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Part XI - Technology Policing

Published online by Cambridge University Press:  09 August 2019

David Weisburd
Affiliation:
George Mason University, Virginia
Anthony A. Braga
Affiliation:
Northeastern University, Boston
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Summary

For nearly forty years, policymakers within law enforcement, commercially motivated interest groups, and scholars have made the case for an augmented implementation of technology in policing, particularly information technologies. The prominent discourse is efficiency and cost-effectiveness of operations, as technology is hypothesized to improve the quality of law enforcement on a wide range of outcomes and outputs. Prima facie, technology can revolutionize law enforcement; ample examples indicate where this is the case. Research areas in support of technology in policing include computers, GPS-based technologies, video recording of crime scenes, and forensic evidence, such as DNA testing. Our collective view should be that the pertinent question is one of scale: why not more? Why are information technologies not more pronounced in law enforcement? What stopped the information revolution from establishing a more prominent place in policing?

Type
Chapter
Information
Police Innovation
Contrasting Perspectives
, pp. 483 - 563
Publisher: Cambridge University Press
Print publication year: 2019

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References

References

Antrobus, E., & Pilotto, A. (2016). Improving forensic responses to residential burglaries: Results of a randomized controlled field trialJournal of Experimental Criminology12(3), 319345.Google Scholar
Antrobus, E., Thompson, I., & Ariel, B. (2017). Procedural justice training for police recruits: Results of a randomized controlled trial. Journal of Experimental Criminology. https://link.springer.com/article/10.1007/s11292-018-9331-9.Google Scholar
Ariel, B. (2011). Hot Dots and Hot Lines: Analysis of Crime in the London Underground. Presented at the Annual American Society of Criminology, Washington, DC, 06 November 2011.Google Scholar
Ariel, B. (2012). Deterrence and moral persuasion effects on corporate tax compliance: Findings from a randomized controlled trial. Criminology, 50(1), 2769.Google Scholar
Ariel, B. (2016a). Increasing cooperation with the police using body worn cameras. Police Quarterly, 19(3), 326362.Google Scholar
Ariel, B. (2016b). Police body cameras in large police departments. Journal of Criminal Law and Criminology, 106(4), 729768.Google Scholar
Ariel, B. (2016c). The puzzle of police body cams. IEEE Spectrum, 53(7), 3237.CrossRefGoogle Scholar
Ariel, B., Bland, M., & Sutherland, A. (2017). Lowering the threshold of effective deterrence – Testing the effect of private security agents in public spaces on crime: A randomized controlled trial in a mass transit system. PLoS one, 12(12), e0187392.Google Scholar
Ariel, B., Farrar, W. A., & Sutherland, A. (2015). The effect of police body-worn cameras on use of force and citizens’ complaints against the police: A randomized controlled trial. Journal of Quantitative Criminology, 31(3), 509535.Google Scholar
Ariel, B., & Partridge, H. (2016). Predictable policing: Measuring the crime control benefits of hotspots policing at bus stops. Journal of Quantitative Criminology, 125.Google Scholar
Ariel, B., & Tankebe, J. (2016). Racial stratification and multiple outcomes in police stops and searches. Policing and Society, 119.Google Scholar
Ariel, B., Sutherland, A., Henstock, D., Young, J., Drover, P., Sykes, J., Megicks, S., & Henderson, R. (2016a). Wearing body cameras increases assaults against officers and does not reduce police use of force: Results from a global multi-site experiment. European Journal of Criminology, 13(6), 744755.Google Scholar
Ariel, B., Sutherland, A., Henstock, D., Young, J., Drover, P., Sykes, J., Megicks, S., & Henderson, R. (2016b). Report: Increases in police use of force in the presence of body-worn cameras are driven by officer discretion: A protocol-based subgroup analysis of ten randomized experiments. Journal of Experimental Criminology, 12(3), 453463.Google Scholar
Ariel, B., Sutherland, A., Henstock, D., Young, J., Drover, P., Sykes, J., Megicks, S., & Henderson, R. (2017a). “Contagious accountability”: A global multisite randomized controlled trial on the effect of police body-worn cameras on citizens’ complaints against the police. Criminal Justice and Behavior, 44(2), 293316.Google Scholar
Ariel, B., Sutherland, A., Henstock, D., Young, J., Drover, P., Sykes, J., Megicks, S., & Henderson, R. (2017b). Paradoxical effects of self-awareness of being observed: testing the effect of police body-worn cameras on assaults and aggression against officers. Journal of Experimental Criminology, 129.Google Scholar
Ariel, B., Sutherland, A., Henstock, D., Young, J., & Sosinski, G. (2017c). The deterrence spectrum: Explaining why police body-worn cameras “work” or “backfire” in aggressive police–public encountersPolicing: A Journal of Policy and Practice12(1), 626.Google Scholar
Ariel, B., Weinborn, C., & Boyle, A. (2015). Can routinely collected ambulance data about assaults contribute to reduction in community violence? Emerg Med J, 32(4), 308313.Google Scholar
Ariel, B., Weinborn, C., & Sherman, L. W. (2016). “Soft” policing at hotspots – do police community support officers work? A randomized controlled trial. Journal of Experimental Criminology, 12(3), 277317.Google Scholar
Baker, W. E., & Faulkner, R. R. (2003). Diffusion of fraud: Intermediate economic crime and investor dynamics. Criminology, 41(4), 11731206.Google Scholar
Baldwin, J. (1993). Police interview techniques: Establishing truth or proof? The British Journal of Criminology, 33(3), 325352.Google Scholar
Bayley, D. H. (2008). Police reform: Who done it? Policing & Society, 18(1), 717.Google Scholar
Beale, M. (2009). Understanding Arrest for Domestic Violence in Staffordshire – An Exploratory Analysis. MA dissertation, Cambridge University.Google Scholar
Beck, C., & McCue, C. (2009). Predictive policing: what can we learn from Wal-Mart and Amazon about fighting crime in a recession? Police Chief76(11), 18.Google Scholar
Berk, R. A. (2013). Algorithmic criminology. Security Informatics, 2(1), 5.Google Scholar
Berk, R. A., & Bleich, J. (2013). Statistical procedures for forecasting criminal behavior. Criminology & Public Policy, 12(3), 513544.Google Scholar
Berk, R. A., Sherman, L., Barnes, G., Kurtz, E., & Ahlman, L. (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 (Statistics in Society), 172(1), 191211.Google Scholar
Berk, R. A., Sorenson, S. B., & Barnes, G. (2016). Forecasting domestic violence: A machine learning approach to help inform arraignment decisions. Journal of Empirical Legal Studies, 13(1), 94115.Google Scholar
Bichler, G., Lim, S., & Larin, E. (2017). Tactical social network analysis: Using affiliation networks to aid serial homicide investigation. Homicide Studies, 21(2), 133158.Google Scholar
Boudreau, M. C., & Robey, D. (2005). Enacting integrated information technology: A human agency perspective. Organization Science, 16(1), 318.Google Scholar
Boyle, A. A., Snelling, K., White, L., Ariel, B., & Ashelford, L. (2013). External validation of the Cardiff model of information sharing to reduce community violence: Natural experiment. Emerg Med J, 30(12), 10201023.Google Scholar
Braga, A. A., & Weisburd, D. L. (2012). The effects of focused deterrence strategies on crime: A systematic review and meta-analysis of the empirical evidence. Journal of Research in Crime and Delinquency, 49(3), 323358.Google Scholar
Braga, A. A., & Weisburd, D. L. (2014). Must we settle for less rigorous evaluations in large area-based crime prevention programs? Lessons from a Campbell review of focused deterrence. Journal of Experimental Criminology, 10(4), 573597.Google Scholar
Braga, A. A., Apel, R., & Welsh, B. C. (2013). The spillover effects of focused deterrence on gang violence. Evaluation Review, 37(3–4), 314342.Google Scholar
Braga, A. A., Flynn, E. A., Kelling, G. L., & Cole, C. M. (2011). Moving the work of criminal investigators towards crime control. Executive Session on Policing and Public Safety.Google Scholar
