data from this sample, and interpreting the data. The study of methods concerns a detailed description and analysis of these processes. It includes evaluative aspects by comparing different methods. This way, it is assessed what advantages and disadvantages they have and for what research goals they may be used. These descriptions and evaluations depend on philosophical background assumptions. Examples are how to conceptualize the studied phenomena and what constitutes evidence for or against them. When understood in the widest sense, methodology also includes the discussion of these more abstract issues.
Methodologies are traditionally divided into quantitative and qualitative research. Quantitative research is the main methodology of the natural sciences. It uses precise numerical measurements. Its goal is usually to find universal laws used to make predictions about future events. The dominant methodology in the natural sciences is called the scientific method. It includes steps like observation and the formulation of a hypothesis. Further steps are to test the hypothesis using an experiment, to compare the measurements to the expected results, and to publish the findings.
Qualitative research is more characteristic of the social sciences and gives less prominence to exact numerical measurements. It aims more at an in-depth understanding of the meaning of the studied phenomena and less at universal and predictive laws. Common methods found in the social sciences are surveys, interviews, focus groups, and the nominal group technique. They differ from each other concerning their sample size, the types of questions asked, and the general setting. In recent decades, many social scientists have started using mixed-methods research, which combines quantitative and qualitative methodologies.
Many discussions in methodology concern the question of whether the quantitative approach is superior, especially whether it is adequate when applied to the social domain. A few theorists reject methodology as a discipline in general. For example, some argue that it is useless since methods should be used rather than studied. Others hold that it is harmful because it restricts the freedom and creativity of researchers. Methodologists often respond to these objections by claiming that a good methodology helps researchers arrive at reliable theories in an efficient way. The choice of method often matters since the same factual material can lead to different conclusions depending on one's method. Interest in methodology has risen in the 20th century due to the increased importance of interdisciplinary work and the obstacles hindering efficient cooperation.
== Definitions ==
The term "methodology" is associated with a variety of meanings. In its most common usage, it refers either to a method, to the field of inquiry studying methods, or to philosophical discussions of background assumptions involved in these processes. Some researchers distinguish methods from methodologies by holding that methods are modes of data collection while methodologies are more general research strategies that determine how to conduct a research project. In this sense, methodologies include various theoretical commitments about the intended outcomes of the investigation.
=== As method ===
The term "methodology" is sometimes used as a synonym for the term "method". A method is a way of reaching some predefined goal. It is a planned and structured procedure for solving a theoretical or practical problem. In this regard, methods stand in contrast to free and unstructured approaches to problem-solving. For example, descriptive statistics is a method of data analysis, radiocarbon dating is a method of determining the age of organic objects, sautéing is a method of cooking, and project-based learning is an educational method. The term "technique" is often used as a synonym both in the academic and the everyday discourse. Methods usually involve a clearly defined series of decisions and actions to be used under certain circumstances, usually expressable as a sequence of repeatable instructions. The goal of following the steps of a method is to bring about the result promised by it. In the context of inquiry, methods may be defined as systems of rules and procedures to discover regularities of nature, society, and thought. In this sense, methodology can refer to procedures used to arrive at new knowledge or to techniques of verifying and falsifying pre-existing knowledge claims. This encompasses various issues pertaining both to the collection of data and their analysis. Concerning the collection, it involves the problem of sampling and of how to go about the data collection itself, like surveys, interviews, or observation. There are also numerous methods of how the collected data can be analyzed using statistics or other ways of interpreting it to extract interesting conclusions.
=== As study of methods ===
However, many theorists emphasize the differences between the terms "method" and "methodology". In this regard, methodology may be defined as "the study or description of methods" or as "the analysis of the principles of methods, rules, and postulates employed by a discipline". This study or analysis involves uncovering assumptions and practices associated with the different methods and a detailed description of research designs and hypothesis testing. It also includes evaluative aspects: forms of data collection, measurement strategies, and ways to analyze data are compared and their advantages and disadvantages relative to different research goals and situations are assessed. In this regard, methodology provides the skills, knowledge, and practical guidance needed to conduct scientific research in an efficient manner. It acts as a guideline for various decisions researchers need to take in the scientific process.
Methodology can be understood as the middle ground between concrete particular methods and the abstract and general issues discussed by the philosophy of science. In this regard, methodology comes after formulating a research question and helps the researchers decide what methods to use in the process. For example, methodology should assist the researcher in deciding why one method of sampling is preferable to another in a particular case or which form of data analysis is likely to bring the best results. Methodology achieves this by explaining, evaluating and justifying methods. Just as there are different methods, there are also different methodologies. Different methodologies provide different approaches to how methods are evaluated and explained and may thus make different suggestions on what method to use in a particular case.
According to Aleksandr Georgievich Spirkin, "[a] methodology is a system of principles and general ways of organising and structuring theoretical and practical activity, and also the theory of this system". Helen Kara defines methodology as "a contextual framework for research, a coherent and logical scheme based on views, beliefs, and values, that guides the choices researchers make". Ginny E. Garcia and Dudley L. Poston understand methodology either as a complex body of rules and postulates guiding research or as the analysis of such rules and procedures. As a body of rules and postulates, a methodology defines the subject of analysis as well as the conceptual tools used by the analysis and the limits of the analysis. Research projects are usually governed by a structured procedure known as the research process. The goal of this process is given by a research question, which determines what kind of information one intends to acquire.
=== As discussion of background assumptions ===
Some theorists prefer an even wider understanding of methodology that involves not just the description, comparison, and evaluation of methods but includes additionally more general philosophical issues. One reason for this wider approach is that discussions of when to use which method often take various background assumptions for granted, for example, concerning the goal and nature of research. These assumptions can at times play an important role concerning which method to choose and how to follow it. For example, Thomas Kuhn argues in his The Structure of Scientific Revolutions that sciences operate within a framework or a paradigm that determines which questions are asked and what counts as good science. This concerns philosophical disagreements both about how to conceptualize the phenomena studied, what constitutes evidence for and against them, and what the general goal of researching them is. So in this wider sense, methodology overlaps with philosophy by making these assumptions explicit and presenting arguments for and against them. According to C. S. Herrman, a good methodology clarifies the structure of the data to be analyzed and helps the researchers see the phenomena in a new light. In this regard, a methodology is similar to a paradigm. A similar view is defended by Spirkin, who holds that a central aspect of every methodology is the world view that comes with it.
The discussion of background assumptions can include metaphysical and ontological issues in cases where they have important implications for the proper research methodology. For example, a realist perspective considering the observed phenomena as an external and independent reality is often associated with an emphasis on empirical data collection and a more distanced and objective attitude. Idealists, on the other hand, hold that external reality is not fully independent of the mind and tend, therefore, to include more subjective tendencies in the research process as well.
For the quantitative approach, philosophical debates in methodology include the distinction between the inductive and the hypothetico-deductive interpretation of the scientific method. For qualitative research, many basic assumptions are tied to philosophical positions such as hermeneutics, pragmatism, Marxism, critical theory, and postmodernism. According to Kuhn, an important factor in such debates is that the different paradigms are incommensurable. This means that there is no overarching framework to assess the conflicting theoretical and methodological assumptions. This critique puts into question various presumptions of the quantitative approach associated with scientific progress based on the steady accumulation of data.
Other discussions of abstract theoretical issues in the philosophy of science are also sometimes included. This can involve questions like how and whether scientific research differs from fictional writing as well as whether research studies objective facts rather than constructing the phenomena it claims to study. In the latter sense, some methodologists have even claimed that the goal of science is less to represent a pre-existing reality and more to bring about some kind of social change in favor of repressed groups in society.
=== Related terms and issues ===
Viknesh Andiappan and Yoke Kin Wan use the field of process systems engineering to distinguish the term "methodology" from the closely related terms "approach", "method", "procedure", and "technique". On their view, "approach" is the most general term. It can be defined as "a way or direction used to address a problem based on a set of assumptions". An example is the difference between hierarchical approaches, which consider one task at a time in a hierarchical manner, and concurrent approaches, which consider them all simultaneously. Methodologies are a little more specific. They are general strategies needed to realize an approach and may be understood as guidelines for how to make choices. Often the term "framework" is used as a synonym. A method is a still more specific way of practically implementing the approach. Methodologies provide the guidelines that help researchers decide which method to follow. The method itself may be understood as a sequence of techniques. A technique is a step taken that can be observed and measured. Each technique has some immediate result. The whole sequence of steps is termed a "procedure". A similar but less complex characterization is sometimes found in the field of language teaching, where the teaching process may be described through a three-level conceptualization based on "approach", "method", and "technique".
One question concerning the definition of methodology is whether it should be understood as a descriptive or a normative discipline. The key difference in this regard is whether methodology just provides a value-neutral description of methods or what scientists actually do. Many methodologists practice their craft in a normative sense, meaning that they express clear opinions about the advantages and disadvantages of different methods. In this regard, methodology is not just about what researchers actually do but about what they ought to do or how to perform good research.
