Racial and Ethnic Disparities in Enforcement

Traffic Stops by Suffolk County Police

In 2014, the Suffolk County Police Department (SCPD) entered into an agreement with the U.S. Department of Justice, which required that SCPD collect and analyze data on traffic stops.  SCPD contracted with the Institute to conduct analysis of racial and ethnic disparities in traffic stops and post-stop outcomes.

Our analysis included an assessment the data on traffic stops and a description of selected features of the traffic stops, including the SCPD units that made the stops, the reasons for stops, the temporal distributions of the stops (i.e., across days of the week and times of the day), and the characteristics of the drivers whose vehicles are stopped. We also described patterns of post-stop outcomes, including searches of vehicles, drivers, and passengers, commands to exit the vehicle, use of force, and dispositions. We explained the analytical challenges in drawing inferences about bias from stop data, as well as how those challenges have been addressed in previous studies of racial profiling.  We applied the veil-of-darkness method of analyzing bias in the initial stop decisions by SCPD officers.  We used propensity score matching to form comparison groups of similarly situated stops of White drivers against which to assess outcomes in stops of Black and Hispanic drivers, respectively.

Supported by Suffolk County [April, 2019 – December, 2020]

Publications, Reports and Presentations

Worden, Robert E., Kenan M. Worden, and Hannah Cochran, 2020. Traffic Stops by Suffolk County PoliceAlbany, NY: John F. Finn Institute for Public Safety, Inc.


Addressing Allegations of Racial Profiling in Milwaukee

Litigation against the City of Milwaukee and its police department alleged racial and ethnic bias in police enforcement: traffic and pedestrian stops and post-stop outcomes (Collins, et al. v. City of Milwaukee, No. 17 CV 00234 (Eastern District of Wisconsin). The City contracted with the Institute to assess the analyses, findings, and conclusions summarized in the report by the Plaintiff’s expert.

Supported by the City of Milwaukee [August, 2017 – July, 2018]

Publications, Reports and Presentations

Robert E. Worden, 2018.  Report of Robert E. Worden, Ph.D., Collins, et al. v. City of Milwaukee, No. 17 CV 00234, Eastern District of Wisconsin.


Stops by Syracuse Police

A 2001 Syracuse ordinance mandates the collection of data on stops, and the Common Council has twice commissioned analyses of the data, first in 2006 and again in 2010 – studies that relied on an approach known as the “outcome test.” Skeptical about the utility of the outcome test in analyzing the Syracuse data, Institute researchers proposed to conduct an analysis using the “veil-of-darkness” method, an approach devised by researchers at the RAND Corporation. Analyzing vehicle stops in the “inter-twilight” period – the times of day when it might be light or dark, depending on the time of year – the Institute tested to see whether African-Americans were more likely to be stopped during daylight, when drivers’ race can be more readily determined by officers, than in darkness. Finding no consistent differences between stops in daylight and stops in darkness, the Institute’s analysis detected no persuasive evidence of racial bias in stops.

Supported by NYS DCJS [July, 2009 – June, 2010]

Publications, Reports and Presentations

Robert E. Worden, Sarah J. McLean, and Andrew Wheeler (2010).  Stops by Syracuse Police.  Report to the Syracuse Police Department. Albany, NY: John F. Finn Institute for Public Safety, Inc.

Robert E. Worden, Sarah J. McLean and Andrew P. Wheeler (2012). “Testing for Racial Profiling with the Veil-of-Darkness Method,” Police Quarterly 15 (March): 92-111.