Skip to main content
Log in

From Poisson to the present: Applying operations research to problems of crime and justice

  • Published:
Journal of Quantitative Criminology Aims and scope Submit manuscript

Abstract

In the 1830s Siméon-Denis Poisson developed the distribution that bears his name, basing it on the binomial distribution. He used it to show how the inherent variance in jury decisions affected the inferences that could be made about the probability of conviction in French courts. In recent years there have been a number of examples where researchers have either ignored or forgotten this inherent variance, and how operations research, in particular mathematical modeling, can be used to incorporate this variance in analyses. These are described in this paper, as well as other contributions made by operations research to the study of crime and criminal justice.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Ahn, C. W., Blumstein, A., and Schervish, M. (1990). Estimation of arrest careers using hierarchical stochastic models.J. Quant. Criminol. 6: 131–152.

    Article  Google Scholar 

  • Avi-Itzhak, B., and Shinnar, R. (1973). Quantitative models in crime control.J. Crim. Just. 1(3): 185–217.

    Google Scholar 

  • Barlow, R., and Proschan, F. (1975).Statistical Theory of Reliability and Life Testing: Probability Models, Holt, Rinehart and Winston, New York.

    Google Scholar 

  • Barnett, A. (1978). Crime and capital punishment: Some recent studies.J. Crim. Just. 6: 291–303.

    Google Scholar 

  • Barnett, A. (1981a). The deterrent effect of capital punishment: A test of some recent studies.Operat. Res. 29: 346–370.

    Google Scholar 

  • Barnett, A. (1981b). Further standards of accountability in deterrence research. In Fox, J. A. (ed.),Methods in Quantitative Criminology, Academic Press, New York, pp. 127–145.

    Google Scholar 

  • Barnett, A. (1982). Learning to live with homicide.J. Crim. Just. 10(1): 69–72.

    Google Scholar 

  • Barnett, A. (1983a). The capital punishment controversy: Part I.Interfaces 13(3): 24–28.

    Google Scholar 

  • Barnett, A. (1983b). The capital punishment controversy: Part II.Interfaces 13(5): 35–39.

    Google Scholar 

  • Barnett, A. (1987). Prison populations: A projection model.Operat. Res. 35(1): 18–34.

    Google Scholar 

  • Barnett, A., and Lofaso, A. J. (1985). Selective incapacitation and the Philadelphia Cohort data.J. Quant. Criminol. (1): 3–36.

    Article  Google Scholar 

  • Barnett, A., and Lofaso, A. J. (1986). On the optimal allocation of prison space. In Swersey, A. J. (ed.),Delivery of Urban Services, TIMS Series in the Management Sciences, Vol. 22, Elsevier North-Holland, Amsterdam.

    Google Scholar 

  • Barnett, A., and Schwartz, E. (1989). Urban homicide: Still the same.J. Quant. Criminol. 5: 83–100.

    Article  Google Scholar 

  • Barnett, A., Kleitman, D., and Larson, R. C. (1975). On urban homicide: A statistical analysis.J. Crim. Just. 3: 85–110.

    Google Scholar 

  • Barnett, A., Essenfeld, E., and Kleitman, D. (1980). Urban homicide: Some recent developments.J. Crim. Just. 8: 379–385.

    Google Scholar 

  • Barnett, A., Blumstein, A., and Farrington, D. (1987). Probabilistic models of youthful criminal careers.Criminology 25: 83–108.

    Article  Google Scholar 

  • Barnett, A., Blumstein, A., and Farrington, D. (1989). A prospective test of a criminal career model.Criminology 27: 373–385.

    Article  Google Scholar 

  • Barnett, A., Blumstein, A., Cohen, J., and Farrington, D. (1992). Not all criminal career models are equally valid.Criminology 30: 133–140.

    Article  Google Scholar 

  • Barr, R., and Pease, K. (1990). Crime placement, displacement, and deflection. In Tonry, N., and Morris, M. (eds.),Crime and Justice: A Review of Research, Vol. 12, University of Chicago Press, Chicago.

    Google Scholar 

  • Barton, R. R., and Turnbull, B. (1979). Evaluation of recidivism data: Use of failure rate regression models.Evaluat. Q. 3: 629–641.

    Google Scholar 

  • Barton, R. R., and Turnbull, B. (1981). A failure rate regression model for the study of recidivism. In Fox, J. A. (ed.),Models in Quantitative Criminology, Academic Press, New York, pp. 81–101.

    Google Scholar 

  • Bevaja, A., Batta, R., Caulkins, J. P., and Karwan, M. H. (1993). Modeling the response of illicit drug markets to local enforcement.J. Socio-Econ. Plan. Sci. 27(2):73–89.

    Google Scholar 

  • Becker, G. S. (1967). Crime and punishment: An economic approach.J. Pol. Econ. 78: 526–536.

    Google Scholar 

  • Belkin, J., Blumstein, A., Glass, W., and Lettre, M. (1972). JUSSIM, an interactive computer program and its uses in criminal justice planning. In Cooper, G. (ed.),Proceedings of the International Symposium on Criminal Justice Information and Statistics Systems, Project SEARCH, Sacramento, CA, pp. 467–477.

  • Belkin, J., Blumstein, A., and Glass, W. (1973). Recidivism as a feedback process: An analytical model and empirical validation.J. Crim. Jus. 1: 7–26.