== Types ==
Theorists often distinguish various general types or approaches to methodology. The most influential classification contrasts quantitative and qualitative methodology.
=== Quantitative and qualitative ===
Quantitative research is closely associated with the natural sciences. It is based on precise numerical measurements, which are then used to arrive at exact general laws. This precision is also reflected in the goal of making predictions that can later be verified by other researchers. Examples of quantitative research include physicists at the Large Hadron Collider measuring the mass of newly created particles and positive psychologists conducting an online survey to determine the correlation between income and self-assessed well-being.
Qualitative research is characterized in various ways in the academic literature but there are very few precise definitions of the term. It is often used in contrast to quantitative research for forms of study that do not quantify their subject matter numerically. However, the distinction between these two types is not always obvious and various theorists have argued that it should be understood as a continuum and not as a dichotomy. A lot of qualitative research is concerned with some form of human experience or behavior, in which case it tends to focus on a few individuals and their in-depth understanding of the meaning of the studied phenomena. Examples of the qualitative method are a market researcher conducting a focus group in order to learn how people react to a new product or a medical researcher performing an unstructured in-depth interview with a participant from a new experimental therapy to assess its potential benefits and drawbacks. It is also used to improve quantitative research, such as informing data collection materials and questionnaire design. Qualitative research is frequently employed in fields where the pre-existing knowledge is inadequate. This way, it is possible to get a first impression of the field and potential theories, thus paving the way for investigating the issue in further studies.
Quantitative methods dominate in the natural sciences but both methodologies are used in the social sciences. Some social scientists focus mostly on one method while others try to investigate the same phenomenon using a variety of different methods. It is central to both approaches how the group of individuals used for the data collection is selected. This process is known as sampling. It involves the selection of a subset of individuals or phenomena to be measured. Important in this regard is that the selected samples are representative of the whole population, i.e. that no significant biases were involved when choosing. If this is not the case, the data collected does not reflect what the population as a whole is like. This affects generalizations and predictions drawn from the biased data. The number of individuals selected is called the sample size. For qualitative research, the sample size is usually rather small, while quantitative research tends to focus on big groups and collecting a lot of data. After the collection, the data needs to be analyzed and interpreted to arrive at interesting conclusions that pertain directly to the research question. This way, the wealth of information obtained is summarized and thus made more accessible to others. Especially in the case of quantitative research, this often involves the application of some form of statistics to make sense of the numerous individual measurements.
Many discussions in the history of methodology center around the quantitative methods used by the natural sciences. A central question in this regard is to what extent they can be applied to other fields, like the social sciences and history. The success of the natural sciences was often seen as an indication of the superiority of the quantitative methodology and used as an argument to apply this approach to other fields as well. However, this outlook has been put into question in the more recent methodological discourse. In this regard, it is often argued that the paradigm of the natural sciences is a one-sided development of reason, which is not equally well suited to all areas of inquiry. The divide between quantitative and qualitative methods in the social sciences is one consequence of this criticism.
Which method is more appropriate often depends on the goal of the research. For example, quantitative methods usually excel for evaluating preconceived hypotheses that can be clearly formulated and measured. Qualitative methods, on the other hand, can be used to study complex individual issues, often with the goal of formulating new hypotheses. This is especially relevant when the existing knowledge of the subject is inadequate. Important advantages of quantitative methods include precision and reliability. However, they have often difficulties in studying very complex phenomena that are commonly of interest to the social sciences. Additional problems can arise when the data is misinterpreted to defend conclusions that are not directly supported by the measurements themselves. In recent decades, many researchers in the social sciences have started combining both methodologies. This is known as mixed-methods research. A central motivation for this is that the two approaches can complement each other in various ways: some issues are ignored or too difficult to study with one methodology and are better approached with the other. In other cases, both approaches are applied to the same issue to produce more comprehensive and well-rounded results.
Qualitative and quantitative research are often associated with different research paradigms and background assumptions. Qualitative researchers often use an interpretive or critical approach while quantitative researchers tend to prefer a positivistic approach. Important disagreements between these approaches concern the role of objectivity and hard empirical data as well as the research goal of predictive success rather than in-depth understanding or social change.
=== Others ===
Various other classifications have been proposed. One distinguishes between substantive and formal methodologies. Substantive methodologies tend to focus on one specific area of inquiry. The findings are initially restricted to this specific field but may be transferrable to other areas of inquiry. Formal methodologies, on the other hand, are based on a variety of studies and try to arrive at more general principles applying to different fields. They may also give particular prominence to the analysis of the language of science and the formal structure of scientific explanation. A closely related classification distinguishes between philosophical, general scientific, and special scientific methods.
One type of methodological outlook is called "proceduralism". According to it, the goal of methodology is to boil down the research process to a simple set of rules or a recipe that automatically leads to good research if followed precisely. However, it has been argued that, while this ideal may be acceptable for some forms of quantitative research, it fails for qualitative research. One argument for this position is based on the claim that research is not a technique but a craft that cannot be achieved by blindly following a method. In this regard, research depends on forms of creativity and improvisation to amount to good science.
Other types include inductive, deductive, and transcendental methods. Inductive methods are common in the empirical sciences and proceed through inductive reasoning from many particular observations to arrive at general conclusions, often in the form of universal laws. Deductive methods, also referred to as axiomatic methods, are often found in formal sciences, such as geometry. They start from a set of self-evident axioms or first principles and use deduction to infer interesting conclusions from these axioms. Transcendental methods are common in Kantian and post-Kantian philosophy. They start with certain particular observations. It is then argued that the observed phenomena can only exist if their conditions of possibility are fulfilled. This way, the researcher may draw general psychological or metaphysical conclusions based on the claim that the phenomenon would not be observable otherwise.
== Importance ==
It has been argued that a proper understanding of methodology is important for various issues in the field of research. They include both the problem of conducting efficient and reliable research as well as being able to validate knowledge claims by others. Method is often seen as one of the main factors of scientific progress. This is especially true for the natural sciences where the developments of experimental methods in the 16th and 17th century are often seen as the driving force behind the success and prominence of the natural sciences. In some cases, the choice of methodology may have a severe impact on a research project. The reason is that very different and sometimes even opposite conclusions may follow from the same factual material based on the chosen methodology.
Aleksandr Georgievich Spirkin argues that methodology, when understood in a wide sense, is of great importance since the world presents us with innumerable entities and relations between them. Methods are needed to simplify this complexity and find a way of mastering it. On the theoretical side, this concerns ways of forming true beliefs and solving problems. On the practical side, this concerns skills of influencing nature and dealing with each other. These different methods are usually passed down from one generation to the next. Spirkin holds that the interest in methodology on a more abstract level arose in attempts to formalize these techniques to improve them as well as to make it easier to use them and pass them on. In the field of research, for example, the goal of this process is to find reliable means to acquire knowledge in contrast to mere opinions acquired by unreliable means. In this regard, "methodology is a way of obtaining and building up ... knowledge".
Various theorists have observed that the interest in methodology has risen significantly in the 20th century. This increased interest is reflected not just in academic publications on the subject but also in the institutionalized establishment of training programs focusing specifically on methodology. This phenomenon can be interpreted in different ways. Some see it as a positive indication of the topic's theoretical and practical importance. Others interpret this interest in methodology as an excessive preoccupation that draws time and energy away from doing research on concrete subjects by applying the methods instead of researching them. This ambiguous attitude towards methodology is sometimes even exemplified in the same person. Max Weber, for example, criticized the focus on methodology during his time while making significant contributions to it himself. Spirkin believes that one important reason for this development is that contemporary society faces many global problems. These problems cannot be solved by a single researcher or a single discipline but are in need of collaborative efforts from many fields. Such interdisciplinary undertakings profit a lot from methodological advances, both concerning the ability to understand the methods of the respective fields and in relation to developing more homogeneous methods equally used by all of them.
== Criticism ==
Most criticism of methodology is directed at one specific form or understanding of it. In such cases, one particular methodological theory is rejected but not methodology at large when understood as a field of research comprising many different theories. In this regard, many objections to methodology focus on the quantitative approach, specifically when it is treated as the only viable approach. Nonetheless, there are also more fundamental criticisms of methodology in general. They are often based on the idea that there is little value to abstract discussions of methods and the reasons cited for and against them. In this regard, it may be argued that what matters is the correct employment of methods and not their meticulous study. Sigmund Freud, for example, compared methodologists to "people who clean their glasses so thoroughly that they never have time to look through them". According to C. Wright Mills, the practice of methodology often degenerates into a "fetishism of method and technique".
