bability-based sampling methods. Both provide computers and internet connections for respondents who do not already have them. Both panels collect demographic information about respondents separately and provide this information with each data set. R


0 (22%) 350 (35%) 250 (25%) 100 (10%) 80 (8%)
    NOTES: Percentages are rounded and might not
sum to 100. Respondents could pick only one race.
 2 For some groups in the ALP, our target sample size was limited by the total sample who had participate


ix.
4 It was formerly known as the Knowledge Networks Panel and was administered by Knowledge Networks.
5 Thirteen respondents were dropped from the sample by Ipsos for leaving more than half of the questions blank or completing the survey in less th


urvey represents the first wave of a planned four-wave survey study. We intend to conduct wave 2 in the fall of 2020, wave 3 in the winter of 2021, and wave 4 in the spring of 2021. When future waves are collected, updated versions of this report wil


or proportions near 0 percent or 100 percent and the largest MOE for proportions near 50 percent. Because the overall sample size of our survey is large, 5,164 respondents, the MOE for the full sample ranges from 0.10 percent to 2.33 percent for prop


nt the unweighted demographic characteristics so that readers can see the original survey sample composition before we applied weighting procedures. This can aid users of the survey data, who might apply other weighting approaches in their analyses.


      None or almost Some of
All of the time
Missing
      4.3 0.1
       D. Have a lot of energy
Sample none of the time time
Wave 1 15.9 50.0 SOURCE: Santa Monica Well-Being Survey.
      None or almost Some of
All of the time
Missing
      3.5 0.


ecify 10.3
Refused 0.7
SOURCE: Census Household COVID-19 Pulse Survey, slightly modified on coronavirus term use.
                    16
Q8. [w1_leaveui] (If NO to Q7). In the last 7 days, were you receiving pay for the time you were not working?
Sel


-19) (through a nasal swab or blood test)?
Sample Yes No Missing
Wave 1 12.3 87.4 0.3 SOURCE: Modified from COVID Impact Survey.
Q13. [w1_covidexp1- w1_covidexp14] Are you experiencing or have you experienced any of the following as a result of the c


 since coronavirus (COVID-19) started
1.3
My household applied or asked for but has not received assistance from this program since coronavirus (COVID-19) started
3.9
No, my household has not received nor applied for assistance from this program sinc


           22
 G. Housing or renter’s assistance programs
Yes, my
My household applied or asked for but has not received assistance from this program since coronavirus (COVID-19) started
1.6
No, my household has not received nor applied for assistanc


                       Somewhat Sample Strongly agree agree
Wave 1 30.2 27.3 SOURCE: Developed by RWJF and RAND.
Neither agree nor disagree
28.4
Somewhat disagree
5.1
Strongly
disagree Missing
8.7 0.4
              Q22. [w1_pocimpact2] People of colo


Some of the
Most of the time time Rarely Never Missing
              Wave 1
SOURCE: Developed by RWJF and RAND.
38.1 47.6 10.4 3.6 0.3
      Views, Mindset, and Expectations: Views of Government Roles
Q26. [w1_stgovt2] How much trust do you have that


DNA)
No effect
Sample 1 2 3 4 5 Missing
               Very strong effect
              28
Q30. [w1_equalaccess] Do you agree or disagree with the following statement: It is the obligation of the government to ensure that everyone has access to healt


 15.9 SOURCE: Developed by RWJF and RAND.
Neither agree nor disagree
21.0
Somewhat disagree
12.1
Strongly disagree
Missing
              31.8 0.3
       30
Survey Respondent Demographics
Both panels collect demographic information about respondents s


last wave. The methods used for this wave were identical to those described in the main text. For the general-population results, we calculated new weights that match the distribution of characteristics in our sample as closely as possible to that o


None or almost
Most of the time
Missing
4.3 .a
All of the time
      48.0 32.0
a The period indicates true 0 (rather than a number that has been rounded down to 0).
General-population 15.7 wave 1
      SOURCE: Santa Monica Well-Being Survey.
 E. Feel


The period indicates true 0 (rather than a number that has been rounded down to 0).
COVID Impacts: Feelings of Safety
More than a year
37.0
Sample
1–3 months
Missing
.a
        General- population wave 1
22.8 18.7
        SOURCE: Developed by RWJF an


whites.
        Somewhat Sample Strongly agree agree
General-population 33.1 26.2 wave 1
SOURCE: Developed by RWJF and RAND.
Neither agree nor disagree
30.2
Somewhat disagree
5.0
Strongly disagree
Missing
       5.6 0.0
       Q23. [w1_sysracism] Sys


   General- 40.3 46.6 9.0 4.1 0.1 population
wave 1
SOURCE: Developed by RWJF and RAND.
a The period indicates true 0 (rather than a number that has been rounded down to 0).
      40
Views, Mindset, and Expectations: Views of Government Roles
Q26. [w


about their diet, exercise, smoking, etc.
No effect
Sample 1 2 3 4 5 Missing
               Very strong effect
       General-population 2.7 5.3 13.3 wave 1
SOURCE: Developed by RWJF and RAND.
How they were born (their genetics/DNA)
No effect
Sample


 disagree
Missing
              40.6 0.1
       Q36. [w1_ racism] Racism is a major public health crisis. Select only one answer.
       Somewhat Sample Strongly agree agree
General-population 31.7 18.0 wave 1
SOURCE: Developed by RWJF and RAND.
Neit


5.0
Unknown
0.2
    Sample
General- population wave 1
Small to midsize or large city, 50k+
78.7
Rural or small town, under 50k
21.1
     46
References
Carman, Katherine Grace, Anita Chandra, Carolyn Miller, Matthew D. Trujillo, Douglas Yeung, Sarah W


ated. As of October 9, 2020:
https://www.pewresearch.org/politics/values/
———, “Explore the Data,” webpage, 2020. As of October 9, 2020: https://www.pewresearch.org/pathways-2020/covid_econopen/total_us_adults/us_adults/
Plough, Alonzo, and Anita Cha


 Wearable Sensor Technology and Potential Uses Within Law Enforcement
Identifying High-Priority Needs to Improve Officer Safety, Health, and Wellness Using Wearable Sensor Technology
Sean E. Goodison, Jeremy D. Barnum, Michael J. D. Vermeer, Dulani W


emented.
• A sequenced or phased approach should be devel- oped for taking validated technology to the field for scaled evaluations.
Technology and data measurement
• Individual baselines should be established to account for differences among individ


seamlessly integrate with the technology that law enforcement already carries, measures need to be valid and reliable, interpretation of the data needs to be clear, and policies need to be in place for managing and monitoring the data. WST has the po


rm personnel or staffing selections for assignments (e.g., make changes to officers’ duties in response to indicators of prolonged sedentary behavior or chronic stress indicators while on duty) (Arroyo, 2019; Bedford, 2019; Cashion, 2018). Future sce


cies that are needed to create good policy or best practices for use in law enforcement (Jackson et al., 2020).
Although the sequence of events just described is consis- tent with WST to date and could accurately reflect the future WST trajectory in


s of the workshop.
Measurement
WSTs, which we refer to as wearables when we describe the commercially available mass-market devices, contain sensors worn on the body to collect biomarkers from the user. For example, wristwatches are a common form of


ed with psychological conditions, such as mental stress. The ability to collect real-time feedback from individual users on a suite of behavioral, physiological, and psychological indicators demon- strates the potential for this emerging technology t


cross platforms, have limited battery life, must be worn for extended periods of time, and are typically much bulkier and less practi- cal for everyday wear (Dunn, Runge, and Snyder, 2018). These devices also require personal calibration to produce m


mise for WST
application in law enforcement and other first responder groups (Shaw et al., 2004). This program used a suite of sensors embedded in clothing fabric, chest harnesses, wrist devices, and wrist devices with chest straps to demonstrate a p


est to law enforcement agencies, technology manufacturers, the research community focused on officer health, and public policy and privacy advocates involved in the collection and use of health data. For a detailed description of the panel selection


ta.
  There are too many devices to choose from, and there is • inadequate information about their performance.
Policy adaptation
WST data are sensitive, personal information and need to be • protected by strong security.a •
It is difficult to change


ured, and what WST metrics are most meaningful and relevant for law enforcement.a
There are too many devices to choose from, and there is
inadequate information about their performance.
Potential Solution
• Evaluate technologies based on technology r


lighted the goal of securing buy- in through policy protections, along with systematically decid- ing what devices to use. The rest of the needs in this category identify as opportunities (1) the apparent willingness among officers to adopt WST for p


ield of products. Establishing baselines to account for indi- vidual variability in each officer was seen as a potential solu-
tion to challenges with individualization. Five of the potential solutions called for evaluations and studies of the techno


hese efforts.
This section provides further context from the workshop discussion on the identified needs, organized by the four need categories developed as a result of responses at the meeting (i.e., policy adoption, policy adaptation, technology an


this issue: (1) the acceptability of WST as a tool in policing and (2) the willing- ness of officers to wear and use WST. Experts discussed how a growing number of police leaders are beginning to understand the need for agencies to support the mental


ut also at home to capture an individual’s universe of stressors and what strategies might be effective for mitigating their impact.
Police leaders must also find ways to ensure that officers wear and use WSTs. According to the experts, one way to do


elieved that the devices ultimately would be used against them. Agencies will need to take steps to ensure that data collected from wearable sensors are used to inform strategies that support officers’ health and wellness and improve police operation


ST data like any other law enforcement–sensitive data to ensure that they enjoy the same safeguards. Other experts believed that data belong to the users from whom they are collected, allowing users to make decisions about how the data are shared and


arency to the public. For example, some experts imagined a dashboard displaying average heart rates of officers across time and space. However, other experts cau- tioned that de-identification is difficult, especially as open data become increasingly


critical incidents through better training, conditioning, and recovery. Experts recommended that agencies help officers by providing guidance on objectively assessing their progress over time in response to different interventions as part of the coac


ations around WST in the near term, especially as industries begin to approach police leaders to market and sell their devices. Experts believed that it would be helpful to evalu-
ate WSTs using the U.S. Department of Defense’s technology readiness l


olve a determination of the specific needs for data accuracy, reliability, and processing for each use case. Determining who will use or be assigned WST devices also will help resolve uncertainty about what form factors and data collection, shar- ing


iform policies, tactical requirements, and data security requirements. The challenge will be to strike a bal- ance between customizing devices to the needs of a particular agency and standardizing devices for use in law enforcement more generally. If


making but highlighted a strong need to lay the policy groundwork now given the high ceiling of potential for WST. Now is the time to plan for the potential implications of WST, while the technology is still developing
and personal adoption is increa


that were not included in the existing list and suggested new ones. Although the process of expert elicitation that we describe in this appendix was designed to gather unbiased, representative results from experts and practitioners in the field, we n


ension, participants were instructed that 1 was a low score and 9 was a high score. Participants were told to score a need’s importance with a 1 if it would have little or no impact on the problem and with a 9 if it would reduce the impact of the pro


orithm to minimize within-cluster variance when deter- mining the breaks between tiers. The choice of three tiers is arbitrary but was done in part to remain consistent across the set of technology workshops that we have conducted for NIJ. Also, the