Braga, A. A., Papachristos, A. V., & Hureau, D. M. (2014). The effects of hotspots policing on crime: An updated systematic review and meta-analysis. Justice Quarterly, 31(4), 633663.Google Scholar
Braga, A. A., Welsh, B. C., Papachristos, A. V., Schnell, C., & Grossman, L. (2014). The growth of randomized experiments in policing: The vital few and the salience of mentoring. Journal of Experimental Criminology, 10(1), 128.Google Scholar
Bratton, W. J., Morgan, J., & Malinowski, S. (2009). Fighting crime in the information age: The promise of predictive policing. Annual Meeting of the American Society of Criminology, Philadelphia, PA.Google Scholar
Bruce, V., Henderson, Z., Greenwood, K., Hancock, P. J., Burton, A. M., & Miller, P. (1999). Verification of face identities from images captured on video. Journal of Experimental Psychology: Applied, 5(4), 339.Google Scholar
Brynielsson, J., Horndahl, A., Johansson, F., Kaati, L., Mårtenson, C., & Svenson, P. (2013). Harvesting and analysis of weak signals for detecting lone wolf terrorists. Security Informatics, 2(1), 11.Google Scholar
Byrne, J. M., & Rebovich, D. J. (2007). The New Technology of Crime, Law and Social Control. Monsey, NY: Criminal Justice Press.Google Scholar
Byrne, J., & Marx, G. (2011). Technological innovations in crime prevention and policing. A review of the research on implementation and impact. Journal of Police Studies, 20(3), 1740.Google Scholar
Byrne, J., & Pattavina, A. (2006). Assessing the role of clinical and actuarial risk assessment in an evidence-based community corrections system: Issues to consider. Fed. Probation, 70, 64.Google Scholar
Cardenas, A. A., Manadhata, P. K., & Rajan, S. P. (2013). Big data analytics for security. IEEE Security & Privacy, 11(6), 7476.Google Scholar
Casady, T. K., Cottingham, I., Paulo, J., Ramírez, A. S., Tomkins, A. J., Farrell, K., Hamm, J. A., Rosenbaum, D. I., & Shank, N. (2015). A Randomized-Trial Evaluation of a Law Enforcement Application for Smartphones and Laptops that Uses GIS and Location-Based Services’ to Pinpoint Persons-of-Interest. Retrieved from www.ncjrs.gov/pdffiles1/nij/grants/248593.pdf.Google Scholar
Chabris, C., & Simons, D. (2010). The Invisible Gorilla: And Other Ways Our Intuitions Deceive. HarperCollins.Google Scholar
Chaiken, J. M., & Dormont, P. (1978). A patrol car allocation model: Capabilities and algorithms. Management Science, 24(12), 12911300.Google Scholar
Chainey, S., & Ratcliffe, J. (2005). Mapping crime with local community data. GIS and Crime Mapping, 183222.Google Scholar
Chowdhury, H. K., Parvin, N., Weitenberner, C., & Becker, M. (2006). Consumer attitude toward mobile advertising in an emerging market: An empirical studyInternational Journal of Mobile Marketing1(2).Google Scholar
Cooper, R. B., & Zmud, R. W. (1990). Information technology implementation research: A technological diffusion approach. Management Science, 36(2), 123139.Google Scholar
Coudert, F., Butin, D., & Le Métayer, D. (2015). Body-worn cameras for police accountability: Opportunities and risks. Computer Law & Security Review, 31(6), 749762.Google Scholar
Crowther, R. F. (1964). The use of a computer system for police manpower allocation in St. Louis, Missouri. Indiana University, Department of Police Administration.Google Scholar
Cubitt, T. I., Lesic, R., Myers, G. L., & Corry, R. (2017). Body-worn video: A systematic review of literature. Australian & New Zealand Journal of Criminology, 50(3), 379396.Google Scholar
Dalcher, D., & Genus, A. (2003). Introduction: Avoiding IS/IT implementation failure. Technology Analysis & Strategic Management, 15(4), 403407.Google Scholar
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319340.Google Scholar
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical modelsManagement Science35(8), 9821003.Google Scholar
de Brito, C., & Ariel, B. (2017). Does tracking and feedback boost patrol time in hot spots? Two testsCambridge Journal of Evidence-Based Policing1(4), 244262.Google Scholar
Denley, J., and Ariel, B. (forthcoming). Whom should we target to prevent? Analysis of organized crime in England using intelligence records. European Journal of Crime, Criminal Law and Criminal Justice.Google Scholar
Diniz, E. H., Luvizan, S. S., Hino, M. C., & Ferreira, P. C. (2018). Unveiling the big data adoption in banks: Strategizing the implementation of a new technology. In Digital Technology and Organizational Change (pp. 149162). Cham: Springer.Google Scholar
Dixon, D. (2013). Regulating police interrogation. In Williamson, T. (ed.) Investigative Interviewing (pp. 318352). New York: Willan Publishing.Google Scholar
Drover, P., & Ariel, B. (2015). Leading an experiment in police body-worn video cameras. International Criminal Justice Review, 25(1), 8097.Google Scholar
Duwe, G., & Kim, K. (2015). Out with the old and in with the new? An empirical comparison of supervised learning algorithms to predict recidivism. Criminal Justice Policy Review, 0887403415604899.Google Scholar
Duxbury, S. W., & Haynie, D. L. (2017). The network structure of opioid distribution on a darknet cryptomarket. Journal of Quantitative Criminology, 121.Google Scholar
Egnoto, M., Egnoto, M., Ackerman, G., Ackerman, G., Iles, I., Iles, I., … & Liu, B. F. (2017). What motivates the blue line for technology adoption? Insights from a police expert panel and survey. Policing: An International Journal of Police Strategies & Management, 40(2), 306320.Google Scholar
Englefield, A., & Ariel, B. (2017). Searching for influential actors in co-offending networks: The recruiter. International Journal of Social Science Studies, 5(5), 2445.Google Scholar
Farrar, W., & Ariel, B. (2013). Self-awareness to being watched and socially desirable behavior: A field experiment on the effect of body-worn cameras on police use-of-force. Washington, DC: Police Foundation.Google Scholar
Farrington, D. P., Gottfredson, D. C., Sherman, L. W., & Welsh, B. C. (2002). The Maryland scientific methods scale. Evidence-Based Crime Prevention, 1321.Google Scholar
Fisher, B. A., & Fisher, D. R. (2012). Techniques of Crime Scene Investigation. CRC Press.Google Scholar
Fox, B. H., & Farrington, D. P. (2015). An experimental evaluation on the utility of burglary profiles applied in active police investigations. Criminal Justice and Behavior, 42(2), 156175.Google Scholar
Gardner, L., & Shoemaker, D. J. (1989). Social bonding and delinquency. The Sociological Quarterly, 30(3), 481500.Google Scholar
Garicano, L., & Heaton, P. (2010). Information technology, organization, and productivity in the public sector: Evidence from police departments. Journal of Labor Economics, 28(1), 167201.Google Scholar
Gaub, J. E., Choate, D. E., Todak, N., Katz, C. M., & White, M. D. (2016). Officer perceptions of body-worn cameras before and after deployment: A study of three departments. Police Quarterly, 19(3), 275302.Google Scholar
Gawrylowicz, J., & Memon, A. (2014). Interviewing Eyewitnesses. In Encyclopedia of Criminology and Criminal Justice (pp. 26792688). New York: Springer.Google Scholar
Goddard, N., & Ariel, B. (2014). How much time should officers spend in night-time economy hotspots? Lessons from a “Randomized Controlled Trial in Northern Ireland.” Presented at the Annual American Society of Criminology (San Francisco, CA, 18–20 November 2014).Google Scholar
Goold, B. J. (2003). Public area surveillance and police work: The impact of CCTV on police behavior and autonomy. Journal of Surveillance and Society, 1(2), 191203.Google Scholar
Groff, E. R., Ratcliffe, J. H., Haberman, C. P., Sorg, E. T., Joyce, N. M., & Taylor, R. B. (2015). Does what police do at hotspots matter? The Philadelphia policing tactics experiment. Criminology, 53(1), 2353.Google Scholar
Haberman, C. P., & Ratcliffe, J. H. (2012). The predictive policing challenges of near repeat armed street robberies. Policing: A Journal of Policy and Practice, 6(2), 151166.Google Scholar
Haggerty, K. D., & Ericson, R. V. (2000). The surveillant assemblageThe British Journal of Sociology51(4), 605622.Google Scholar
Hanson, R., & Morton-Bourgon, K. (2004). Predictors of Sexual Recidivism: An Updated Meta-Analysis. Ottawa, ON: Public Safety and Emergency Preparedness Canada.Google Scholar