Some even hold that methodological reflection is not just a waste of time but actually has negative side effects. Such an argument may be defended by analogy to other skills that work best when the agent focuses only on employing them. In this regard, reflection may interfere with the process and lead to avoidable mistakes. According to an example by Gilbert Ryle, "[w]e run, as a rule, worse, not better, if we think a lot about our feet". A less severe version of this criticism does not reject methodology per se but denies its importance and rejects an intense focus on it. In this regard, methodology has still a limited and subordinate utility but becomes a diversion or even counterproductive by hindering practice when given too much emphasis.
Another line of criticism concerns more the general and abstract nature of methodology. It states that the discussion of methods is only useful in concrete and particular cases but not concerning abstract guidelines governing many or all cases. Some anti-methodologists reject methodology based on the claim that researchers need freedom to do their work effectively. But this freedom may be constrained and stifled by "inflexible and inappropriate guidelines". For example, according to Kerry Chamberlain, a good interpretation needs creativity to be provocative and insightful, which is prohibited by a strictly codified approach. Chamberlain uses the neologism "methodolatry" to refer to this alleged overemphasis on methodology. Similar arguments are given in Paul Feyerabend's book "Against Method".
However, these criticisms of methodology in general are not always accepted. Many methodologists defend their craft by pointing out how the efficiency and reliability of research can be improved through a proper understanding of methodology.
A criticism of more specific forms of methodology is found in the works of the sociologist Howard S. Becker. He is quite critical of methodologists based on the claim that they usually act as advocates of one particular method usually associated with quantitative research. An often-cited quotation in this regard is that "[m]ethodology is too important to be left to methodologists". Alan Bryman has rejected this negative outlook on methodology. He holds that Becker's criticism can be avoided by understanding methodology as an inclusive inquiry into all kinds of methods and not as a mere doctrine for converting non-believers to one's preferred method.
== In different fields ==
Part of the importance of methodology is reflected in the number of fields to which it is relevant. They include the natural sciences and the social sciences as well as philosophy and mathematics.
=== Natural sciences ===
The dominant methodology in the natural sciences (like astronomy, biology, chemistry, geoscience, and physics) is called the scientific method. Its main cognitive aim is usually seen as the creation of knowledge, but various closely related aims have also been proposed, like understanding, explanation, or predictive success. Strictly speaking, there is no one single scientific method. In this regard, the expression "scientific method" refers not to one specific procedure but to different general or abstract methodological aspects characteristic of all the aforementioned fields. Important features are that the problem is formulated in a clear manner and that the evidence presented for or against a theory is public, reliable, and replicable. The last point is important so that other researchers are able to repeat the experiments to confirm or disconfirm the initial study. For this reason, various factors and variables of the situation often have to be controlled to avoid distorting influences and to ensure that subsequent measurements by other researchers yield the same results. The scientific method is a quantitative approach that aims at obtaining numerical data. This data is often described using mathematical formulas. The goal is usually to arrive at some universal generalizations that apply not just to the artificial situation of the experiment but to the world at large. Some data can only be acquired using advanced measurement instruments. In cases where the data is very complex, it is often necessary to employ sophisticated statistical techniques to draw conclusions from it.
The scientific method is often broken down into several steps. In a typical case, the procedure starts with regular observation and the collection of information. These findings then lead the scientist to formulate a hypothesis describing and explaining the observed phenomena. The next step consists in conducting an experiment designed for this specific hypothesis. The actual results of the experiment are then compared to the expected results based on one's hypothesis. The findings may then be interpreted and published, either as a confirmation or disconfirmation of the initial hypothesis.
Two central aspects of the scientific method are observation and experimentation. This distinction is based on the idea that experimentation involves some form of manipulation or intervention. This way, the studied phenomena are actively created or shaped. For example, a biologist inserting viral DNA into a bacterium is engaged in a form of experimentation. Pure observation, on the other hand, involves studying independent entities in a passive manner. This is the case, for example, when astronomers observe the orbits of astronomical objects far away. Observation played the main role in ancient science. The scientific revolution in the 16th and 17th century affected a paradigm change that gave a much more central role to experimentation in the scientific methodology. This is sometimes expressed by stating that modern science actively "puts questions to nature". While the distinction is usually clear in the paradigmatic cases, there are also many intermediate cases where it is not obvious whether they should be characterized as observation or as experimentation.
A central discussion in this field concerns the distinction between the inductive and the hypothetico-deductive methodology. The core disagreement between these two approaches concerns their understanding of the confirmation of scientific theories. The inductive approach holds that a theory is confirmed or supported by all its positive instances, i.e. by all the observations that exemplify it. For example, the observations of many white swans confirm the universal hypothesis that "all swans are white". The hypothetico-deductive approach, on the other hand, focuses not on positive instances but on deductive consequences of the theory. This way, the researcher uses deduction before conducting an experiment to infer what observations they expect. These expectations are then compared to the observations they actually make. This approach often takes a negative form based on falsification. In this regard, positive instances do not confirm a hypothesis but negative instances disconfirm it. Positive indications that the hypothesis is true are only given indirectly if many attempts to find counterexamples have failed. A cornerstone of this approach is the null hypothesis, which assumes that there is no connection (see causality) between whatever is being observed. It is up to the researcher to do all they can to disprove their own hypothesis through relevant methods or techniques, documented in a clear and replicable process. If they fail to do so, it can be concluded that the null hypothesis is false, which provides support for their own hypothesis about the relation between the observed phenomena.
=== Social sciences ===
Significantly more methodological variety is found in the social sciences, where both quantitative and qualitative approaches are used. They employ various forms of data collection, such as surveys, interviews, focus groups, and the nominal group technique. Surveys belong to quantitative research and usually involve some form of questionnaire given to a large group of individuals. It is paramount that the questions are easily understandable by the participants since the answers might not have much value otherwise. Surveys normally restrict themselves to closed questions in order to avoid various problems that come with the interpretation of answers to open questions. They contrast in this regard to interviews, which put more emphasis on the individual participant and often involve open questions. Structured interviews are planned in advance and have a fixed set of questions given to each individual. They contrast with unstructured interviews, which are closer to a free-flow conversation and require more improvisation on the side of the interviewer for finding interesting and relevant questions. Semi-structured interviews constitute a middle ground: they include both predetermined questions and questions not planned in advance. Structured interviews make it easier to compare the responses of the different participants and to draw general conclusions. However, they also limit what may be discovered and thus constrain the investigation in many ways. Depending on the type and depth of the interview, this method belongs either to quantitative or to qualitative research. The terms research conversation and muddy interview have been used to describe interviews conducted in informal settings which may not occur purely for the purposes of data collection. Some researcher employ the go-along method by conducting interviews while they and the participants navigate through and engage with their environment.
Focus groups are a qualitative research method often used in market research. They constitute a form of group interview involving a small number of demographically similar people. Researchers can use this method to collect data based on the interactions and responses of the participants. The interview often starts by asking the participants about their opinions on the topic under investigation, which may, in turn, lead to a free exchange in which the group members express and discuss their personal views. An important advantage of focus groups is that they can provide insight into how ideas and understanding operate in a cultural context. However, it is usually difficult to use these insights to discern more general patterns true for a wider public. One advantage of focus groups is that they can help the researcher identify a wide range of distinct perspectives on the issue in a short time. The group interaction may also help clarify and expand interesting contributions. One disadvantage is due to the moderator's personality and group effects, which may influence the opinions stated by the participants. When applied to cross-cultural settings, cultural and linguistic adaptations and group composition considerations are important to encourage greater participation in the group discussion.
The nominal group technique is similar to focus groups with a few important differences. The group often consists of experts in the field in question. The group size is similar but the interaction between the participants is more structured. The goal is to determine how much agreement there is among the experts on the different issues. The initial responses are often given in written form by each participant without a prior conversation between them. In this manner, group effects potentially influencing the expressed opinions are minimized. In later steps, the different responses and comments may be discussed and compared to each other by the group as a whole.
Most of these forms of data collection involve some type of observation. Observation can take place either in a natural setting, i.e. the field, or in a controlled setting such as a laboratory. Controlled settings carry with them the risk of distorting the results due to their artificiality. Their advantage lies in precisely controlling the relevant factors, which can help make the observations more reliable and repeatable. Non-participatory observation involves a distanced or external approach. In this case, the researcher focuses on describing and recording the observed phenomena without causing or changing them, in contrast to participatory observation.
An important methodological debate in the field of social sciences concerns the question of whether they deal with hard, objective, and value-neutral facts, as the natural sciences do. Positivists agree with this characterization, in contrast to interpretive and critical perspectives on the social sciences. According to William Neumann, positivism can be defined as "an organized method for combining deductive logic with precise empirical observations of individual behavior in order to discover and confirm a set of probabilistic causal laws that can be used to predict general patterns of human activity". This view is rejected by interpretivists. Max Weber, for example, argues that the method of the natural sciences is inadequate for the social sciences. Instead, more importance is placed on meaning and how people create and maintain their social worlds. The critical methodology in social science is associated with Karl Marx and Sigmund Freud. It is based on the assumption that many of the phenomena studied using the other approaches are mere distortions or surface illusions. It seeks to uncover deeper structures of the material world hidden behind these distortions. This approach is often guided by the goal of helping people effect social changes and improvements.