 A.2. Example of the Delphi Round 3 Voting Form
Question
Issue: The effectiveness of using the technology to improve officer safety and wellness is uncertain.
Need: Develop a sequenced or phased approach to taking validated technology to the field fo


e that there were gaps between these boundaries, so some of the modified expected values could fall in between tiers. See Figure A.3.) As with prior work, we set a higher bar for a need to move up or down two tiers (from Tier 1 to Tier 3, or vice ver


• 17 were related to policy adoption
• 24 were related to policy adaptation
• 13 were related to technology and data measurement • seven were related to technology and data usage.
 Tier 1 Tier 2 Tier 3
Round 2
         Round 3
        7.5
 Expected


t for law enforcement.a
There has been a shift in how law enforcement takes care • Provide coaching, mentoring, and evidence-based pro- of its personnel, and greater attention has been paid gramming for officers to help them understand the infor- to


, bio- metrics, and bioanalytics and how they inform selected outcomes; or do both.
Conduct validation studies of WST devices, and conduct
23
          reliability studies as technology changes.
• Define a set of best practices for consumer wearable


 a policing career, are potentially more aware of health, and might be willing to try new technology.a
Laws and regulations are outdated when it comes to handling digital data.
Variation in law enforcement agencies across the country highlights the d


r data are displayed so that they are meaningful.
    a This problem or opportunity is associated with needs that fell into different tiers.
26
Notes
1 We define wearability as a qualitative measure of the comfort of a worn device. We define validity


 17, 2020: https://www.ericsson.com/4a2d0e/assets/local/reports-papers/ consumerlab/reports/2016/wearable-technology-and-the-internet-of- things-ericsson-consumerlab-2016.pdf
Evenson, Kelly R., Michelle M. Goto, and Robert D. Furberg, “Systematic Rev


 of September 22, 2020:
https://www.ncjrs.gov/pdffiles1/nij/grants/250382.pdf
27
28
Institute of Medicine and National Research Council, “Appendix E: Technology Readiness Levels in the Department of Defense,” in Technologies to Enable Autonomous Dete


the Field,” Electronic Frontier Foundation, November 4, 2015.
Majumder, Sumit, Tapas Mondal, and M. Jamal Deen, “Wearable Sensors for Remote Health Monitoring,” Sensors, Vol. 17, No. 1, 2017.
Miller, Lindsay, Jessica Toliver, and Police Executive Res


 Institute in Environmental Medicine and the Soldier Systems Center, Lexington, Mass.: Lincoln Laboratory, Massachusetts Institute of Technology, November 1, 2004. As of July 17, 2020: https://apps.dtic.mil/dtic/tr/fulltext/u2/a428022.pdf
Shcherbina,


would like to acknowledge the participation and assistance of the members of the workshop on wearable sensor technology and potential uses within law enforcement, who are listed in the report. This effort would not have been possible without their w


venile Justice and a research assistant at the Personality Studies Laboratory and the Regents’ Center for Learning Disorders at the University of Geor- gia. Siara holds an M.S. in criminology.
Shoshana R. Shelton is a senior policy analyst at the RAN


Priority Law Enforcement Issues and Needs, Santa Monica, Calif.: RAND Corporation, RR-2930-NIJ, 2019.
Mentions of products or companies do not represent endorsement by NIJ, the RAND Corporation, or PERF.
 This publication was made possible by Award N


  THE BENEFITS AND COSTS OF DECARBONIZING COSTA RICA’S ECONOMY
Informing the implementation
of Costa Rica’s National Decarbonization Plan under uncertainty
David G. Groves, James Syme, Edmundo Molina-Perez, Carlos Calvo Hernandez (RAND Corporation)
L


ocial development means that the same households that face the greatest economic difficulties also suffer the most from environmental crises like the pandemic. Today in Costa Rica and beyond, the priority is to stop the pandemic, alleviate its social


mong the best internationally. This effort makes it easier for
 iii
iv The Benefits and Costs of Decarbonizing Costa Rica’s Economy
public policies to benefit both from academic science and from the knowledge that actors in each sector bring to the t


e RAND Corporation, the Costa Rica Climate Change Directorate, and the Inter-American Development Bank (IDB). It was funded by the Inter-American Develop- ment Bank’s (IDB)’s French Climate Fund (RG-T3193) and Sustainable Energy and Climate Change In


laborated with government ministries providing technical support in the design of policies. For more informa- tion, email eperlab.eie@ucr.ac.cr.
About Costa Rica’s Climate Change Directorate
The Climate Change Directorate of Costa Rica is an office o


 . . . . . . . . . . . . . . . . . . . . . . .
APPENDIXES
The following appendixes are available in a separate volume at www.rand.org/t/RRA633-1:
A. Modeling Details and Sector Benefit and Cost Factors B. Developing Socioeconomic Scenarios
C. Transpo


. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.9. Levelized Cost of Electricity over Time Without Decarbonization and with the Implementation o


counted Net Benefits and 2050 GHG Emissions for All 3,003 Futures, ClassifiedbyOutcomeRisk.....................................................................
4.4. Total GHG Emissions in 2050, by Economic Growth Scenario . . . . . . . . . . . . . .


missions means that all GHG emissions (not just CO2) do not exceed the natural sequestration from forests.
  xiii
xiv The Benefits and Costs of Decarbonizing Costa Rica’s Economy
ing health and environmental conditions through the reduction in use of


d Lempert, 2007; Lempert, 2019), which guides the evaluation and analysis of thousands of plausible futures to explore the risks and opportunities associated with decarbonization. As part of this process, we developed and used an interactive tool to


quivalent (MtCO2e) today to almost 19 MtCO2e by 2050. Bending this trajectory downward in order to reach net- zero emissions by 2050 will require a substantial transformation in how the economy is pow- ered and how natural resources are used and pres


ra et al., 2020).
Efficiency gains in industry, and the economic value of recycled materials and treated wastewater, result in a small net benefit for the industry and waste sectors: $1.3 billion together. Figure S.2 shows modest net costs for the el


nagement, also can restore many of these lost ecosystem services.
There is a large potential to reduce GHG emissions in the freight transport, industry, and waste sectors, and the benefits are of similar scale to the costs. For example, there are sig


e suggestive of the plausible range of outcomes for each line of action.
To understand what the calculated ranges of emissions and net benefits mean to Costa Rica decarbonization efforts, we identify the conditions that lead to high emissions or low


th of electric private and freight transport
Growth of hydrogen heavy freight Growth of share of non-motorized trans- port and public transport use
Development of new renewables to meet increasing demand
Household energy use
Percentage of household e


Rica); Felipe De León and Andrea Meza Murillo (Ministry of Environment and Energy, Climate Change Directorate); and Valentina Saavedra Gómez and Adrien Vogt-Schilb (Inter-American Development Bank [IDB]). The IDB team worked under the supervision


verall goal to stabilize the increase in global temperature at well below 2°C, and as close to 1.5°C as possible (United Nations, 2015). This ambitious goal requires reaching net-zero emissions of carbon dioxide (CO2) by 2050, and drastically reducin


ensity of industry, agriculture,
and livestock
5. collecting, treating, and reusing liquid and solid waste.
To facilitate these changes, the NDP lays out a wide-range of policy reforms. Table 1.1 lists some of the specific actions considered in the N


experts in policy analysis. Over time, this model can be improved to yield more-refined estimates of emissions and of the benefits and costs of decarbonization. Co-constructing data, models, and analytic approaches leads to results that are relevant


ible futures in which the NDP will be implemented. This means evaluating thousands of different assump- tions about the drivers of emissions and decarbonization, as well as factors that describe how benefits and cost could accrue. We use methods for


e then estimated how emissions would change under one possible approach for implementing the NDP (called “with implementation of the National Decarbonization Plan”). Next, we roughly estimated the monetary benefits and costs to provide a high-level a


y and estimate its benefits and costs. This framework combines previously developed models of transportation and energy sectors (Godínez-Zamora et al., 2020) with new aggregated models of other sectors that do not have more detailed models available


d emissions rates.
We use a general equilibrium model of the Costa Rican economy—Plataforma de Mod- elación Económico-Ambiental Integrada (Integrated Economic-Environmental Modeling [IEEM])—to derive three scenarios of underlying economic activity


ng Costa Rica’s Economy
Figure 2.1
Modeling Schematic for the Costa Rica Integrated Decarbonization Pathways Model
are a very small fraction of all the climate change reduction benefits that would accrue if all countries reduced emissions per the 1.5


 9
   How COVID-19 Might Affect Costa Rica’s Decarbonization Efforts
The analysis presented here was designed and developed in large part before the COVID-19 pandemic hit, in February 2019. The socioeconomic impacts of the pandemic and the decarboniz


eflect uncertainty about future drivers and the achievement of decarbonization actions, we devel- oped a range of estimates for the model factors and created a large set of plausible futures, as described below. These futures should not be assumed to


ergy savings
• improved productivity from reduced congestion
• reduced medical costs from accidents
• reduced health impacts from pollution
• reduced social cost of carbon emissions, which reflect country-specific climate change
impacts in Costa Rica


dix A provides details and numerical values.
Table 2.2
Transport Sector Benefits and Costs of Decarbonization Modeled in This Study
  Benefits of Decarbonization
• Operations and maintenance costs savings due to alternative fuel vehicles and reduced


additional electricity is used. The OSeMOSYS-CR model estimates the required additional renewable energy sources (and associated investment costs), and the GHG emissions savings and fuel cost savings from using these sources instead of existing foss


ctices
Increased use of wood and natural building materials
Model Implementation
• Reduced household energy use
• Increased share of electricity use (and corresponding
decrease in use of fossil fuels)
Not included in the study.
       Table 2.6
Build


an Actions and Model Implementation
   Decarbonization Plan Actions
Process improvement to reduce energy use Electrification of processes
Process improvements to reduce emissions
Increased efficiency of use and reduction in emissions from industrial


