Update README.md

README.md

@@ -25,15 +25,6 @@ This segmentation aims to classify funding organizations by geographic scope bas
 
 ## Definitions
 
-Concept grew from this Slack message from Marc:  
-*We (Marc, Annie, Ali) had a good checkin about nailing down the geographical stuff for this project. Because Annie's first and second attempt at classifying orgs as local / state / regional / national / international was not very successful, we simplified our definition (but still meets the needs of our own team's segmentation) and will redo the classifier on a larger set of narrower organizations. Namely:*  
-*local: IF an org is registered in only one state, we'll train a batch and:*  
-*determine city/county vs statewide*  
-*If org is registered in 10+ states, we'll treat as regional/national*  
-*If ang org has a foreign office, we'll treat as international*  
-*anything in between, or orgs with an regional/branch office outside the US will be excluded from our "state/local" training set.*  
-*We don't try to determine if an org is in multiple counties but not the whole state, or is "regional" like one part of the US but not the whole US, because our data is noisiest for these. Placenames in text are used for many other thing besides "this is where we work". Final geo-scope in our API output will be: city/county, state (or sub-state), regional/national, international. These are probably the ones in which we can be most confident. Grantmakers: follow different logic, where we will use the locations of their grantees to define their scope. It might make more sense to just report a list of states where they've made grants instead of "regional/national" for these.*
-
 This segmentation aims to classify funding organizations by geographic scope based on their grantmaking behavior into three categories:
 
 1. Local/Regional: Orgs operating primarily in one state or a few localities