=== Philosophy ===
Philosophical methodology is the metaphilosophical field of inquiry studying the methods used in philosophy. These methods structure how philosophers conduct their research, acquire knowledge, and select between competing theories. It concerns both descriptive issues of what methods have been used by philosophers in the past and normative issues of which methods should be used. Many philosophers emphasize that these methods differ significantly from the methods found in the natural sciences in that they usually do not rely on experimental data obtained through measuring equipment. Which method one follows can have wide implications for how philosophical theories are constructed, what theses are defended, and what arguments are cited in favor or against. In this regard, many philosophical disagreements have their source in methodological disagreements. Historically, the discovery of new methods, like methodological skepticism and the phenomenological method, has had important impacts on the philosophical discourse.
A great variety of methods has been employed throughout the history of philosophy:
Methodological skepticism gives special importance to the role of systematic doubt. This way, philosophers try to discover absolutely certain first principles that are indubitable.
The geometric method starts from such first principles and employs deductive reasoning to construct a comprehensive philosophical system based on them.
Phenomenology gives particular importance to how things appear to be. It consists in suspending one's judgments about whether these things actually exist in the external world. This technique is known as epoché and can be used to study appearances independent of assumptions about their causes.
The method of conceptual analysis came to particular prominence with the advent of analytic philosophy. It studies concepts by breaking them down into their most fundamental constituents to clarify their meaning.
Common sense philosophy uses common and widely accepted beliefs as a philosophical tool. They are used to draw interesting conclusions. This is often employed in a negative sense to discredit radical philosophical positions that go against common sense.
Ordinary language philosophy has a very similar method: it approaches philosophical questions by looking at how the corresponding terms are used in ordinary language.
Many methods in philosophy rely on some form of intuition. They are used, for example, to evaluate thought experiments, which involve imagining situations to assess their possible consequences in order to confirm or refute philosophical theories.
The method of reflective equilibrium tries to form a coherent perspective by examining and reevaluating all the relevant beliefs and intuitions.
Pragmatists focus on the practical consequences of philosophical theories to assess whether they are true or false.
Experimental philosophy is a recently developed approach that uses the methodology of social psychology and the cognitive sciences for gathering empirical evidence and justifying philosophical claims.
=== Mathematics ===
In the field of mathematics, various methods can be distinguished, such as synthetic, analytic, deductive, inductive, and heuristic methods. For example, the difference between synthetic and analytic methods is that the former start from the known and proceed to the unknown while the latter seek to find a path from the unknown to the known. Geometry textbooks often proceed using the synthetic method. They start by listing known definitions and axioms and proceed by taking inferential steps, one at a time, until the solution to the initial problem is found. An important advantage of the synthetic method is its clear and short logical exposition. One disadvantage is that it is usually not obvious in the beginning that the steps taken lead to the intended conclusion. This may then come as a surprise to the reader since it is not explained how the mathematician knew in the beginning which steps to take. The analytic method often reflects better how mathematicians actually make their discoveries. For this reason, it is often seen as the better method for teaching mathematics. It starts with the intended conclusion and tries to find another formula from which it can be deduced. It then goes on to apply the same process to this new formula until it has traced back all the way to already proven theorems. The difference between the two methods concerns primarily how mathematicians think and present their proofs. The two are equivalent in the sense that the same proof may be presented either way.
=== Statistics ===
Statistics investigates the analysis, interpretation, and presentation of data. It plays a central role in many forms of quantitative research that have to deal with the data of many observations and measurements. In such cases, data analysis is used to cleanse, transform, and model the data to arrive at practically useful conclusions. There are numerous methods of data analysis. They are usually divided into descriptive statistics and inferential statistics. Descriptive statistics restricts itself to the data at hand. It tries to summarize the most salient features and present them in insightful ways. This can happen, for example, by visualizing its distribution or by calculating indices such as the mean or the standard deviation. Inferential statistics, on the other hand, uses this data based on a sample to draw inferences about the population at large. That can take the form of making generalizations and predictions or by assessing the probability of a concrete hypothesis.
=== Pedagogy ===
Pedagogy can be defined as the study or science of teaching methods. In this regard, it is the methodology of education: it investigates the methods and practices that can be applied to fulfill the aims of education. These aims include the transmission of knowledge as well as fostering skills and character traits. Its main focus is on teaching methods in the context of regular schools. But in its widest sense, it encompasses all forms of education, both inside and outside schools. In this wide sense, pedagogy is concerned with "any conscious activity by one person designed to enhance learning in another". The teaching happening this way is a process taking place between two parties: teachers and learners. Pedagogy investigates how the teacher can help the learner undergo experiences that promote their understanding of the subject matter in question.
Various influential pedagogical theories have been proposed. Mental-discipline theories were already common in ancient Greek and state that the main goal of teaching is to train intellectual capacities. They are usually based on a certain ideal of the capacities, attitudes, and values possessed by educated people. According to naturalistic theories, there is an inborn natural tendency in children to develop in a certain way. For them, pedagogy is about how to help this process happen by ensuring that the required external conditions are set up. Herbartianism identifies five essential components of teaching: preparation, presentation, association, generalization, and application. They correspond to different phases of the educational process: getting ready for it, showing new ideas, bringing these ideas in relation to known ideas, understanding the general principle behind their instances, and putting what one has learned into practice. Learning theories focus primarily on how learning takes place and formulate the proper methods of teaching based on these insights. One of them is apperception or association theory, which understands the mind primarily in terms of associations between ideas and experiences. On this view, the mind is initially a blank slate. Learning is a form of developing the mind by helping it establish the right associations. Behaviorism is a more externally oriented learning theory. It identifies learning with classical conditioning, in which the learner's behavior is shaped by presenting them with a stimulus with the goal of evoking and solidifying the desired response pattern to this stimulus.
The choice of which specific method is best to use depends on various factors, such as the subject matter and the learner's age. Interest and curiosity on the side of the student are among the key factors of learning success. This means that one important aspect of the chosen teaching method is to ensure that these motivational forces are maintained, through intrinsic or extrinsic motivation. Many forms of education also include regular assessment of the learner's progress, for example, in the form of tests. This helps to ensure that the teaching process is successful and to make adjustments to the chosen method if necessary.
== Related concepts ==
Methodology has several related concepts, such as paradigm and algorithm. In the context of science, a paradigm is a conceptual worldview. It consists of a number of basic concepts and general theories, that determine how the studied phenomena are to be conceptualized and which scientific methods are considered reliable for studying them. Various theorists emphasize similar aspects of methodologies, for example, that they shape the general outlook on the studied phenomena and help the researcher see them in a new light.
In computer science, an algorithm is a procedure or methodology to reach the solution of a problem with a finite number of steps. Each step has to be precisely defined so it can be carried out in an unambiguous manner for each application. For example, the Euclidean algorithm is an algorithm that solves the problem of finding the greatest common divisor of two integers. It is based on simple steps like comparing the two numbers and subtracting one from the other.
== See also ==
Paradigm – Set of distinct concepts or thought patterns
Philosophical methodology
Political methodology
Scientific method
Software development process
Survey methodology
== References ==
== Further reading ==
Berg, Bruce L., 2009, Qualitative Research Methods for the Social Sciences. Seventh Edition. Boston MA: Pearson Education Inc.
Creswell, J. (1998). Qualitative inquiry and research design: Choosing among five traditions. Thousand Oaks, California: Sage Publications.
Creswell, J. (2003). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Thousand Oaks, California: Sage Publications.
Franklin, M.I. (2012). Understanding Research: Coping with the Quantitative-Qualitative Divide. London and New York: Routledge.
Guba, E. and Lincoln, Y. (1989). Fourth Generation Evaluation. Newbury Park, California: Sage Publications.
Herrman, C. S. (2009). "Fundamentals of Methodology", a series of papers On the Social Science Research Network (SSRN), online.
Howell, K. E. (2013) Introduction to the Philosophy of Methodology. London, UK: Sage Publications.
Ndira, E. Alana, Slater, T. and Bucknam, A. (2011). Action Research for Business, Nonprofit, and Public Administration - A Tool for Complex Times . Thousand Oaks, CA: Sage.
Joubish, Farooq Dr. (2009). Educational Research Department of Education, Federal Urdu University, Karachi, Pakistan
Patton, M. Q. (2002). Qualitative research & evaluation methods (3rd edition). Thousand Oaks, California: Sage Publications.