    Google Scholar 

  • Berecochea, J. E., Himelson, A. N., and Miller, D. E. (1972). The risk of failure during the early parole period: A methodological note.J. Crim. Law Criminol. Police Sci. 63(1): 93–97.

    Google Scholar 

  • Berk, R. A., Rauma, D., Messinger, S. L., and Cooley, T. F. (1981). A test of the stability of punishment hypothesis: The case of California, 1851–1970.Am. Sociol. Rev. 45: 805–829.

    Google Scholar 

  • Berk, R. A., Messinger, S. L., Rauma, D., and Berecochea, J. E. (1983). Prisons as selfregulating systems: A comparison of historical patterns in California for male and female offenders.Law Soc. Rev. 17(4): 547–586.

    Google Scholar 

  • Beyleveld, D. (1982). Ehrlich's analysis of deterrence.Br. J. Criminol. 22: 101–123.

    Google Scholar 

  • Bloch, A. (1977)Murphy's Law and Other Reasons Why Things Go Wrong, Price/Stern/Sloan, Los Angeles.

    Google Scholar 

  • Block, C. R. (1989).Spatial and Temporal Analysis of Crime: Users Manual and Technical Manual, Illinois Criminal Justice Information Authority, Chicago.

    Google Scholar 

  • Block, C. R., and van der Werff, C. (1991).Initiation and Continuation of a Criminal Career: Who Are the Most Active and Dangerous Offenders in the Netherlands? Ministry of Justice, WODC, The Hague.

    Google Scholar 

  • Block, C. R., Dabdoub, M., and Fregly, S. (eds.). (1995).Crime Analysis Through Computer Mapping, Police Executive Research Forum, Washington, DC.

    Google Scholar 

  • Blumstein, A. (1983). Selective incapacitation as a means of crime control.Am. Behav. Sci. 27: 87–108.

    Google Scholar 

  • Blumstein, A. (1988). Prison populations: A system out of control? In Morris, N., and Tonry, M. (eds.),Crime and Justice: An Annual Review of Research, Vol. 10, University of Chicago Press, Chicago, pp. 231–266.

    Google Scholar 

  • Blumstein, A., and Cohen, J. (1973). A theory of the stability of punishment.J. Crim. Law Criminol. Police Sci. 63(2): 198–207.

    Google Scholar 

  • Blumstein, A. and Cohen, J. (1979). Estimating of individual crime rates from arrest records.J. Crim. Law Criminol. 70(4): 561–585.

    Google Scholar 

  • Blumstein, A., and Cohen, J. (1987). Characterizing criminal careers.Science 238(4818): 985–991.

    Google Scholar 

  • Blumstein, A., and Larson, R. C. (1967). A systems approach to the study of crime and criminal justice. In Morse, P. M., and Bacon, L. (eds.),Operations Research for Public Systems, MIT Press, Cambridge, MA, pp. 159–180.

    Google Scholar 

  • Blumstein, A., and Larson, R. C. (1969). Models of a total criminal justice system.Operat. Res. 17(2): 219–232.

    Google Scholar 

  • Blumstein, A., and Larson, R. C. (1971). Problems in modeling and measuring recidivism.J. Res. Crime Delinq. 8: 124–132.

    Google Scholar 

  • Blumstein, A., and Moitra, S. (1979). An analysis of the time series of the imprisonment rate in the states of the United States: A further test of the stability of punishment hypothesis.J. Crim. Law Criminol. 70(3): 376–390.

    Google Scholar 

  • Blumstein, A., and Moitra, S. (1980). The identification of ‘career criminals’ from ‘chronic offenders’ in a cohort.Law Policy Q 2: 321–334.

    Google Scholar 

  • Blumstein, A., and Nagin, D. (1978). On the optimum use of incarceration for crime control.Operat. Res. 26(3): 381–403. [Reprinted (with modifications) in Fox (1981b), pp. 39–59].

    Google Scholar 

  • Blumstein, A., Cohen, J., and Nagin, D. (1976). The dynamics of a homeostatic punishment process.J. Crim. Law Criminol. 67(3): 317–334.

    Google Scholar 

  • Blumstein, A., Cohen, J., and Nagin, D. (1978).Deterrence and Incapacitation: Estimating the Effects of Criminal Sanctions on Crime Rates, National Academy of Sciences, Washington, DC.

    Google Scholar 

  • Blumstein, A., Cohen, J., and Miller, H. (1980). Demographically disaggregated projections of prison populations.J. Crim. Just. 8(1): 1–25.

    Google Scholar 

  • Blumstein, A., Cohen, J., Moitra, S., and Nagin, D. (1981). On testing the stability of punishment hypothesis: A reply.J. Crim. Law Criminol. 72(4): 1799–1808.

    Google Scholar 

  • Blumstein, A., Cohen, J., and Hsieh, P. (1982).The Durations of Adult Criminal Careers, Final Report to the National Institute of Justice, Carnegie-Mellon University, Pittsburgh, PA.

    Google Scholar 

  • Blumstein, A., Farrington, D. P., and Moitra, S. (1985). Delinquency careers: Innocents, desisters, and persisters. In Tonry, M., and Morris, N. (eds.),Crime and Justice Vol. 6, University of Chicago Press, Chicago.

    Google Scholar 

  • Blumstein, A., Cohen, J., Roth, J. A., and Visher, C. A. (eds.). (1986).Criminal Careers and Career Criminals, Vols. I and II, National Academy Press, Washington, DC.