Harris, A., & Lurigio, A. J. (2007). Mental illness and violence: A brief review of research and assessment strategies. Aggression and Violent Behavior, 12(5), 542551.Google Scholar
Harris, C. (2007). Police and soft technology: How information technology contributes to police decision making. The New Technology of crime, Law and Social Control, 153183.Google Scholar
Henstock, D., & Ariel, B. (2017). Testing the effects of police body-worn cameras on use of force during arrests: A randomised controlled trial in a large British police force. European Journal of Criminology, 1477370816686120.Google Scholar
Hess, J., & Turner, S. (2013). Risk Assessment Accuracy in Corrections Population Management: Testing the Promise of Tree Based Ensemble Predictions. Irvine: Center for Evidence-Based Corrections, University of California.Google Scholar
Hickman, M. J., & Reaves, B. A. (2006). Bureau of Justice Statistics Special Report. Washington, DC: US Department of Justice.Google Scholar
Hipgrave, S. (2013). Smarter fraud investigations with big data analytics. Network Security, 12, 79.Google Scholar
Hoffman, P. (1992). The feds, lies, and videotape: The need for an effective federal role in controlling police abuse in urban America. S. Cal. L. Rev., 66, 1453.Google Scholar
Hutt, O., Bowers, K., Johnson, S., & Davies, T. (2018). Data and evidence challenges facing place-based policingPolicing: An International Journal of Police Strategies & Management41(3), 339351.Google Scholar
Hummer, D. (2007). Policing and “hard” technology. In The New Technology of Crime, Law and Social Control (pp. 133152). Monsey, NY: Criminal Justice Press.Google Scholar
Hyatt, J. M., & Barnes, G. C. (2017). An experimental evaluation of the impact of intensive supervision on the recidivism of high-risk probationers. Crime & Delinquency, 63(1), 338.Google Scholar
Jennings, W. G., Fridell, L. A., & Lynch, M. D. (2014). Cops and cameras: Officer perceptions of the use of body-worn cameras in law enforcement. Journal of Criminal Justice, 42(6), 549556.Google Scholar
Johnson, S. D., Davies, T., Murray, A., Ditta, P., Belur, J., & Bowers, K. (2017). Evaluation of operation swordfish: A near-repeat target-hardening strategy. Journal of Experimental Criminology, 121.Google Scholar
Kahneman, D., & Egan, P. (2011). Thinking, fast and slow. New York: Farrar, Straus and Giroux.Google Scholar
Kelling, G. L., Pate, T., Dieckman, D., & Brown, C. E. (1974). The Kansas City preventive patrol experiment. Washington, DC: Police Foundation.Google Scholar
Kennedy, D. M., Kleiman, M. A., & Braga, A. A. (2017). Beyond deterrence. In Handbook of Crime Prevention and Community Safety, 157.Google Scholar
Koper, C. S. (1995). Just enough police presence: Reducing crime and disorderly behavior by optimizing patrol time in crime hot spotsJustice Quarterly12(4), 649672.Google Scholar
Koper, C. S., Lum, C., & Willis, J. J. (2014). Optimizing the use of technology in policing: Results and implications from a multi-site study of the social, organizational, and behavioral aspects of implementing police technologies. Policing: A Journal of Policy and Practice, 8(2), 212221.Google Scholar
Koper, C. S., Taylor, B. G., & Kubu, B. (2009). Law Enforcement Technology Needs Assessment: Future Technologies to Address the Operational Needs of Law Enforcement. Police Executive Research Forum.Google Scholar
Kriegler, B., & Berk, R. (2010). Small area estimation of the homeless in Los Angeles: An application of cost-sensitive stochastic gradient boosting. The Annals of Applied Statistics, 12341255.Google Scholar
Lapointe, L., & Rivard, S. (2005). A multilevel model of resistance to information technology implementation. MIS Quarterly, 461491.Google Scholar
Lartney, J. (2017). US police killings undercounted by half, study using Guardian data finds. The Guardian. Retrieved October 13, 2017, from https://tinyurl.com/y7kzug3 h.Google Scholar
Lassiter, G. D., Munhal, P. J., Geers, A. L., Weiland, P. E., & Handley, I. M. (2001). Accountability and the camera perspective bias in videotaped confessions. Analyses of Social Issues and Public Policy, 1(1), 5370.Google Scholar
Levine, E. S., Tisch, J., Tasso, A., & Joy, M. (2017). The New York City Police Department’s Domain Awareness System. Interfaces, 47(1), 7084.Google Scholar
Lewin, K. (1948). Conduct, knowledge, and acceptance of new values. In Weis Lewin, G. (ed.) Resolving Social Conflicts: Selected Papers on Group Dynamics (pp. 5668). New York: Harper & Row.Google Scholar
Liu, J. L., & Wyatt, J. C. (2011). The case for randomized controlled trials to assess the impact of clinical information systemsJournal of the American Medical Informatics Association18(2), 173180.Google Scholar
Lum, C. (2010). Technology and mythology of progress in American law enforcement. Science Progress, Feb 11.Google Scholar
Lum, C. (2013). Is crime analysis evidence-based? Translational Criminology, 5, 1214.Google Scholar
Lum, C., Hibdon, J., Cave, B., Koper, C. S., & Merola, L. (2011). License plate reader (LPR) police patrols in crime hotspots: an experimental evaluation in two adjacent jurisdictions. Journal of Experimental Criminology, 7(4), 321345.Google Scholar
Lum, C., Koper, C. S., Merola, L. M., Scherer, A., & Reioux, A. (2015). Existing and Ongoing Body Worn Camera Research: Knowledge Gaps and Opportunities. George Mason University.Google Scholar
Macbeth, E., & Ariel, B. (2017). Place-based statistical versus clinical predictions of crime hotspots and harm locations in Northern Ireland. Justice Quarterly, 134.Google Scholar
Manning, P. K. (1992). Technological dramas and the police: Statement and counterstatement in organizational analysis. Criminology, 30(3), 327346.Google Scholar
Manning, P. K. (2008). The Technology of Policing: Crime Mapping, Information Technology, and the Rationality of Crime Control. New York: New York University Press.Google Scholar
Maskaly, J., Donner, C., Jennings, W. G., Ariel, B., & Sutherland, A. (2017). The effects of body-worn cameras (BWCs) on police and citizen outcomes: A state-of-the-art review. Policing: An International Journal of Police Strategies & Management, 40(4), 672688.Google Scholar
Mastrofski, S. D., Weisburd, D., & Braga, A. A. (2010). Rethinking policing: The policy implications of hot spots of crime. Contemporary Issues in Criminal Justice Policy, 251264.Google Scholar
Mastrofski, S. D., & Willis, J. J. (2010). Police organization continuity and change: Into the twenty-first century. Crime and Justice, 39(1), 55144.Google Scholar
McCahill, M., & Norris, C., (2004). From cameras to control rooms: The mediation of the image by cctv operatives. CCTV and Social Control: The politics and practice of video surveillance. European and Global Perspectives1.Google Scholar
McGloin, J. (2005). Policy and intervention considerations of a network analysis of street gangs. Criminology & Public Policy, 4(3), 607635.Google Scholar
Meehl, P. E. (1954). Clinical vs. Statistical Prediction (pp. 389391). Minneapolis: University of Minnesota Press.Google Scholar
Merton, R. K. (1938). Social structure and anomie. American Sociological Review, 3(5), 672682.Google Scholar
Michalski, R. S., Carbonell, J. G., & Mitchell, T. M. (eds.). (2013). Machine Learning: An Artificial Intelligence Approach. Springer Science & Business Media.Google Scholar
Mohler, G. O., Short, M. B., Malinowski, S., Johnson, M., Tita, G E., Bertozzi, A., & Brantingham, P. J. (2015). Randomized controlled field trials of predictive policing. Journal of the American Statistical Association, 110(512), 13991411.Google Scholar
Morin, A. (2011). Self‐awareness part 1: Definition, measures, effects, functions, and antecedents. Social and Personality Psychology Compass, 5(10), 807823.Google Scholar
Morselli, C. (2003). Career opportunities and network-based privileges in the Cosa Nostra. Crime, Law and Social Change, 39(4), 383418.Google Scholar
Natarajan, M. (2006). Understanding the structure of a large heroin distribution network: A quantitative analysis of qualitative data. Journal of Quantitative Criminology, 22(2), 171192.Google Scholar
