Journal of Quantitative Criminology

Several aspects of the incivilities thesis, or the role of social and physical disorder in encouraging crime and fear, deserve further testing. These include examining individual- and streetblock-level impacts on reactions to crime and local commitment over time, and testing for lagged and co-occurring impacts at each level. We model these four types of impacts on three reactions to crime and community satisfaction using a panel study of residents (n = 305) on fifty streetblocks, interviewed two times a year apart. At the individual level, incivilities showed unambiguous, lagged impacts on satisfaction, fear, and worry; furthermore, changes in perceived incivilities accompanied changes in resident satisfaction and fear. At the streetblock level: incivilities failed to demonstrate expected lagged impacts on either of the two outcomes where data structures permitted such impacts; changing incivilities, however, were accomp-anied by changing community satisfaction and changing perceptions of relative risk. Before we conclude that lagged ecological impacts of incivilities are weaker than previous theorizing suggests, we must resolve some outstanding theoretical and methodological issues.

This paper presents the first systematic quantitative examination of participation in vigilante behavior. Data collected as part of a larger study of Jewish settler violence in the Israeli-controlled West Bank region are used to analyze the factors that lead members of a community to become involved in vigilante violence. Using logistic regression techniques it is found that settlers who fulfill requirements of the vigilante role and those located in outposts where the demand for vigilantes is greatest are most likely to be involved in vigilante activities. In conclusion, it is argued that these findings provide strong support for a criminological model of vigilante behavior that emphasizes the role of the vigilante as an agent of community social control.

To assess the impact of schools on crime in neighborhoods. We utilize data of charter and public schools in Philadelphia to estimate the effect of school openings on neighborhood crime patterns between 1998 and 2010. We estimate the change in crime in areas surrounding schools before and after their opening compared to areas where schools were always open with Poisson regression models. We also estimate changes in crime in census tracts as schools are added compared to census tracts that never had schools. Finally, we compare estimates from Poisson regression models to those derived from permutation tests where schools are randomly assigned different opening dates. We find no evidence that school openings increase crime relative to locations where schools were always open or never had schools. The models generally produce null effects, though there is some evidence for a reduction in property crimes for public school openings and a reduction in violent crimes for charter school openings within certain distances. Estimates at the census tract level show that changes in the number of schools are not associated with any changes in crime relative to tracts with no schools. Contrary to a large theoretical and empirical literature, the results suggest that school locations play a minimal role in neighborhood crime production in Philadelphia. Future research should investigate specific contexts and mechanisms, such as land-use characteristics and travel patterns to schools, which may interact with specific school settings in ways that are related to crime production.

This study uses UCR and NCVS crime data to assess which data source appears to be more valid for analyses of long-term trends in crime. The relationships between UCR and NCVS trends in violence and six factors from prior research are estimated to illustrate the impact of data choice on findings about potential sources of changes in crime over time. Crime-specific data from the UCR and NCVS for the period 1973–2012 are compared to each other using a variety of correlational techniques to assess correspondence in the trends, and to UCR homicide data which have been shown to be externally valid in comparison with other mortality records. Log-level trend correlations are used to describe the associations between trends in violence, homicide and the potential explanatory factors. Although long-term trends in robbery, burglary and motor vehicle theft in the UCR and NCVS are similar, this is not the case for rape, aggravated assault, or a summary measure of serious violence. NCVS trends in serious violence are more highly correlated with homicide data than are UCR trends suggesting that the NCVS is a more valid indicator of long-term trends in violence for crimes other than robbery. This is largely due to differences during the early part of the time series for aggravated assault and rape when the UCR data exhibited consistent increases in the rates in contrast to general declines in the NCVS. Choice of data does affect conclusions about the relationships between hypothesized explanatory factors and serious violence. Most notably, the reported association between trends in levels of gasoline lead exposure and serious violence is likely to be an artifact associated with the reliance on UCR data, as it is not found when NCVS or homicide trend data are used. The weight of the evidence suggests that NCVS data represent more valid indicators of the trends in rape, aggravated assault and serious violence from 1973 to the mid-1980s. Studies of national trends in serious violence that include the 1973 to mid-1980s period should rely on NCVS and homicide data for analyses of the covariates of violent crime trends.

