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

Maltz, Michael D.

doi:10.1007/bf02354470

Cited by 57 publications

(34 citation statements)

References 130 publications

(111 reference statements)

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“…The number of sexual offenses for a given individual in a population of offenders is assumed to follow a Poisson distribution. Approximating criminal offending as a Poisson process is a common method of computing probabilistic models of recidivism (Maltz, ). This Poisson distribution is defined for offense frequencies (e.g., 0, 1, 2, 3, …) for a particular time interval, T .…”

Section: Model and Analysismentioning

confidence: 99%

“…Each individual's offending propensity is defined by the mean, λ i , of the individual offender's Poisson distribution. Unlike early models of offending and recidivism that assumed a constant λ for all offenders (Maltz, ), we assume a diverse population of offenders with different propensities of offending, λ i . We assume that the distribution of λ i is right skewed over individual offenders and can be represented by a gamma distribution, consistent with later models of offending and recidivism (Maltz, ).…”

Section: Model and Analysismentioning

confidence: 99%

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The dark figure of sexual recidivism

Scurich

John

2019

Behavioral Sci & The Law

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Empirical studies of sexual offender recidivism have proliferated in recent decades. Virtually all of the studies define recidivism as a new legal charge or conviction for a sexual crime, and these studies tend to find recidivism rates of the order of 5–15% after 5 years and 10–25% after 10+ years. It is uncontroversial that such a definition of recidivism underestimates the true rate of sexual recidivism because most sexual crime is not reported to legal authorities, a principle known as the “dark figure of crime.” To estimate the magnitude of the dark figure of sexual recidivism, this paper uses a probabilistic simulation approach in conjunction with the following: (i) victim self‐report survey data about the rate of reporting sexual crime to legal authorities; (ii) offender self‐report data about the number of victims per offender; and (iii) different assumptions about the chances of being convicted of a new sexual offense given that it is reported. Under any configuration of assumptions, the dark figure is substantial, and as a consequence the disparity between recidivism defined as a new legal charge or conviction for a sex crime and recidivism defined as actually committing a new sexual crime is large. These findings call into question the utility of recidivism studies that rely exclusively on official crime statistics to define sexual recidivism, and highlight the need for additional, long‐term studies that use a variety of different measures to assess whether or not sexual recidivism has occurred.

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Section: Model and Analysismentioning

confidence: 99%

Section: Model and Analysismentioning

confidence: 99%

The dark figure of sexual recidivism

Scurich

John

2019

Behavioral Sci & The Law

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“…The academic literature on jail and prison location is very scarce, even though mathematical methods have been used in crime and justice problems (Maltz 1996). One of the few articles related to the subject is Korporaal et al (2000), who propose a model for assessing the needs for prison capacity in the Netherlands.…”

Section: Discussionmentioning

confidence: 99%

Applications of Location Analysis

Eiselt¹,

Marianov²

2015

International Series in Operations Research &Amp; Management Science

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“…0. Although other distributions could be used for modelling the random component of suffering crime, such as a Negative Binomial (Park and Eck 2013), the Poisson distribution allows to focus on a single parameter (the rate k), and so it is frequently used in crime science (Maltz 1996).…”

Section: A Probabilistic Approach To the Crime And Victimisation Ratesmentioning

confidence: 99%

Measuring the Distribution of Crime and Its Concentration

2017

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Objectives Generally speaking, crime is, fortunately, a rare event. As far as modelling is concerned, this sparsity of data means that traditional measures to quantify concentration are not appropriate when applied to crime suffered by a population. Our objective is to develop a new technique to measure the concentration of crime which takes into account its low frequency of occurrence and its high degree of concentration in such a way that this measure is comparable over time and over different populations.Methods This article derives an estimate of the distribution of crime suffered by a population based on a mixture model and then evaluates a new and standardised measurement of the concentration of the rates of suffering a crime based on that distribution. ResultsThe new measure is successfully applied to the incidence of robbery of a person in Mexico and is able to correctly quantify the concentration crime in such a way that is comparable between different regions and can be tracked over different time periods. ConclusionsThe risk of suffering a crime is not uniformly distributed across a population. There are certain groups which are statistically immune to suffering crime but there are also groups which suffer chronic victimisation. This measure improves our understanding of how patterns of crime can be quantified allowing us to determine if a Electronic supplementary material The online version of this article (doi:10.1007/s10940-017-9354-9) contains supplementary material, which is available to authorized users. prevention policy results in a crime reduction rather than target displacement. The method may have applications beyond crime science.

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

Cited by 57 publications

References 130 publications

The dark figure of sexual recidivism

The dark figure of sexual recidivism

Applications of Location Analysis

Measuring the Distribution of Crime and Its Concentration

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