Full Citation
Title: Gang Violence Predictability: Using Risk Terrain Modeling to Study Gang Homocides and Gang Assaults in East Los Angeles
Citation Type: Journal Article
Publication Year: 2018
ISBN:
ISSN:
DOI: 10.1016/J.JCRIMJUS.2018.06.001
NSFID:
PMCID:
PMID:
Abstract: PURPOSE The current study investigates the application of risk terrain modeling (RTM) to forecast gang violence. RTM is routinely utilized to predict future criminal events in micro-units (i.e., city blocks) based upon features of the physical environment. The particular focus of the current study is RTM's ability to separately predict future gang assaults and gang homicides in the Los Angeles Police Department's (LAPD) Hollenbeck Community Policing Area. METHOD Guided by the existing gang literature and knowledge of the region, 22 environmental risk factors are anticipated to spatially influence gang assaults and gang homicides. An RTM is established for 2009 gang assaults and 2009–2011 gang homicides. The RTM is then used to predict 2012 gang assaults and 2012 gang homicides respectively. RESULTS Places most at risk of experiencing a gang assault are in close proximity to where gang members are frequently observed loitering by police and Metro rail stops while also contending with residential concentrations of local gang members. Areas most at risk of experiencing a gang homicide cope with residential concentrations of local gang members and gang set space. The ability for RTM to successfully forecast future gang violence may be limited. CONCLUSIONS RTM is able to successfully identify and evaluate meaningful environment risk factors that spatially influence gang assaults and gang violence. However, the ability for RTM to successfully forecast future gang violence may be limited.
Url: https://www.sciencedirect.com/science/article/pii/S0047235218302058
User Submitted?: No
Authors: Valasik, Matthew
Periodical (Full): Journal of Criminal Justice
Issue:
Volume: 58
Pages: 10-21
Data Collections: IPUMS NHGIS
Topics: Crime and Deviance, Other
Countries: