Black and Asian people in the United Kingdom are more likely to be stopped and searched by police than White people. Following a panel of 36,000 searches by 1,100 police officers at a major English police force, we provide officer-specific measures of over-searching relative to two baselines: the ethnic composition of crime suspects officers interact with and the ethnic composition of the areas they patrol. We show that the vast majority of officers over-search ethnic minorities against both baselines. But we also find that the over-searching by individual officers cannot account for all of the over-representation of ethnic minorities in stop and search: over-patrolling of minority areas is also a key factor. Decomposing the overall search bias, we find that the over-representation of Asian people in stop and search is primarily accounted for by over-patrolling, while the over-representation of Black people is a combination of officer and patrol effects, with the larger contribution coming from biases of officers.
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This research is based on data resources provided by West Midlands Police. Data were originally collected as part of routine police record-keeping. The data are not publicly available and were provided to the authors under an Information Sharing Agreement with West Midlands Police. Under the terms of this agreement, the authors are not at liberty to share the data. Other researchers can contact West Midlands Police to obtain a data-sharing agreement.
All the code used to produce the results is available online on Github at https://github.com/laravomfell/ethnic_bias_stop_and_search. Since the original data from West Midlands Police may not be publicly shared, we generated synthetic data to demonstrate our code. The repository includes a folder, “/data”, that contains the synthetic data as well as the file “code/generate_synthetic_data.R” used to generate the data. The distributions of the variables in the synthetic data match the distributions in our data.
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Support for this research was provided by a grant from the Leverhulme Trust (to L.V.), and the West Midlands Police and Crime Commissioner and Economic and Social Research Council grants ES/P008976/1, ES/V004867/1 and ES/N018192/1 (to N.S.). West Midlands Police provided access to the data. Members of West Midlands Police and the West Midlands Police and Crime Commissioner provided comments on the manuscript, but had no role in study design and analysis, decision to publish or preparation of the manuscript. The other funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Special thanks goes to J. Knoblauch for invaluable discussions. We also thank P. Newall, J. Richards, J. Trueblood, G. Wall, D. Whordley and the West Midlands Police Stop and Search Commission for comments.
The authors declare no competing interests.
Peer review information Nature Human Behaviour thanks Michael Shiner and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Aisha Bradshaw.
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Extended Data Fig. 1 Densities of posterior distributions of search shares over all officers for each 6-month time period based on 10,103 observations of officer search counts.
The black dot represents the median of the distributions aggregated over officers and the black lines show 50% and 90% uncertainty intervals.
Extended Data Fig. 2 Posterior densities of DS and DP by time period based on 10,103 observations of officer search counts.
For visual clarity, we only show values between [0.3, 10.0]. Note that the y-axis is on the log scale. The black dots represent the medians; the black lines represent 50% and 90% uncertainty intervals.
Extended Data Fig. 3 Comparison of observed search counts to predicted search counts based on inferred search shares p.
Each grey dot is the observed search count by an officer in time period t and ethnic group e against the prediction error (observed - predicted). The black dots show the observed data against the error from the median prediction for that observation. The plot shows that key features of the data are captured in the model. The figure is based on 10,103 observations of officer search counts.
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Vomfell, L., Stewart, N. Officer bias, over-patrolling and ethnic disparities in stop and search. Nat Hum Behav (2021). https://doi.org/10.1038/s41562-020-01029-w