Understanding the Random Effect on Victimization Distributions: A Statistical Analysis of Random Repeat Victimizations

Park, Seong min; Eck, John E.

doi:10.1080/15564886.2013.814612

Cited by 18 publications

(27 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Random Variation in the Spatial Distribution of Crime Park and Eck (2013) maintain that the random component in the distribution of criminal victimization has not been adequately modeled in studies of repeat victimization. As a result, nonrandom processes have been overestimated, including risk heterogeneity (some individuals are more vulnerable to victimization than others) and event dependence (prior victimization increases the risk of future victimization).…”

mentioning

confidence: 98%

“…As a result, nonrandom processes have been overestimated, including risk heterogeneity (some individuals are more vulnerable to victimization than others) and event dependence (prior victimization increases the risk of future victimization). Ignoring the random component in repeat victimization, Park and Eck (2013) advise, can lead to wasteful and ineffective policy interventions. The authors point out that the same is true of ''the interpretation of locational crime concentration and allocation of crime prevention resources' ' (412-413).…”

mentioning

confidence: 98%

“…These are valuable results, but it is equally important for explanatory and policy purposes to know the extent of crime concentration if crimes were randomly distributed over place. Park and Eck (2013) recommended that investigators explicitly model the random component in victimization and repeat victimization before concluding that the nonrandom component, even if statistically discernible, is substantively meaningful. The same considerations apply to the analysis of crime events across urban spaces.…”

mentioning

confidence: 99%

See 2 more Smart Citations

The Law of Crime Concentration: An Application and Recommendations for Future Research

2016

View full text Add to dashboard Cite

Objective We address four outstanding empirical questions related to the ''law of crime concentration'' (Weisburd in Criminology 53:133-157, 2015): (1) Is the spatial concentration of crime stable over time? (2) Do the same places consistently rank among those with the highest crime counts? (3) How much crime concentration would be observed if crimes were distributed randomly over place? (4) To what degree does the spatial concentration of crime depend on places that are crime free?Methods The data are annual counts of violent and property crimes in St. Louis between 2000 and 2014. Temporal stability in the spatial inequality of crime is measured by computing the fraction of crimes that occur in the 5% of street segments with the highest crime frequencies each year. The spatial mobility of crime is measured by computing the number of years each street segment appears in the top 5% of street segments. Poisson simulations are used to estimate the fraction of crimes that could appear in the top 5% of street segments on the basis of chance alone. The impact of crime-free locales on the spatial concentration of crime is evaluated by comparing results from analyses that include and exclude crime-free street segments from the crime distributions. ResultsThe concentration of crime is highly unequal and stable over time. The specific street segments with the highest crime frequencies, however, change over time. Nontrivial fractions of street segments may appear among the 5% with the highest crime frequencies on the basis of chance. Spatial concentration of crime is reduced when crime-free street segments are excluded from the crime distributions.

show abstract

mentioning

confidence: 98%

mentioning

confidence: 98%

mentioning

confidence: 99%

See 1 more Smart Citation

The Law of Crime Concentration: An Application and Recommendations for Future Research

2016

View full text Add to dashboard Cite

show abstract

“…We use one state (Guerrero) and over one year (2016) to test against a random distribution of crime (Park and Eck 2013). With the observed number of crimes, c ¼ 0:069 we would expect, from Eq.…”

Section: At a National Level Thementioning

confidence: 99%

“…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

View full text Add to dashboard Cite

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.

show abstract