Benchmarking Disparities in Police Stops: A Comparative Application of 2nd and 3rd Generation Techniques

Abstract

This study used 2016–2017 data from San Jose, California to examine the nature, distribution, and correlates of racial/ethnic disparities in traffic stops made by the San Jose Police Department (SJPD). We employed multiple second and third generation benchmarks to assist in understanding whether drivers of color were, among other things, disproportionately stopped by the SJPD and how those findings may have differed across benchmarks. Using traffic citations as a proxy for driving behavior, we also tested the proposition that minorities, but not White drivers, may alter their driving behavior during the daytime, which could affect the validity of the Veil of Darkness approach for estimating stop disparities. Finally, we examined whether officer race may condition the assignment of fault in vehicle crash investigations and thereby bias traffic crash-based benchmarks. We found some support for both propositions – citation rates for Black and White drivers diverged during daylight hours, suggesting the Black drivers may have altered their driving behavior to avoid attention from the police, and Hispanic officers were less likely to issue citations to Hispanic drivers, although other officer-driver race dyads showed no evidence of same-race leniency. Implications of our findings for stop disparity research are discussed, and suggestions are made for future researchers to consider.