Silverman, David (Ed). (2011). Qualitative Research: Issues of Theory, Method and Practice, Third Edition. London, Thousand Oaks, New Delhi, Singapore: Sage Publications
Soeters, Joseph; Shields, Patricia and Rietjens, Sebastiaan. 2014. Handbook of Research Methods in Military Studies New York: Routledge.
Ioannidis, J. P. (2005). "Why Most Published Research Findings Are False". PLOS Medicine. 2 (8): e124. doi:10.1371/journal.pmed.0020124. PMC 1182327. PMID 16060722.
== External links ==
Freedictionary, usage note on the word Methodology
Researcherbook, research methodology forum and resources | Wikipedia/Methodological |
Basic research, also called pure research, fundamental research, basic science, or pure science, is a type of scientific research with the aim of improving scientific theories for better understanding and prediction of natural or other phenomena. In contrast, applied research uses scientific theories to develop technology or techniques, which can be used to intervene and alter natural or other phenomena. Though often driven simply by curiosity, basic research often fuels the technological innovations of applied science. The two aims are often practiced simultaneously in coordinated research and development.
In addition to innovations, basic research serves to provide insights and public support of nature, possibly improving conservation efforts. Technological innovations may influence engineering concepts, such as the beak of a kingfisher influencing the design of a high-speed bullet train.
== Overview ==
Basic research advances fundamental knowledge about the world. It focuses on creating and refuting or supporting theories that explain observed phenomena. Pure research is the source of most new scientific ideas and ways of thinking about the world. It can be exploratory, descriptive, or explanatory; however, explanatory research is the most common.
Basic research generates new ideas, principles, and theories, which may not be immediately utilized but nonetheless form the basis of progress and development in different fields. Today's computers, for example, could not exist without research in pure mathematics conducted over a century ago, for which there was no known practical application at the time. Basic research rarely helps practitioners directly with their everyday concerns; nevertheless, it stimulates new ways of thinking that have the potential to revolutionize and dramatically improve how practitioners deal with a problem in the future.
== By country ==
In the United States, basic research is funded mainly by the federal government and done mainly at universities and institutes. As government funding has diminished in the 2010s, however, private funding is increasingly important.
== Basic versus applied science ==
Applied science focuses on the development of technology and techniques. In contrast, basic science develops scientific knowledge and predictions, principally in natural sciences but also in other empirical sciences, which are used as the scientific foundation for applied science. Basic science develops and establishes information to predict phenomena and perhaps to understand nature, whereas applied science uses portions of basic science to develop interventions via technology or technique to alter events or outcomes. Applied and basic sciences can interface closely in research and development. The interface between basic research and applied research has been studied by the National Science Foundation. A worker in basic scientific research is motivated by a driving curiosity about the unknown. When his explorations yield new knowledge, he experiences the satisfaction of those who first attain the summit of a mountain or the upper reaches of a river flowing through unmapped territory. Discovery of truth and understanding of nature are his objectives. His professional standing among his fellows depends upon the originality and soundness of his work. Creativeness in science is of a cloth with that of the poet or painter.It conducted a study in which it traced the relationship between basic scientific research efforts and the development of major innovations, such as oral contraceptives and videotape recorders. This study found that basic research played a key role in the development in all of the innovations. The number of basic science research that assisted in the production of a given innovation peaked between 20 and 30 years before the innovation itself. While most innovation takes the form of applied science and most innovation occurs in the private sector, basic research is a necessary precursor to almost all applied science and associated instances of innovation. Roughly 76% of basic research is conducted by universities.
A distinction can be made between basic science and disciplines such as medicine and technology. They can be grouped as STM (science, technology, and medicine; not to be confused with STEM [science, technology, engineering, and mathematics]) or STS (science, technology, and society). These groups are interrelated and influence each other, although they may differ in the specifics such as methods and standards.
The Nobel Prize mixes basic with applied sciences for its award in Physiology or Medicine. In contrast, the Royal Society of London awards distinguish natural science from applied science.
== See also ==
Blue skies research
Hard and soft science
Metascience
Normative science
Physics
Precautionary principle
Pure mathematics
Pure Chemistry
== References ==
== Further reading ==
Levy, David M. (2002). "Research and Development". In David R. Henderson (ed.). Concise Encyclopedia of Economics (1st ed.). Library of Economics and Liberty. OCLC 317650570, 50016270, 163149563 | Wikipedia/Basic_science |
Structural functionalism, or simply functionalism, is "a framework for building theory that sees society as a complex system whose parts work together to promote solidarity and stability".
This approach looks at society through a macro-level orientation, which is a broad focus on the social structures that shape society as a whole, and believes that society has evolved like organisms. This approach looks at both social structure and social functions. Functionalism addresses society as a whole in terms of the function of its constituent elements; namely norms, customs, traditions, and institutions.
A common analogy called the organic or biological analogy, popularized by Herbert Spencer, presents these parts of society as human body "organs" that work toward the proper functioning of the "body" as a whole. In the most basic terms, it simply emphasizes "the effort to impute, as rigorously as possible, to each feature, custom, or practice, its effect on the functioning of a supposedly stable, cohesive system". For Talcott Parsons, "structural-functionalism" came to describe a particular stage in the methodological development of social science, rather than a specific school of thought.
== Theory ==
In sociology, classical theories are defined by a tendency towards biological analogy and notions of social evolutionism:
Functionalist thought, from Comte onwards, has looked particularly towards biology as the science providing the closest and most compatible model for social science. Biology has been taken to provide a guide to conceptualizing the structure and function of social systems and analyzing evolution processes via mechanisms of adaptation ... functionalism strongly emphasises the pre-eminence of the social world over its individual parts (i.e. its constituent actors, human subjects).
While one may regard functionalism as a logical extension of the organic analogies for societies presented by political philosophers such as Rousseau, sociology draws firmer attention to those institutions unique to industrialized capitalist society (or modernity).
Auguste Comte believed that society constitutes a separate "level" of reality, distinct from both biological and inorganic matter. Explanations of social phenomena had therefore to be constructed within this level, individuals being merely transient occupants of comparatively stable social roles. In this view, Comte was followed by Émile Durkheim.
A central concern for Durkheim was the question of how certain societies maintain internal stability and survive over time. He proposed that such societies tend to be segmented, with equivalent parts held together by shared values, common symbols or (as his nephew Marcel Mauss held), systems of exchanges. Durkheim used the term mechanical solidarity to refer to these types of "social bonds, based on common sentiments and shared moral values, that are strong among members of pre-industrial societies". In modern, complex societies, members perform very different tasks, resulting in a strong interdependence. Based on the metaphor above of an organism in which many parts function together to sustain the whole, Durkheim argued that complex societies are held together by "organic solidarity", i.e. "social bonds, based on specialization and interdependence, that are strong among members of industrial societies".
The central concern of structural functionalism may be regarded as a continuation of the Durkheimian task of explaining the apparent stability and internal cohesion needed by societies to endure over time. Societies are seen as coherent, bounded and fundamentally relational constructs that function like organisms, with their various (or social institutions) working together in an unconscious, quasi-automatic fashion toward achieving an overall social equilibrium. All social and cultural phenomena are therefore seen as functional in the sense of working together, and are effectively deemed to have "lives" of their own. They are primarily analyzed in terms of this function. The individual is significant not in and of themselves, but rather in terms of their status, their position in patterns of social relations, and the behaviours associated with their status. Therefore, the social structure is the network of statuses connected by associated roles.
Functionalism also has an anthropological basis in the work of theorists such as Marcel Mauss, Bronisław Malinowski and Radcliffe-Brown. The prefix 'structural' emerged in Radcliffe-Brown's specific usage. Radcliffe-Brown proposed that most stateless, "primitive" societies, lacking strong centralized institutions, are based on an association of corporate-descent groups, i.e. the respective society's recognised kinship groups. Structural functionalism also took on Malinowski's argument that the basic building block of society is the nuclear family, and that the clan is an outgrowth, not vice versa.
It is simplistic to equate the perspective directly with political conservatism. The tendency to emphasize "cohesive systems", however, leads functionalist theories to be contrasted with "conflict theories" which instead emphasize social problems and inequalities.
== Prominent theorists ==
=== Auguste Comte ===
Auguste Comte, the "Father of Positivism", pointed out the need to keep society unified as many traditions were diminishing. He was the first person to coin the term sociology. Comte suggests that sociology is the product of a three-stage development:
Theological stage: From the beginning of human history until the end of the European Middle Ages, people took a religious view that society expressed God's will. In the theological state, the human mind, seeking the essential nature of beings, the first and final causes (the origin and purpose) of all effects—in short, absolute knowledge—supposes all phenomena to be produced by the immediate action of supernatural beings.
Metaphysical stage: People began seeing society as a natural system as opposed to the supernatural. This began with enlightenment and the ideas of Hobbes, Locke, and Rousseau. Perceptions of society reflected the failings of a selfish human nature rather than the perfection of God.
