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Police Officer Learning, Mentoring, and Racial Bias in Traffic Stops

Award Information

Award #
2016-R2-CX-0041
Location
Awardee County
Onondaga
Congressional District
Status
Open
Funding First Awarded
2016
Total funding (to date)
$279,810

Description of original award (Fiscal Year 2016, $279,810)

For the last decade, the Syracuse Police Department has dealt with increasing claims of racial profiling of its citizens. In response, the Syracuse Common Council commissioned racial profiling studies in 2005 and 2010, which uncovered officer bias against African-American citizens. Those studies gave no policy prescriptions or understanding of the causes of officer bias. The goals of this project are to: 1) better understand the effects of officer experience and exposure to citizens of differing race on their perceived proclivities for racial bias in traffic stops, while controlling for officer, citizen, and neighborhood demographics; 2) develop and estimate an econometric peer-effect model of police "on the job trail"!ing" that explicitly captures how racially biased behaviors may be transmitted from senior officers to rookie officers, while accounting for the selectivity bias induced by the chiefs choices of mentor/mentee pairings; and 3) mentor a PhD student in the econometrics of police behavior.
Subjects: We have geocoded field data on the activities of police officers in the City of Syracuse, New York from 2006-2009, and demographic data on the officers and the citizens they encounter.
Partnerships: A racially diverse team from Syracuse and Kent State Universities.
Research Design and Methods: The data will be used to estimate officer-level measures of racial bias proclivity as an outcome variable in regression models to uncover the effects of experience, mentoring, and exposure on officer racial biases. Year 1 will focus on regression models that account for officer mentoring, experience, and exposure to citizens of differing race. Year 2 will focus on peer-effects regressions that allow for the racial bias proclivities of one officer to affect another, while accounting for the selectivity bias induced by the chiefs choices of how officers are paired and assigned to a beat.
Analysis: Regression models will account for non-random assignment of officers to partners and to geographic locations with varying race, income, and crime composition.
Products, Reports, and Data Archiving: The results provide police with a road map on how to best mentor rookie officers with the goals of minimizing their proclivities for bias and creating a culture of fairness and equity toward citizens. Results of the study will be made public in two working papers to the Syracuse Police Department, Common Council, and Post-Standard (one per year). They will ultimately be published in scholarly journals. Data and codes will be archived following ICPSR guidelines. ca/ncf

Date Created: September 13, 2016