Analysis of racial profiling by police

When
Start: 03/08/2012 - 4:15pm
End  : 03/08/2012 - 4:15pm

Category
Statistics/OR/Math Finance Seminar

Speaker
Greg Ridgeway (Rand Corporation)

Abstract

Several studies and high profile incidents around the nation involving police and minorities, such as the July 2009 arrest of Harvard Professor Henry Louis Gates, have brought the issue of racial profiling to national attention. While civil rights issues continue to arise in other areas such as offers of employment, job promotions, and school admissions, the issue of race disparities in traffic stops seems to have garnered much of the attention in recent years. Many communities have asked, and at times the U.S. Department of Justice has required, that law enforcement agencies collect and analyze data on all traffic stops.
Data collection efforts, however, so far have outpaced the development of methods that can isolate the effect of race bias on officers' decisions to stop, cite, or search motorists. In this talk Dr. Ridgeway will describe a test for detecting race bias in the decision to stop a driver that does not require explicit, external estimates of the driver risk set. Second, he’ll describe an internal benchmarking methodology for identifying potential problem officers. Lastly, he will describe methods for assessing racial disparities in citation, searches, and stop duration. He will present results from his studies of the Oakland (CA), Cincinnati, and New York City Police Departments.

Where
Davidson Lecture room, Adams Hall, Claremont McKenna College

Misc. Information

Greg Ridgeway, Ph.D., is a Senior Statistician and Director of the Safety & Justice Research Program at the RAND Corporation.

Some related papers to the talk:
J. Grogger and G. Ridgeway (2006). “Testing for racial profiling in traffic stops from behind a veil of darkness,” Journal of the American Statistical Association 101(475):878‐887. ASA 2007 Outstanding Statistical Application Award
G. Ridgeway (2006). “Assessing the effect of race bias in post‐traffic stop outcomes using propensity scores,” Journal of Quantitative Criminology 22(1):1‐29.
G. Ridgeway and J.M. MacDonald (2009). “Doubly Robust Internal Benchmarking and False Discovery Rates for Detecting Racial Bias in Police Stops,” Journal of the American Statistical Association 104(486):661–668.