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Abstract: Objectives Government officials use criminal records as proxies for past conduct to decide who and how to investigate, arrest, charge, and punish. But those records may be racially biased measures of individual behavior. This paper develops a theoretical definition of bias in criminal records in terms of measurement error. It then seeks to provide empirical estimates of racial bias in official arrest records for a broad swath of offenses. Method I use official arrest and self-reported crime data from the Pathways to Desistance study to estimate Black-to-white and Hispanic-to-white crime ratios conditional on arrest. I also develop a novel, theory-based empirical test of differential reporting across racial and ethnic groups. Results Compared to white subjects with the same number of arrests, I estimate that Black subjects committed 53, 30, 23, and 56% fewer property, violent, drug, and DUI offenses, respectively, and that Hispanic subjects committed 19 and 46% fewer drug and DUI offenses. The analysis finds relatively little evidence of differential reporting that would bias my estimates upwards, with the possible exception of drug trafficking offenses. Conclusion The results provide evidence that Pathways subjects’ arrest records are racially biased measures of their past criminal behavior, which could bias decisions of criminal justice officials and risk assessment algorithms that are based on arrest records. PubDate: 2024-09-01
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Abstract: Purpose Crime data analysis has gained significant interest due to its peculiarities. One key characteristic of property crimes is the uncertainty surrounding their exact temporal location, often limited to a time window. Methods This study introduces a spatio-temporal logistic regression model that addresses the challenges posed by temporal uncertainty in crime data analysis. Inspired by the aoristic method, our Bayesian approach allows for the inclusion of temporal uncertainty in the model. Results To demonstrate the effectiveness of our proposed model, we apply it to both simulated datasets and a dataset of residential burglaries recorded in Valencia, Spain. We compare our proposal with a complete cases model, which excludes temporally-uncertain events, and also with alternative models that rely on imputation procedures. Our model exhibits superior performance in terms of recovering the true underlying crime risk. Conclusions The proposed modeling framework effectively handles interval-censored temporal observations while incorporating covariate and space–time effects. This flexible model can be implemented to analyze crime data with uncertainty in temporal locations, providing valuable insights for crime prevention and law enforcement strategies. PubDate: 2024-09-01
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Abstract: Objectives We aim to encourage scholars who conduct cross-national criminological studies to routinely assess measurement invariance (MI), that is, verify if multi-item instruments that capture latent constructs are conceptualized and understood similarily across different populations. To promote the adoption of MI tests, we present an analytical protocol, including an annotated R script and output file. We implement the protocol and, doing so, document the first test of configural, metric, and scalar invariance of the three-factor Morally Debatable Behavior Scale (MDBS). Methods We worked with data from wave seven of the World Values Survey (WVS). Applying multi-group confirmatory factor analyses, we, first, explored invariance of the MDBS in 44 countries (N = 59,482). Next, we conducted analyses separately for seven South-american, six South-east Asian, six East-asian, two North American and Australasian, and all four Anglophone countries. Results The MDBS displays an overall lack of invariance. However, we confirmed configural invariance of the MDBS for the South-east Asian sample, metric invariance in the sample of Anglophone countries, and scalar invariance for the Australasian and North American countries. Conclusions Wave seven of the WVS can be used for latent mean score comparisons of the MDBS between the Australasian and North American countries. Associative relationships can be compared in the larger Anglophone sub-sample. Taken together, MI must be tested, and cannot be assumed, even when analyzing data from countries for which previous research has established cultural similarities. Our protocol and practical recommendations guide researchers in this process. PubDate: 2024-09-01
