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This article reports rates of recidivism among initially substantiated and initially unsubstantiated child maltreatment events to determine if substantiation status is associated with higher risk of recidivism. This is an important question given recent concerns that unsubstantiated cases may have as high or almost as high a risk of recidivism as do substantiated cases. The data are analyzed at both the victim level and the case level, divided by type of maltreatment, and followed for 4.5 years. The data used are administrative and combine a series of state databases with census data. Analyses are performed at the bivariate and multivariate (Cox proportional hazards model) levels. The main finding is that unsubstantiated cases are at high risk for recidivism, in many cases as high a risk as substantiated cases. Implications for practice, policy, and research are presented with a focus on the importance of providing preventative services to unsubstantiated cases.

Politicians, armed with opinion polls for support, rush to enact crime bills where sentences grow steeper, where higher minimum sentences are made mandatory, and where the death sentence is applied in more cases. Despite apparent support from suspect polls, the empirical question remains: Does community sentiment favor "steeper-firmer-deadlier" punishments that are disproportionate to the act and invariate to the actors, or does sentiment favor individualized and proportionate punishment? In experiments dealing with recidivist, accessory felony-murder, and perpetrator-by-means cases—where the law asks for excessive or invariate punishment—subjects favor proportional and individualized punishment and judge defendants based on perceived culpability.

AbstractUsing administrative and survey data from Georgia, this chapter examines the risk factors for recidivism among welfare leavers and the relationship between recidivism and leavers' ability to find sustained employment.

This article discusses the application of latent Markov modelling for the analysis of recidivism data. We briefly examine the relations of Markov modelling with log–linear analysis, pointing out pertinent differences as well. We show how the restrictive Markov model may be more easily applicable by adding latent variables to the model, in which case the latent Markov model is a dynamic version of the latent class model. As an illustration, we apply latent Markov analysis on an empirical data set of juvenile prosecution careers, showing how the Markov analyses producing well‐fitting and interpretable solutions. We end by comparing the possible contributions of Markov modelling in recidivism research, outlining its drawbacks as well. Recommendations and directions for future research conclude the article.

In 1995, the Texas Legislature enacted H. B. 1863, which formed the basis for Texas' waiver from existing Federal laws governing the Aid to Families with Dependent Children (AFDC) program. This paper discusses policy recommendations to reduce welfare recidivism and to reinforce the efforts of poor Texas families to avoid receipt of AFDC. ; Texas Department of Human Services ; Ray Marshall Center for the Study of Human Resources

With welfare reform soundly launched and its effects already praised, it is time to examine its impact on former welfare recipients. A typology of adaptation to welfare—comprising dependency, supplementation, self-reliance, and autonomy—was developed based on former welfare recipients' financial status and employment status. An examination was also made of ways in which welfare recipients changed from more independent modes of adaptation (autonomy and self-reliance) to less independent modes (supplementation and dependency). Using longitudinal data extracted from a U. S. Department of Labor survey, event history analysis was applied to investigate changes in adaptation mode and factors contributing to these changes, among former welfare recipients across a period of 1 8 years. The investigation found that return to welfare was uncommon. Furthermore, the results show that nonpoor former recipients most often joined the ranks of the working poor because of welfare reform, ethnicity, education level, occupational skills, family income, housing subsidy, child care, and prior experience in welfare use. Some nonpoor former recipients who spent long spells in welfare returned to welfare because they suffered income reductions and needed food stamps. Working poor former recipients were likely to become nonpoor if they were married and had no need for child care or food stamps. Working poor White, single mothers with little work experience and little child support were likely to return to welfare and become further dependent on it.