- tion Plan (Política Nacional de Saneamiento en Aguas Residuales; PNSAR) calls for many of these same investments due to these potential benefits (AyA, 2016). We estimate the costs of collecting and processing waste for landfill disposal, compostin


pment. Emissions associated with electricity use are captured in the electricity sector. The GHG emissions for each type of animal is based on per animal emissions rates, which are composed of separate emission factors for enteric fermentation and ma


all other crops. Costs from the livestock sector are based on aggregate GHG emissions reductions, per academic studies. We consulted representatives from a range of stakeholders from these sectors, who are listed in Appendix D.
The forestry sector mo


lay out exactly as anticipated today, and thus there is uncertainty about how emissions could evolve in the future without decarbonization. Uncertainty about model estimates of future emissions stems from (1) inaccurate or incomplete information abou


timates were developed prior to the spread of COVID-19. Recent studies suggest, however, that the pandemic-related reductions are likely to be temporary (Forster et al., 2020). As such, any impact on long-term economic activities can be suitably refl


try
Waste
Agriculture, livestock, and forestry
Driver Uncertainties
• Economic growth rate •
Decarbonization Uncertainties
N/A
    • Demand for transport (linked to economic •
growth) transport
• Cost of fuels • • Infrastructure costs for electrifica


emissions, and by how much? What range of net benefits might be achieved? Second, we seek to understand what future conditions could lead Costa Rica’s decar- bonization strategy to not achieve its goals. This information then informs how to implemen


f 4.9 MtCO2e. The current elec- tricity system is nearly 100 percent renewable and has significant excess capacity. So, while emissions reductions are not directly coming from the electricity sector, the current renew- able capacity of the electricit


bon Economic benefits
Savings from electrification and efficiency Opportunity costs
-Investment costs
Net benefits
12.9 10.1
          7.6
      3.6 1.7
2030
investment costs are quickly outweighed by the benefits.2 Opportunity costs include those re


costs associated with a particular line of action do not need to translate into costs for the economic actors of that sector. The distribution of costs and benefits over con- sumers and firms depends crucially on government policy, which is not cons


ductions in costs associated with pollution, accidents, and congestion—about $11 billion. Most benefits come from reduced accidents, accomplished through reduction in the numbers of private vehicles used and distance traveled
   Public and private tr


 for under the respective lines of actions.
Implementing the NDP increases electricity consumption (Figure 3.8). In 2018, electric- ity use was about 31 petajoules (PJ) per year, and it increases to almost 140 PJ per year under baseline assumptions.


on benefits in the residential sector result primarily from energy cost sav- ings to residential and commercial building energy customers (Figure 3.11). Costs, though dif- ficult to estimate for the commercial sector, are considerably higher for comm


ing emissions from industrial products—about $0.6 billion—and increasing energy efficiency—about $200 million, under baseline assump- tions. The net benefits under these baseline assumptions are $2 billion.
Figure 3.12
Emissions from the Industrial S


d—about $440 million in aggregate (Dixon, 2012). Similar assessments reveal another $200 million to the regional environment and groundwater benefits from reducing untreated wastewater in communities. There may be additional ecosystem benefits from i


 2050, but would yield about $25 billion of benefits from increased agricultural and
livestock yields and additional forest ecosystem services.
The agriculture, livestock, and forestry sector collectively leads to net sequestration in Costa Rica. Agr


increased agricultural output due to improved management ($4 billion);3 (2) increased ecosystem ser- vice benefits from not removing wet, dry, or mangrove forests ($7.2 billion), and (3) improv- ing forest management ($13.5 billion).4 According to ou


shown in this chapter are all based on a set of baseline assumptions. There is significant uncertainty around these assumptions, so it is important to understand whether and how these uncertainties could affect the achievement of the NDP emissions ta


 Benefits and Costs of Decarbonizing Costa Rica’s Economy
Figure 4.1
Projections of GHG Emissions Without Decarbonization (yellow) and with the Implementation of the National Decarbonization Plan (green) Across 3,003 Plausible Futures
    National De


ssions.
• Low Net Benefits: We consider two different thresholds, as each can provide important insight. We first set the threshold at zero net benefits and describe which factors drive the small number of cases in which net emissions are negative. T


050 ($ billions)
How Uncertain Is the Success of Costa Rica’s Decarbonization Plan? 43
several specific techniques to sort through the large set of uncertainties and identify what is most important. There are many seemingly obvious reasons why the ND


 and High Growth economic scenarios correspond to long-term average growth of 2 percent, 3.5 percent, and 4 percent growth per year.
44 The Benefits and Costs of Decarbonizing Costa Rica’s Economy
Table 4.1
Sector-Specific Median GHG Emissions in 205


ysis is between 70 and 100 percent.
How Uncertain Is the Success of Costa Rica’s Decarbonization Plan? 45
Figure 4.5
Range of Uncertain Factors Defining the “Low Adoption of Alternative Fueled Vehicles” Vulnerability
Adoption rate of electric private


l Vehicles with High Economic Growth” Vulnerability
Economic growth
Low (2%/yr) Moderate (3.5%/yr)
Cost ratio of alternative versus conventional vehicles
37% 103%
Fuel efficiency of conventional vehicles
50% 60%
High (4%/yr)
285%
150%
       Vulnerab


above 98%
N/A
Low adoption of electric trucks: share of electric light freight below 92%
N/A
       Uncertainties Relevant to Transportation
Demand for transport (linked to economic growth)
Technological costs
Vehicle efficiencies
Growth of electric


 less negative emissions) would occur under futures in which the sequestration rates of wet forests are lower than expected or
Table 4.3
Industry Uncertainties and Definition of Key Emissions Vulnerability
  Industry Uncertainties
Economic growth Ind


lands), emissions from converting forests to grassland or agricultural land, and sequestration rates from dry, moist, palm, and mangrove forests (primary and secondary forests) and sequestration rates from secondary wet forests. This vulnerability de


ost of decarbonization. Fifty-two percent of the cases that display these conditions are vul- nerable, and this vulnerability describes 41 percent of the low net benefits cases. It is defined by the following conditions (Figure 4.8):
• Low economic g


res in which demand for light freight transportation is above 10.14 gross tonne kilometers (Gtkm; considering 12.5 percent less demand from baseline conditions).
Together, these two scenarios describe the key risks for achieving substantial positive


i- mates large benefits accruing from preserving and improving the management of primary forest (about $20 billion across all forest types under baseline assumptions). Estimating eco- system services benefits is also highly imprecise. Second, uncerta


suring sufficient decoupling and emissions reduc- tions with significant net benefits to the economy.
In the transport sector, our analysis suggests that Costa Rica needs to pay attention to uncertainties around both the drivers of emissions, costs,


ansportation.
For the other sectors, the NDP may not achieve zero or close to zero net emissions if the industrial and livestock emissions rates are not low enough to compensate for high economic activity. Further, the success of the NDP emissions re


ied uncertainties. Shaping actions are those that ensure particular unfavorable conditions do not occur in the first place.
Our analysis of the transport sector further validates the importance of several principles established in the NDP. First, the


ions reduction targets for each sector, but it should also indicate whether and when such targets should be revised. For example, the transition rate from conventional to alternative fueled vehicles could be connected to the relative cost of alternat


en Español
Model Assumptions and Emissions Results
11 August 2020
For more information, please contact:
David Groves (groves@rand.org)
Felipe de Leon (felipe@climatrader.com) Adrien Vogt-Schilb (avogtschilb@iadb.org) Jairo Quiros (jairohumberto.quir


rtin Cicowiez, The Integrated Economic-Environmental Modeling (IEEM) Platform, IEEM Platform Technical Guides: IEEM Mathematical Statement, IDB Technical Note No. 01842, Washington, D.C.: Inter-American Development Bank, 2020.
Banerjee, Onil, Martin


tico, 2020, Análisis de costo-beneficio de la descarbonización del sector transporte y la importancia del TRP, August 2020.
Electric Power and Energy Research Laboratory, “The OSeMOSYS–CR Model,” GitHub, 2020. As of October 7, 2020:
https://osemosy


e, Vol. 17, No. 1, February 2007, pp. 73–85.
Groves, David G., Edmundo Molina-Perez, Evan Bloom, and Jordan R. Fischbach, “Robust Decision Making (RDM): Application to Water Planning and Climate Policy,” in Vincent A. W. J. Marchau, Warren E. Walker,


Alejandro, Philip Keefer, Allen Blackman, Matías Busso, Eduardo Cavallo, Gregory Elacqua, Ana María Ibáñez, Julián Messina, Mauricio Moreira, Carlos Scartascini, Norbert Schady, and Tomás Serebrisky, Emerging from the Pandemic Tunnel with Fast


 Is Increasing or Decreasing? Washington, D.C.: World Bank, 2014.
Saget, Catherine, Adrien Vogt-Schilb, and Trang Luu, Jobs in a Net-Zero Emissions Future in Latin America and the Caribbean, Inter-American Development Bank and International Labour Or


o-emissions public transport. Energy savings in buildings, efficiency gains in industry, and the economic value of recycled materials and treated water complete our estimates.
Recognizing uncertainty about the future, we evaluate thousands of differe


 CORPORATION
KARLYN D. STANLEY, MICHELLE GRISÉ, JAMES M. ANDERSON
Autonomous Vehicles and the Future of Auto Insurance
    For more information on this publication, visit www.rand.org/t/RRA878-1
  Library of Congress Cataloging-in-Publication Data i


in law and business, other researchers, and the public. The ICJ is part of the Justice Policy Program within the RAND Social and Economic Well-Being Division. The program focuses on such topics as access to justice, polic- ing, corrections, drug pol


rance Policy? . . . . . . . . . . . . . How Important Is Consumer Acceptance to the Deployment of Autonomous Vehicles?. . . How Might Different Auto Insurance Frameworks Accommodate Technologies for
Autonomous Vehicles? . . . . . . . . . . . . . . .