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Abstract: Objectives Approaches to the study of Outlaw Motorcycle Gangs OMCGs tend to focus on offending at the individual level, with limited focus on the nature and extent of co-offending among these affiliates. We aim to examine co-offending by using relational hyper event models (RHEM) to determine what additional insights can be discerned on co-offending above and beyond more traditional network approaches. Methods Using de-identified police recorded incident data for affiliates of OMCGs in New South Wales, Australia, including their rank and club affiliation, we examined the positioning of OMCG affiliates in co-offending network structures. The data comprised 2,364 nodes and 12,564 arrest events. We argue that Relational Hyperevent Models (RHEM) are the optimal analytical strategy for co-offending data as it overcomes some of the limitations of traditional co-offending analyses. Results We conducted RHEM modelling and found that co-offending networks were stable over time, whereby actors tended to repeatedly co-offend with the same partners. Lower ranked members were more likely to engage in co-offending compared with office bearers. Conclusions Results provide some support for the scenario in which OMCGs operate as criminal organisations, but also the protection and distance from offending that is afforded to office bearers. We review implications of the results for law enforcement policy and practice and for the scholarship of OMCGs. PubDate: 2024-09-01
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Abstract: Objective The goal of this study is to examine how the age-crime distribution in South Korea has shifted over time and the role of cohorts in driving this shift. This study highlights the impact of social change and historical events on cohort effects, potentially leading to shifts in the age-crime distribution.. Methods Age-Period-Cohort-Interaction (APC-I) models are estimated on age-specific-arrest statistics for offenses in South Korea from 1967 and 2011. The APC-I models take into account the interdependence of age, period, and cohort, thus permitting the identification of inter-and intra-cohort differences in crime over the life course. Results The age-crime distribution in South Korea has changed over time to an older peak age of arrest. Korean baby boomers born between 1955 and 1963 have a higher risk of arrest earlier in life than other cohorts, perpetuating an overall increased risk over the life course. Conclusion Changes in socio-historical conditions differentiate crime trajectories across cohorts over the life course. Thus, this study suggests that social change and historical events impact the age-crime dynamics in South Korea. PubDate: 2024-09-01
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Abstract: Objectives Evaluate the impact of missing data on observed racial disparities in the likelihood of an incarceration sentence, given that complete case analysis in the common analytic approach used in criminological research. Methods Using a simulation study with data based on cases sentenced in the Court of Common Pleas in Pennsylvania between 2010 and 2019, we assess the differences in the likelihood of incarceration between similarly situated White and Black defendants based on varying sample sizes and patterns of missing data. Results Complete case analysis (CCA) of incomplete data can fail to provide unbiased estimates of the race effect, even with less than 10% of cases missing. The degree of bias introduced depends on the amount, pattern, assumptions, and treatment of missing data. Multiple imputation provides an established, valid methodology for the unbiased estimation of race effects when data are missing at random, and this holds across sample sizes and number of imputations. Conclusions The existence and magnitude of race effects on the likelihood of an incarceration sentence can vary greatly based on the degree, pattern, assumptions, and treatment of missing data. Limitations include that missing data mechanisms cannot be truly known outside of a data simulation. Future sentencing research should prioritize the identification, treatment, and reporting of missing data prior to isolating race effects, in line with calls from the field for more open science practices. Sensitivity analyses should also be prioritized. PubDate: 2024-09-01
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Abstract: Purpose The aim of this paper is to construct a single sentence severity scale incorporating the full range of custodial and non-custodial sentences meted out by the courts. Such a scale would allow us to measure and rank the severity of sentences, relative to other sentences. Methods We use disaggregated individual level sentencing data to model the association between offenses and their associated sentences using the Goodman Row Column (RC) Association Model. We then extend this model to control for three legal factors; conviction history, offense plea, and number of offenses, to produce a series of standardised scores. We use linear interpolation and extrapolation to convert the scores to equivalent days in custody. Results The scores from the model enable the sentences to be ranked in order of severity; longer custodial sentences dominate at the severe end whilst non-custodial sentences congregate towards the lower end. In the middle of the scale, non-custodial and shorter custodial sentences interweave. We then demonstrate one use of the scale by applying it to Crown Court data, illustrating change in sentencing severity over time. Conclusions The Goodman RC Association Model provides a suitable methodology for scoring sentence severity on a single scale. The study found that by extending the model, we were also able to control for three legal factors. The sentence severity scale, as a research tool is specific to England and Wales but the method is universal and can be applied in any jurisdiction where the relevant data is available. PubDate: 2024-08-19
