This study introduces a statistical estimator that can be used to examine disproportionate traffic stop behavior of police officers. This estimator can be employed in concert with internal benchmark data and a tree diagram algorithm to identify and classify disproportionate behavior. These methodologies are multilevel and can be used (a) at the macrolevel to examine disproportionality of a police department as an organization and (b) at the microlevel to draw inferences about reasons for individual officers’ disproportionate behavior. These statistical routines were tested using data from a medium sized midwestern community. Results suggest that the models are effective in detecting disproportionality in both a police organization and an individual officers’ traffic stop activity. Moreover, the methods may serve as an initial step in pointing toward the sources of the officers’ behavior.
Mike Rowe, Megan O’Neill, Sofie De Kimpe and István Hoffman have published the paper Policing during a pandemic – for…Read more
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