Explaining the directionality of gang violence with court records

Abstract

Purpose Studies of gang violence typically use police reports to investigate the structure of gang conflict, but overreliance on a singular data source could impede crime control efforts. Extending networked criminology, this study aims to explore what court records reveal about the directionality of gang conflicts. Design/methodology/approach Controlling for the presence of a civil gang injunction (CGI), the authors use multivariate quadratic assignment procedure regression models to disentangle factors thought to account for structural patterns of gang violence mapped from 933 prosecutions involving 307 gangs associated with violent conflict affecting the City of Los Angeles (1998–2013). Specifically, the authors compare competitive advantage to the explanatory power of turf proximity. Findings One measure of turf proximity outperforms all other explanatory factors – gangs with turf centrally positioned in a turf adjacency matrix are significantly more likely to launch attacks, be victimized and exhibit the highest levels of imbalance in their violent involvements. Regarding competitive advantage, the number of cliques and level of internal conflict are significant. Finally, being subject to a CGI is associated with initiating violence. Originality/value Court cases offer a feasible alternative to police data when investigating patterns of intergroup street gang violence.

Guest editorial

“…Thomas and Taylor (2021) remind us of the continued importance and relevance of the school as a setting for studying gang membership. Bichler et al (2021) demonstrate how publicly available court records can be used to study networks of violence for an entire system of gangs in Los Angeles over several years. All three papers provide important ways forward for the application of social network analysis in gang research, which has previously been limited primarily to the use of data extracted from arrest records and field interview data (Faust and Tita, 2019;Gravel, 2018).…”