    Google Scholar 

  • Blumstein, A., Cohen, J., and Farrington, D. P. (1988a). Criminal career research: Its value for criminology.Criminology 26(1):1–35.

    Google Scholar 

  • Blumstein, A., Cohen, J., and Farrington, D. P. (1988b). Criminal career research: Further clarifications.Criminology 26(1): 57–74.

    Google Scholar 

  • Blumstein, A., Cohen, J., Das, S., and Moitra, S. D., (1988c). Specialization and seriousness during adult criminal careers.J. Quant. Criminol. 4: 303–345.

    Google Scholar 

  • Blumstein, A., Canela-Cacho, J. A., and Cohen, J. (1993). Filtered sampling from populations with heterogeneous event frequencies.Manage. Sci. 39(7): 886–899.

    Google Scholar 

  • Bowers, W. J., and Pierce, G. L. (1975). The illusion of deterrence in Isaac Ehrlich's research on capital punishment.Yale Law J. 85: 187–208.

    Google Scholar 

  • Brantingham, P., and Brantingham, P. (1984).Patterns in Crime, Macmillan, New York.

    Google Scholar 

  • Brantingham, P. J., Dyreson, D. A., and Brantingham, P. L. (1976). Crime seen through a cone of resolution.Am. Behav. Sci. 20: 261–273.

    Google Scholar 

  • Broadhurst, R. R., and Maller, R. (1991). Estimating the numbers of prison terms in criminal careers from the one-step probabilities of recidivism.J. Quant. Criminol. 7: 275–290.

    Article  Google Scholar 

  • Broadhurst, R. R., Maller, R., Maller, M., and Duffecy, J. (1988). Aboriginal and non-aboriginal recidivism in Western Australia: A failure-rate analysis.J. Res. Crime and Delinq. 25: 83–108.

    Google Scholar 

  • Brounstein, S. H., and Kamrass, M. (1976).Operations Research in Law Enforcement, Justice, and Societal Security, Lexington Books, Lexington MA.

    Google Scholar 

  • Capone, D., and Nichols, W. J. (1976). Urban structure and criminal mobility.Am. Behav. Sci. 20: 199–213.

    Google Scholar 

  • Carr-Hill, G. A., and Carr-Hill, R. A. (1972). Reconviction as a process.Br. J. Criminol. 12: 35–43.

    Google Scholar 

  • Cassidy, R. G. (1985). Modelling a criminal justice system. In Farrington, D. P., and Tarling, R. (eds.),Prediction in Criminology, State University of New York Press, Albany, pp. 193–207.

    Google Scholar 

  • Caulkins, J. P. (1993a). Local drug markets' response to focused police enforcement.Operat. Res. 41(5): 848–863.

    Google Scholar 

  • Caulkins, J. P. (1993b). Zero tolerance: Could it increase, the consumption of illegal drugs.Manage. Sci. 39(4): 458–476.

    Google Scholar 

  • Caulkins, J. P. (1994).Developing Price Series for Cocaine, Report MR-317-DPRC, Rand Corp., Santa Monica, CA.

    Google Scholar 

  • Caulkins, J. P. (1995). Domestic geographic variation in illicit drug prices.J. Urban Econ. 37: 38–56.

    Article  Google Scholar 

  • Caulkins, J. P., and Padman, R. (1993). Quantity discounts and quality premia for illicit drugs.J. Am. Stat. Assoc. 88(423): 748–757.

    Google Scholar 

  • Chaiken, J. M., and Chaiken, M. R. (1982).Varieties of Criminal Behavior, Report R-2814-NIJ, Rand Corp., Santa Monica, CA.

    Google Scholar 

  • Chaiken, J., Crabill, T., Holliday, L., Jaquette, D., Lawless, M., and Quade, E. (1975).Criminal Justice Models: An Overview, Report R-1859-DOJ, Rand Corp., Santa Monica, CA.

    Google Scholar 

  • Chevalier, L. (1973).Labbring Classes and Dangerous Classes in, Paris During the First Half of the Nineteenth Century, Princeton University Press, Princeton, NJ [Translation (by F. Jellinek) ofClasses Laborieuses et Classes Dangereuses à Paris Pendant la Première Moitié du XIX Siècle, Librairie Plon, Paris, France, 1958.]

    Google Scholar 

  • Christensen, R. (1967). Projected percentage of U.S. population with criminal arrest and conviction records.Science and Technology Task Force Report, Appendix J, pp. 216–228.

  • Cohen, J. (1978). The incapacitative effect of imprisonment: A critical review of the literature. In Blumstein, A., Cohen, J., and Nagin, D. (eds.),Deterrence and Incapacitation: Estimating the Effects of Criminal Sanctions on Crime Rates, National Academy of Sciences, Washington, DC, pp. 187–243.

    Google Scholar 

  • Cohen, J. (1983). Incapacitation as a strategy for crime control: Possibilities and pitfalls. In Tonry, M., and Morris, N. (eds.),Crime and Justice, Vol. 5, University of Chicago Press, Chicago, pp. 1–84.

    Google Scholar 

  • Cohn, E. G., and Farrington, D. P. (1990). Differences between British and American criminology: An analysis of citations.Br. J. Criminol. 30: 467–482.