Quantitative criminology research published in the United Kingdom (England, Wales, Scotland, and Northern Ireland) in the 1990s is reviewed. Publications are divided into five topical categories: measurement; explanations or correlates; police or crime prevention; sentencing; and correctional treatment. The most sophisticated studies are on longitudinal and criminal career research, correlates of victimization, quasi-experimental analysis of policing strategies, prediction of reconviction and sentencing, and evaluation of correctional treatment using statistical controls. More fundamental long-term research on the causes of crime is needed, together with more concern for reliability and validity issues, and more evaluation research including controls for extraneous variables using quasiexperimental or (preferably) experimental techniques.

Boston, like many other major U.S. cities, experienced an epidemic of gun violence during the late 1980s and early 1990s that was followed by a sudden large downturn in gun violence in the mid 1990s. The gun violence drop continued until the early part of the new millennium. Recent advances in criminological research suggest that there is significant clustering of crime in micro places, or “hot spots,” that generate a disproportionate amount of criminal events in a city. In this paper, we use growth curve regression models to uncover distinctive developmental trends in gun assault incidents at street segments and intersections in Boston over a 29-year period. We find that Boston gun violence is intensely concentrated at a small number of street segments and intersections rather than spread evenly across the urban landscape between 1980 and 2008. Gun violence trends at these high-activity micro places follow two general trajectories: stable concentrations of gun assaults incidents over time and volatile concentrations of gun assault incidents over time. Micro places with volatile trajectories represent less than 3% of street segments and intersections, generate more than half of all gun violence incidents, and seem to be the primary drivers of overall gun violence trends in Boston. Our findings suggest that the urban gun violence epidemic, and sudden downturn in urban gun violence in the late 1990s, may be best understood by examining highly volatile micro-level trends at a relatively small number of places in urban environments.

The notion of transitions is an increasingly central concept in contemporary criminology and such issues are particularly significant in the study of intimate partner violence (IPV). Here, attention focuses on relationship dynamics and movement into and out of relationships for understanding long-term patterns of victimization over the life course. Still, a focus on transitions raises questions about how IPV is patterned over time and across relationships and how this contributes to stability and change in victimization risk over the life span. Our study examines this issue using data from the National Violence Against Women Survey. Findings from latent transition analyses reveal strong evidence for change in victimization experiences across the life course. Among women, those who experienced serious, multifaceted violence are most likely to transition out of relationships followed by transition into subsequent relationships characterized by conflict and aggression and a similar pattern is observed among men. At the same time, men who experience physical aggression in previous relationships are most likely to transition into non-violent relationships, while women with similar experiences are much less differentiated in the types of relationships they enter into. When we account for background characteristics (e.g., respondent’s race, education, and age) and childhood experiences of parental violence, the latter is particularly significant in accounting for exposure to serious IPV in later adulthood. Such findings extend our understanding of how life course transitions connect to violence and offending and highlight processes of continuity and change beyond the traditional focus on criminal offending.

There is no scholarly consensus as to the proper functional form of the crime equation, particularly with regard to one critical, explanatory variable—prison population. The critical questions are whether crime and prison rates must be differenced, whether they are cointegrated, and whether they are simultaneously determined—whether crime and prison cause one another. To determine the proper specification, different researchers have applied unit-root, cointegration, and Granger tests to very similar data sets and obtained very different results. This has led to very different specifications and predictably different implications for public policy. These differences are more likely to be due to the methods used, rather than to real differences among the data sets. When the best available methods are used to identify the proper specification for a panel of U.S. states, results are fairly clear. Crime rates and prison populations are close to unit-root; crime and prison are not cointegrated; crime clearly affects subsequent prison populations. Thus the best specification of the crime equation must rely on differenced data and instrumental variables. Alternative specifications run a substantial risk of spurious results.