Positive or scientific stage: Describing society through the application of the scientific approach, which draws on the work of scientists.
=== Herbert Spencer ===
Herbert Spencer (1820–1903) was a British philosopher famous for applying the theory of natural selection to society. He was in many ways the first true sociological functionalist. In fact, while Durkheim is widely considered the most important functionalist among positivist theorists, it is known that much of his analysis was culled from reading Spencer's work, especially his Principles of Sociology (1874–96). In describing society, Spencer alludes to the analogy of a human body. Just as the structural parts of the human body—the skeleton, muscles, and various internal organs—function independently to help the entire organism survive, social structures work together to preserve society.
While reading Spencer's massive volumes can be tedious (long passages explicating the organic analogy, with reference to cells, simple organisms, animals, humans and society), there are some important insights that have quietly influenced many contemporary theorists, including Talcott Parsons, in his early work The Structure of Social Action (1937). Cultural anthropology also consistently uses functionalism.
This evolutionary model, unlike most 19th century evolutionary theories, is cyclical, beginning with the differentiation and increasing complication of an organic or "super-organic" (Spencer's term for a social system) body, followed by a fluctuating state of equilibrium and disequilibrium (or a state of adjustment and adaptation), and, finally, the stage of disintegration or dissolution. Following Thomas Malthus' population principles, Spencer concluded that society is constantly facing selection pressures (internal and external) that force it to adapt its internal structure through differentiation.
Every solution, however, causes a new set of selection pressures that threaten society's viability. Spencer was not a determinist in the sense that he never said that
Selection pressures will be felt in time to change them;
They will be felt and reacted to; or
The solutions will always work.
In fact, he was in many ways a political sociologist, and recognized that the degree of centralized and consolidated authority in a given polity could make or break its ability to adapt. In other words, he saw a general trend towards the centralization of power as leading to stagnation and ultimately, pressures to decentralize.
More specifically, Spencer recognized three functional needs or prerequisites that produce selection pressures: they are regulatory, operative (production) and distributive. He argued that all societies need to solve problems of control and coordination, production of goods, services and ideas, and, finally, to find ways of distributing these resources.
Initially, in tribal societies, these three needs are inseparable, and the kinship system is the dominant structure that satisfies them. As many scholars have noted, all institutions are subsumed under kinship organization, but, with increasing population (both in terms of sheer numbers and density), problems emerge with regard to feeding individuals, creating new forms of organization—consider the emergent division of labour—coordinating and controlling various differentiated social units, and developing systems of resource distribution.
The solution, as Spencer sees it, is to differentiate structures to fulfill more specialized functions; thus, a chief or "big man" emerges, soon followed by a group of lieutenants, and later kings and administrators. The structural parts of society (e.g. families, work) function interdependently to help society function. Therefore, social structures work together to preserve society.
=== Talcott Parsons ===
Talcott Parsons began writing in the 1930s and contributed to sociology, political science, anthropology, and psychology. Structural functionalism and Parsons have received much criticism. Numerous critics have pointed out Parsons' underemphasis of political and monetary struggle, the basics of social change, and the by and large "manipulative" conduct unregulated by qualities and standards. Structural functionalism, and a large portion of Parsons' works, appear to be insufficient in their definitions concerning the connections amongst institutionalized and non-institutionalized conduct, and the procedures by which institutionalization happens.
Parsons was heavily influenced by Durkheim and Max Weber, synthesizing much of their work into his action theory, which he based on the system-theoretical concept and the methodological principle of voluntary action. He held that "the social system is made up of the actions of individuals". His starting point, accordingly, is the interaction between two individuals faced with a variety of choices about how they might act, choices that are influenced and constrained by a number of physical and social factors.
Parsons determined that each individual has expectations of the other's action and reaction to their own behavior, and that these expectations would (if successful) be "derived" from the accepted norms and values of the society they inhabit. As Parsons himself emphasized, in a general context there would never exist any perfect "fit" between behaviors and norms, so such a relation is never complete or "perfect".
Social norms were always problematic for Parsons, who never claimed (as has often been alleged) that social norms were generally accepted and agreed upon, should this prevent some kind of universal law. Whether social norms were accepted or not was for Parsons simply a historical question.
As behaviors are repeated in more interactions, and these expectations are entrenched or institutionalized, a role is created. Parsons defines a "role" as the normatively-regulated participation "of a person in a concrete process of social interaction with specific, concrete role-partners". Although any individual, theoretically, can fulfill any role, the individual is expected to conform to the norms governing the nature of the role they fulfill.
Furthermore, one person can and does fulfill many different roles at the same time. In one sense, an individual can be seen to be a "composition" of the roles he inhabits. Certainly, today, when asked to describe themselves, most people would answer with reference to their societal roles.
Parsons later developed the idea of roles into collectivities of roles that complement each other in fulfilling functions for society. Some roles are bound up in institutions and social structures (economic, educational, legal and even gender-based). These are functional in the sense that they assist society in operating and fulfilling its functional needs so that society runs smoothly.
Contrary to prevailing myth, Parsons never spoke about a society where there was no conflict or some kind of "perfect" equilibrium. A society's cultural value-system was in the typical case never completely integrated, never static and most of the time, like in the case of the American society, in a complex state of transformation relative to its historical point of departure. To reach a "perfect" equilibrium was not any serious theoretical question in Parsons analysis of social systems, indeed, the most dynamic societies had generally cultural systems with important inner tensions like the US and India. These tensions were a source of their strength according to Parsons rather than the opposite. Parsons never thought about system-institutionalization and the level of strains (tensions, conflict) in the system as opposite forces per se.
The key processes for Parsons for system reproduction are socialization and social control. Socialization is important because it is the mechanism for transferring the accepted norms and values of society to the individuals within the system. Parsons never spoke about "perfect socialization"—in any society socialization was only partial and "incomplete" from an integral point of view.
Parsons states that "this point ... is independent of the sense in which [the] individual is concretely autonomous or creative rather than 'passive' or 'conforming', for individuality and creativity, are to a considerable extent, phenomena of the institutionalization of expectations"; they are culturally constructed.
Socialization is supported by the positive and negative sanctioning of role behaviours that do or do not meet these expectations. A punishment could be informal, like a snigger or gossip, or more formalized, through institutions such as prisons and mental homes. If these two processes were perfect, society would become static and unchanging, but in reality, this is unlikely to occur for long.
Parsons recognizes this, stating that he treats "the structure of the system as problematic and subject to change", and that his concept of the tendency towards equilibrium "does not imply the empirical dominance of stability over change". He does, however, believe that these changes occur in a relatively smooth way.
Individuals in interaction with changing situations adapt through a process of "role bargaining". Once the roles are established, they create norms that guide further action and are thus institutionalized, creating stability across social interactions. Where the adaptation process cannot adjust, due to sharp shocks or immediate radical change, structural dissolution occurs and either new structures (or therefore a new system) are formed, or society dies. This model of social change has been described as a "moving equilibrium", and emphasizes a desire for social order.
=== Davis and Moore ===
Kingsley Davis and Wilbert E. Moore (1945) gave an argument for social stratification based on the idea of "functional necessity" (also known as the Davis-Moore hypothesis). They argue that the most difficult jobs in any society have the highest incomes in order to motivate individuals to fill the roles needed by the division of labour. Thus, inequality serves social stability.
This argument has been criticized as fallacious from a number of different angles: the argument is both that the individuals who are the most deserving are the highest rewarded, and that a system of unequal rewards is necessary, otherwise no individuals would perform as needed for the society to function. The problem is that these rewards are supposed to be based upon objective merit, rather than subjective "motivations." The argument also does not clearly establish why some positions are worth more than others, even when they benefit more people in society, e.g., teachers compared to athletes and movie stars. Critics have suggested that structural inequality (inherited wealth, family power, etc.) is itself a cause of individual success or failure, not a consequence of it.
=== Robert Merton ===
Robert K. Merton made important refinements to functionalist thought. He fundamentally agreed with Parsons' theory but acknowledged that Parsons' theory could be questioned, believing that it was over generalized. Merton tended to emphasize middle range theory rather than a grand theory, meaning that he was able to deal specifically with some of the limitations in Parsons' thinking. Merton believed that any social structure probably has many functions, some more obvious than others. He identified three main limitations: functional unity, universal functionalism and indispensability. He also developed the concept of deviance and made the distinction between manifest and latent functions. Manifest functions referred to the recognized and intended consequences of any social pattern. Latent functions referred to unrecognized and unintended consequences of any social pattern.
Merton criticized functional unity, saying that not all parts of a modern complex society work for the functional unity of society. Consequently, there is a social dysfunction referred to as any social pattern that may disrupt the operation of society. Some institutions and structures may have other functions, and some may even be generally dysfunctional, or be functional for some while being dysfunctional for others. This is because not all structures are functional for society as a whole. Some practices are only functional for a dominant individual or a group.