Neuilly, M. A., Zgoba, K. M., Tita, G. E., & Lee, S. S. (2011). Predicting recidivism in homicide offenders using classification tree analysis. Homicide sStudies, 15(2), 154176.Google Scholar
Newton, A., & Felson, M. (2015). Crime patterns in time and space: The dynamics of crime opportunities in urban areas. Crime Science, 4(1), 15.Google Scholar
Oatley, G., Ewart, B., & Zeleznikow, J. (2006). Decision support systems for police: Lessons from the application of data mining techniques to “soft” forensic evidence. Artificial Intelligence and Law, 14(1–2), 35100.Google Scholar
Palmer, D. (2016). The mythical properties of police body-worn cameras: A solution in the search of a problem. Surveillance & Society, 14(1), 138.Google Scholar
Papachristos, A. V. (2009). Murder by structure: Dominance relations and the social structure of gang homicide. American Journal of Sociology, 115(1), 74128.Google Scholar
Papachristos, A. V. (2011). The coming of a networked criminology. In MacDonald, J. (ed.). Advances in Criminological Theory (pp. 101140). New Brunswick, NJ: Transactions Publishers.Google Scholar
Papachristos, A. V., Braga, A. A., & Hureau, D. M. (2012). Social networks and the risk of gunshot injuryJournal of Urban Health89(6), 9921003.Google Scholar
Pedahzur, A., & Perliger, A. (2006). The changing nature of suicide attacks: A social network perspective. Social Forces, 84(4), 19872008.Google Scholar
Pentland, B. T., & Feldman, M. S. (2005). Organizational routines as a unit of analysis. Industrial and Corporate Change, 14(5), 793815.Google Scholar
Piza, E., Caplan, J. M., Kennedy, L. W., & Gilchrist, A. M. (2015). The effects of merging proactive CCTV monitoring with directed police patrol: A randomized controlled trial. Journal of Experimental Criminology, 11(1), 4369.Google Scholar
Police Executive Res. Forum. (2014). Future Trends in Policing. Washington, DC: Police Executive Res. Forum.Google Scholar
Ratcliffe, J. H., & McCullagh, M. J. (2001). Chasing ghosts? Police perception of high crime areas. British Journal of Criminology, 41(2), 330341.Google Scholar
Ratcliffe, J. H., & Sorg, E. T. (2017). A history of foot patrol. In Foot Patrol (pp. 720). Cham: Springer.Google Scholar
Ratcliffe, J. H., Taniguchi, T., & Taylor, R. B. (2009). The crime reduction effects of public CCTV cameras: A multi‐method spatial approach. Justice Quarterly, 26(4), 746770.Google Scholar
Ratcliffe, J. H., Taniguchi, T., Groff, E. R., & Wood, J. D. (2011). The Philadelphia foot patrol experiment: A randomized controlled trial of police patrol effectiveness in violent crime hotspots. Criminology, 49(3), 795831.Google Scholar
Reiss, A Jr. J. (1986). Co-offender influences on criminal careers. Criminal Careers and Career Criminals2, 121160.Google Scholar
Ren, A., Chen, C., & Luo, Y. (2008). Simulation of emergency evacuation in virtual realityTsinghua Science and Technology13(5), 674680.Google Scholar
Rengert, G. F., & Pelfrey, W. V. (1997). Cognitive mapping of the city center: Comparative perceptions of dangerous places. Crime Mapping and Crime Prevention, 193218.Google Scholar
Ridgway, G. (2018). Policing in the era of big dataAnnual Review of Criminology1, 401419.Google Scholar
Roman, J. K., Reid, S. E., Chalfin, A. J., & Knight, C. R. (2009). The DNA field experiment: a randomized trial of the cost-effectiveness of using DNA to solve property crimes. Journal of Experimental Criminology, 5(4), 345.Google Scholar
Rosenfeld, R., Deckard, M. J., & Blackburn, E. (2014). The effects of directed patrol and self-initiated enforcement on firearm violence: A randomized controlled study of hot spot policingCriminology, 52(3), 428449.Google Scholar
Sampson, R. J., & Raudenbush, S. W. (1999). Systematic social observation of public spaces: A new look at disorder in urban neighborhoodsAmerica Journal of Sociology105(3), 603651.Google Scholar
Sarnecki, J. (1990). Delinquent networks in Sweden. Journal of Quantitative Criminology, 6(1), 3150.Google Scholar
Sarnecki, J. (2001). Delinquent Networks: Youth Co-Offending in Stockholm. Cambridge University Press.Google Scholar
Saunders, J., Hunt, P., & Hollywood, J. S. (2016). Predictions put into practice: a quasi-experimental evaluation of Chicago’s predictive policing pilotJournal of Experimental Criminology12(3), 347371.Google Scholar
Scott, H. (1949). Police Problems of Today (Vol. 3). Stevens.Google Scholar
Shaw, C. R., & McKay, H. D. (1942). Juvenile Delinquency and Urban Areas. Chicago: University of Chicago Press.Google Scholar
Sherman, L. W. (1975). Middle management and police democratization: A reply to John E. Angell. Criminology, 12(4), 363378.Google Scholar
Sherman, L. W. (1980). Causes of police behavior: The current state of quantitative research. Journal of Research in Crime and Delinquency, 17(1), 69100.Google Scholar
Sherman, L. W. (1990). Police crackdowns: Initial and residual deterrenceCrime and Justice12, 148.Google Scholar
Sherman, L. W. (1998). Evidence-Based Policing. Washington, DC: Police Foundation.Google Scholar
Sherman, L. W. (2009). Evidence and liberty: The promise of experimental criminology. Criminology & Criminal Justice, 9(1), 528.Google Scholar
Sherman, L. W. (2013). The rise of evidence-based policing: Targeting, testing, and tracking. Crime and Justice, 42(1), 377451.Google Scholar
Sherman, L. W., & Weisburd, D. (1995). General deterrent effects of police patrol in crime “hotspots”: A randomized, controlled trial. Justice Quarterly, 12(4), 625648.Google Scholar
Sherman, L. W., Gartin, P. R., & Buerger, M. E. (1989). Hotspots of predatory crime: Routine activities and the criminology of place. Criminology, 27(1), 2756.Google Scholar
Sherman, L. W., Williams, S., Ariel, B., Strang, L. R., Wain, N., Slothower, M., & Norton, A. (2014). An integrated theory of hotspots patrol strategy: Implementing prevention by scaling up and feeding back. Journal of Contemporary Criminal Justice, 30(2), 95122.Google Scholar
Sherman, L. W., and Eck, J. E. (2002). Policing for Crime Prevention. In Sherman, L. W., Farrington, D. P., Welsh, B. C., & MacKenzie, D. L. (eds.), Evidence-Based Crime Prevention (pp. 295329). London: Routledge.Google Scholar
Skogan, W. G., & Hartnett, S. M. (1997). Community Policing, Chicago Style. New York: Oxford University Press.Google Scholar
Skogan, W. G., & Hartnett, S. M. (2005). The diffusion of information technology in policingPolice Practice and Research6(5), 401417.Google Scholar
Snodgrass, G. M., Rosay, A. B., & Gover, A. R. (2014). Modeling the referral decision in sexual assault cases: An application of random forests. American Journal of Criminal Justice, 39(2), 267291.Google Scholar
Soghoian, C. (2011). An end to privacy theater: Exposing and discouraging corporate disclosure of user data to the government. Minnesota Journal of Law, Science & Technology, 12, 191.Google Scholar
Solove, D. J. (2004). The digital person: Technology and privacy in the information age. New York: New York University Press.Google Scholar
Sorg, E. T., Wood, J. D., Groff, E. R., & Ratcliffe, J. H. (2014). Boundary adherence during place-based policing evaluations: A research note. Journal of Research in Crime and Delinquency, 51(3), 377393.Google Scholar
Stanley, J. (2013). Police body-mounted cameras: With right policies in place, a win for all. New York: ACLU. www.aclu.org/sites/default/files/assets/police_body-mounted_cameras.pdf.Google Scholar
Strang, K. D., & Sun, Z. (2017). Analyzing relationships in terrorism big data using hadoop and statistics. Journal of Computer Information Systems, 57(1), 6775.Google Scholar
Sutherland, A., Ariel, B., Farrar, W., & De Anda, R. (2017). Post-experimental follow-ups – Fade-out versus persistence effects: The Rialto police body-worn camera experiment four years on. Journal of Criminal Justice. https://doi.org/10.1016/j.jcrimjus.2017.09.008CrossRefGoogle Scholar
Sutherland, E. H. (1947). Principles of Criminology, 4th ed. Philadelphia: Lippincott.Google Scholar
Taniguchi, T. A., & Gill, C. (2013). The mobilization of crime mapping and intelligence gathering: Evaluating smartphone deployment and custom app development in a mid-size law enforcement agency. Washington, DC: Police Foundation. www.policefoundation.org/content/ mobilization-crime-mapping.Google Scholar