    Google Scholar 

  • Collins, M. F., and Wilson, R. M. (1990). Automobile theft: Estimating the size of the criminal population.J. Quant. Criminol. 6(4): 395–409.

    Article  Google Scholar 

  • Copas, J. B., and Tarling, R. (1986). Some methodological issues in making predictions. In Blumstein, A.,et al., (eds.),Criminal Careers and Career Criminals, Vol. II, National Academy Press, Washington, DC, pp. 291–313.

    Google Scholar 

  • Copas, J. B., and Tarling, R. (1988). Stochastic models for analyzing criminal careers.J. Quant. Criminol. 4: 173–186.

    Article  Google Scholar 

  • Cornish, D. B., and Clarke, R. V. (1986).The Reasoning Criminal, Springer-Verlag, New York.

    Google Scholar 

  • Cox, D. R., and Oakes, D. (1984).Analysis of Survival Data, Chapman and Hall, London, England.

    Google Scholar 

  • Daston, L. (1988).Classical Probability in the Enlightenment, Princeton University Press, Princeton, NJ.

    Google Scholar 

  • DeGroot, M. H., Fienberg, S. E., and Kadane, J. B. (eds.) (1986).Statistics and the Law, Wiley, New York.

    Google Scholar 

  • Eck, J. E., and Riccio, L. J. (1979). Relationship between reported crime rates and victimization survey results: An empirical and analytical study.J. Crim. Just. 7: 293–308.

    Google Scholar 

  • Ehrlich, I. (1975). The deterrent effect of capital punishment: A question of life and death.Am. Econ. Rev. 65: 397–417.

    Google Scholar 

  • Ellerman, R., Sullo, P., and Tien, J. M. (1992). An alternative approach to modeling recidivism using quantile residual life functions.Opera. Res. 40: 485–504.

    Google Scholar 

  • Everingham, S. S., and Rydell, C. P. (1994).Modeling the Demand for Cocaine, Report MR-332-ONDCP/A/DPRC; Rand Corp. Santa Monica, CA.

    Google Scholar 

  • Farrington, D. P., Homel, R., Junger, M., and Wikstrom, P.-O. (1996). Quantitative criminology in the English-speaking world outside North America.J. Quant. Criminol. (to appear).

  • Farrington, D. P., and Hawkins, J. D. (1991). Predicting participation, early onset and later persistence in officially recorded offending.Crim. Behav. Ment. Health 1: 1–33.

    Google Scholar 

  • Farrington, D. P., and Tarling, R. (eds.) (1995).Prediction in Criminology, State University of New York Press, Albany.

    Google Scholar 

  • Felson, M. (1994).Crime and Everyday Life: Insights and Implications for Society, Pine Forge Press, Thousand Oaks, CA.

    Google Scholar 

  • Finkelstein, M. O. (1978).Quantitative Methods in Law, Free Press, New York.

    Google Scholar 

  • Fisher, F. M., and Nagin, D. (1978). On the feasibility of identifying the crime function in a simultaneous model of crime rates and sanction levels. In Blumstein, A.,et al. (eds.),Deterrence and Incapacitation: Estimating the Effects of Criminal Sanctions on Crime Rates, National Academy of Sciences, Washigton, DC, pp. 361–399.

    Google Scholar 

  • Fox, J. A. (1978).Forecasting Crime Data, D. C. Heath, Lexington, MA.

    Google Scholar 

  • Fox, J. A. (ed.) (1981a).Methods in Quantitative Criminology, Academic Press, New York.

    Google Scholar 

  • Fox, J. A. (ed.) (1981b).Models in Quantitative Criminology, Academic Press, New York.

    Google Scholar 

  • Gerchak, Y., and Kubat, P. (1986). Patterns and dynamics of population heterogeneity in mixtures models.Quality Quant. 120: 285–291.

    Google Scholar 

  • Gigerenzer, G., Zeno, S., Porter, T., Daston, L., Beatty, J., and Kruger, L. (1989).The Empire of Chance, Cambridge University Press, Cambridge, England.

    Google Scholar 

  • Gottfredson, M. R., and Gottfredson, D. M. (1987).Decision Making in Criminal Justice: Toward the Rational Exercise of Discretion, 2nd ed., Plenum Press, New York.

    Google Scholar 

  • Gottfredson, M., and Hirschi, T. (1986). The true value of lambda would appear to be zero: An essay on career criminals, criminal careers, selective incapacitation, cohort studies, and related topics.Criminology 24 (2): 213–234.

    Article  Google Scholar 

  • Gottfredson, M., and Hirschi, T. (1987). The methodological adequacy of longitudinal research on crime.Criminology 25(4): 581–614.

    Google Scholar 

  • Gottfredson, M., and Hirschi, T. (1988). Science, public policy, and the career paradigm.Criminology 26(1): 37–56.

    Article  Google Scholar 

  • Gottfredson, M., and Hirschi, T. (1989). A propensity-event theory of crime. In Laufer, W. S., and Adler, F., (eds.),Advances in Criminological Theory, Transaction, New Brunswick, NJ.

    Google Scholar 

  • Gottfredson, M., and Hirschi, T. (1990).A General Theory of Crime, Stamford University Press, Stanford, CA.

    Google Scholar 

  • Gottfredson, S. D., and Gottfredson, D. M. (1986). Accuracy of prediction models. In Blumstein, A., et al. (eds.),Criminal Careers and Career Criminals, Vol. II National Academy Press, Washington, DC, pp. 212–290.