There are two types of functions that Merton discusses the "manifest functions" in that a social pattern can trigger a recognized and intended consequence. The manifest function of education includes preparing for a career by getting good grades, graduation and finding good job. The second type of function is "latent functions", where a social pattern results in an unrecognized or unintended consequence. The latent functions of education include meeting new people, extra-curricular activities, school trips.
Another type of social function is "social dysfunction" which is any undesirable consequences that disrupts the operation of society. The social dysfunction of education includes not getting good grades, a job. Merton states that by recognizing and examining the dysfunctional aspects of society we can explain the development and persistence of alternatives. Thus, as Holmwood states, "Merton explicitly made power and conflict central issues for research within a functionalist paradigm."
Merton also noted that there may be functional alternatives to the institutions and structures currently fulfilling the functions of society. This means that the institutions that currently exist are not indispensable to society. Merton states "just as the same item may have multiple functions, so may the same function be diversely fulfilled by alternative items." This notion of functional alternatives is important because it reduces the tendency of functionalism to imply approval of the status quo.
Merton's theory of deviance is derived from Durkheim's idea of anomie. It is central in explaining how internal changes can occur in a system. For Merton, anomie means a discontinuity between cultural goals and the accepted methods available for reaching them.
Merton believes that there are 5 situations facing an actor.
Conformity occurs when an individual has the means and desire to achieve the cultural goals socialized into them.
Innovation occurs when an individual strives to attain the accepted cultural goals but chooses to do so in novel or unaccepted method.
Ritualism occurs when an individual continues to do things as prescribed by society but forfeits the achievement of the goals.
Retreatism is the rejection of both the means and the goals of society.
Rebellion is a combination of the rejection of societal goals and means and a substitution of other goals and means.
Thus it can be seen that change can occur internally in society through either innovation or rebellion. It is true that society will attempt to control these individuals and negate the changes, but as the innovation or rebellion builds momentum, society will eventually adapt or face dissolution.
=== Almond and Powell ===
In the 1970s, political scientists Gabriel Almond and Bingham Powell introduced a structural-functionalist approach to comparing political systems. They argued that, in order to understand a political system, it is necessary to understand not only its institutions (or structures) but also their respective functions. They also insisted that these institutions, to be properly understood, must be placed in a meaningful and dynamic historical context.
This idea stood in marked contrast to prevalent approaches in the field of comparative politics—the state-society theory and the dependency theory. These were the descendants of David Easton's system theory in international relations, a mechanistic view that saw all political systems as essentially the same, subject to the same laws of "stimulus and response"—or inputs and outputs—while paying little attention to unique characteristics. The structural-functional approach is based on the view that a political system is made up of several key components, including interest groups, political parties and branches of government.
In addition to structures, Almond and Powell showed that a political system consists of various functions, chief among them political socialization, recruitment and communication: socialization refers to the way in which societies pass along their values and beliefs to succeeding generations, and in political terms describe the process by which a society inculcates civic virtues, or the habits of effective citizenship; recruitment denotes the process by which a political system generates interest, engagement and participation from citizens; and communication refers to the way that a system promulgates its values and information.
== Unilineal descent ==
In their attempt to explain the social stability of African "primitive" stateless societies where they undertook their fieldwork, Evans-Pritchard (1940) and Meyer Fortes (1945) argued that the Tallensi and the Nuer were primarily organized around unilineal descent groups. Such groups are characterized by common purposes, such as administering property or defending against attacks; they form a permanent social structure that persists well beyond the lifespan of their members. In the case of the Tallensi and the Nuer, these corporate groups were based on kinship which in turn fitted into the larger structures of unilineal descent; consequently Evans-Pritchard's and Fortes' model is called "descent theory". Moreover, in this African context territorial divisions were aligned with lineages; descent theory therefore synthesized both blood and soil as the same. Affinal ties with the parent through whom descent is not reckoned, however, are considered to be merely complementary or secondary (Fortes created the concept of "complementary filiation"), with the reckoning of kinship through descent being considered the primary organizing force of social systems. Because of its strong emphasis on unilineal descent, this new kinship theory came to be called "descent theory".
With no delay, descent theory had found its critics. Many African tribal societies seemed to fit this neat model rather well, although Africanists, such as Paul Richards, also argued that Fortes and Evans-Pritchard had deliberately downplayed internal contradictions and overemphasized the stability of the local lineage systems and their significance for the organization of society. However, in many Asian settings the problems were even more obvious. In Papua New Guinea, the local patrilineal descent groups were fragmented and contained large amounts of non-agnates. Status distinctions did not depend on descent, and genealogies were too short to account for social solidarity through identification with a common ancestor. In particular, the phenomenon of cognatic (or bilateral) kinship posed a serious problem to the proposition that descent groups are the primary element behind the social structures of "primitive" societies.
Leach's (1966) critique came in the form of the classical Malinowskian argument, pointing out that "in Evans-Pritchard's studies of the Nuer and also in Fortes's studies of the Tallensi unilineal descent turns out to be largely an ideal concept to which the empirical facts are only adapted by means of fictions". People's self-interest, manoeuvring, manipulation and competition had been ignored. Moreover, descent theory neglected the significance of marriage and affinal ties, which were emphasized by Lévi-Strauss's structural anthropology, at the expense of overemphasizing the role of descent. To quote Leach: "The evident importance attached to matrilateral and affinal kinship connections is not so much explained as explained away."
== Biological ==
Biological functionalism is an anthropological paradigm, asserting that all social institutions, beliefs, values and practices serve to address pragmatic concerns. In many ways, the theorem derives from the longer-established structural functionalism, yet the two theorems diverge from one another significantly. While both maintain the fundamental belief that a social structure is composed of many interdependent frames of reference, biological functionalists criticise the structural view that a social solidarity and collective conscience is required in a functioning system. By that fact, biological functionalism maintains that our individual survival and health is the driving provocation of actions, and that the importance of social rigidity is negligible.
=== Everyday application ===
Although the actions of humans without doubt do not always engender positive results for the individual, a biological functionalist would argue that the intention was still self-preservation, albeit unsuccessful. An example of this is the belief in luck as an entity; while a disproportionately strong belief in good luck may lead to undesirable results, such as a huge loss in money from gambling, biological functionalism maintains that the newly created ability of the gambler to condemn luck will allow them to be free of individual blame, thus serving a practical and individual purpose. In this sense, biological functionalism maintains that while bad results often occur in life, which do not serve any pragmatic concerns, an entrenched cognitive psychological motivation was attempting to create a positive result, in spite of its eventual failure.
== Decline ==
Structural functionalism reached the peak of its influence in the 1940s and 1950s, and by the 1960s was in rapid decline. By the 1980s, its place was taken in Europe by more conflict-oriented approaches, and more recently by structuralism. While some of the critical approaches also gained popularity in the United States, the mainstream of the discipline has instead shifted to a myriad of empirically oriented middle-range theories with no overarching theoretical orientation. To most sociologists, functionalism is now "as dead as a dodo".
As the influence of functionalism in the 1960s began to wane, the linguistic and cultural turns led to a myriad of new movements in the social sciences: "According to Giddens, the orthodox consensus terminated in the late 1960s and 1970s as the middle ground shared by otherwise competing perspectives gave way and was replaced by a baffling variety of competing perspectives. This third generation of social theory includes phenomenologically inspired approaches, critical theory, ethnomethodology, symbolic interactionism, structuralism, post-structuralism, and theories written in the tradition of hermeneutics and ordinary language philosophy."
While absent from empirical sociology, functionalist themes remained detectable in sociological theory, most notably in the works of Luhmann and Giddens. There are, however, signs of an incipient revival, as functionalist claims have recently been bolstered by developments in multilevel selection theory and in empirical research on how groups solve social dilemmas. Recent developments in evolutionary theory—especially by biologist David Sloan Wilson and anthropologists Robert Boyd and Peter Richerson—have provided strong support for structural functionalism in the form of multilevel selection theory. In this theory, culture and social structure are seen as a Darwinian (biological or cultural) adaptation at the group level.
== Criticisms ==
In the 1960s, functionalism was criticized for being unable to account for social change, or for structural contradictions and conflict (and thus was often called "consensus theory"). Also, it ignores inequalities including race, gender, class, which cause tension and conflict. The refutation of the second criticism of functionalism, that it is static and has no concept of change, has already been articulated above, concluding that while Parsons' theory allows for change, it is an orderly process of change [Parsons, 1961:38], a moving equilibrium. Therefore, referring to Parsons' theory of society as static is inaccurate. It is true that it does place emphasis on equilibrium and the maintenance or quick return to social order, but this is a product of the time in which Parsons was writing (post-World War II, and the start of the cold war). Society was in upheaval and fear abounded. At the time social order was crucial, and this is reflected in Parsons' tendency to promote equilibrium and social order rather than social change.
