Social Disorganization Outside the Metropolis: An Analysis of Rural Youth Violence

In order to extend the study of community social disorganization and crime beyond its exclusive focus on large urban centers, we present an analysis of structural correlates of arrest rates for juvenile violence in 264 nonmetropolitan counties of four states. Findings support the generality of social disorganization theory: Juvenile violence was associated with rates of residential instability, family disruption, and ethnic heterogeneity. Though rates of poverty were not related to juvenile violence, this is also in accord with social disorganization theory because, unlike urban settings, poverty was negatively related to residential instability. Rates of juvenile violence varied markedly with population size through a curvilinear relationship in which counties with the smallest juvenile populations had exceptionally low arrest rates. Analyses used negative binomial regression (a variation of Poisson regression) because the small number of arrests in many counties meant that arrest rates would be ill suited to least-squares regression

Community Correlates of Rural Youth Violence

Rates of crime and delinquency vary widely across communities, and research going back many decades provides a good understanding of the nature, correlates, and probable causes of these community differences. Unfortunately, previous studies have been limited in an important way. Virtually all studies of communities and crime are based on large urban areas, almost totally excluding nonmetropolitan areas—that is, rural areas and smaller cities and towns. The findings in this Bulletin help to fill some gaps in the research by examining variations in rates of juvenile violence across nonmetropolitan communities in Florida, Georgia, Nebraska, and South Carolina. Social disorganization is the primary theory by which criminologists account for rates of crime in urban communities. If this theory also applies to rural settings, then what is known about crime in urban areas can provide a basis for developing programs that address the problem of delinquency in smaller communities. The research presented in this Bulletin indicates that the principles of social disorganization theory hold up quite well in rural settings. As in urban areas, rates of juvenile violence are considerably higher in rural communities that have a large percentage of children living in single-parent households, a high rate of population turnover, and significant ethnic diversity. These factors, it should be noted, are statistical correlates and not causes of such violence; nor are they the only correlates

Poisson-based regression analysis of aggregate crime rates.

This article introduces the use of regression models based on the Poisson distribution as a tool for resolving common problems in analyzing aggregate crime rates. When the population size of an aggregate unit is small relative to the offense rate, crime rates must be computed from a small number of offenses. Such data are ill-suited to least-squares analysis. Poisson-based regression models of counts of offenses are preferable because they are built on assumptions about error distributions that are consistent with the nature of event counts. A simple elaboration transforms the Poisson model of offense counts to a model of per capita offense rates. To demonstrate the use and advantages of this method, this article presents analyses of juvenile arrest rates for robbery in 264 nonmetropolitan counties in four states. The negative binomial variant of Poisson regression effectively resolved difficulties that arise in ordinary least-squares analyses

Book reviews

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45374/1/11031_2004_Article_BF00992995.pd

Vulnerable Populations and the Transition to Adulthood

D. Wayne Osgood, E. Michael Foster, and Mark E. Courtney examine the transition to adulthood for youth involved in social service and justice systems during childhood and adolescence. They survey the challenges faced by youth in the mental health system, the foster care system, the juvenile justice system, the criminal justice system, and special education, and by youth with physical disabilities and chronic illness, as well as runaway and homeless youth

EXPLAINING THE RELATIONSHIP BETWEEN EMPLOYMENT AND JUVENILE DELINQUENCY*

Most criminological theories predict an inverse relationship between employment and crime, but teenagers' involvement in paid work during the school year is positively correlated with delinquency and substance use. Whether the work-delinquency association is causal or spurious has long been debated. This study estimates the effect of paid work on juvenile delinquency using longitudinal data from the national Monitoring the Future project. We address issues of spuriousness by using a two-level hierarchical model to estimate the relationships of within-individual changes in juvenile delinquency and substance use to those in paid work and other explanatory variables. We also disentangle effects of actual employment from preferences for employment to provide insight about the likely role of time-varying selection factors tied to employment, delinquency, school engagement, and leisure activities. Whereas causal effects of employment would produce differences based on whether and how many hours respondents worked, we found significantly higher rates of crime and substance use among non-employed youth who preferred intensive versus moderate work. Our findings suggest the relationship between high-intensity work and delinquency results from preexisting factors that lead youth to desire varying levels of employment

Community Correlates of Rural Youth Violence

Rates of crime and delinquency vary widely across communities, and research going back many decades provides a good understanding of the nature, correlates, and probable causes of these community differences. Unfortunately, previous studies have been limited in an important way. Virtually all studies of communities and crime are based on large urban areas, almost totally excluding nonmetropolitan areas—that is, rural areas and smaller cities and towns. The findings in this Bulletin help to fill some gaps in the research by examining variations in rates of juvenile violence across nonmetropolitan communities in Florida, Georgia, Nebraska, and South Carolina. Social disorganization is the primary theory by which criminologists account for rates of crime in urban communities. If this theory also applies to rural settings, then what is known about crime in urban areas can provide a basis for developing programs that address the problem of delinquency in smaller communities. The research presented in this Bulletin indicates that the principles of social disorganization theory hold up quite well in rural settings. As in urban areas, rates of juvenile violence are considerably higher in rural communities that have a large percentage of children living in single-parent households, a high rate of population turnover, and significant ethnic diversity. These factors, it should be noted, are statistical correlates and not causes of such violence; nor are they the only correlates

Social Disorganization Outside the Metropolis: An Analysis of Rural Youth Violence

In order to extend the study of community social disorganization and crime beyond its exclusive focus on large urban centers, we present an analysis of structural correlates of arrest rates for juvenile violence in 264 nonmetropolitan counties of four states. Findings support the generality of social disorganization theory: Juvenile violence was associated with rates of residential instability, family disruption, and ethnic heterogeneity. Though rates of poverty were not related to juvenile violence, this is also in accord with social disorganization theory because, unlike urban settings, poverty was negatively related to residential instability. Rates of juvenile violence varied markedly with population size through a curvilinear relationship in which counties with the smallest juvenile populations had exceptionally low arrest rates. Analyses used negative binomial regression (a variation of Poisson regression) because the small number of arrests in many counties meant that arrest rates would be ill suited to least-squares regression