port, we discuss vehicles we
call autonomous—those that operate at Level 4 or 5:
• At Level 4, or high automation, “[a]n automated driving system (ADS) on the vehicle can itself perform all driving tasks and monitor the driving environment— essential


assigned to the driver in 94 percent (±2.2%) of the crashes” (NHTSA, 2015, p. 1). In 2016, NHTSA stated that it was working to “address the human choices that are linked to 94 percent of serious crashes” (NHTSA, 2017). It also stated that it
continue


ing AVs than an analysis that focuses on driver performance would be. To be clear, this is a descriptive prediction of how courts and legal analysts are likely to apply the predominant justifications of tort law to this new technology and not a norma


ge automobile insurance law to see technology to automate vehicles advance. Currently, insurance is governed by states, and each state sets its own particular requirements and requires rate approval. This makes some sense in the U.S. federal system b


e sig- nificant changes to the existing U.S. automobile insurance system, or is the cur- rent insurance model flexible enough to handle vehicles that incorporate tech- nologies that permit autonomous operation at most or all times? A majority of U.S.


i
xiv Autonomous Vehicles and the Future of Auto Insurance
Several experts were proponents of self-insurance by manufacturers. These experts thought that OEMs might purchase insurance companies and have them handle the insurance for their AVs. Accord


ystem of suppliers and, in some cases, make it more difficult to determine which supplier was at fault, insurers anticipated continuing to “handle this like [they] handle suppliers today.”
In the future, how might accidents between AVs and convention


king any major overhaul of the existing auto insurance framework. As one Australian expert noted, Australian regulators recognize that what they develop needs to be proportional and scalable over time. Other countries, such as the UK and Japan, are f


.
We conclude this report with three recommendations:
• Insurers, manufacturers, and other stakeholders should collaborate to develop a framework for collecting and sharing data on AVs. Further research to explore methods for information-sharing betw


merican Trucking Associations, the Association of British Insurers, AXA UK, the Centre for Connected and Autonomous Vehicles, the Consumer Federation of America, Consumer Reports, Ford Motor Company, General Motors, the Insurance Bureau of Canada, IT


ion might be slow, despite the tremendous investments made by OEMs and related companies. Failure to inspire consumer confidence in AV technologies could result in market failure and the loss of the social benefits of these technologies (Anderson, Ka


wever, the introduction of AVs will likely create uncertainty regarding regulation and insurance. The challenge for policymakers is to maximize the benefits associated with AVs while reducing the uncertainty occasioned by their introduction.
Despite


r automobile insur- ance?
• In the future, how might accidents between AVs and conventional vehicles and between AVs and pedestrians be handled?
• Will minor accidents and “fender benders” become significantly more costly due to the cost of repairing


ay that allowed for both consistency, based on a set of common questions that all participants were asked to answer, and flexibility, whereby interviews could focus on specific topics based on the particular expertise and perspective of the participa


Canada, and Australia and explain how these models may inform future reforms of the U.S. automobile insurance industry. In Chapter Five, we explore key risks associated with AVs, including software updates, the cost of sensors, cybersecurity, remote


sis is descriptive rather than normative.
7
8 Autonomous Vehicles and the Future of Auto Insurance
Deterrence
A critical justification for the tort system is its role in deterring wrongdoing. Imposing the costs of wrongful actions on the wrongdoer cr


instead of accident in part to emphasize the fact that these incidents are the result of specific decisions and not unavoidable. However, much of the legal literature predates the adoption of this term and uses the term accident. In this report, we


ng party, that party would pay the cheapest cost avoider to take whatever accident reduction methods were cost justified (Coase, 1960). For example, imagine that the most efficient way of reducing manufacturing defects in cars was under the manufactu


 injured party.
As was the case with deterrence (and for somewhat similar reasons), we anticipate that the increase of automation will change defendants’ relative moral culpability. It is harder to view the individual driver as morally culpable for a


bly by the fleet operator, the most morally responsible entity may be the manufacturer that designed the vehicle.
Compensation
In this view, tort law exists primarily to compensate the injured. The focus is not so much on deterring misconduct or achi


t an increase in vehi- cle automation will lead to a decrease in individual driver liability and an increase in vehicle manufacturer liability. But Oliver Wendell Holmes famously observed that “[t]he life of the law has not been logic: it has been ex


ficant reasons to anticipate some variation of the existing legal system for some time, for reasons of both claim administration and underwriting.
The existing infrastructure for handling crashes is likely to resist change. This is partly due to shee


ary to underwrite efficiently. Even if humans are playing a significant role in the driving function, manufacturers may be able to more easily collect rich data on human driving behavior and the sources of risk than insurers are. Manufacturers, howev


seek subrogation from the manufacturer because automation makes the manufacturer more responsible, as dis- cussed above. In this way, the ultimate liability may be shifted onto the manufacturer despite the continuation of the existing automobile ins


ested at the OEM’s feet.
 16 Autonomous Vehicles and the Future of Auto Insurance
these claims. And although one hopes that increased automation will lead to fewer crashes, this transition is likely to be gradual. Insurers have considerable specializ


gated to self-insure up to higher than anticipated retentions, based on the fact that there is no data on which insurers can appropriately price liability policies.”
16 Thestate-by-stateinsurancesystemdoesposeasignificantburdentonewentrantswantingtoo


ummarizes U.S. experts’ perceptions of the likelihood of success of future U.S. insurance frameworks. Table 3.2 outlines the experts’ assessments of the
19
20 Autonomous Vehicles and the Future of Auto Insurance
criteria these experts used to assess


id not view the introduction of a national no-fault insurance system for AVs as a realistic possibility. Although national no-fault schemes have been enacted in the context of injuries stemming from both vaccines and nuclear reactors, stakeholders no


. 85-256, as codified at 42 U.S.C. § 2210).3 The Price–Anderson Act was intended to promote investment in nuclear energy research by imposing statutory constraints on possible catastrophic tort liability in the event of a nuclear accident (Rabin, 199


mehow enacted, the federal bureaucracy was not equipped to administer a complex statutory insurance program. One insurer characterized a national no-fault insurance system as an interesting, but ultimately premature, idea that might make
4 Under the


ture of Auto Insurance
sense in a fully autonomous world, noting that “we are a very long way away from [such a world] today.”
A State No-Fault Insurance Model for Autonomous Vehicles
In the past, state no-fault auto insurance schemes have not lived


ntroduce a no-fault insurance system.
Stakeholders expressed concerns that a state no-fault insurance model would not properly incentivize manufacturers to design and produce safe AVs. It was noted that “costs make people act better.” According to on


ally quite low. But this is no longer the case in Florida.
10 See Zuby, undated, pp. 1–2 (“Since 1995, IIHS [the Insurance Institute for Highway Safety] has created a rigorous program of crash test ratings that have led to measureable improvements in


better positioned to collect the information necessary to underwrite efficiently. Even if humans are driving, manufacturers may be able to more easily collect rich data on human driving behav- ior and the sources of risk than insurers. Manufacturers,


hat, under this model, fleet owners should bear responsibility for accidents caused by AVs.13 As we explained in Chapter Two, owners of fleets of AVs may be in
11 Although many experts predicted that the fleet model would eventually become dominant,


policies yet. They also raised potential ethical issues asso- ciated with personal mobility policies, including that such policies “make the victim responsible for protecting against [the] negligence” of others—although it could be argued that this


turn, and the pro- fessionals will figure it out,” as one expert told us. Another expert underscored that the existing insurance framework “does not need to be blown up and replaced with something new.” Rather, the “existing structure [of the insuran


us Vehicles in Auto Insurance Claim Scenarios
We asked stakeholders about specific types of insurance claim incidents that might occur with AVs and how they would be handled. These incidents were
• an AV colliding with a conventional vehicle
• an acc


he different business models of AV manufacturers will affect the extent to which subroga- tion remains a common feature of the claims process.15
A Crash Involving an Autonomous Vehicle and a Pedestrian
In response to our questions about how common au


One stakeholder concluded, “The risks of property damage are the same for AVs and non-AVs.”
At the same time, new concerns about property damage are likely to emerge as AVs become more popular. Some stakeholders told us that, in the absence of a huma


UR
International Models for Insuring Autonomous Vehicles
 This chapter provides an overview of recent developments in insurance and the reg- ulation of AVs in the UK, Australia, Canada, and Japan. We selected these coun- tries because compensating th


t]he single insurance policy’s intent is to align the tort process for automated vehicle claims with traditional claims involving conventional vehicles” (IBC, 2018, p. 11). Of particular interest to insurance regulators in the United States is that t


driver which will pay the bulk of the claim” (Butcher and Edmonds, 2018, p. 5). However, unlike in the U.S. insurance structure, in the UK framework, “even where there is no ‘fault,’ victims are assured of compensation” (Butcher and Edmonds, 2018, p.


 However, at Levels 4 and 5, if the vehicle is driving itself at the time and the person in the driver’s seat is not in the fallback position, the person is not responsible for the accident. A UK insurance expert explained,
[I]n the UK, if you are dr


he insurance industry and the public, NTC will bring the recommendations to the Australian legislature. The focus of NTC’s consultations is changes to MAII to provide for injuries that result from an accident involving an automated vehicle or AV. Eac


compulsory third-party insurance scheme. Australian courts use tests similar to those in the United States in products liability cases.
Australia also has the NIIS, which ensures that “people who sustain eligible seri- ous or catastrophic, lifetime i


es caused by human error rather than product faults. If MAII schemes were to cover ADS crash inju- ries, significant redesign of MAII schemes may be required to ensure that the cost of ADS crashes is borne by those who can control the risks. These pa


automated technology. The policy “would ensure that vehicles continue to be prop- erly insured and that people injured in collisions involving automated vehicles are compensated fairly and quickly” (IBC, 2018, p. 11). IBC has noted that, “[u]nlike no


uded, “These rules are based on years of jurisprudence and how the courts assigned fault in cases.”
The insurance expert indicated that, once AV technology was introduced, an injured party would have to prove that the other party caused the accident.


