This paper examined problems with police traffic stop data and proposed an early warning system solution.
In response to widespread allegations of racial and ethnic discrimination in traffic stops (sometimes labeled "racial profiling"), law enforcement agencies are now collecting data on traffic stops that include drivers' race or ethnicity. Interpreting these data to determine whether there is a pattern of race discrimination poses enormous difficulties. Specifically, it is not clear what baseline (often referred to as "the denominator") should be used to assess the racial and ethnic distribution of people stopped. Using the first traffic stop data reports from the San Jose Police Department (1999, 2000) as a case study, the paper examined baselines that were commonly used or discussed as appropriate. The paper argued that resident population data and/or official crime data were not adequate as baselines. As an alternative, the paper proposed an approach based on police early warning (EW) systems. These systems have emerged in recent years as an accountability measure designed to identify officers whose records indicate repeated problematic performance, such as high rates of citizen complaints. The paper argued that an EW approach not only resolves the central problem related to interpreting traffic stop data but also provided practical direction for police managers seeking to correct improper officer performance. Notes, references
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