Tankebe, J., & Ariel, B. (2016). Cynicism Towards Change: The Case of Body-Worn Cameras Among Police Officers. Research paper.Google Scholar
Taylor, B., Koper, C. S., & Woods, D. (2012). Combating vehicle theft in arizona: A randomized experiment with license plate recognition technology. Criminal Justice Review, 37(1), 2450.Google Scholar
Taxman, F. S., & Caudy, M. S. (2015). Risk tells us who, but not what or how. Criminology & Public Policy, 14(1), 71103.Google Scholar
Telep, C. W., Mitchell, R. J., & Weisburd, D. (2014). How much time should the police spend at crime hot spots? Answers from a police agency directed randomized field trial in Sacramento, CaliforniaJustice Quarterly31(5), 905933.CrossRefGoogle Scholar
Tinati, R., Halford, S., Carr, L., & Pope, C. (2014). Big data: Methodological challenges and approaches for sociological analysis. Sociology, 48(4), 663681.Google Scholar
Tversky, A., & Kahneman, D. (1975). Judgment under uncertainty: Heuristics and biases. In Utility, Probability, and Human Decision Making (pp. 141162). Netherlands: Springer.Google Scholar
van Bommel, M., van Prooijen, J. W., Elffers, H., & van Lange, P. A. (2014). Intervene to be seen: The power of a camera in attenuating the bystander effect. Social Psychological and Personality Science, 5(4), 459466.Google Scholar
Wain, N., & Ariel, B. (2014). Tracking of police patrol. Policing: A Journal of Policy and Practice, 8(3), 274283.Google Scholar
Wain, N., Ariel, B., & Tankebe, J. (2017). The collateral consequences of GPS-LED supervision in hotspots policing. Police Practice and Research, 18(4), 376390.Google Scholar
Weinborn, C., Ariel, B., Sherman, L. W., & O’Dwyer, E. (2017). Hotspots vs. harmspots: Shifting the focus from counts to harm in the criminology of place. Applied Geography, 86, 226244.Google Scholar
Weisburd, D. (2015). The law of crime concentration and the criminology of place. Criminology, 53(2), 133157.CrossRefGoogle Scholar
Weisburd, D., & Majmundar, M. (2018). Proactive Policing: Effects on Crime and Communities. National Academy of Sciences. Washington, DC: The National Academies Press.Google Scholar
Weisburd, D., & Amram, S. (2014). The law of concentrations of crime at place: The case of Tel Aviv-Jaffa. Police Practice and Research, 15(2), 101114.Google Scholar
Weisburd, D., Groff, E. R., & Yang, S. M. (2012). The Criminology of Place: Street Segments and Our Understanding of the Crime Problem. Oxford University Press.Google Scholar
Weisburd, D., Groff, E. R., Jones, G., Cave, B., Amendola, K. L., Yang, S. M., & Emison, R. F. (2015). The Dallas patrol management experiment: Can AVL technologies be used to harness unallocated patrol time for crime prevention? Journal of Experimental Criminology, 11(3), 367391.Google Scholar
Weisburd, D., Telep, C. W., Hinkle, J. C., & Eck, J. E. (2010). Is problem‐oriented policing effective in reducing crime and disorder? Criminology & Public Policy, 9(1), 139172.Google Scholar
Welsh, B. C., & Farrington, D. P. (2002). Crime Prevention Effects of Closed Circuit Television: A Systematic Review (vol. 252). London: Home Office.Google Scholar
Welsh, B. C., & Farrington, D. P. (2009). Public area CCTV and crime prevention: An updated systematic review and meta‐analysis. Justice Quarterly, 26(4), 716745.Google Scholar
Willis, J. J., Koper, C., & Lum, C. (2017). The adaptation of license-plate readers for investigative purposes: Police technology and innovation re-invention. Justice Quarterly, 125.Google Scholar
Willis, J. J., Mastrofski, S. D., and Weisburd, D. (2007). Making sense of Compstat: A theory-based analysis of organizational change in three police departments. Law and Society Review, 41, 147–188.Google Scholar
Wilson, D. B., McClure, D., & Weisburd, D. (2010). Does forensic DNA help to solve crime? The benefit of sophisticated answers to naive questions. Journal of Contemporary Criminal Justice, 26(4), 458469.Google Scholar
Wilson, D. B., Weisburd, D., McClure, D., & Wilson, D. B. (2011). Use of DNA testing in police investigative work for increasing offender. Campbell Systematic Reviews, 7.Google Scholar

References

Agrawal, M., Rao, R. H., & Sanders, L. G. (2003). Impact of mobile computing terminals in police work. Journal of Organizational Computing and Electronic Commerce, 13(2), 7389.Google Scholar
Ariel, B., Farrar, W. A., & Sutherland, A. (2015). The effect of police body-worn cameras on use of force and citizens’ complaints against the police: A randomized controlled trial. Journal of Quantitative Criminology, 31(3), 509535.Google Scholar
Ariel, B., Sutherland, A. Henstock, D., Young, J., Drover, P., Sykes, J., Megicks, S., & Henderson, R. (2016). Report: Increases in police use of force in the presence of body-worn cameras are driven by officer discretion: A protocol-based subgroup analysis of ten randomized experiments. Journal of Experimental Criminology, 12(3), 453463.Google Scholar
Boudreau, M.-C., & Robey, D. (2005). Enacting integrated information technology: A human agency perspective. Organization Science, 16(1), 318.Google Scholar
Braga, A. A., Flynn, E. A., Kelling, G. L., & Cole, C. M. (2011). Moving the work of criminal investigators toward crime control. New Perspectives in Policing. Washington, DC: National Institute of Justice.Google Scholar
Brown, M. M. (2001). The benefits and costs of information technology innovations: An empirical assessment of a local government agency. Public Performance & Management Review, 24(4), 351366.Google Scholar
Brown, M. M. (2015). Revisiting the It productivity paradox. The American Review of Public Administration, 45(5), 565583.Google Scholar
Brown, M. M., & Brudney, J. L. (2003). Learning organizations in the public sector? A study of police agencies employing information and technology to advance knowledge. Public Administration Review, 63(1), 3043.Google Scholar
Brynjolfsson, E. (1993). The productivity paradox of information technology. Communications of the ACM, 36(12), 6777.CrossRefGoogle Scholar
Brynjolfsson, E., & Witt, L. M. (2000). Beyond computation: Information technology, organizational transformation and business performance. Journal of Economic Perspectives, 14(4), 2348.Google Scholar
Burch, A. M. (2012). Sheriffs’ Offices, 2007 – Statistical Tables. Washington, DC: Bureau of Justice Statistics.Google Scholar
Byrne, J., & Marx, G. (2011). Technological innovations in crime prevention and policing. A review of the research on implementation and impact. Journal of Police Studies, 20(3), 1740.Google Scholar
Chan, J. (2001). The technological game: How information technology is transforming police practice. Criminology and Criminal Justice, 1(2), 139159.Google Scholar
Chan, J. (2003). Police and new technologies. In Newburn, T. (ed.), Handbook of Policing (pp. 655679). Portland: Willan Publishing.Google Scholar
Chan, J., Brereton, D., Legosz, M., & Doran, S. (2001). E-Policing: The Impact of Information Technology on Police Practices. Brisbane: Criminal Justice Commission.Google Scholar
Cohen, I. M., Plecas, D., & McCormick, A. V. (2007). A Report on the Utility of the Automated License Plate Recognition System in British Columbia. Abbotsford, British Columbia: School of Criminology and Criminal Justice, University College of the Fraser Valley.Google Scholar
Colvin, C. (2001). Evaluation of innovative technology: implications for the community policing roles of law enforcement officers. San Francisco: Psychology Department, San Francisco State University.Google Scholar
Cope, N. (2004). Intelligence led policing or policing led intelligence? Integrating volume crime analysis into policing. British Journal of Criminology, 44(2), 188203.Google Scholar
Cordner, G., & Biebel, E. P. (2005). Problem-oriented policing in practice. Criminology & Public Policy, 4(2), 155–80.Google Scholar
Danziger, J. N., & Kraemer, K. L. (1985). Computerized data-based systems and productivity among professional workers: The case of detectives. Public Administration Review (January/February), 196209.Google Scholar
Ericson, R. V., & Haggerty, K. D. (1997). Policing the Risk Society. Toronto: University of Toronto Press.Google Scholar