Furthermore, Durkheim favoured a radical form of guild socialism along with functionalist explanations. Also, Marxism, while acknowledging social contradictions, still uses functionalist explanations. Parsons' evolutionary theory describes the differentiation and reintegration systems and subsystems and thus at least temporary conflict before reintegration (ibid). "The fact that functional analysis can be seen by some as inherently conservative and by others as inherently radical suggests that it may be inherently neither one nor the other."
Stronger criticisms include the epistemological argument that functionalism is tautologous, that is, it attempts to account for the development of social institutions solely through recourse to the effects that are attributed to them, and thereby explains the two circularly. However, Parsons drew directly on many of Durkheim's concepts in creating his theory. Certainly Durkheim was one of the first theorists to explain a phenomenon with reference to the function it served for society. He said, "the determination of function is…necessary for the complete explanation of the phenomena." However Durkheim made a clear distinction between historical and functional analysis, saying, "When ... the explanation of a social phenomenon is undertaken, we must seek separately the efficient cause which produces it and the function it fulfills." If Durkheim made this distinction, then it is unlikely that Parsons did not.
However Merton does explicitly state that functional analysis does not seek to explain why the action happened in the first instance, but why it continues or is reproduced. By this particular logic, it can be argued that functionalists do not necessarily explain the original cause of a phenomenon with reference to its effect. Yet the logic stated in reverse, that social phenomena are (re)produced because they serve ends, is unoriginal to functionalist thought. Thus functionalism is either undefinable or it can be defined by the teleological arguments which functionalist theorists normatively produced before Merton.
Another criticism describes the ontological argument that society cannot have "needs" as a human being does, and even if society does have needs they need not be met. Anthony Giddens argues that functionalist explanations may all be rewritten as historical accounts of individual human actions and consequences (see Structuration).
A further criticism directed at functionalism is that it contains no sense of agency, that individuals are seen as puppets, acting as their role requires. Yet Holmwood states that the most sophisticated forms of functionalism are based on "a highly developed concept of action," and as was explained above, Parsons took as his starting point the individual and their actions. His theory did not however articulate how these actors exercise their agency in opposition to the socialization and inculcation of accepted norms. As has been shown above, Merton addressed this limitation through his concept of deviance, and so it can be seen that functionalism allows for agency. It cannot, however, explain why individuals choose to accept or reject the accepted norms, why and in what circumstances they choose to exercise their agency, and this does remain a considerable limitation of the theory.
Further criticisms have been levelled at functionalism by proponents of other social theories, particularly conflict theorists, Marxists, feminists and postmodernists. Conflict theorists criticized functionalism's concept of systems as giving far too much weight to integration and consensus, and neglecting independence and conflict. Lockwood, in line with conflict theory, suggested that Parsons' theory missed the concept of system contradiction. He did not account for those parts of the system that might have tendencies to mal-integration. According to Lockwood, it was these tendencies that come to the surface as opposition and conflict among actors. However Parsons thought that the issues of conflict and cooperation were very much intertwined and sought to account for both in his model. In this however he was limited by his analysis of an ‘ideal type' of society which was characterized by consensus. Merton, through his critique of functional unity, introduced into functionalism an explicit analysis of tension and conflict. Yet Merton's functionalist explanations of social phenomena continued to rest on the idea that society is primarily co-operative rather than conflicted, which differentiates Merton from conflict theorists.
Marxism, which was revived soon after the emergence of conflict theory, criticized professional sociology (functionalism and conflict theory alike) for being partisan to advanced welfare capitalism. Gouldner thought that Parsons' theory specifically was an expression of the dominant interests of welfare capitalism, that it justified institutions with reference to the function they fulfill for society. It may be that Parsons' work implied or articulated that certain institutions were necessary to fulfill the functional prerequisites of society, but whether or not this is the case, Merton explicitly states that institutions are not indispensable and that there are functional alternatives. That he does not identify any alternatives to the current institutions does reflect a conservative bias, which as has been stated before is a product of the specific time that he was writing in.
As functionalism's prominence was ending, feminism was on the rise, and it attempted a radical criticism of functionalism. It believed that functionalism neglected the suppression of women within the family structure. Holmwood shows, however, that Parsons did in fact describe the situations where tensions and conflict existed or were about to take place, even if he did not articulate those conflicts. Some feminists agree, suggesting that Parsons provided accurate descriptions of these situations. On the other hand, Parsons recognized that he had oversimplified his functional analysis of women in relation to work and the family, and focused on the positive functions of the family for society and not on its dysfunctions for women. Merton, too, although addressing situations where function and dysfunction occurred simultaneously, lacked a "feminist sensibility".
Postmodernism, as a theory, is critical of claims of objectivity. Therefore, the idea of grand theory and grand narrative that can explain society in all its forms is treated with skepticism. This critique focuses on exposing the danger that grand theory can pose when not seen as a limited perspective, as one way of understanding society.
Jeffrey Alexander (1985) sees functionalism as a broad school rather than a specific method or system, such as Parsons, who is capable of taking equilibrium (stability) as a reference-point rather than assumption and treats structural differentiation as a major form of social change. The name 'functionalism' implies a difference of method or interpretation that does not exist. This removes the determinism criticized above. Cohen argues that rather than needs a society has dispositional facts: features of the social environment that support the existence of particular social institutions but do not cause them.
== Influential theorists ==
Kingsley Davis
Michael Denton
Émile Durkheim
David Keen
Niklas Luhmann
Bronisław Malinowski
Robert K. Merton
Wilbert E. Moore
George Murdock
Talcott Parsons
Alfred Reginald Radcliffe-Brown
Herbert Spencer
Fei Xiaotong
== See also ==
Causation (sociology)
Functional structuralism
Historicism
Neofunctionalism (sociology)
New institutional economics
Pure sociology
Sociotechnical system
Systems theory
Vacancy chain
Dennis Wrong (critic of structural functionalism)
== Notes ==
== References ==
Barnard, A. 2000. History and Theory in Anthropology. Cambridge: CUP.
Barnard, A., and Good, A. 1984. Research Practices in the Study of Kinship. London: Academic Press.
Barnes, J. 1971. Three Styles in the Study of Kinship. London: Butler & Tanner.
Elster, J., (1990), “Merton's Functionalism and the Unintended Consequences of Action”, in Clark, J., Modgil, C. & Modgil, S., (eds) Robert Merton: Consensus and Controversy, Falmer Press, London, pp. 129–35
Gingrich, P., (1999) “Functionalism and Parsons” in Sociology 250 Subject Notes, University of Regina, accessed, 24/5/06, uregina.ca
Holy, L. 1996. Anthropological Perspectives on Kinship. London: Pluto Press.
Homans, George Casper (1962). Sentiments and Activities. New York: The Free Press of Glencoe.
Hoult, Thomas Ford (1969). Dictionary of Modern Sociology.
Kuper, A. 1996. Anthropology and Anthropologists. London: Routledge.
Layton, R. 1997. An Introduction to Theory in Anthropology. Cambridge: CUP.
Leach, E. 1954. Political Systems of Highland Burma. London: Bell.
Leach, E. 1966. Rethinking Anthropology. Northampton: Dickens.
Lenski, Gerhard (1966). "Power and Privilege: A Theory of Social Stratification." New York: McGraw-Hill.
Lenski, Gerhard (2005). "Evolutionary-Ecological Theory." Boulder, CO: Paradigm.
Levi-Strauss, C. 1969. The Elementary Structures of Kinship. London: Eyre and Spottis-woode.
Maryanski, Alexandra (1998). "Evolutionary Sociology." Advances in Human Ecology. 7:1–56.
Maryanski, Alexandra and Jonathan Turner (1992). "The Social Cage: Human Nature and the Evolution of Society." Stanford: Stanford University Press.
Marshall, Gordon (1994). The Concise Oxford Dictionary of Sociology. ISBN 0-19-285237-X
Parsons, T., (1961) Theories of Society: foundations of modern sociological theory, Free Press, New York
Perey, Arnold (2005) "Malinowski, His Diary, and Men Today (with a note on the nature of Malinowskian functionalism)
Ritzer, George and Douglas J. Goodman (2004). Sociological Theory, 6th ed. New York: McGraw-Hill.
Sanderson, Stephen K. (1999). "Social Transformations: A General Theory of Historical Development." Lanham, MD: Rowman & Littlefield.
Turner, Jonathan (1995). "Macrodynamics: Toward a Theory on the Organization of Human Populations." New Brunswick: Rutgers University Press.
Turner, Jonathan and Jan Stets (2005). "The Sociology of Emotions." Cambridge. Cambridge University Press. | Wikipedia/Functionalists |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.