Bill” (IBC, 2018, p. 13). The authors noted that the two other data elements provide relevant information from the vehicle’s dashboard. The Canadian insurance expert we interviewed noted that IBC officials did not think that any of the data elements


o the authors, the expert provided an unofficial but helpful translation of the provisions of the legislation:
The “automatic operation device” is to process the sensor for detecting the operat- ing state and surrounding conditions of the vehicle and


acturer of the AV.” Regard- ing other anticipated changes to the automobile insurance industry, the expert com- mented, “It is an important duty to modify or introduce a new insurance system, espe- cially for AVs. Insurance could help or become an ob


ance could either help or delay the deployment of AVs, an important point for consideration by regulators and policymakers in the United States.
Table 4.1 illustrates some of the similarities and differences of the auto insurance frameworks we have d


e of data-sharing between OEMs and insurance companies. Finally, we examined expert perspectives on the importance of consumer acceptance of AVs, in response to our research question.
 49
50 Autonomous Vehicles and the Future of Auto Insurance
Will N


uding road markings and signage, and are therefore vital to the operation of the automation. Sensors can be very expensive, costing many thousands of dollars to replace or recalibrate.
The expensive nature of AVs’ sensors has important implications f


r technology embedded in them and that, therefore, the overall cost to the industry would probably be about equal to what it is today. For example, one manufacturer interviewee explained that the “decreased frequency [of collisions] will offset the i


-sophisticated organizations,” such as a fleet operator, which could face a situation in which its fleet is disabled and the operator is required to pay a ransom.
 54 Autonomous Vehicles and the Future of Auto Insurance
policies would increase as net


y negligent in a crash. However, U.S. insurance experts viewed this approach as misguided and unrealistic, noting that it placed too much responsibility on consumers, especially given that “convenience out- weighs responsibility.” One expert suggeste


clude any information gleaned from a vehicle following any crime where the vehicle can reveal evidence, even the driver’s personal data.
3 One insurance expert noted in comments to the authors provided April 1, 2020, that the manufacturer could make


. 6). The workshop participant concluded that “all stakeholders are thinking about data—and everyone is guarding them” (p. 6).
Another workshop participant explained that, “for the insurance world, data are used to resolve claims” (Anderson, Kalra, S


eport concluded that
there was a substantial consensus that information should be shared for the greater good of developing automated vehicles. Respondents willing to share vehicle data expressed an overwhelming desire to help manufacturers and desig


nitor the status of the vehi- cle and the two-way communication link while the autonomous test vehicle is being operated without a driver;
(B) A description of how the manufacturer will monitor the communication link; and,
(C) An explanation of how a


AVs; they are employees of AV manufacturers, or, perhaps, they are independent contrac- tors retained for this specific purpose. If a remote operator is an employee of an AV manufacturer, engaged in work within the scope of employment, the operator


ology can get them from point A to point B, all the resources that have been invested will be wasted. The safe deployment of these vehicles in the public is the best way to show the public that these are safe and reliable ways to get around. This is


n:
The level of consumer trust with fully automated self-driving vehicles, or ADS, is currently in a year-over-year decline. In the J.D. Power 2017 U.S. Tech Choice Study,SM consumers displayed more skepticism and a growing level, with more saying th


by manufacturers
• fleet insurance policies
• adaptation of the existing automobile insurance framework.
For illustrative purposes, we compared the five frameworks on the following char- acteristics: (1) the ability to accommodate the cost of new tec


ovid- ers. If manufacturers decide to establish their own auto insurance organization, it is unknown how they might handle these challenges. Consumer acceptance, however, might be enhanced if manufacturers bundled insurance with the sale of AVs, acco


hat the existing insurance framework would be able to adapt to the deployment of AVs (see Table 3.3 in Chapter Three). As one manufacturer interviewee told us, there is “no reason that the current system cannot keep working.” Experts noted the histor


al experts, this would allow OEMs to bundle insurance with the sale of AVs, which might provide the benefit of indicating to consumers that the OEMs considered their vehicles to be safe. One expert thought that bundling of insurance with the price of


future, how might accidents between AVs and conventional vehicles and between AVs and pedestrians be handled? A majority of stakeholders indicated that, for accidents involving AVs and conventional cars, the claims process would not change significan


o victim compensation.1 All of the countries we investigated followed an adaptive approach to incorporating AVs into auto insurance schemes. The experts we consulted indicated that the current framework for auto insurance would be flexible enough to


iven the lack of clarity about AV data-sharing and its importance to the development of AVs, federal regulators are monitoring the issue in the AV industry. If necessary, they could seek to facilitate data-sharing. Meanwhile, U.S. cities and local tr


us international experts following their interviews, as develop- ments occurred in their countries that were relevant to the subject of our study.
The United Kingdom
On October 16, 2019, the UK Law Commission and Scottish Law Commission jointly publi


ested comments on six options that offered possible avenues for people injured in accidents with AVs to receive compensation. The six options for recovery were originally outlined in the NTC discussion paper published in October 2018 (NTC, 2018) that


 caused inju- ries would be complex.
Suggestions were sought from stakeholders on design elements of the scheme. Option 5: Minimum benchmarks
This option creates agreed national benchmarks for the scope and coverage of ADS crash injuries. States and


the short to medium term cover for injuries should be provided by MAII schemes. The approach should be reviewed by MAII schemes when automated vehicles are a statistically sufficient portion of registered vehicles to enable assessment of their safety


g device equipped with the automatic opera- tion device shall be capable of recording the following information.
– Time when the operation status of the Automatic operation device
changes.
– Time when the handover alarm by the automatic operation dev


he provincial insurance regulators, announced that it is studying the current limitations in the insurance laws pertaining to automated vehicles. Studying the current limitations will help the regulators identify future regulatory needs. Currently, C


, 2018. As of July 20, 2020:
https://www.rand.org/pubs/conf_proceedings/CF383.html
Anderson, James M., Nidhi Kalra, Karlyn D. Stanley, Paul Sorensen, Constantine Samaras, and Tobi A. Oluwatola, Autonomous Vehicle Technology: A Guide for Policymakers,


y of Legal Issues Arising from the Deployment of Autonomous and Connected Vehicles,” Michigan Telecommunications and Technology Law Review, Vol. 23, No. 2, 2017, pp. 191–320.
Dreyer, Paul, Therese Jones, Kelly Klima, Jenny Oberholtzer, Aaron Strong,


 Canada, Auto Insurance for Automated Vehicles: Preparing for the Future of Mobility, 2018. As of October 1, 2020:
http://www.ibc.ca/on/the-future/automated-vehicles
Insurance Information Institute, “No-Fault Insurance Fraud in New York State Is Ramp


n, “Automated Vehicles for Safety,” undated a. As of February 14, 2020: https://www.nhtsa.gov/technology-innovation/automated-vehicles-safety
———, “Driver Assistance Technologies,” undated b. As of October 2, 2020: https://www.nhtsa.gov/equipment/dri


cal History of the Intellectual Foundations of Modern Tort Law,” Journal of Legal Studies, Vol. 14, No. 3, December 1985, pp. 461–527.
Rabin, Robert L., “Some Thoughts on the Efficacy of a Mass Toxics Administration Compensation Scheme,” Maryland Law


w Commission, Automated Vehicles: Consultation Paper 2 on Passenger Services and Public Transport, Law Commission Consultation Paper 245/Scottish Law Commission Discussion Paper 169, London, October 19, 2019. As of October 1, 2020:
h t t p s : // w w


 Justice,” Georgetown Law Journal, Vol. 91, 2003, pp. 695–756.
Zuby, David, Consumer Safety Information Programs at IIHS, Arlington, Va.: Insurance Institute for Highway Safety, Paper 15-0228, undated. As of November 15, 2020: https://www-esv.nhtsa.d


  CORPORATION
SARAH B. HUNTER, ADAM SCHERLING
Los Angeles County Office of Diversion
and Reentry's Supportive Housing Program
A Study of Participants’ Housing Stability and New Felony Convictions
Los Angeles (LA) County is home to the largest jail sy


nclusive.
Therefore, it is important to understand whether supportive housing is achieving its goals. The LA County program’s goals are to improve housing sta- bility and reduce criminal justice involvement among individuals enrolled into the program


Y are from the Office of Diversion and Reentry (ODR) and represent participants enrolled in ODR’s supportive housing program in LA County between April 2016 and April 2019.
STUDY ANALYSIS INDICATES that out of 187 study participants, 169 had stable h


12.5% 22.5% 2.9% 50.5% 58.2% 0.6% 78.1% 39.2%
2.9%
     NOTE: Percentages might not sum to 100 because of rounding.
Six Months
Of the full group of 187 individuals, 169 people were in a permanent housing situation at six months. One individual had mo


os Angeles County Board of Supervisors, Los Angeles, Calif., July 28, 2015.
———, “Homeless Initiative Quarterly Report No. 8,” memorandum to the Los Angeles County Board of Supervisors, Los Angeles, Calif., February 8, 2018. As of June 24, 2019: http


roject leader, Sarah B. Hunter, at Sarah_Hunter@rand.org.
The RAND Corporation is a research organization that develops solutions to public policy challenges to help make communities throughout
the world safer and more secure, healthier and more pros


 SOCIAL AND ECONOMIC WELL-BEING
Forensic Familial and
Moderate Stringency
DNA Searches
Policies and Practices in the United States, England, and Wales
Tepring Piquado, Carl F. Matthies, Lucy Strang, James M. Anderson
Prepared for the National Institu


Policy Program within RAND Social and Economic Well-Being. The program focuses on such topics as access to justice, policing, corrections, drug policy, and court system reform, as well as other policy concerns pertaining to public safety and criminal


esting has been one of the great success stories of law enforcement over the past 30 years. The United States national network of forensic DNA databases has helped law enforcement solve many crimes, often long after the investigative trail has gone c


gency matches suggestive of kinship in
certain circumstances.
 viii
Finally, we conducted qualitative interviews in England and Wales. We conducted semistructured interviews with ten subject matter experts (SMEs) who are academics and practitioners w


ine), while just over a third of responding LDIS laboratories reported no immediate plans to switch from their current evidence profile interpretation method.
We were also interested in whether probabilistic genotyping software, CODIS 20 Short Tandem


pulation, also have the two largest SDIS databanks.3 California has one of the nation’s most proactive DNA sampling regimes, mandating DNA collection from all felony arrestees, regardless of adjudication. DNA database laws in Texas are more restricti


Wales Interviews: History and Context of Familial DNA Testing
In England and Wales, the practice of familial DNA searching started without a legislative framework to cover it, and an SME noted that only after the method had been employed on a number


ent policies, both have meaningfully restricted its use to situations where the public safety implications are most acute. The English and Welsh experience provides examples of polities with similar common-law backgrounds successfully but sparingly u


rate stringency DNA testing practices and policies, conducted interviews with administrators of forensic databases in two states, and conducted interviews with subject matter experts in England and Wales.
Background
Local, State, and National DNA Tes


or mixtures) from various evidence types (e.g., blood stains, sexual assault kits, “touch DNA”). As of January 1, 2017, CODIS database searches use 20 core loci (40 alleles) from the evidence and offender samples to determine a match.4 In England an


de polymorphisms (SNPs) to generate DNA profiles from variation in hundreds of known point mutations in the human genome. SNPs are used for ancestry testing, mostly by private laboratories, not by local, state, or national forensic laboratories.
Fami


e the offender DNA databases are disproportionately comprised of people of color,6 and, as a result of this disproportion, increased use of familial DNA testing may disproportionately lead to suspicion of suspects of color. This may, in turn, perpetu


nited States?
 What is the typical process for familial or moderate stringency searching and partial match reporting in the United States?
 How often is familial and moderate stringency search practiced in the United States?
 Can the history and p


n SDIS, is essentially a local DNA database.
2 United States Department of Justice, Office of Justice Programs, Bureau of Justice Statistics, Census of Publicly Funded Forensic Crime Laboratories, 2014, Ann Arbor, Mich.: Inter-university Consortium f


eof). We also interviewed SMEs about implementation of the current policy. The topics discussed during the semistructured interviews were
5 We used a convenience sample of recognized subject matter experts within the National Police Chiefs’ Council.