Farrar, W. A., & Ariel, B. (2013). Self-Awareness to Being Watched and Socially-Desirable Behavior: A Field Experiment on the Effect of Body-Worn Cameras on Police Use of Force. Washington, DC: Police Foundation.Google Scholar
Frank, J., Brandl, S. G., & Watkins, R. C. (1997). The content of community policing: A comparison of the daily activities of community and “beat” officers. Policing: An International Journal of Police Strategies & Management, 20(4), 716728.Google Scholar
Foley, P., & Alfonso, X. (2009). eGovernment and the transformation agenda. Public Administration, 87(2), 371396.Google Scholar
Garg, A. X., Adhikari, N. K. J., McDonald, H., Rosas-Arellano, M. P., Devereaux, P. J., Beyene, J., Sam, J., & Haynes, R. B. (2005). Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: A systematic review. JAMA, 293(10), 12231238.Google Scholar
Garicano, L., & Heaton, P. (2010). Information technology, organization, and productivity in the public sector: Evidence from police departments. Journal of Labor Economics, 28(1), 167201.Google Scholar
Goodall, M. (2007). Guidance for the Police Use of Body-Worn Video Devices. London: Home Office.Google Scholar
Goldfinch, S. (2007). Pessimism, computer failure, and information systems development in the public sector. Public Administration Review, 67(5), 917929.Google Scholar
Goolsbee, A., & Guryan, J. (2006). The impact of internet subsidies in public schools. The Review of Economics and Statistics, 88(2), 336347.Google Scholar
Groff, E. R., & McEwen, T. (2008). Identifying and Measuring the Effects of Information Technologies on Law Enforcement Agencies. Washington, DC: Office of Community Oriented Policing Services; Alexandria, VA: Institute for Law and Justice.Google Scholar
Harris, C. J. (2007). The police and soft technology: How information technology contributes to police decision making. In Byrne, J. M., & Rebovich, D. J. (eds.), The New Technology of Crime, Law and Social Control (pp. 153183). Monsey, NY: Criminal Justice Press.Google Scholar
Hunt, P., Saunders, J., & Hollywood, J. (2014). Evaluation of the Shreveport Predictive Policing Experiment. Santa Monica, CA: RAND Corporation.Google Scholar
Ioimo, R. E., & Aronson, J. E. (2003). The benefits of police field mobile computing realized by non-patrol sections of a police department. International Journal of Police Science & Management, 5(3), 195206.Google Scholar
Ioimo, R. E., & Aronson, J. E. (2004). Police field mobile computing: Applying the theory of task-technology fit. Police Quarterly, 7(4), 403428.Google Scholar
Jaitman, L. (2017). Evaluating Predictive Policing in Latin America. Presentation at the Center for Evidence-Based Crime Policy annual symposium. Arlington, Virginia.Google Scholar
Katz, C. M., Choate, D. E., Ready, J. R., & Nuño, L. (2014). Evaluating the Impact of Officer Worn Body Cameras in the Phoenix Police Department. Phoenix: Center for Violence Prevention & Community Safety, Arizona State University.Google Scholar
Katz, C. M., Kurtenbach, M., Choate, D. E., & White, M. D. (2015). Phoenix, Arizona, Smart Policing Initiative: Evaluating the Impact of Police Officer Body-Worn Cameras. Washington, DC: Bureau of Justice Assistance.Google Scholar
Kennedy, L., Caplan, J., & Piza, E. (2015). A Multi‐Jurisdictional Test of Risk Terrain Modeling and a Place‐Based Evaluation of Environmental Risk‐Based Patrol Deployment Strategies. Newark, NJ: Rutgers Center on Public Security, Rutgers University.Google Scholar
Koen, M. (2016). Technological Frames: Making Sense of Body-Worn Cameras in a Police Organization. PhD Dissertation, George Mason University.Google Scholar
Koper, C. S., Lum, C., & Hibdon, J. (2015b). The uses and impacts of mobile computing technology in hot spots policing. Evaluation Review, 39(6), 587624.Google Scholar
Koper, C. S., Lum, C., & Willis, J. J. (2014). Optimizing the use of technology in policing: results and implications from a multi-site study of the social, organizational, and behavioral aspects of implementing police technologies. Policing: A Journal of Policy and Practice, 8(2), 212221.Google Scholar
Koper, C. S., Lum, C., Willis, J. J., Happeny, S., Johnson, W. D., Nichols, J., Stoltz, M., Vovak, H., Wu, X., & Nagin, D. (2018). Evaluating the Crime Control and Cost-Benefit Effectiveness of License Plate Reader Technology. Report to the National Institute of Justice, US Department of Justice. Fairfax, VA: Center for Evidence-Based Crime Policy, George Mason University.Google Scholar
Koper, C. S., Lum, C., Willis, J. J., Woods, D. J., & Hibdon, J. (2015a). Realizing the Potential of Technology in Policing: A Multi-Site Study of the Social, Organizational, and Behavioral Aspects of Implementing Policing Technologies. Report to the National Institute of Justice. Fairfax, VA: Center for Evidence-Based Crime Policy, George Mason University and Police Executive Research Forum.Google Scholar
Koper, C. S., Moore, G. E., & Roth, J. A. (2002). Putting 100,000 Officers on the Street: A Survey-Based Assessment of the Federal Cops Program. Washington, DC: The Urban Institute.Google Scholar
Koper, C. S., & Roth, J. A. (2000). Putting 100,000 Officers on the Street: Progress as of 1998 and Preliminary Projections Through 2003. In Roth, J. A., Ryan, J. F. et al. (eds.). National Evaluation of the COPS Program – Title I of the 1994 Crime Act. Research Report (pp. 149178). Washington, DC: US Department of Justice.Google Scholar
Koper, C. S., Taylor, B. G., & Kubu, B. E. (2009). Law Enforcement Technology Needs Assessment: Future Technologies to Address the Operational Needs of Law Enforcement. Washington, DC: Police Executive Research Forum and the Lockheed Martin Corporation.Google Scholar
Koper, C. S., Taylor, B. G., & Woods, D. J. (2013). A randomized test of initial and residual deterrence from directed patrols and use of license plate readers at crime hot spots. Journal of Experimental Criminology, 9(2), 213244.Google Scholar
Kraemer, K. L., & Danziger, J. N. (1984). Computers and control in the work environment. Public Administration Review, 44(1), 3242.Google Scholar
Lee, G., & Perry, J. L. (2002). Are computers boosting productivity? A test of the paradox in state governments. Journal of Public Administration Research and Theory, 12(1), 77102.Google Scholar
Lehr, B., & Lichtenberg, F. (1999). Information technology and its impact on productivity: Firm-level evidence from government and private data sources, 1977–1993. Canadian Journal of Economics, 32(2), 335362.Google Scholar
Lu, Y. (2003). Getting away with the stolen vehicle: An investigation of journey-after-crime. The Professional Geographer, 55(4), 422433.Google Scholar
Lum, C. (2010). Technology and the Mythology of Progress in American Law Enforcement. Science Progress (Center for American Progress). Feb. 11. Retrieved from www.Scienceprogress.Org/2010/02/Police-Technology/.Google Scholar
Lum, C. (2013). Is crime analysis evidence-based? Translational Criminology, (Fall), 1214.Google Scholar
Lum, C., & Koper, C. S. (2017). Evidence-Based Policing: Translating Research into Practice. Oxford, UK: Oxford University Press.Google Scholar
Lum, C., Koper, C. S., Merola, L. M., Scherer, A., & Reioux, A. (2015). Existing and Ongoing Body Worn Camera Research: Knowledge Gaps and Opportunities. Report for the Laura and John Arnold Foundation. Fairfax, VA: Center for Evidence-Based Crime Policy, George Mason University.Google Scholar
Lum, C., Koper, C. S., & Willis, J. (2017). Understanding the limits of technology’s impact on police effectiveness. Police Quarterly, 20(2), 135163.Google Scholar
Lum, C., Koper, C. S., Willis, J., Happeny, S., Vovak, H., & Nichols, J. (2016c). The Rapid Diffusion of License Plate Readers in U.S. Law Enforcement Agencies: A National Survey . Report to the National Institute of Justice, US Department of Justice. Fairfax, VA: Center for Evidence-Based Crime Policy, George Mason University.Google Scholar
Lum, C., Koper, C. S., Willis, J., Happeny, S., Vovak, H., & Nichols, J. (2018). The rapid diffusion of license plate readers in US law enforcement agencies. Policing: An International Journal of Police Strategies and Management, DOI 10.1108/PIJPSM-04-2018-0054.Google Scholar
