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Gang violence predictability: Using risk terrain modeling to study gang homicides and gang assaults in East Los Angeles

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  • Valasik, Matthew

Abstract

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.

Suggested Citation

  • Valasik, Matthew, 2018. "Gang violence predictability: Using risk terrain modeling to study gang homicides and gang assaults in East Los Angeles," Journal of Criminal Justice, Elsevier, vol. 58(C), pages 10-21.
    • Handle: RePEc:eee:jcjust:v:58:y:2018:i:c:p:10-21
    DOI: 10.1016/j.jcrimjus.2018.06.001
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    References listed on IDEAS

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    1. Thomas, Shaun A. & Drawve, Grant, 2018. "Examining interactive effects of characteristics of the social and physical environment on aggravated assault," Journal of Criminal Justice, Elsevier, vol. 57(C), pages 89-98.
    2. Lersch, Kim Michelle, 2017. "Risky places: An analysis of carjackings in Detroit," Journal of Criminal Justice, Elsevier, vol. 52(C), pages 34-40.
    3. Richard Berk & Lawrence Sherman & Geoffrey Barnes & Ellen Kurtz & Lindsay Ahlman, 2009. "Forecasting murder within a population of probationers and parolees: a high stakes application of statistical learning," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 191-211, January.
    4. Blasko, Brandy L. & Roman, Caterina Gouvis & Taylor, Ralph B., 2015. "Local gangs and residents’ perceptions of unsupervised teen groups: Implications for the incivilities thesis and neighborhood effects," Journal of Criminal Justice, Elsevier, vol. 43(1), pages 20-28.
    5. Drawve, Grant & Thomas, Shaun A. & Walker, Jeffery T., 2016. "Bringing the physical environment back into neighborhood research: The utility of RTM for developing an aggregate neighborhood risk of crime measure," Journal of Criminal Justice, Elsevier, vol. 44(C), pages 21-29.
    6. G. O. Mohler & M. B. Short & Sean Malinowski & Mark Johnson & G. E. Tita & Andrea L. Bertozzi & P. J. Brantingham, 2015. "Randomized Controlled Field Trials of Predictive Policing," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1399-1411, December.
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    Cited by:

    1. Connealy, Nathan T. & Piza, Eric L., 2019. "Risk factor and high-risk place variations across different robbery targets in Denver, Colorado," Journal of Criminal Justice, Elsevier, vol. 60(C), pages 47-56.
    2. Nicole J. Johnson & Caterina G. Roman & Alyssa K. Mendlein & Courtney Harding & Melissa Francis & Laura Hendrick, 2020. "Exploring the Influence of Drug Trafficking Gangs on Overdose Deaths in the Largest Narcotics Market in the Eastern United States," Social Sciences, MDPI, vol. 9(11), pages 1-21, November.
    3. Álvaro Briz‐Redón & Jorge Mateu & Francisco Montes, 2022. "Identifying crime generators and spatially overlapping high‐risk areas through a nonlinear model: A comparison between three cities of the Valencian region (Spain)," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 76(1), pages 97-120, February.
    4. Matthew Valasik & Shannon E. Reid, 2021. "East Side Story: Disaggregating Gang Homicides in East Los Angeles," Social Sciences, MDPI, vol. 10(2), pages 1-17, February.

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