A Multi-Method Examination of Police Stops in San Jose, California

• In Event: Poster Session II

Abstract

This study investigates the influence of citizen race and ethnicity on traffic and pedestrian stops conducted by officers from the San Jose, California Police Department over a 30 month period (September 2013 – March 2016). Data from more than 50,000 traffic stops and 25,000 pedestrian stops were analyzed as part of this large-scale project that included quantitative analyses, focus groups, and field observations. Multiple benchmarks were used to model the initial stop decision for both traffic and pedestrian stops. In addition, official stop data, Census information, citizen attributes, and officer characteristics, were used in a series of cross-classified, multi-level models to examine racial and ethnic disparities in stops and stop outcomes in one of the nation’s most racially diverse cities. While unexplained disparities were observed across a number of dimensions, the findings diverged from much of the reported racial profiling and stop and frisk literature in significant ways. The nature of the observed disparities, as well as those that did not emerge from the analysis, are presented and discussed.

Authors

• Michael R. Smith, University of Texas at San Antonio

• Robert Tillyer, University of Texas at San Antonio

• Jeff Rojek, UTEP

• Caleb D Lloyd, Centre for Forensic Behavioural Science, Swinburne University of Technology (Australia)