Summary
Aim
The current research describes the development of a technique known as the Group Risk Assessment Model (GRAM), which adjusts for the characteristics of offenders coming before the courts in order to obtain more accurate estimates of trends in re-offending over time.
Abstract
Internationally, governments are making renewed efforts to reduce rates of re-offending. Measuring progress against this objective is difficult because officially recorded reconviction rates are determined not only by how effective the justice system is in dealing with offenders but also by the characteristics of offenders coming to court in the first place. The current research describes the development of a technique known as the Group Risk Assessment Model (GRAM), which adjusts for the characteristics of offenders coming before the courts in order to obtain more accurate estimates of trends in re-offending over time. Separate logistic regression models were developed for juvenile and adult offenders given non-custodial sanctions in 2002. For juvenile offenders, age, sex, Indigenous status, prior convictions and concurrent convictions were found to be highly predictive of subsequent reconviction. For adult offenders, these same offender characteristics, in combination with the jurisdiction in which the offender was dealt with and the offenders’ most serious index offence, were found to provide a good model of reconviction likelihood. An application of the models in relation to the 2003 and 2004 adult and juvenile offender cohorts revealed that there had been a statistically significant decrease in rates of reconviction among juveniles convicted in 2004 but not among adults convicted in 2004. The observed reconviction rates among the 2003 adult or juvenile cohorts were not significantly different from the expected rates given the characteristics of those cohorts.