This paper presents the authors’ research and findings regarding the impacts of body-worn cameras on police-community member interactions, examining factors behind public perceptions of interactions with police, and provides discussion of the policy implications of those findings.
The objective of this study was to use interval-level metrics to code a random sample of body-worn camera footage from a large (N ∼ 700) municipal police department in 2019. Just over 1,100 videos were coded for the following: community member factors; officer behaviors, including an overall “performance” score; and encounter outcomes. The authors’ goal was to answer the following questions: Do police receive higher overall performance scores when interacting with some types of community members compared to others? Which community member factors significantly predict specific officer behaviors? Which community member factors significantly predict encounter outcomes? They found that officers received higher performance scores when interacting with women, and with community members with mental illness. The authors also found that socio-economic-status and gender were the most common predictors of officer behaviors, while race and ethnicity, socio-economic-status, gender, and armed status predicted encounter outcomes. They discuss policy implications of these findings. Publisher Abstract Provided