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Abstract: Objectives This study explores the level to which Gunshot Detection Technology (GDT) leads to increased arrests and stops as compared to shots fired calls for service (CFS) in Chicago, Illinois. Methods A two-process Knox test and point process test are applied to measure the level to which GDT alerts and CFS cluster with arrests and stops in space and time. Both tests are first applied to the aggregate arrest and stops data. We then disaggregate arrests and stops by type as well as suspect race/ethnicity to measure any disproportionate effects across GDT and CFS. Results Both GDT alerts and CFS are significantly associated with arrests and stops occurring in close spatial and temporal proximity. The relative effect of GDT and CFS was consistent across race in the majority of instances. The small number of instances with disparate effects did not exhibit any clear patterning. For some racial groups and arrest/stop types, GDT was associated with heightened enforcement while CFS had a null effect, with the opposite relationship observed for other racial groups and arrest/stop types. Conclusions Overall, the results indicate that GDT systems may not generate racial disparities in arrests and stops above and beyond what results from the standard police response to gunfire. Racial disparities resulting from police responses to reported gunfire likely relate to aspects of the reporting and dispatch processes generally rather than as they relate specifically to GDT. PubDate: 2024-07-02
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Abstract: Objectives Since 2000, sentencing scholars have commonly controlled for racial/ethnic differences in underlying criminal conduct using presumptive sentence. In recent years, the presumptive sentence approach has been critiqued for (amongst other things) filtering out racial/ethnic disparities that accumulate pre-sentencing. To circumvent this concern, a small but growing body of literature has begun to employ the base offense level approach. The goal of this study is to analyze the implications of using the presumptive sentence versus base offense level approach to isolate racial/ethnic effects on federal sentencing outcomes. Methods Using data from the United States Sentencing Commission (2018–2020), this analysis tracks racial/ethnic differences throughout the pre-sentence process (base offense level to final offense level). Subsequently, we compare racial/ethnic effects obtained in a series of multi-level multivariate regression models using both the presumptive sentence and base offense level approaches. Results Findings indicate that the two approaches provide vastly different starting points for racial/ethnic differences in underlying criminal conduct and, therefore, different conclusions about how race/ethnicity matters in sentencing. Most notably, Hispanic defendants are advantaged relative to Whites when accounting for racial/ethnic differences in base offense level but disadvantaged relative to Whites when accounting for racial/ethnic differences in presumptive sentence. Conclusions Findings suggest that the presumptive sentence approach filters out important racial/ethnic differences in the pre-sentence process and that the two modeling approaches are not interchangeable. Results clearly indicate that modeling matters in sentencing research, and future research should pay close attention to their baselines for between-group differences in relevant conduct. PubDate: 2024-06-01 DOI: 10.1007/s10940-023-09573-0
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Abstract: Objectives Test the effect of perceived likelihood of arrest on criminal behavior under a relaxed set of measurement assumptions. Specifically, responses that are commonly associated with inaccurate reporting practices–particularly, the 0%, 50%, and 100% categories–can be treated as partially identified. By doing so, scholars are able to bound the effect of perceived arrest risk on criminality, which provides more credible, although less precise, estimates of \({\beta }_{1}\) . Scholars can use this approach to not only produce more defensible findings, on the whole, but also gain insight into the possible threat posed by measurement misspecification. Methods Point estimates of a perceived certainty effect were elicited via Quasi-Poisson regression using data derived from the Pathways to Desistance study. These estimates were subsequently bounded under progressively weaker measurement assumptions by a series of hill-climb algorithms. Results In nine out of seventeen total algorithms, the worst-case bound remained in the expected direction and was statistically significant. For as long as a relatively minor level of response inaccuracy is assumed, supportive conclusions can be drawn. Conclusions Support for a certainty effect can be found under relaxed measurement assumptions, up to a point. This not only provides further support for the deterrence hypothesis, but also implies the effect might be somewhat resilient to measurement error. PubDate: 2024-06-01 DOI: 10.1007/s10940-023-09569-w