Lum, C., Merola, L., Willis (Hibdon), J., & Cave, B. (2010). License Plate Recognition Technology: Impact Evaluation and Community Assessment. Final Report to SPAWAR and the National Institute of Justice. Fairfax, VA: Center for Evidence-Based Crime Policy, George Mason University.Google Scholar
Lum, C., Stoltz, M., Koper, C. S., & Scherer, J. A. (2019, forthcoming). Research on body worn cameras: What we know, what we need to know. Criminology and Public Policy, 18(1).Google Scholar
Lum, C., Wellford, C., Scott, T., & Vovak, H. (2016a). Trajectories of U.S. Crime Clearance Rates. Report for the Laura and John Arnold Foundation. Fairfax, VA: Center for Evidence-Based Crime Policy, George Mason University.Google Scholar
Lum, C., Willis (Hibdon), J., Cave, B., Koper, C. S., & Merola, L. (2011). License plate reader (lpr) police patrols in crime hot spots: An experimental evaluation in two adjacent jurisdictions. Journal of Experimental Criminology, 7(4), 321345.Google Scholar
Manning, P. K. (1992). Technological dramas and the police: Statement and counterstatement in organizational analysis. Criminology, 30(3), 327346.Google Scholar
Manning, P. K. (2008). The Technology of Policing. New York, NY: NYU Press.Google Scholar
Maryland State Highway Authority. (2005). Evaluation of the License Plate Recognition System. Retrieved from the American Association of State Highway and Transportation Officials at Http://Ssom.Transportation.Org/Documents/Lpr_Report_Part3.PdfGoogle Scholar
Mastrofski, S. D., & Wadman, R. (1991). Personnel and agency performance measurement. In Garmire, B. L. (ed.), Local Government Police Management (pp. 363–397). Washington, DC: International City Management Association.Google Scholar
Mastrofski, S. D., & Willis, J. J. (2010). Police organization continuity and change: Into the twenty-first century. Crime and Justice, 39(1), 55144.Google Scholar
Merola, L. M., & Lum, C.. (2013). Predicting public support for the use of license plate recognition technology by police. Police Practice and Research: An International Journal, DOI: 10.1080/15614263.2013.814906.Google Scholar
Merola, L. M., Lum, C., Cave, B., & Hibdon, J. (2014). Community support for the use of license plate recognition by police. Policing: An International Journal of Police Strategies and Management, 37(1), 3051.Google Scholar
Mazerolle, L., Bennett, S., Manning, M., Davis, J., & Sargeant, E. (2013). Legitimacy in policing: A systematic review. Campbell Systematic Reviews, No. 1 (January).Google Scholar
Mazerolle, L., Rogan, D., Frank, J., Famega, C., & Eck, J. E. (2002). Managing citizen calls to the police: The impact of Baltimore’s 3‐1‐1 call system. Criminology & Public Policy, 2(1), 97124.Google Scholar
Milgrom, P., & Roberts, J. (1990). The economics of modern manufacturing: Technology, strategy, and organization. The American Economic Review, 80(3), 511528.Google Scholar
Mohler, G. O., Short, M. B., Malinowski, S., Johnson, M., Tita, G E., Bertozzi, A., & Brantingham, P. J. (2015). Randomized controlled field trials of predictive policing. Journal of the American Statistical Association, 110 (512), 13991411.Google Scholar
National Academies of Sciences, Engineering, and Medicine. (2017). Proactive Policing: Effects on Crime and Communities. Washington, DC: The National Academies Press. doi: https: doi.org/10.17226/24928.Google Scholar
Nunn, S. (1994). How capital technologies affect municipal service outcomes: The case of police mobile digital terminals and stolen vehicle recoveries. Journal of Policy Analysis and Management, 13(3), 539559.Google Scholar
Nunn, S., & Quinet, K. (2002). Evaluating the effects of information technology on problem-oriented-policing: If it doesn’t fit, must we quit? Evaluation Review, 26(1), 81108.Google Scholar
ODS Consulting. (2011). Body Worn Video Projects in Paisley and Aberdeen, Self Evaluation. Glasgow: ODS Consulting.Google Scholar
Ohio State Highway Patrol. (2005). Automatic Plate Reader Technology. Ohio Planning Services Section, Research and Development Unit.Google Scholar
Orlikowski, W. J. (1992). The duality of technology: Rethinking the concept of technology in organizations. Organization Science, 3(3), 398427.Google Scholar
Orlikowski, W. J., & Gash, D. C. (1994). Technological frames: Making sense of information technology in organizations. ACM Transactions on Information Systems (TOIS), 12(2), 174207.Google Scholar
O’Shea, T., & Nicholls, K. (2003). Police crime analysis: A survey of US police departments with 100 or more sworn personnel. Police Practice and Research, 4(3), 233250.Google Scholar
Owens, C., Mann, D., & Mckenna, R. (2014). The Essex BWV Trial: The Impact of BWV on Criminal Justice Outcomes of Domestic Abuse Incidents. London, United Kingdom: College of Policing.Google Scholar
Pa Consulting Group. (2003). Engaging Criminality – Denying Criminals Use of the Roads. London: Author.Google Scholar
Palys, T. S., Boyanowsky, E. O., & Dutton, D. G. (1984). Mobile data access terminals and their implications for policing. Journal of Social Issues, 40(3), 113127.Google Scholar
Patch, D. (2005). License Plate Scanners Lead to Recovery of Stolen Vehicles. Toledoblade.Com. Retrieved January 11, 2007, from Http://Toledoblade.Com/Apps/Pbcs.Dll/Article?Aid=/20050105/News11/501050412.Google Scholar
Paulsen, D. J. (2004). To map or not to map: Assessing the impact of crime maps on police officer perceptions of crime. International Journal of Police Science & Management, 6(4), 234246.Google Scholar
Ready, J. T., & Young, J. T. (2015). The impact of on-officer video cameras on police-citizen contacts: Findings from a controlled experiment in Mesa, AZ. Journal of Experimental Criminology, 11(3), 445458.Google Scholar
Reaves, B. A. (2010). Local Police Departments, 2007. Washington, DC: Bureau of Justice Statistics.Google Scholar
Robey, D., Boudreau, M.-C., & Rose, G. M. (2000). Information technology and organizational learning: A review and assessment of research. Accounting, Management and Information Technologies, 10(2), 125155.Google Scholar
Roberts, D. J., & Casanova, M. (2012). Automated License Plate Recognition (ALPR) Systems: Policy and Operational Guidance for Law Enforcement. Alexandria, VA: International Association of Chiefs of Police.Google Scholar
Rocheleau, B. (1993). Evaluating public sector information systems: Satisfaction versus impact. Evaluation and Program Planning, 16(2), 119129.Google Scholar
Roman, J. K., Reid, S., Reid, J., Chalfin, A., Adams, W., & Knight, C. (2008). The DNA Field Experiment: Cost-Effectiveness Analysis of the Use of DNA in the Investigation of High-Volume Crimes. Washington, DC: The Urban Institute.Google Scholar
Roth, J. A., Ryan, J. F., Gaffigan, S. J., Koper, C. S., Moore, M. H., Roehl, J. A., Johnson, C. C. et al. (2000). National Evaluation of the Cops Program Title I of the 1994 Crime Act. Washington, DC: National Institute of Justice.Google Scholar
Sanders, C. B., & Henderson, S. (2013). Police “empires” and information technologies: Uncovering material and organisational barriers to information sharing in Canadian police services. Policing and Society, 23(2), 243260.Google Scholar
Sanders, C. B., Weston, C., & Schott, N. (2015). Police innovations, “secret squirrels” and accountability: Empirically studying intelligence-led policing in Canada. British Journal of Criminology, 55(4), 711729.Google Scholar
Santos, R. Boba. (2014). The effectiveness of crime analysis for crime reduction: Cure or diagnosis? Journal of Contemporary Criminal Justice, 30(2), 147168.Google Scholar
Sherman, L. W., & Eck, J. E. (2002). Policing for crime prevention. In Sherman, L. W., Farrington, D. P., Welsh, B. C., & MacKenzie, D. L., Evidence-Based Crime Prevention (pp. 295329). London, UK: Routledge.Google Scholar
Sparrow, M. K., Moore, M. H., & Kennedy, D. M. (1990). Beyond 9–1-1: A New Era for Policing. New York: Basic Books.Google Scholar
Stiroh, K. J. (2002). Information technology and the US productivity revival: What do the industry data say? The American Economic Review, 92(5), 15591576.Google Scholar
Taylor, B., & Boba, R. (2011: updated in 2013). The Integration of Crime Analysis into Patrol Work: A Guidebook. Washington, DC: Office of Community Oriented Policing Services.Google Scholar
