Improving police use-of-force training is methodologically difficult. By providing a method for identifying the “expert” response to any given scenario, and by triangulating multiple methods, we aim to contribute towards police departments’ capacities to engage in more effective and targeted training. Forty-two police experts and 36 novices watched five scenarios taken from body-worn camera footage. The videos would pause at several points, and respondents gave both close-ended survey answers and open-ended written answers. Using a mixed-methods approach combining quantitative regression and natural-language-processing techniques, we triangulated our findings to reach conclusions regarding the differences between experts and novices. Relative to novices, expert police officers were more likely to report the importance of force mitigation opportunities to any given scenario in close-ended questions, and were more likely to use words associated with verbal de-escalation; novices were more likely to use words associated with physical control. The materials can be accessed at https://osf.io/wujkz/.
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This work was supported by the Department of Justice within the Office of Justice Programs (grant number BJA-2016-VI-BX-K005).
Conflict of Interest
This research was classified as “exempt” under Title 45 of the Code of Federal Regulations, §46.104, Exempt Research, Category 3(i). Research involved collection of information from adult subjects via written responses/data entry. Subject prospectively agreed to participate in data collection and the information obtained was recorded by investigators in such a manner that the identity of the human subjects cannot readily be ascertained, directly or through identifiers linked to the subjects.
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Mangels, L., Suss, J. & Lande, B. Police Expertise and Use of Force: Using a Mixed-Methods Approach to Model Expert and Novice Use-of-Force Decision-Making. J Police Crim Psych 35, 294–303 (2020). https://doi.org/10.1007/s11896-020-09364-4
- Expertise, use of force
- Body-worn cameras
- Mixed methods
- Natural language processing