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Abstract: Objectives This paper examines the impact of local economic activity on criminal behavior. We build on existing research by relaxing the identification assumptions required for causal inference, and estimate the impact of local economic activity on recidivism. Methods We use the fracking boom as a source of credibly exogenous variation in the economic conditions into which incarcerated people are released. We replicate and extend existing instrumental variables analyses of fracking on how many released offenders return to state prison seperately from aggregate crime and arrests. Results Our instrumental variables estimates imply that a ten thousand dollar increase in the value of per capita production is associated with a 2.8% reduction in the 1-year recidivism of ex-offenders at the county level. Improved labor market conditions, specifically an increase in wages for young adults, may explain a non-negligible fraction of the reduction in recidivism associated with economic booms. In contrast, we replicate existing work finding that fracking increased aggregate measures of crime and arrests. Conclusion Increased economic opportunity appears to have a different impact of overall crime than on recidivism. This suggests that the relationship between economic opportunity and offending may be conditioned by local social ties. Further research examining how social connections and labor markets affect individual criminal behavior is needed. PubDate: 2024-06-01 DOI: 10.1007/s10940-023-09571-2
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Abstract: Objectives Prior studies indicate risk for recidivism declines with time spent in the community post-incarceration. The current study tested whether declines in risk scores occurred uniformly for all individuals in a community corrections sample or whether distinct groups could be identified on the basis of similar trajectories of change in acute risk and time to recidivism. We additionally tested whether accounting for group heterogeneity improved prospective prediction of recidivism. Methods This study used longitudinal, multiple-reassessment data gathered from 3,421 individuals supervised on parole in New Zealand (N = 92,104 assessments of theoretically dynamic risk factors conducted by community corrections supervision officers). We applied joint latent class modelling (JLCM) to model group trajectories of change in acute risk following re-entry while accounting for data missing due to recidivism (i.e., missing not at random). We compared accuracy of dynamic predictions based on the selected joint latent class model to an equivalent joint model with no latent class structure. Results We identified four trajectory groups of acute dynamic risk. Groups were consistently estimated across a split sample. Trajectories differed in direction and degree of change but using the latent class structure did not improve discrimination when predicting recidivism. Conclusions There may be significant heterogeneity in how individuals’ assessed level of acute risk changes following re-entry, but determining risk for recidivism should not be based on probable group membership. JLCM revealed heterogeneity in early re-entry unlikely to be observed using traditional analytic approaches. PubDate: 2024-06-01 DOI: 10.1007/s10940-022-09566-5
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Abstract: Objectives Self-reported criminal behaviour has the potential to provide clearer insights into patterns of criminality compared to using police statistics. The risk of inaccurate responses however forms a major obstacle to its validity. This study therefore examines underreporting bias of self-reported criminal behaviour among five ethnic groups and compares different methods to facilitate the creation of valid intergroup comparisons. Methods This study includes data from the Monitor on Youthful Delinquency (N = 6,218) which was connected to police suspect registrations. To identify patterns of underreporting, we compared self-reported and police recorded crime with a social desirability measure, which was adjusted to be invariant across ethnic groups. Three different methods to correct for underreporting bias were subsequently compared; partialling out the effect of social desirability, listwise deletion, and a novel technique which we named Social Desirability based Score Replacement (SDSR). Results The study reveals that police suspects with a high social desirability score display a low likelihood to self-report crime when they have an ethnic minority background, but not when they have a native Dutch background or when they have a moderate to low social desirability score. This finding points towards systematic differences in underreporting bias. Model outcomes are shown to be significantly impacted depending on the method that is used to address this issue. Conclusion Neglecting to correct underreporting-bias hinders the validity of intergroup comparisons of self-reported criminal behaviour. The inclusion of a social desirability measure is therefore recommended to help identify and correct underreporting bias, particularly through the use of SDSR. PubDate: 2024-06-01 DOI: 10.1007/s10940-023-09567-y
