Abstract: A Positive Deviance Approach to Improve Relations between Police and African American Neighborhoods (Society for Social Work and Research 25th Annual Conference - Social Work Science for Social Change)

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A Positive Deviance Approach to Improve Relations between Police and African American Neighborhoods

Schedule:
Friday, January 22, 2021
* noted as presenting author
Betty Wilson, MSW, Doctoral Student, University of South Carolina, Columbia, SC
Terry Wolfer, PhD, Professor, University of South Carolina, Associate Professor, University of South Carolina
Background and Purpose

Multiple high-profile incidents (e.g., Walter Scott, Michael Brown, Eric Garner) have brought increased attention to the longstanding problem of excessive use of force (EUF) by police in African American neighborhoods. Studies show that African Americans, males especially, are more likely to be racially profiled while driving, subject to stop and frisk, and victims of EUF. As a result of these encounters, relationships between police and African Americans remain fractured and tense. Moreover, recent events and increasing public attention involving police EUF in African American neighborhoods highlight a crucial need to understand and improve police-community relations.

There is a growing body of research that focuses on the strained and failed relationships between law enforcement and African American neighborhoods. There is a paucity of research, however, on the practices of police officers to build positive relationships and handle race-related tensions in African American neighborhoods. To help address this gap, the current study investigated what the best officers do to effectively manage racial tensions, mitigate incidents of EUF, and improve relations between police and African American neighborhoods.

Methods

The first author conducted semi-structured interviews with department heads for two jurisdictions in central South Carolina, in-depth, semi-structured interviews with a diverse sample of ten police officers (White, African American, Latino, Middle Eastern) nominated as positive deviants by their department heads, and follow-up focus groups with interviewees to validate and elaborate study findings. The study used Positive Deviance—a systematic method for identifying positive deviants (i.e., statistical outliers) in communities as a source of insight and innovation for tackling difficult problems—and grounded theory data analysis of interview transcripts.

Results

The study uncovered a number of effective practices for engaging communities, building relationships, and navigating race-related tensions that positive deviant law enforcement officers employ in African American neighborhoods. Officers reported seeking and maintaining relationships with residents and also using pre-existing relationships to resolve problems. Officers also described navigating racial incidents by listening to perspectives of both fellow officers and residents, using empathic communication as a de-escalation tool, and allowing residents to verbally vent their frustrations with law enforcement. Following racial incidents, officers reported additional efforts to deal with the aftermath in ways that avoided broader community tensions such as reviewing body camera footage to better assess the situation, being transparent with the community, and acknowledging possible mistakes made by law enforcement. Furthermore, non-White officers described using their ethnicity as a way to relate to African Americans residents and reduce residents’ anxiety during police encounters.

Conclusion and Implications

Findings highlight the importance of continued positive engagement and relationship building between law enforcement officers and African American neighborhoods, and the potential of these efforts to reduce tensions and conflict law enforcement and African American neighborhoods. Based on their successful efforts, these officers have much to teach other officers about how to improve relations in these neighborhoods, diffuse tension and conflict with communities, and eliminate EUF.