red on the side
of caution.4
California was the first state to authorize intentional familial searching, and in 2010, the technique led to the identification of the “Grim Sleeper,” a serial killer who murdered several women in south Los Angeles over


ps it is time for policies to permit familial DNA searching at the national level and for explicit and uniform policies for all SDIS and LDIS laboratories, at least in the most
serious cases.
Compared to efforts to expand the scope of DNA databases i


e arisen as to whether it should be applied to less serious offenses. Roman and colleagues investigated the impact of DNA testing on property crimes and found that offenders were five times more likely to be identified and nine times more likely to b


eased just before the change in eligibility went into effect, is not in the DNA database. A report prepared for The Urban Institute estimated a small deterrent effect (2–3 percent decrease) for the offenses of robbery and burglary only, but large pro


diminished expectation of privacy as a result of their conviction or arrest. This justification obviously does not apply to offenders’ relatives who may be implicated in familial searches, raising ethical and constitutional concerns over what the se


 that this distinction between the accidental discovery of familial matches via moderate stringency searches and deliberate efforts to conduct familial searches is illogical.
International Use of Familial and Moderate Stringency Searches
Forensic DNA


lusions on the effectiveness of the database.34
Survey Results
SDIS Respondent Summary
We received responses from nine of the 50 SDIS laboratories. None of the surveys we received were complete. Eight of the ten SDIS surveys returned were filled out


010 and 2018 (prorated) for state and national matches. The share of exact matches increased between 2010 and 2018. Both the absolute number and the share of moderate and partial matches decreased in 2018. A lower (and decreasing) rate of return on m


 surveyed (and if validation proceeds according to schedule they are now online), while nine responding LDIS laboratories reported no immediate plans to switch from their current evidence profile interpretation method.
 18
Figure 3.4. LDIS Laboratori


ndicated that they also retain forensic profiles, partials, and mixtures ineligible for SDIS and NDIS. The same fraction reported also maintaining elimination/contamination profiles from laboratory and law enforcement personnel; two LDIS labs retain


ene profiles are often partially degraded and/or contain DNA from more than one contributor)
  22
Figure 3.9. LDIS Laboratories: Average Number of Forensic SDIS Uploads by Category, 2010 vs. 2018
Our research team was interested in whether probabilis


se fortuitous partial matches performed or outsourced Y-STR testing, but only seven of the 16 responding LDIS laboratories that performed outsourced Y-STRs use familial searching (data not shown).
 24
Figure 3.11. Number of LDIS Laboratories Using Fo


 995/46,586 = .02;
(.02 – .03)/.03 = −.37 or −37% change in share of total matches.
As a follow-up question, LDIS laboratories were asked to comment on why they could not complete all items in this portion of the survey. Seven of eight responding LDI


ries uploading hundreds of forensic profiles every month, means that California and Texas generate numerous “hits” every month (hundreds in the case of California), some portion of which are not exact matches. Thus, these SDIS laboratory administrato


with the submission of joint written requests from the investigating and prosecuting agencies. The request forms describe the conditions under which the familial search will be conducted and require applicants’ signatures to attest that they underst


st, the DNA technical lead, and three other SDIS laboratory personnel. In California, there are seven people on the FDS committee, including the state CODIS administrator, DNA technical lead, and other SDIS laboratory personnel, but also a Bureau of


secutors understand the significance of the prospective FDS match and the proper ways to go about confirming it. For example, a prospective FDS match is not grounds for conducting a raid on a residence the way an exact database match might be. Texas


work relating to the collection, use, and retention of biometric samples.
Volume and Purposes of Familial DNA Testing
According to the most recent figures provided by the National DNA Database Strategy Board, a total of 13 familial searches were carr


A Database and meet a number of requirements. First, a regional representative of the National Crime Agency must have seen the request and be willing to provide the resources to support the search. In addition, the law enforcement agency applying wil


hundred years of data on births, deaths, and marriages in England and Wales were gathered and used to produce a bell curve showing the probability of an individual having a child at a particular age, and, based on the predicted age of the offender,


e few investigations rely solely on a list that has not been enhanced through prioritization, there are cases where the genetic similarity between the crime scene sample and a profile in the National DNA Database is so high that investigators do not


ase:
For example, if there is a case from the 1980s and we think the person was in his 30s at the time, they are likely to be in their 50s or 60s now. The chances of finding a brother or sister is really quite low because very few people in the datab


usly, the relevant law enforcement agency typically covers the cost of a familial DNA search, although it may seek additional funding from another agency, such as the Home Office, which only rarely provides financial support for such a purpose (Inter


her?”
Second, the interviewee expressed the view that the burden of becoming involved in a criminal investigation, even when one is not a suspect, is considerable and must be taken into account. According to Interviewee 1, “Any involvement in a crimi


d Wales are increasingly mixed and identification more complex.
Interviewee 3 stated that if the process does raise the risk of amplifying racial and geographic biases, it may still be a justifiable course of action; risks must be identified at the e


ll take a scientist who can identify a major profile in these and match it to the [National] DNA Database. I know from an operational point of view, the frustration of getting results we can do nothing with and the frustration of spending a lot of mo


which are kept on file, often on paper, but nobody looks across to make those links. The best we can hope for is speculative searches of the database which can give a list of names, which is often long and difficult to investigate, and it is over to


the state of familial searches and moderate stringency matches. Still, some potentially interesting insights were gleaned from the responses of participating laboratories. Maintaining detailed records on the correlations between evidence type and DNA


ufficient quality for inclusion in SDIS.8 While we acknowledge that some law enforcement agencies use forensic DNA databases to store or conduct forensic DNA analysis outside of the
1 “Ancestry Surpasses 15 Million Members in Its DNA Network, Powerin


low the example set by Texas and automatically expunge profiles for those who have not been convicted. This would also be in line with the practice in Europe, following the ruling of the European Court of Human Rights,14 which resulted in the removal


have dramatically lowered the cost of achieving a potentially worrisome level of surveillance over mass populations.
The use of familial DNA searching raises important privacy and surveillance concerns. Comparing an unknown DNA sample to a database o


o help law enforcement develop leads in investigations that would otherwise go unsolved. However, the acknowledgment of racial disparities and privacy issues in the administration of familial and moderate stringency searches raises concerns about the


 implications of those expansions.
To date, Arizona, California, Colorado, Florida, Minnesota, New York, Ohio, Texas, Utah, Virginia, Wisconsin, and Wyoming are the only states that have solved cold cases using familial DNA searches. Illinois and Lou


to better appreciate the costs and benefits of this forensic DNA database application. Future research could examine whether such an expansion of the United States DNA databases would be acceptable by society and investigate how many crimes could po


rtable, relatively inexpensive DNA analysis technology may make DNA testing more common. Private-sector DNA laboratories such as Parabon NanoLabs have recently begun using SNPs to identify and investigate leads in cold cases. Already the method has b


omic Approach,” Journal of Political Economy, Vol. 76, 1968, pp. 169–217.
Bhati, A., Quantifying the Specific Deterrent Effects of DNA Databases, Washington, D.C.: Justice Policy Center, The Urban Institute, 2010. As of May 9, 2013: https://www.urban


. As of June 25, 2019: https://www.fbi.gov/services/laboratory/biometric-analysis/codis
———, “Frequently Asked Questions on CODIS and NDIS,” undated. As of June 11, 2019: https://www.fbi.gov/services/laboratory/biometric-analysis/codis/codis-and-ndis


P. Gilld, M. Kaysere, W. R. Mayrf, N. Morlingg, et al., “DNA Commission of the International Society of Forensic Genetics (ISFG): An Update of the Recommendations on the Use of Y-STRs in Forensic Analysis,” International Journal of Legal Medicine, V


gants’ Access to DNA Database Searches to Prove Innocence,” Boston College Law Review, Vol. 60, No. 2, 2019, pp. 709–751.
Miller, G., “Scientists Explain How Familial Testing Nabbed Alleged Serial Killer,” Science Insider, July 12, 2010.
“Murders Sus


/news/a-not-so-perfect-match/
Scientific Working Group on DNA Analysis Methods Ad Hoc Committee on Partial Matches, “SWGDAM Recommendations to the FBI Director on the ‘Interim Plan for the Release of Information in the Event of a Partial Match at NDI


 DNA Profiling in Support of Criminal Investigations,” Journal of Law, Medicine, and Ethics, Vol. 33, No. 3, 2005, pp. 545–558.
55


          What America’s Users Spend on Illegal Drugs, 2006–2016
Gregory Midgette, Steven Davenport, Jonathan P. Caulkins, Beau Kilmer
 CORPORATION
For more information on this publication, visit www.rand.org/t/RR3140
  Library of Congress Cataloging


onomic well-being of populations and communities throughout the world. This research was conducted in the Social and Behavioral Policy Program within RAND Social and Economic Well- Being. The program focuses on such topics as risk factors and prevent


and policies, policymakers need to know what is happening in the markets for these substances: How many people are using them? How much are they using? How much money are they spending? How have these quantities changed over time? This report provide


in the United States and at the southwest border from 2007 through 2016. Changes in the composition of heroin users, potentially involving increased use among individuals without criminal histories, have increased the uncertainty underlying these est


pe, and a recent wastewater testing report from Australia finds that fentanyl consumption likely doubled outside of capital city jurisdictions from April 2017 to April 2018 (Australian Criminal Intel- ligence Commission, 2018). Although the utility o