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Abstract: Objectives Research in criminology and criminal justice is a rapidly growing interdisciplinary, international network of intersecting research topics. Quantifying the substantive content of criminology allows us to empirically disentangle this network and analyze how the interplay of research topic and international context influences knowledge production in the study of crime. Methods In this paper we apply the topic embedding model, top2vec, mapping two decades of research in criminology and criminal justice (2001–2020). Using data generated by top2vec we enrich coauthorship network data—introducing themes and subdisciplines, and topical similarity measures—and analyze the relationship between topical and subdisciplinary overlap, geospatial distance, and publication coauthorship in a sample of mid-career researchers (N = 4068). Results We find that these researchers disproportionately favor collaboration within their immediate network of collaborators and subdiscipline of criminology, but tend to establish new, synergistic collaborations with topically adjacent researchers. New collaborations appear to be independent of geographic distance, but US criminologists are less likely to collaborate internationally than Eurasian and Oceanic criminologists. Conclusions Facilitating communication between researchers and organizations from adjacent subdisciplines could benefit researchers and produce new, innovative research. Encouraging comparative research would help international scholars, many of whom may rely on US collaborators, benefit more from US scholarship. Further applications for top2vec in the scientometric study of criminology, criminal justice, and legal studies are discussed. PubDate: 2024-06-01 DOI: 10.1007/s10940-023-09574-z
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Abstract: Objectives Understanding how covert networks are formed is key to disrupting the operation of illicit activities. Applying standard network measures to a covert network, while useful, is limited in identifying the peculiar properties of the network in question. It is important that we compare the covert network against a benchmark, be it random networks or, more ideally, the counterpart (overt) network in the same context. We report a study in collaboration with law enforcement agency to examine the co-voyage network of criminals and non-criminals. A comparison of the two groups of actors in their network positions allows us to test whether criminals tend to blend in or hide out from the population of non-criminals. Methods Drawing on data on maritime activities in Taiwan recorded from years 2016 to 2018, we map a maritime co-voyage network of 53,009 nodes and 2,592,288 weighted links. We follow a bootstrap resampling procedure to estimate the structural features of the co-voyage networks of criminals and non-criminals. Results Criminals are more likely to co-voyage with their own type than non-criminals. Similarly, criminals are more clustered in the co-voyage network than non-criminals. Conclusions It is more supported that criminals segregate from than blend in non-criminals in the co-voyage network. PubDate: 2024-06-01 DOI: 10.1007/s10940-023-09572-1
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Abstract: Objectives To examine the perceptual deterrent effect of an increase in police presence for a sample of previously adjudicated adolescents and address the limitations of existing perceptual deterrence research. Methods This study exploits the timing of Operation Safe Streets, a hot spots policing intervention designed to increase officer presence, which occurred during an ongoing longitudinal survey of previously adjudicated adolescents (n = 700). The effect of this intervention is tested using first-difference models of perceptions of arrest risk within-person over time. Sensitivity analyses and falsification tests are also conducted to provide further confidence in the findings. Results Results show that Operation Safe Streets is related to an increase in perceptions of arrest risk for one’s self, as well as perceptions of other’s arrest risk. This pattern holds for those who were and were not arrested. Furthermore, null findings for the effect of Operation Safe Streets on perceived social costs of punishment, as well as null findings from in-time placebo models, lend strong support that an increase in police officer presence did increase individuals’ perceptions of arrest risk in the months following the intervention. Conclusions This study is the first to test the perceptual deterrent effect of a police intervention aimed to reduce street crime. It is also one of the first to demonstrate that criminal justice policies impact perceptions of arrest risk. This study adds to our understanding of the success of hot spots policing by suggesting that one pathway for decreased crime is through changes in perceptions of arrest risk. PubDate: 2024-06-01 DOI: 10.1007/s10940-023-09570-3