    Google Scholar 

  • Greenberg, D. F. (1975). The incapacitative effect of imprisonment: Some estimates.Law Society Rev. 9(4): 541–580.

    Google Scholar 

  • Greenberg, D. F. (1977). The dynamics of oscillatory punishment processes.J. Crim. Law Criminol. Police Sci 68(4): 643–651.

    Google Scholar 

  • Greenberg, D. F. (1978). Recidivism as radioactive decay.J. Res. Crime Delinq. 24: 124–125.

    Google Scholar 

  • Greenberg, D. F. (1979).Mathematical Criminology, Rutgers University Press, New Brunswick, NJ.

    Google Scholar 

  • Greenberg, D. F. (1991). Modeling criminal careers.Criminology 29(1): 17–46.

    Article  Google Scholar 

  • Greenberg, D. F. (1992). Comparing criminal career models.Criminology 30(1): 141–147.

    Article  Google Scholar 

  • Greene, M. A. (1984). Estimating the size of the criminal population using an open population approach.Proc. Am. Stat. Assoc., Suv. Res Methods Sect. 8–13.

  • Greene, M. A., and Stollmack, S. (1981). Estimating the number of criminals. In Fox, J. A. (ed.),Models in Quantitative Criminology, Academic Press, New York, pp. 1–24.

    Google Scholar 

  • Greenwood, P. W., with Abrahamse, A. (1982).Selective Incapacitation, Report R-2815-NIJ, Rand Corp., Santa Monica, CA.

    Google Scholar 

  • Greenwood, P., and Turner, S. (1987),Selective Incapacitation Revisited: Why the High-Rate Offenders Are Hard to Predict, Report R-3397-NIJ, Rand Corp., Santa Monica, CA.

    Google Scholar 

  • Gruenwald, P. J., and West, B. (1989). Survival models of recidivism among juvenile delinquents.J. Quant. Criminol. 5: 215–229.

    Google Scholar 

  • Hacking, I. (1990).The Taming of Chance, Cambridge University Press, Cambridge, England.

    Google Scholar 

  • Harada, Y. (1991). Testing the “stable criminality” hypothesis with Japanese data. Paper delivered at the 50th Meeting of the American Society of Criminology, San Francisco, CA, Nov. 22.

  • Harries, K. D. (1980).Crime and the Environment, Charles C Thomas, Springfield, IL.

    Google Scholar 

  • Harries, K. D. (1990).Geographic Factors in Policing, Police Foundation, Washington, DC.

    Google Scholar 

  • Harris, C. M., and Stollmack, S. (1976). Failure-rate analysis in correctional systems. In Brounstein, S. H., and Kamrass, M. (eds.),Operations Research in Law Enforcement, Justice, and Societal Security, Lexington Books, Lexington, MA, pp. 143–153.

    Google Scholar 

  • Harris, C. M., Kaylan, A. R., and Maltz, M. D. (1981). Recent advances in the statistics of recidivism measurement. In Fox, J. A. (ed.),Models in Quantitative Criminology, Academic Press, New York, pp. 61–79.

    Google Scholar 

  • Hodges, J. S. (1991). Six (or so) things you can do with a bad model.Operat. Res. 39: 355–365.

    Google Scholar 

  • Hoffman, P. B., and Adelberg, S. (1980). The salient factor score: A nontechnical overview.Fed. Probat. 44: 44–52.

    Google Scholar 

  • Hoffman, P. B., and Beck, J. L. (1974). Parole decision-making: A salient factor score.J. Crim. Just. 2: 195–206.

    Google Scholar 

  • Hser, Y.-I., Anglin, M. D., Wickens, T. D., Brecht, M.-L. and Homer, J. (1992).Techniques for the Estimation of Illicit Drug-Use Prevalence, Research Report NCJ 133786, National Institute of Justice, Washington, DC May.

    Google Scholar 

  • Hwang, S.-A. (1990). Modeling the suppression effect of correctional programs on juvenile delinquency.J. Quant. Criminol 6: 377–393.

    Article  Google Scholar 

  • Illinois Criminal Justice Information Authority (1991). Despite improvements, many rap sheets still missing disposition information.The Compiler, Spring Issue, ICJIA, Chicago.

    Google Scholar 

  • Institute for Law and Justice (1991)CJSSIM: Criminal Justice System Simulation Model. Software and User Manual, Institute for Law and Justice, Alexandria, VA.

    Google Scholar 

  • Jefferys, W. H., and Berger, J. O. (1992). Ockham's razor and Bayesian analysis.Am. Sci. 80: 64–72.

    Google Scholar 

  • Johnson, B. D., Goldstein, P. J., Preble, E., Schmeidler, J., Lipton, D. S., Spunt, B., and Miller, T. (1985).Taking Care of Business: The Economics of Crime by Heroin Abusers, Lexington Books, Lexington, MA.

    Google Scholar 

  • Kalbfleisch, J. D., and Prentice, R. L. (1980).The Statistical Analysis of Failure Time Data, Wiley, New York.

    Google Scholar 

  • Klein, L. R., Forst, B., and Filatov, V. (1978). The deterrent effect of capital punishment: An assessment of the estimates. In Blumstein, A., et al. (eds.),Deterrence and Incapacitation: Estimating the Effects of Criminal Sanctions on Crime Rates, National Academy of Sciences, Washington, DC, pp. 336–360.

