Overview
Predictive policing is a new concept for law enforcement in the twenty-first century. While still in its infancy and relatively untested, predictive policing has the potential to change the way in which law enforcement deals with crime and victims. This entry describes predictive policing in terms of its definition and roots, the theories and models that have been developed, applications in law enforcement, and the issues that surround it.
Conceptually, predictive policing involves the use of data and predictive analytics to predict or forecast where and when the next crime or series of crimes will take place. The concept has engendered new terminology in law enforcement. “Predictive analytics,” “data mining,” “nonobvious relationships,” and “predictive spatial analysis” are among the new phrases used by chief executives, policy makers, and researchers to describe aspects of predictive policing. These and other phrases will be...
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Recommended Reading and References
Beck C, McCue C (2009) Predictive policing: what can we learn from Wal-Mart and Amazon about fighting crime in a recession? The Police Chief 76(11)
Berk R (2008) Forecasting methods in crime and justice. Ann Rev Law Soc Sci 4:219–238
Berk R (2009) Statistical learning from a regression perspective. Springer, New York
Berk R (2011) Asymmetric loss functions for forecasting in criminal justice settings. J Quant Criminol 27:107–123
Bowers K, Johnson S, Pease K (2004) Prospective hot spotting: the future of crime mapping? Brit J Criminol 44(5):641–658
Bratton W, Morgan J, Malinowski S (2009) The need for innovation in policing today. Unpublished manuscript, Harvard Executive Sessions, October
Brown DE, Kerchner SH (2000) Spatial-temporal point process models for criminal events. Paper presented at the National Institute of Justice Annual Crime Mapping Conference. Washington, DC. Included in Brown DE (2002) Final report: predictive models for law enforcement. U.S. Department of Justice, Washington, DC
Bursik RJ, Grasmick HG (1993) Neighborhoods and crime: the dimensions of effective community control. Lexington Books, Lanham
Caplan JM, Kennedy LW, Miller J (2011) Risk terrain modeling: brokering criminological theory and GIS methods for crime forecasting. Justice Quarterly 28(2):360–381
Cohen LE, Felson M (1979) Social change and crime rate trends: a routine activity approach. Am Sociol Rev 44(4):588–605
Fox JS, Huddleston H, Gerber M, Brown DE (2012) Investigating a Bayesian hierarchical framework for feature-space modeling of criminal site-selection problems. Paper presented at the Midwest artificial intelligence and cognitive science conference 2012, Cincinnati, 21–22 Apr 2012. Retrieved 29 May 2012, from http://ceur-ws.org/Vol-841/submission_31.pdf
Goldstein H (1990) Problem-oriented policing. McGraw Hill, New York
Groff ER, La Vigne NG (2002) Forecasting the future of predictive crime mapping. Crime Prevention Studies 13:29–57
Gorr W, Olligschlaeger A (2002) Crime hot spot forecasting: modeling and comparative evaluation. Final report. U.S. Department of justice. National Institute of Justice. Washington, D.C
Harris C (2008) Richmond, Virginia, police department helps lower crime rates with crime prediction software. Retrieved 10 Dec 2009, from http://www.govtech.com/gt/print_article.php?id=575229
Johnson SD, Bowers KJ, Birks DJ, Pease K (2009) Predictive mapping of crime by ProMap: accuracy, units of analysis, and the environmental backcloth. In: Weisburd D, Bernasco W, Gerben JN, Bruinsma J (eds) Putting crime in its place. Springer, New York
Lewis M (2004) Moneyball: the art of winning an unfair game. W.W. Norton, New York
Liu H, Brown DE (2000) A new point process transition density model for space-time event prediction. In: Brown DE (ed) (2002). Final report. Predictive models for law enforcement. U.S. Department of justice. Washington, DC
McCue C, Parker A (2003) Connecting the dots: data mining and predictive analytics in law enforcement and intelligence analysis. Police Chief 10(10):115–124
Mohler GO, Short MB, Brantingham PJ, Schoenberg FP, Tita GE (2011) Self-exciting point process modeling of crime. J Am Stat Assoc 106(493):100–108
OurWeekly (2010). Retrieved 5 May 2012, from http://ourweekly.com/los-angeles/los-angeles-police-chief-charlie-beck
Pearsall B (2009) Predictive policing: the future of law enforcement? NIJ J/Issue No. 266, at 16 (National Institute of Justice)
Radcliffe J (2008) Intelligence-led policing. Willan, London
Sampson RJ, Groves W (1989) Community structure and crime: testing social disorganization theory. Am J Sociol 94(4):774–802
Sherman LW, Gartin P, Buerger M (1989) Hot spots of predatory crime. Criminology 27(1):27–56
Swatt M (2003) Short-term forecasting of crime for small geographic areas. Unpublished PhD dissertation, University of Nebraska at Omaha, 216 pp
Townsley M, Homel R, Chasling J (2003) Infectious burglaries: A test of near repeat hypothesis. Brit J Criminol 43:615–633
Uchida CD (2009) Predictive policing in Los Angeles: planning and development. A white paper published by Justice & Security Strategies, Inc., December
Weisburd D (2012) Bringing social context back into the equation. Criminol Public Policy 11(2):317
Williams G (2011) Data mining with rattle and R: the art of excating data for knowledge discovery. Springer, New York
Wilson R, Smith SC, Markovic JD, LeBeau JL (2009) Geospatial technical working group: meeting report on predictive policing. US Department of Justice, National Institute of Justice
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Uchida, C.D. (2014). Predictive Policing. In: Bruinsma, G., Weisburd, D. (eds) Encyclopedia of Criminology and Criminal Justice. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-5690-2_260
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