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Abstract: Objectives A growing body of evidence suggests focused deterrence strategies successfully reduce criminal behavior. Very little of this evidence comes from randomized experiments. This paper takes a step toward filling this gap in the literature. We present the results of a randomized experiment evaluating a series of youth outreach forums that leverage several focused deterrence strategies. Methods This paper presents the results of a randomized controlled trial of a youth outreach forums program run in the Cook County Juvenile Detention Center (JTDC) by the Northern Illinois Project Safe Neighborhoods Task Force. Results We find the program caused a 20 percent reduction in the number of new spells at the JTDC in the eight months after random assignment and reduced total arrests by 18 percent in the first year after random assignment. While both of these impacts are somewhat imprecisely estimated, the reduction in total arrests is driven by statistically significant 43 and 40 percent reductions in arrests for violent and drug crime, respectively, and a large but less precisely estimated 30 percent reduction in arrests for property crime. These correspond to very valuable and proportionally large reductions in the social costs of crime. Our estimates also suggest the forums increase attachment to school. Conclusion The results of our study suggest juvenile detention centers may better reduce the future criminal behavior of residents by implementing similar programs to the youth outreach forums program. PubDate: 2024-05-28 DOI: 10.1007/s10940-024-09584-5
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Abstract: Purpose Two important issues constrain the neighborhood effects literature. First, most prior research examining neighborhood effects on aggression and self-reported violence uses a point in time (i.e., cross-sectional) estimate of neighborhood disadvantage even though the duration of exposure to neighborhood disadvantage varies between families. Second, neighborhood effects may be understated due to over-controlling for family socioeconomic conditions. Both limitations suggest that prior research may be underestimating neighborhood effects, which impacts research on the invariance thesis and explanation of ethnoracial differences. Methods The sample is drawn from the restricted use Future of Families and Child Well-being study. Data to measure youth’s exposure to neighborhood disadvantage is drawn from birth through age 9, with dependent variables measured at age 15. We estimate marginal structural models (MSM) with inverse probability of treatment weights (IPTW. Results The results support hypotheses, indicating that the duration weighted measure of neighborhood disadvantage is more strongly associated with aggression and self-reported violence than the point in time, and that it accounts for a larger share of the ethnoracial differences. Conclusions The findings provide a clear image of the consequences of long-term exposure to neighborhood disadvantage for aggression and violence. They suggest that criminologists addressing neighborhood effects should attempt, when feasible, to document and model the duration of exposure to neighborhood disadvantage. They are also consistent with and add to a growing literature addressing MSM modeling with IPTW weights. PubDate: 2024-05-07 DOI: 10.1007/s10940-024-09588-1
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Abstract: Purpose We test current models of racial bias in policing, identify limitations, and propose a test of racial bias, that does not depend on unknown population contraband rate. Methods We conceptualize police officer search decisions as a 2 (search/no search) by 2 (contraband present/absent) table, with missing data (if the police did not search, the presence of contraband is unknown). We constrain the feasible problem space using properties of a 2 x 2 contingency table. Then we examine all possible feasible 2 x 2 tables to identify instances of racial differences in police officer hit and false alarm rates. To do this, we develop a new test of racial bias, the Overlapping Condition Test. We analyze state and county data across 25 United States police departments. Results These departments have an observable racial difference in false alarm rate regardless of the true value of missing data (under every feasible 2 x 2 table there is a racial difference). This effect is found in 10 out of 14 state police departments and 9 out of 11 local departments across the United States. That is, for every feasible real world scenario police officers have lower false alarm rates for White drivers than Black drivers. Conclusion We interpret this difference in false alarm rate as a threshold bias. That is, officers use different criteria for searching Black drivers than White drivers and this conclusion is not qualified by the unknown contraband rate. Future directions should explore how police officers make the decision to search drivers and develop interventions to address the racial bias in search rate. PubDate: 2024-04-27 DOI: 10.1007/s10940-024-09585-4
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