    Google Scholar 

  • Koopman, B. O. (1986). An empirical formula for visual search.Operat. Res. 34(3): 377–383.

    Google Scholar 

  • Land, K. C. (1992). Models of criminal careers: Some suggestions for moving beyond the current debate.Criminology 30: 149–155.

    Article  Google Scholar 

  • Langan, P. A. (1991). America's, soaring prison population.Science 251: 1568–1573.

    Google Scholar 

  • Larson, R. C. (1972).Urban Police Patrol Analysis, MIT Press, Cambridge, MA.

    Google Scholar 

  • Lattimore, P. K., and Baker, J. R. (1992). The impact of recidivism and capacity on prison populations: A projection model.J. Quant. Criminol. 8: 155–173.

    Article  Google Scholar 

  • Lehoczky, J. P. (1986). Random paramete stochastic-process models of criminal careers. In Blumstein, A., et al. (eds.),Criminal Careers and Career Criminals, National Academy Press, Washington, DC, pp. 380–404.

    Google Scholar 

  • Maltz, M. D. (1972).Evaluation of Crime Control Programs, National Institute of Law Enforcement and Criminal Iustice, U.S. Department of Justice, Washington, DC.

    Google Scholar 

  • Maltz, M. D. (1975). Crime statistics: A mathematical perspective.J. Crim. Just. 3(3): 177–194.

    Google Scholar 

  • Maltz, M. D. (1976). On the estimation of smuggling in a “gray market” commodity,Operat. Res. 23(6): 1156–1163.

    Google Scholar 

  • Maltz, M. D. (1977). Crime statistics: A historical perspective.Crime and Delinq. 23(1): 32–40.

    Google Scholar 

  • Maltz, M. D. (1980). Beyond suppression: More sturm and drang on the correctional front.Crime Delinq. 26(3): 389–397.

    Google Scholar 

  • Maltz, M. D. (1981). Transportation modeling in analyzing an economic crime. In Fox, J.A. (ed.),Methods in Quantitative Criminology Academic Press, New York, pp. 77–97.

    Google Scholar 

  • Maltz, M. D. (1984).Recidivism, Academic Press, Orlando, FL.

    Google Scholar 

  • Maltz, M. D. (1990).Measuring the Effectiveness of Organized Crime Control Efforts (monograph), Office of International Criminal Justice, University of Illinois at Chicago, Chicago.

    Google Scholar 

  • Maltz, M. D. (1994a). Deviating from the mean: The declining significance of significance.J. Res. Crime Delinq. 31(4): 434–463.

    Google Scholar 

  • Maltz, M. D. (1994b). Operations research in studying crime and justice: Its history and accomplishments. In Pollock, S. M., Barnett, A., and Rothkopf, M. H. (eds.),Operations Research and the Public Sector (Volume 6 of the Handbooks in Operations Research and Management Science, edited by G. L. Nemhauser and A. H. G. Rinnooy Kan), Elsevier North-Holland, Amsterdam, pp. 201–262.

    Google Scholar 

  • Maltz, M. D., and McCleary, R. (1977). The mathematics of behavioral change: Recidivism and construct validity.Eval. Q. 1(3): 421–438.

    Google Scholar 

  • Maltz, M. D., and Pollock, S. M. (1980a). Analyzing suspected collusion among bidders. In Geis, G. and Stotland, E. (eds.),White-Collar Crime: Theory and Practice, Sage: Beverly Hills, CA, pp. 174–198.

    Google Scholar 

  • Maltz, M. D., and Pollock, S. M. (1980b). Artificial inflation of a delinquency rate by a selection artifact.Operat. Res. 28(3): 547–559.

    Google Scholar 

  • Maltz, M. D., and McCleary, R. (1978). Comments on “Stability of parameter estimates in the split-population exponential distribution.Eval. Q 2(4): 650–654.

    Google Scholar 

  • Maltz, M. D., McCleary, R., and Pollock, S. M. (1979). Recidivism and likelihood functions: A reply to Stollmack.Bval. Q. 2(1): 124–131.

    Google Scholar 

  • Maltz, M. D., Gordon, A. C., McDowall, D., and McCleary, R. (1980). An artifact in pretestposttest designs: How it can mistakenly make delinquency programs look effective.Eval. Rev. 4(2): 225–240.

    Google Scholar 

  • Maltz, M. D., Gordon, A. C., and Friedman, W. (1990).Mapping Crime in Its Community Setting: Event Geography Analysis, Springer-Verlag, New York.

    Google Scholar 

  • Mason, W. M., and Fienberg, S. E. (eds.) (1985),Conort Analysis in the Social Sciences: Beyond the Identification Problem, Springer-Verlag, New York.

    Google Scholar 

  • McEwen, J. T., and Guynes, R. (1990). Criminal justice system simulation model (CJSSIM). Paper presented at the Annual Meeting of the American Society of Criminology, Baltimore, MD.

  • Moffitt, T. E. (1993). Adolescence-limited and life-course-persistent antisocial behavior: A developmental taxonomy.Psychol. Rev. 100(4): 674–701.

    Google Scholar 

  • Monahan, J., and Walker, L. (1984).Social Science in Law: Cases and Materials, Foundations Press, Mineola, NY.