Taylor, B., Koper, C. S., & Woods, D. (2011a). A randomized controlled trial of different policing strategies at hot spots of violent crime. Journal of Experimental Criminology, 7(2), 149181.Google Scholar
Taylor, B., Koper, C. S., & Woods, D. (2011b). Combating Auto Theft in Arizona: A Randomized Experiment with License Plate Recognition Technology. Final Report to the National Institute of Justice, US Department of Justice. Washington, DC: Police Executive Research Forum.Google Scholar
Taylor, B., Koper, C. S., & Woods, D. (2012). Combating vehicle theft in arizona: A randomized experiment with license plate recognition technology. Criminal Justice Review, 37(1), 2450.Google Scholar
Triplett, J. E. (1999). The Solow productivity paradox: What do computers do to productivity? Canadian Journal of Economics, 32(2), 309334.Google Scholar
Vovak, H. (2016). Examining the Relationship between Crime Rates and Clearance Rates Using Dual Trajectory Analysis. PhD Dissertation, George Mason University.Google Scholar
Zaworski, M. J. (2004). Assessing an Automated, Information Sharing Technology in the Post “9–11” Era – Do Local Law Enforcement Officers Think It Meets Their Needs? PhD Dissertation, Florida International University.Google Scholar

References

Bayley, D. H. (1994). Police for the Future. New York: Oxford University Press.Google Scholar
Bayley, D. H., & Nixon, C. (2010). The Changing Environment for Policing, 1985–2008. Cambridge, MA: Harvard Kennedy School Program in Criminal Justice Policy and Management.Google Scholar
Blumstein, A., and Wallman, J. (2000). The recent rise and fall of American violence. In Blumstein, A., & Wallman, J. (eds.), The Crime Drop in America. New York: Cambridge University Press.Google Scholar
Braga, A. A., Papachristos, A. V., & Hureau, D. M. (2014). The effects of hot spots policing on crime: An updated systematic review and meta-analysis. Justice Quarterly, 31, 633663.Google Scholar
Braga, A., Papachristos, A., & Hureau, D. (2012). Hot spots policing effects on crime. Campbell Systematic Reviews, 8, 196.Google Scholar
Chappell, A. T., & Gibson, S. A. (2009). Community policing and homeland security policing: Friend or foe?. Criminal Justice Policy Review, 20, 326343.Google Scholar
Eck, J., & Rosenbaum, D. (1994). The new police order: Effectiveness, equity, and efficiency in community policing. In Rosenbaum, D. (ed.), The Challenge of Community Policing: Testing the Promises. Thousand Oaks, CA: Sage Publications.Google Scholar
Elmore, R. (1997). The paradox of innovation in education: Cycles of reform and the resilience of teaching. In Altshuler, A., & Behn, R. (eds.), Innovations in American Government: Challenges, Opportunities, and Dilemmas. Washington, DC: Brookings Institution Press.Google Scholar
Goldstein, H. (1990). Problem-Oriented Policing. Philadelphia, PA: Temple University Press.Google Scholar
Gottfredson, M. R., & Hirschi, T. (1990). A General Theory of Crime. Stanford, CA: Stanford University Press.Google Scholar
Jackman, T. (2016). U.S. police chiefs group apologizes for “historical mistreatment” of minorities. Washington Post, October 17. Retrieved January 2017 from www.washingtonpost.com/news/true-crime/wp/2016/10/17/head-of-u-s-policechiefs-apologizes-for-historic-mistreatment-of-minorities/?utm_term=.80737fda0070.Google Scholar
Lum, C., & Koper, C. S. (2017). Evidence-Based Policing: Translating Research into Practice. Oxford, UK: Oxford University Press.Google Scholar
MacQueen, S., & Bradford, B. (2015). Enhancing public trust and police legitimacy during road traffic encounters: Results from randomized controlled trial in Scotland. Journal of Experimental Criminology, 11, 419443.Google Scholar
Maguire, E. (2014). Police organizations and the iron cage of rationality. In Reisig, M., & Kane, R. (eds.), Oxford Handbook on Police and Policing. New York: Oxford University Press.Google Scholar
Mazerolle, L., Antrobus, E., Bennett, S., & Tyler, T. (2013). Shaping citizen perceptions of police legitimacy: A randomized field trial of procedural justice. Criminology, 51, 3364.Google Scholar
McGarrell, E. F., Freilich, J. D., & Chermak, S. M. (2007). Intelligence-led policing as a framework for responding to terrorism. Journal of Contemporary Criminal Justice, 23, 142158.Google Scholar
Moore, M., Sparrow, M., & Spelman, W. (1997). Innovations in policing: From production lines to job shops. In Altshuler, A., & Behn, R. (eds.), Innovations in American Government: Challenges, Opportunities, and Dilemmas. Washington, DC: Brookings Institution Press.Google Scholar
Nagin, D., & Telep, C. (2017). Procedural justice and legal compliance. Annual Review of Law and Social Science, 13, 528.Google Scholar
Neyroud, P., & Weisburd, D. (2014). Transforming the police through science: Some new thoughts on the controversy and challenge of translation. Translational Criminology, Spring, 1618.Google Scholar
Pate, T., & Skogan, W. (1985). Coordinated community policing: The Newark experience. Technical Report. Washington, DC: Police Foundation.Google Scholar
President’s Task Force on 21st Century Policing (2015). Final report of the President’s Task Force on 21st Century Policing. Washington, DC: Office of Community Oriented Policing Services, U.S. Department of Justice.Google Scholar
Ratcliffe, J. 2016. Intelligence-Led Policing. 2nd ed. Portland, OR: Willan.Google Scholar
Sahin, N., Braga, A., Apel, R., & Brunson, R. (2017). The impact of procedurally just policing on citizen perceptions of police during traffic stops: The Adana randomized controlled trial. Journal of Quantitative Criminology, 33, 701726.Google Scholar
Sherman, L. W. (2013). The rise of evidence-based policing: Targeting, testing, and tracking. Crime and Justice, 42, 377451.Google Scholar
Sherman, L. W., & Weisburd, D. (1995). General deterrent effects of police patrol in crime “hot spots”: A randomized, controlled trial. Justice Quarterly, 12, 625648.Google Scholar
Sherman, L. W., Williams, S., Ariel, B., Strang, L. R., Wain, N., Slothower, M., & Norton, A. (2014). An integrated theory of hot spots patrol strategy: implementing prevention by scaling up and feeding back. Journal of Contemporary Criminal Justice, 30, 95122.Google Scholar
Skogan, W., & Frydl, K. (2004). Fairness and Effectiveness in Policing: The Evidence. Washington, DC: The National Academies Press.Google Scholar
Skolnick, J. H. (2007). Racial profiling – Then and now. Criminology & Public Policy, 6, 6570.CrossRefGoogle Scholar
Sparrow, M. K., Moore, M. H., & Kennedy, D. M. (1990). Beyond 911: A New Era for Policing. New York: Basic Books.Google Scholar
Tyler, T. (2017). Procedural justice and policing: A rush to judgment? Annual Review of Law and Social Science, 13, 2953.Google Scholar
Tyler, T. R., Jackson, J., & Mentovich, A. (2015). The consequences of being an object of suspicion: Potential pitfalls of proactive police contact. Journal of Empirical Legal Studies, 12, 602636.Google Scholar
Walker, S. (1992). The Police in America: An Introduction. 2nd ed. New York: McGraw-Hill.Google Scholar
Weisburd, D., & Eck, J. (2004). What can police do to reduce crime, disorder, and fear? Annals of the American Academy of Political and Social Science, 593, 4265.Google Scholar
Weisburd, D., & Majmundar, M. (eds.). (2018). Proactive Policing: Effects on Crime and Communities. Washington, DC: The National Academies Press.Google Scholar
Weisburd, D., Hinkle, J., Braga, A., & Wooditch, A. (2015). Understanding the mechanisms underlying broken windows policing. Journal of Research in Crime and Delinquency, 52, 589608.Google Scholar
Weisburd, D., Lum, C. M., & Petrosino, A. (2001). Does research design affect study outcomes in criminal justice? The Annals of the American Academy of Political and Social Science, 578, 5070.Google Scholar
Weisburd, D., Wyckoff, L. A., Ready, J., Eck, J. E., Hinkle, J. C., & Gajewski, F. (2004). Does crime just move around the corner? A study of displacement and diffusion in Jersey City, NJ. US Department of Justice National Institute of Justice.Google Scholar
Wycoff, M., & Skogan, W. (1986). Storefront police offices: The Houston field test. In Rosenbaum, D. (ed.), Community Crime Prevention: Does It Work? Thousand Oaks, CA: Sage Publications.Google Scholar

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