American police officers' use of lethal force is in the headlines after the deaths of George Floyd, Breonna Taylor and Ahmaud Arbery. To pinpoint key issues around deadly force -- and inspire data-driven solutions -- three Oklahoma State University graduate students examined the aftermath of police shootings as their SAS Global Forum Student Symposium project. Are officers indicted? Do underlying biases and prejudices result in letting them off easy? Does the location of shootings happen make indictment more or less likely?
"The goal of this project is to create a predictive model that can identify the variables that lead to a perceived justified or unjustified police shooting and forecast the shootings across the United States for the next 10 months in an effort to provide key insights to those campaigning for reform," wrote Alex Lindsay, AraVind Dhanabal and Mason Kopasz in their paper, What Happens After Police Shootings? The students, pursuing master's degrees in business analytics at Oklahoma State, analyzed data from fatalencounters.org and the U.S. Census Bureau.
Spoiler alert: "The predictive model did not result in finding a racial bias for perceived justified versus unjustified police shootings," the paper concluded. "However, the State, County, Department Involved proved to be the most important variable in deciding if a police shooting will be perceived justified or unjustified. This model could be used in practical application by an oversight committee to ensure there is standardization across police forces for launching investigations into Grand Jury indictments."
Video highlights
00:48 - Background and context for the study
01:54 - Goal of the study
02:33 - Data sources
03:53 - Target variable: whether officer is indicted
04:12 - More white males shot, but disproportionately more African-Americans and Hispanics represented in shootings
07:05 - How predictive analytical models were built
10:21 - High-risk states: Georgia, Nebraska, Arizona, Maryland and Louisiana
11:01 - Conclusion and possible future studies
Read the Paper
Related resources
Decision Tree Model (documentation)
Decision Tree in Layman's Terms (community article)