    Google Scholar 

  • Morgan, P. M. (1985).Modelling the Criminal Justice System, Home Office Research and Planning Unit Paper 35, Home Office, London.

    Google Scholar 

  • Murray, C. A., and Cox, L. A., Jr (1979).Beyond Probation: Juvenile Corrections and the Chronic Delinquent, Sage, Beverly Hills, CA.

    Google Scholar 

  • Nagin, D. (1978). General deterrence: A review of the empirical evidence. In Blumstein., A., et al. (eds.),Deterrence and Incapacitation: Estimating the Effects of Criminal Sanctions on Crime Rates, National Academy of Sciences, Washington, DC, pp. 95–139.

    Google Scholar 

  • Nagin, D. (1981). Crime rates, sanction levels and constraints on prison population.Law Society Rev. 12(3): 341–366. [Reprinted as Methodological issues in estimating the deterrent effect of sanctions. In Fox (1981b), pp. 121–140.

    Google Scholar 

  • Nagin, D., and Smith, D. A. (1990). Participation in and frequency of delinquent behavior: A test for structural differences.Criminology 28: 335–356.

    Google Scholar 

  • Naik, A. V., Baveja, A., Batta, R., and Caulkins, J. P. (1995). Scheduling crackdowns on illicit drug markets.Eur. J. Operat. Res. (in press).

  • New York State Identification and Intelligence System (1967).NYSIIS: System Development Plan, NYSIIS, Albany.

    Google Scholar 

  • Orsagh, T. (1981). A criminometric model of the criminal justice system. In Fox, J. A. (ed.),Models in Quantitative Criminology, Academic Press, New York, pp. 163–187.

    Google Scholar 

  • Partanen, J. (1969). On waiting time distributions.Acta Sociol. 112: 132–143.

    Google Scholar 

  • Passell, P. (1975). The deterrent effect of the death penalty: A statistical test.Stanford Law Rev. 28: 61–80.

    Google Scholar 

  • Philpotts, G. J. O., and Lancucki, L. B. (1979).Previous Convictions, Sentence and Reconviction, Home Office Research Study No. 53, Her Majesty's Stationery Office, London.

    Google Scholar 

  • Pollock, S. M., and Farrell, R. L. (1984). Past intensity of a terminated poisson process.Operat. Res. Lett. 2: 261–263.

    Google Scholar 

  • Pollock, S. M., and Maltz, M. D. (1994). Operations research in the public sector: An introduction and a brief history. In Pollock, S. M., Barnett, A., and Rothkopf, M. H. (eds.),Operations Research and the Public Sector (Volume 6 of the Handbooks in Operations Research and Management Science, edited by G. L. Nemhauser and A. H. G. Rinnooy Kan), Elsevier North-Holland, Amsterdam, pp. 1–22.

    Google Scholar 

  • Porter, T. M. (1986).The Rise of Statistical Thinking, 1820–1900, Princeton University Press, Princeton, NJ.

    Google Scholar 

  • President's Commission on Law Enforcement and Administration of Justice (1967).The Challenge of Crime in a Free Society, U.S. Government Printing Office, Washington, DC.

    Google Scholar 

  • Proschan, F. (1963). Theoretical explanation of observed decreasing failure rate.Technometrics 5: 375–383.

    Google Scholar 

  • Pullinger, H. (1985).The Criminal Justice System Model: The Flow Model, Home Office Research and Planning Unit Paper 36, Home Office, London.

    Google Scholar 

  • Quetelet, L. A. J. (1835).A Treatise on Man (translated by S. Diamond), Scholars Facsimiles and Reprints, Gainesville, FL, 1969.

  • Rauma, D. (1981a). Crime and punishment reconsidered: Some comments on Blumstein's stability of punishment hypothesis.J. Crim. Law Criminol. Police Sci. 72(4): 1772–1798.

    Google Scholar 

  • Rauma, D. (1981b). A concluding note on the stability of punishment: A reply to Blumstein, Cohen, Moitra, and Nagin.J. Crim. Law Criminol. Police Sci. 72(4): 1809–1812.

    Google Scholar 

  • Reiss, A. J., Jr., and Farrington, D. P. (1991). Advancing knowledge about co-offending: Results from a prospective longitudinal survey of London males.J. Crim. Law Criminol. 82: 360–395.

    Google Scholar 

  • Rengert, G. F. (1992). The journey to crime: Conceptual foundations and policy implications. In Evans, D. J., Fyfe, N. R., Nicholas, R., and Herbert, D. T. (eds.),Crime, Policing and Place, Routledge, London.

    Google Scholar 

  • Rengert, G. F., and Wasilchick, J. (1994). Space, Time and Crime. Ethnographic Insights into Residential Burglary. Final Report submitted to U.S. Department of Justice, National Institute of Justice, and Office of Justice Programs, Washington, DC.

    Google Scholar 

  • Rhodes, W. (1989). The criminal career: Estimates of the duration and frequency of crime commission.J. Quant. Criminol. 5: 3–32.

    Article  Google Scholar 

  • Riccio, L. J. (1974). Direct deterrence: An analysis of the effectiveness of police patrol and other crime prevention technologies.J. Crim. Just. 2(3): 207–217.

    Google Scholar 

  • Riccio, L. J., and Finkelstein, R. (1985). Using police arrest data to estimate the number of burglars operating in a suburban conty.J. Crim. Just. 13: 65–73.

