A broad research literature in criminology documents key aspects of how criminal offending develops and changes over the life span. We contribute to this literature by showcasing methods that are useful for studying medium-term patterns of subsequent criminal justice system involvement among a sample of serious adolescent offenders making the transition to early adulthood.
Our approach relies on 7 years of post-enrollment follow-up from the Pathways to Desistance Study. Each person in the study was adjudicated delinquent for or convicted of one or more relatively serious offenses during adolescence. Their local jurisdiction juvenile court petition records and their adult FBI arrest records were systematically searched.
We estimate in-sample 7 year recidivism rates in the 75–80 % range. Our analysis also provides recidivism rate estimates among different demographic groups within the sample. Extrapolated long-term recidivism rates are estimated to be on the order of 79–89 %.
The Pathways data suggest that recidivism rates of serious adolescent offenders are high and quite comparable to the rates estimated on other samples of serious offenders in the extant literature. Our analysis also reveals a pattern of heightened recidivism risk during the earliest months and years of the follow-up period followed by a steep decline.
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We also considered but do not report in detail the results of fitting a split-population Weibull specification. The Weibull distribution is a generalization of the exponential distribution in that it allows for either a monotonically increasing or monotonically decreasing hazard rate. In criminal recidivism data, we generally expect to find evidence for a monotonically decreasing hazard rate—a pattern that is strongly evident in the Pathways data. Our analysis reveals that the fits of the split-population Weibull and split-population exponential models are statistically indistinguishable (a likelihood ratio test comparing the two models with 1° of freedom yields a Chi square value of 2.566 which is not statistically significant). Both models also result in an estimated 79 % long-term recidivism rate. This result suggests that the split-population exponential model is sufficient to capture the monotonic patterns in the waiting time distribution.
As noted previously, we were unable to detect a significant difference between the split-population exponential and split-population Weibull specifications. This result suggests that an allowance for a genuinely monotonically declining hazard rate among persisters does not improve on the fit of the more restrictive split-population exponential model.
An anonymous reviewer cautions that a survival time model only measures the time to the next event, not the "rearrest rate". We concede this point but also note that when events occur more frequently, then the average waiting time between events will be shorter (Schmidt and Witte 1988: p. 92). In a Poisson process, for example, if μ measures the rate at which new arrests occur, then 1/μ measures the average waiting time between successive arrests (see also, Barnett et al. 1987a, b, 1989 for more discussion of this point).
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This study was supported by funds from the following: the Office of Juvenile Justice and Delinquency Prevention (2007-MU-FX-0002), National Institute of Justice (2008-IJ-CX-0023), John D. and Catherine T. MacArthur Foundation, William T. Grant Foundation, Robert Wood Johnson Foundation, William Penn Foundation, Center for Disease Control, National Institute on Drug Abuse (R01DA019697), Pennsylvania Commission on Crime and Delinquency, and Arizona Governors Justice Commission. We are grateful for their support. The content of this paper, however, is solely the responsibility of the authors and does not necessarily represent the official views of these agencies.
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Brame, R., Mulvey, E.P., Schubert, C.A. et al. Recidivism in a Sample of Serious Adolescent Offenders. J Quant Criminol 34, 167–187 (2018). https://doi.org/10.1007/s10940-016-9329-2