When is the officer not seen as safe? Assessing civilian biases regarding police officers with IATs

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When is the officer not seen as safe? Assessing civilian biases regarding police officers with IATs

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2022

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Policing in America has become increasingly politicized and divisive in recent years, and there have been many different opinions about how policing should function. The purpose of this study was to analyze racial biases between POCs (participants of color) and White participants when appraising police officers based on the officer’s race and status as a police officer (as opposed to a civilian). POCs and White participants were asked to take four Internal Association Tests (IATs) to see if there were biases towards or against officers. The conditions for the IATs were White officers versus White civilians, White officers versus Black officers, Black officers versus Black civilians, and White civilians versus Black civilians. The mean scores in the IATs did not significantly differ between races, but they did differ among races; both racial groups appraised police and races similarly, but there were significant biases among each race about what conditions affect appraisal. White participants were significantly biased against White police officers compared to White civilians, POCs were not biased between White police officers and White civilians, both POCs and White participants were biased towards White police officers and White civilians over Black police officers and Black civilians respectively, and both POCs and White participants were not significantly biased between Black police officers and Black civilians. These findings indicate that race does play a difference when appraising officers, but the difference is not significant between races.

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This research was supported by the Undergraduate Research Opportunities Program (UROP).

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Sridhar, Naushil A; Gunnar, Megan R. (2022). When is the officer not seen as safe? Assessing civilian biases regarding police officers with IATs. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/226594.

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