.S. Office of National Drug Control Policy (ONDCP) to generate national estimates of the total number of chronic users, total expenditures, and total consumption for four drugs: cocaine (including crack), heroin, marijuana, and methamphetamine. This


issues as the extent to which one can trust arrestees’ self-reports about their spending on illegal drugs and how to extrapolate from arrestees in just a handful of urban areas to the country as a whole, particularly for methamphetamine, whose user


idered under this definition.1
To generate estimates of CDUs, we employ a model combining drug use preva- lence in ADAM with numerous other drug use indicators and building on prior work, including previous efforts to estimate CDUs for ONDCP. The cur


test positive.
5. Adjust this total to restrict it to adult male arrest events involving a CDU.
6. Convert the total of adult male arrest events involving a CDU to the total of
adult male arrestees who were CDUs (i.e., convert from events to individu


ult male arrests in each county in the annual UCR “Age, Sex, Race” series. This process gener- ated annual estimates for male arrest events involving an arrestee who is projected to test positive for cocaine, opioids, or methamphetamine.5
Steps 5–8:


d 2007-13) ab criminally active CDU get arrested according Take arrests per arrestee from F2, assumes to a Poisson distribution. criminally active CDUs who get
F3 Proportion of adult male
arrested each year
Calculate for three groups: 4–10, 11–20, an


en chronic and less-frequent users. ADAM data indicate daily/near-daily users (21 or more days per month) have strikingly different consumption patterns than those who use weekly or even several times a week. It is the daily/near-daily users in parti


umber of CDUs, but rather a basic indicator of uncertainty around each year’s estimate.
Results
Cocaine
Figure 2.1 presents the best or “point” estimates of the number of chronic cocaine users (i.e., those who used on four or more days in the previou


ms (ICD)-10 code T40.4 “poisoning by other synthetic narcotics” in the CDC Multiple Cause of Death records. T40.4 includes fentanyl and its analogs. NFLIS = National Forensic Laboratory Information System.
6 The impact of fentanyl is felt almost enti


ts were female and 48 per-
Table 2.3
Chronic Cocaine Users by Frequency (millions)
    7 Heroin is a semisynthetic opioid. For a simple typology of opioids, see CDC, 2018b.
14 What America’s Users Spend on Illegal Drugs, 2006–2016
Figure 2.3
Estimate


heroin overdoses and the other measures. It may be that heroin consumption has become increasingly concentrated among a small number of very heavy users who are consuming even more than historical trends would suggest. The differences may be because


to Figure 2.1, the error band in Figure 2.5 is driven by only one source of uncertainty: the 95-percent confidence interval surrounding the predicted share of adult male arrest events involv- ing a positive drug test for methamphetamine.
Table 2.5
Ch


s agreement for 2016. We suggest that the most-defensible position concerning trends in methamphetamine consumption is to acknowledge that the data are insufficient to assume a reduction in users in 2016. Table 2.7 presents the composition of chronic


nly with inflation.
As we will describe further in Chapter Four, prices are not constant over the 2014–2016 period. Therefore, our assumption that users’ drug expenditures are flat over 2013–2016 requires that the overall market is unit elastic—that,


trapolate expenditures. In the absence of available data, we retain prior estimates used in the most recent report (Kilmer et al., 2014a), follow the same method using 2011–2013 ADAM surveys, then inflate average expenditures using the Consumer Price


eport cocaine expenditures by user type from 2006 to 2016. Daily/near-daily users account for a disproportionate share of the reduc- tion in expenditures, decreasing 63 percent over the period versus a 55 percent decrease for the less-frequent user c


nt) (Figure 3.6 and Table 3.9).
28 What America’s Users Spend on Illegal Drugs, 2006–2016
Figure 3.3
Heroin Expenditure Estimates
    Best Higher Lower
          Heroin expenditure (billions, 2018 dollars)
90
80
70
60
50
40
30
20
10
0
2006 2007
  200


on
 In this chapter, we derive estimates for the pure quantities of cocaine, heroin, and meth- amphetamine consumed. Our approach is a continuation of the method described in the previous edition of this report (Kilmer et al., 2014a) and generally si


ding the representativeness of drug enforcement data on the market as a whole. Basing price series for referent purchases on STRIDE makes the strong implicit assumption that prices in the market, which we do not observe, gen- erally are comparable wi


eroin, methamphet- amine, and cocaine have been reported, we cannot assess the impact of fentanyl on heroin or other drug prices due to data limitations. We discuss this challenge in Chap- ter Six.
Results
This section summarizes consumption in pure


ne surveillance data give us serious pause. We can be confident that methamphetamine consumption is increasing, perhaps dramatically, but we cannot make any claim beyond that. As was discussed in Chapter Two, the range depicted by the “higher” and “l


revious versions of this report is no longer the best for estimat- ing consumption and expenditure. We offer a new approach for the latter and do not produce estimates of consumption; however, we offer some ideas for addressing such estimates in Chap


stently lower according to NSDUH data in comparison with MTF data. As in the previ- ous report (Kilmer et al., 2014a), we assume that the MTF survey can more reliably elicit honest responses from young participants because it is administered in schoo


porting. The total number of past-year but not past-month users was fairly stable from 2006 to 2008 but grew steadily through 2016. Trends within other user groups are similar to the infrequent-user trend but more variable; the notable exception is t


nual estimate. Just as we create both an unadjusted and an adjusted series for the numbers of users, we create two estimates for the number of use days (Table 5.2).
Figure 5.2 shows these totals by year, broken down by user group. There has been a la


 per day, estimated separately for each past-month user group: occasional (1.68), weekly (1.92), more than weekly (1.92), and daily/near-daily users (3.87) (Kilmer et al., 2014b).
 Two longstanding issues with this method have become increasingly wor


add grams of wax (which can be more than 75 percent THC by weight) to grams of conventional marijuana that are, on average, 20 percent THC by weight, let alone to grams of THC-infused brownies or beverages (which can have a very low THC concentration


ith implausible reports based on their reported days of marijuana use. Effectively, it uses data from qualified buyers on spending per day of use to impute the spending of respondents whose past-month spending reports were disqualified for being susp


idence on the extent of underreporting of spending, so we cannot simply adjust for the underreporting of spending by multiplying by some factor derived from the literature. Instead, we take the trends found with the RASTUD-based model and adjust them


f use has been stable despite the many changes in mari- juana potency, product variety, and legal status at the state level.
Extending Marijuana Expenditures Through 2016
Because NSDUH did not include the marijuana market module in 2015 or 2016, esti


for the daily/near-daily user group.
Marijuana 51
 52 What America’s Users Spend on Illegal Drugs, 2006–2016
Figure 5.4
Estimated Marijuana Expenditures
   Adjusted
  Unadjusted
    Marijuana expenditure (billions, 2018 dollars)
60
50
40
30
20
10
0
2


).
Extrapolating from Washington State
Caulkins et al. (2019) estimates that Washington state’s 755,000 NSDUH-identified past-month users spent $1.66 billion annually on marijuana over 2015–2016.8 Nation-
8
Using consumption estimates from a Washingt


f products, and increased availability through state and substate policies relaxing restrictions on marijuana access and penalties on possession. Dis- cussions often focus on changes in the motive for consumption (so-called “medical” marijuana versus


ions of THC, but there was more of it. Thus, from a grower’s perspec- tive, much of the THC was not being converted into saleable product.
In jurisdictions where marijuana businesses are state-legal, it is common to use devices of various sorts to ex


ket conditions.
Users, Dollars, and Use Days
Before proceeding to novel metrics, we note that two traditional measures of market size remain viable: dollar value and number of users. One can add $20 spent on brown- ies to $40 spent on dabs to get $60


ys per month) are thought to consume two to three times as much per day of use as those using only rarely. Hence, two markets with identical numbers of days of use could differ in esti- mated quantity consumed if a greater proportion of the use days


d between 1.3 and 1.9 grams per use day, with a best estimate close to 1.6 grams (Kilmer et al., 2013). A similar survey conducted for the Colorado Department of Revenue in 2014 led researchers to conclude that “results confirm that a preliminary est


nges in consumption over time in a set of units that is both standardized across years and sensitive to the fact that frequent users tend to use more per day of use.
THC
The cannabis plant contains scores of cannabinoids, but two (THC and CBD) receiv


to support THC estimates for the nation or over time. Key data sets, such as STRIDE, never reported marijuana potency the way they reported the purity of cocaine and heroin. Seizure data analyzed by the University of Mississippi did record potency,


 data taken at different times to produce a coherent estimate. That would not be the case for fentanyl post-2013.
Another fundamental problem with estimating fentanyl consumption from user surveys is that much of the illicit-market fentanyl appears a


dulterating. Because heroin users tend to have tolerance to opioids, they may be less likely to die if their heroin is adulterated with fentanyl than if a cocaine user’s cocaine is adulterated with fentanyl.
Yet another challenge is that fentanyl is


 Then the national estimate of fentanyl consumption is
Total fentanyl consumption = ∑drugs d ×∑regions i ×Rdi ×Wdi . This estimate could be improved or extended in the following ways:
• summing across types of fentanyls (e.g., folding in carfentanil


AM program—or some version of it—so we can collect real-time drug market data, including objective (biological) consumption measures for cocaine, heroin, meth- amphetamine, and other drugs. For example, it is possible to detect fentanyl in urine spec


z, Lauren Renaud, and Beau Kilmer, “Big Data on a Big New Market: Insights from Washington State’s Legal Marijuana Market,” International Journal of Drug Policy, Vol. 57, July 2018, pp. 86–94.
Caulkins, Jonathan P., Steven Davenport, Anhvinh Doanvo,


ry Drug Problems, Vol. 31, No. 3, 2004, pp. 467–540.
Gonyer, Todd E., “Federal Sentencing in a Post-Chapman World: What Is a ‘Mixture or Substance’ Anyhow?” University of Kansas Law Review, Vol. 46, 1998, pp. 983−1011.
Horowitz, Joel L., “Should the


ps://www.rand.org/pubs/research_reports/RR3138.html
Kilmer, Beau, Susan S. Sohler Everingham, Johnathan P. Caulkins, Gregory Midgette, Rosalie Liccardo Pacula, Peter H. Reuter, Rachel M. Burns, Bing Han, and Russell Lundberg, What America’s Users Spe


Drug Control Policy.
Oregon Liquor Control Commission, 2019 Recreational Marijuana Supply and Demand Legislative Report, Portland, Oreg., January 31, 2019. As of May 20, 2019: https://www.oregon.gov/olcc/marijuana/Documents/Bulletins/2019%20Supply%20


