Understanding Officers Behavior in a Non-Traffic Situation

Monday, May 17, 2021


Though less common, a significant number of people encounter the police through non-traffic street stops. These stops have received limited research attention, and because of that, less is known about the nature and dynamics of such contacts. Moreover, due to the dearth of scientific research, several important questions related to officers’ decision-making processes, attitudes, and behaviors remain unanswered. To answer some of these questions, this study analyzed self-reported data from citizens to explain police-citizens’ interactions during non-traffic situations. Specifically, we examined the factors that influence police use of force during non-traffic street stops as well as assessed the effects of variables predicting police verbal attacks against citizens. Results from the regression models suggest that verbal assault against officers, gender and race predict whether officers will verbally attack a citizen or not. Additionally, the findings revealed that verbal assault against officer, officer’s race and suspect characteristics such as gender and income influence officers’ decision to use force. The findings have serious implications for developing policies and enhancing a formidable relationship between citizens and their local police department. 


Dr. Michael Kwame Dzordzormenyoh is currently a Postdoctoral Fellow at the Center for Black Studies Research (CBSR) at the University of California, Santa Barbara. His teaching and research interests examine the connection between leadership, the development and administration of public policy and its impact on citizens, specifically minorities, in a comparative context. My current research projects examine issues related to policing brutality, access to healthcare, and immigration among others aimed at shaping individuals and government policies regarding the respect for human beings, tackling issues of social inequality and injustice, and sensible care of our country's resources.