Maltz and McCleary present a model to describe recidivism based on two premises: that the parolee population will divide according to those who will recidivate and those who will not and that the likelihood of recidivism can be described by a negative exponential function. They contrast their model with that given previously by Stollmack and Harris (1974) and show that the difference between the two is the first premise. This yields the following two parameterizations: P(t) = 1 - exp(-at) (Stollmack-Harris) and P (t) = rx 1 - exp(-at) (Maltz-McCleary). P(t) is the probability that a particular parolee will be returned to prison before time t; a is the failure rate, and r is the proportion of the parolee population that will ever fail. Maltz and McCleary present data (from Taylor, 1971) which shows that neither model fits the data very well (although Maltz and McCleary do not conclude this). An extension of the Maltz-McCleary model is proposed. The extension derives from the assumption that the speed of recidivism is proportional to the number of persons left to recidivate. This yields an additive constant to the exponent of the Maltz-McCleary model that allows the model to fit Taylor's data rather well. Uses for the model are briefly discussed. Tabular and graphic data and six references are provided.
Downloads
Similar Publications
- Face Recognition Accuracy of Forensic Examiners, Superrecognizers, and Face Recognition Algorithms
- Best Practices for Improving the Use of Criminal Justice Risk Assessments: Insights from the National Institute of Justice’s 2021 Recidivism Forecasting Challenge Winners Symposium
- Imperfect Tools: A Research Note on Developing, Applying, and Increasing Understanding of Criminal Justice Risk Assessments