    Google Scholar 

  • Rice, S. (1984).The Criminal Justice System Model: Magistrates Courts Sub-model, Home Office Research and Planning Unit Paper 24, Home Office, London.

    Google Scholar 

  • Rich, T., and Barnett, A. (1985). Model-based U.S. prison population projections.Public Admin. Rev. 45: 780–789.

    Google Scholar 

  • Rolph, J. E., Chaiken, J. M., and Houchens, R. L. (1981).Methods for Estimating Crime Rates of Individuals, Report No. R-2730-NIJ, Rand Corp., Santa Monica, CA.

    Google Scholar 

  • Rossmo, D. K. (1990). Fugitive migration patterns. Paper presented at the Annual Meeting of the American Society of Criminology, Baltimore, MD.

  • Rossmo, D. K., and Routledge, R. (1990). Estimating the size of criminal populations.J. Quant. Criminol. 6: 293–314.

    Google Scholar 

  • Rydell, C. P., and Everingham, S. S. (1994).Controlling Cocaine: Supply Versus Demand Programs, Report MR-331-ONDCP/A/DPRC, Rand Corp., Santa Monica, CA.

    Google Scholar 

  • Safire, W. (1995). Of nutsiness and madness.The New York Times Magazine, Section 6, Aug. 13.

  • Saks, M. J., and Baron, C. H. (1980).The Use/Nonuse/Misuse of Applied Social Science Research in the Courts, Abt Books, Cambridge, MA.

    Google Scholar 

  • Schmidt, P., and Witte, A. D. (1988).Predicting Recidivism Using Survival Methods, Springer-Verlag, New York.

    Google Scholar 

  • Science and Technology Task Force (1967).Task Force Report: Science and Technology, U.S. Government Printing Office, Washington, DC.

    Google Scholar 

  • Shaw, C., and McKay, H. (1969).Juvenile Delinquency and Urban Areas, University of Chicago Press, Chicago.

    Google Scholar 

  • Shinnar, R., and Shinnar, S. (1975). The effects of the criminal justice system on the control of crime: A quantitative approach.Law Society Rev. 9(4): 581–611.

    Google Scholar 

  • Shover, N., and Thompson, C. Y. (1992). Age, differential crime expectations, and crime desistance.Criminology 30: 89–104.

    Article  Google Scholar 

  • Smith, T. S. (1976). Inverse distance variations for the flow of crime in urban areas.Social Forces 54: 804–815.

    Google Scholar 

  • Stigler, S. M. (1986).The History of Statistics: The Measurment of Uncertainty Before 1900, Belknap Press of Harvard University Press, Cambridge, MA.

    Google Scholar 

  • Stollmack, S. (1973). Predicting inmate population from arrest, court disposition, and recidivism rates.J. Res. Crime Delinq. 10: 141–162.

    Google Scholar 

  • Stollmack, S., and Harris, C. M. (1974). Failure-rate analysis applied to recidivism data.Operat. Res. 22: 1192–1205.

    Google Scholar 

  • Swersey, A. J. (1994). The deployment of police, fire and emergency medical units. In Pollock, S. M., Barnett, A., and Rothkopf, M. H. (eds.),Operations Research and the Public Sector (Volume 6 of the Handbooks in Operations Research and Management Science, edited by G. L. Nemhauser and A. H. G. Rinnooy Kan), Elsevier North-Holland, Amsterdam, pp. 151–200.

    Google Scholar 

  • Tarling, R. (1986). Statistical applications in criminology.Statistician 35: 369–388.

    Google Scholar 

  • Tierney, L. (1983). A selection artifact in delinquency data revisited.Operat. Res. 31(5): 852–865.

    Google Scholar 

  • Tittle, C. R. (1988). Two empirical regularities (maybe) in search of an explanation: Commentary on the age/crime debate.Criminology 26: 75–85.

    Article  Google Scholar 

  • Turnbull, B. W. (1976). The empirical distribution function with arbitrarily grouped, censored and truncated data.J. Roy. Stat. Soc. Ser. B 38(3): 290–295.

    Google Scholar 

  • Visher, C. A. (1986). The Rand inmate survey: A renalaysis. In Blumstein, A.,et al. (eds.),Criminal Careers and Career Criminals, Vol. II, Natinal Academy Press, Washington, DC, pp. 161–211.

    Google Scholar 

  • Visher, C. A., and Linster, R. L. (1990). A survival model of pretrial failure.J. Quant. Criminol. 6: 153–184.

    Article  Google Scholar 

  • von Hirsch, A. (1985).Past or Future Crimes: Deservedness and Dangerousness in the Sentencing of Criminals, Rutgers University Press, New Brunswick, NJ.

    Google Scholar 

  • Willmer, M. A. P. (1970).Crime and Information Theory, Edinburgh University Press, Edinburgh, Scotland.

    Google Scholar 

  • Wolfgang, M. E., Figlio, R. M., and Sellin, T. (1972).Delinquency in a Birth Cohort, University of Chicago Press, Chicago.

    Google Scholar 

  • Zimring, F. K., and Hawkins, G. J. (1973).Deterrence: The Legal Threat in Crime Control, University of Chicago Press, Chicago.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Maltz, M.D. From Poisson to the present: Applying operations research to problems of crime and justice. J Quant Criminol 12, 3–61 (1996). https://doi.org/10.1007/BF02354470

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02354470

Key Words

Navigation