 Prospective Relation of Cannabis Potency, Dosing and Smoking Behaviour with Cannabis Dependence: An Ecological Study,” Addiction, Vol. 109, No. 7, July 2014, pp. 1101–1109.
References 75
Substance use and drug policy are clearly in the national spot


 CORPORATION
Caseload Standards for
Indigent Defenders in
Michigan
Final Project Report for the Michigan Indigent Defense Commission
 Nicholas M. Pace, Dulani Woods, Shamena Anwar, Roberto Guevara, Chau Pham, Karin Liu
For more information on this pu


al defense attorneys followed, in which the results of the earlier time study were presented to participants as evidence of current time expenditures. Informed by those results, respondents then provided their opinions as to the average amount of tim


 find him or herself routinely delivering just the minimum effort necessary to avoid ethical sanctions while hoping for a quick plea deal.
Similar to previous studies in other states that have also addressed the question of reasonable caseloads, this


lready mentioned. Examples: extraditions, detainers, contempt proceedings.
  A survey of criminal defense attorneys in the state followed, in which the results of the earlier time study were presented to participants as evidence of current time expen


s involving indigent defense counsel, participation is most likely when the attorney is a high-volume public defender and least likely when the attorney is in private practice. Indeed, the information we collected on 4,816 cases tracked during the re


he time study that had concluded previously, and, with that information as background, respondents would give their recommendations as to the average amount of attorney time required to provide effective assistance of counsel for each case type of in


percent of the estimated 2017 Michigan population. Other regions in the state also have population proportions that are similar to the respondent group (for example, 5.1 percent of Michigan residents live in the Northern Lower Peninsula, 3.0 percent


strative staff, such as clerks, secretaries, or receptionists; investigators; paralegals or legal assistants; interns and externs; research attorneys; interpreters; social workers; mitigation specialists; and any other nonattorney staff members). Ind


 and public defenders from every region in Michigan. A one-day, in-person group session with the 29 panelists was held in Lansing on September 13, 2018.
Though the information we sought to elicit from the expert panel paralleled that of the attorney


about necessary average hours on a paper form we provided. This was done to help the panelists minimize the effects of anchoring bias by first using self-generated anchors (their own assumptions) rather than relying solely on externally provided ones


The median of the expert panel’s responses, rather than the mean, was chosen as the statistic to report the group’s consensus
4 See Chapter 4.
 xviii
estimate as to average times. The median has the advantage of not being affected by extreme values t


hours per day. A second involves what might be characterized as absence days, which we have assumed to include two weeks of vacation (ten business days), eight business days of sick leave or other personal leave, and a 12.5-day annual holiday schedul


ons
Other adult criminal indigent defense trial court–level matter
Delphi Panel Median Recommended Minimum Hours
Maximum Caseload Standard
   120 15 80 23 50 37 40 46 25 74
8 232
7 265 3.5 530 3 619
  It is important to note that these recommended ca


ghts for types A and B would be 200 and 20, respectively (essentially just the average hours for each of the two types), while the relative case weights for the two categories would be 4.0 (200 hours for type A cases divided by the 50-hour average fo


s than full time to handling adult criminal matters? As Table S.4 suggested, attorneys who participated in the survey varied greatly as to the amount of time they typically spent each week representing adult defendants. Let us assume that the solo pr


ing the newspaper.”
 xxiii
conclusions.8 To the extent that indigent defender caseloads in this state are indeed excessive, such problems cannot be made to disappear simply through the adoption of maximum caseload standards. Far better information ab


.991(2)(b).
 xxiv
Acknowledgments
We would like to express our appreciation to those indigent defense attorneys across Michigan who volunteered to participate in a time study designed to track their case-related activities. We are well aware of the s


) for assistance in determining maximum caseload standards for providers of indigent legal representation to adult defendants in the trial-level courts of the state of Michigan. A “maximum caseload standard,” typically expressed in terms of the numbe


vered. A more functional set of principles can be found in the MIDC’s first four standards for indigent defense delivery systems, covering such areas as the training and education of indigent defense attorneys, the initial client interview, the use o


f the conference participants formed the basis for the recommended maximum caseload standards subsequently described in this report.
It should be emphasized that RAND’s ultimate task in this work was to deliver the final results of the September 2018


d to over the course of a year, assuming that the attorney in question represented only cases of that
3
one type (calculating recommended maximum caseloads in instances where the attorney handles more than one type of case is accomplished through the


ty when applied to attorneys in a particular region of the state due to unpredictable variations in weather and road conditions in that area or chronic shortages in support staff availability. No single set of caseload standards can account for such


attorney per year: not more than 150; misdemeanors (excluding traffic) per attorney per year: not more than 400; juvenile court cases per attorney per year: not more than 200; Mental Health Act cases per attorney per year: not more than 200; and app


sing out of the work of the NAC court task force, can be found in National Legal Aid and Defender Association, undated.
21 See, e.g., ABA, 2002 (“National caseload standards should in no event be exceeded,” citing the numbers in NAC Standard 13.12);


cts usually involved first determining the average amount of hours being spent by indigent defenders on different types of cases using special time studies, fielding a survey in which indigent defenders within the jurisdiction being examined review t


of the NCSC approach has been employed by the ABA’s Standing Committee on Legal Aid and Indigent Defendants (ABA-SCLAID) in a cluster of studies conducted over the past five years. These studies also utilize what might be characterized as a task-base


45 “ensure the effective representation of counsel,”46 “perform the duty effectively,”47 complete the task “with reasonable effectiveness,”48 “provide reasonably effective
31 RubinBrown and ABA-SCLAID, 2017.
32 Postlethwaite & Netterville and ABA-SCL


defenders” at start, 23 attorneys in final session
Expert Decisions or Adjustments
(1) Time needed to complete each task in a case within each case type; (2) percentage of cases within each case type in which each task should take place
(1) Time need


ask across all cases
Average amount of time that should be spent on cases within each case type
Whether or not additional time was needed for performing each task within each case type
Expert Panels
Focus group: “A select group of seasoned” public de


ns.
When more time spent on a task within a case type was believed to be necessary, (1) revised time needed to complete task; (2) revised percentage of cases within case type in which task should take place
            Virginia
NCSC (2010)
Statewide


load standards setting can be quickly and inexpensively extracted from the provider’s case management system (CMS). The only practical alternative when timekeeping is not routine is to conduct a costly and often disruptive special time study in which


s. But such an approach requires that the individual providing the estimates or adjustments can recall individual events in cases of a particular type with a sufficient degree of accuracy. There is also a greater burden on participants if they are as


task-based approach asks the participant to estimate the average time needed to complete each task (a companion question often included asks the participant to estimate the percentage of cases in which the task should be performed). Task-based studie


noted that regardless of whether a second set of experts is utilized, the standards that arise out of this development process are typically characterized as “recommended,” “interim,” or “provisional.” It is not until some sort of policymaking body


fender offices (just eight of Michigan’s 83 counties have a public defender).
Next was the manner in which services for indigent representations are arranged. Michigan has historically been a state where indigent defense is the responsibility of indi


 counsel. The JIS CMS does have a field for that purpose, but reportedly many of the Michigan trial courts with this system in place are not utilizing it. Most courts, but not all, send extracts of the information they collect to the Judicial
55 See,


as the one we were considering) or other quantitative data collection focusing on indigent defenders operating in Michigan trial-level courts had been performed. The 2008 NLADA report (Evaluation of Trial- Level Indigent Defense Systems in Michigan)


aling with large numbers of private law firms. Based on these considerations, we felt that we would maximize the number of participants who consistently kept time throughout the entire study period if the project asked for no more than two months of


those tasks. In addition, we know from our prior work with indigent defense timekeeping that many attorneys routinely submit their time entries based on nothing more than what they recall from memory as to what they did the day or even weeks before.


tiate with a prosecutor all within the same hour. A task-based approach certainly has merit, but we felt that it would be most effectively employed when detailed timekeeping had become a routine business practice for indigent defenders and highly rel


before being formally presented with the data collection results. Armed with both their original estimates and with the data collection results they subsequently received, the experts then entered into the consensus phase of the work with as much re


ifications Used in the Standards Development Explanation
  Case Type
Murder or manslaughter CSC
Other class A offenses Other high-severity felonies
Low-severity felonies and “two-year” high court misdemeanors
“One-year” misdemeanors (potential senten


defense systems across the state as part of other work the commission was conducting at the time.
25
As indicated previously, a time study of indigent defense attorneys was followed by an attorney survey (additional information about the time study a


ts, no longer practicing law, or no longer receiving mail at those addresses.
Invitations for the time study went out to 1,979 attorney email addresses. We learned from the fielding of those invitations and subsequent follow-up communications that 44


ly when the attorneys who handle the bulk of the indigent caseload in the county or the court have conflicts, either ethical in nature or in regard to scheduling. Public defenders and contract counsel program attorneys are likely to have a relatively


that we had fewer relatively younger defenders participating than we might have with a different data collection period because these attorneys are more likely to take their families on vacation at this time than older (and possibly more experienced


. As originally designed, defenderData Prime is a very powerful case manager platform for defender organizations, with, for example, extensive capabilities for scheduling upcoming appearances, processing vouchers, note taking, and report production.


ving a reservoir of existing cases in the system would have been a significant time saver for participants, especially during the early weeks of the time study. Unfortunately, there are about 134 separate indigent defense systems in the state, each o


eived through independent
investigation, including public data, treatment, criminal history,
adoption, and HHS or CPS.
• Drafting discovery and independent investigation requests and memos
of review of information received.
• Other active independent


e MIDC’s staff reach out to the known contacts for each of the indigent defense systems in the state to announce the launch of the caseload standards data collection efforts and request that attorneys operating within those systems be encouraged to p


available in public defender offices (and, to some degree, in relatively larger private law firms), and such encouragement signals that management considers participation to be a legitimate part of one’s job. Attorneys working in assigned counsel or


n the next chapter, public defenders report that they handle significantly more indigent defense cases annually than private counsel). We are not aware of any other contemporary effort to track indigent defender time expenditures in multiple location


 and time frame of this study, such information was not available to us.
Another option would be to utilize imputation methods that closely compare the cases reported on during the time study with the far larger population of indigent defense cases i


state.
We used scenario 1 and 2 cases to calculate median days from appointment to disposition for cases that remained open past different time periods. In addition to calculating median days to disposition for all scenario 1 and 2 cases, we calculat


h it was active within the time study data collection period (i.e., the number of days that a participating attorney would be able to enter time information), and (2) “total open days,” which was either the actual number of days the case was active o