A criminal career is the longitudinal sequence of offences committed by an individual in his life course. Given the complexity of human behavior, quantitative and predictive models are rarely proposed in criminological psychology research. Few previous works have attempted to create mathematical models of continuity in offending i.e. recidivism through a “memorylessness” first-order Markov chain. Given that criminal careers literature, as well as risk assessment studies, have demonstrated the importance of past offences in triggering future criminal involvement, in the present paper we aim to propose a “memoryfulness” perspective which takes into account the individual offending history. We consider an agent-based model of criminal careers in which persistence in the same state reinforces itself. Our model is developed by replicating and testing two models of recidivism presented in mathematical criminology.

The lingering effects of past crimes over future criminal careers

Merlone U.
;
Manassero E.
;
Zara G.
2016-01-01

Abstract

A criminal career is the longitudinal sequence of offences committed by an individual in his life course. Given the complexity of human behavior, quantitative and predictive models are rarely proposed in criminological psychology research. Few previous works have attempted to create mathematical models of continuity in offending i.e. recidivism through a “memorylessness” first-order Markov chain. Given that criminal careers literature, as well as risk assessment studies, have demonstrated the importance of past offences in triggering future criminal involvement, in the present paper we aim to propose a “memoryfulness” perspective which takes into account the individual offending history. We consider an agent-based model of criminal careers in which persistence in the same state reinforces itself. Our model is developed by replicating and testing two models of recidivism presented in mathematical criminology.
2016
Proceedings of the 2016 Winter Simulation Conference.
Crystal Gateway Marriott Arlington, United States
11-14 December 2016
2016 Winter Simulation Conference (WSC)
IEEE
3532
3543
Merlone, U., Manassero, E., Zara, G.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1743294
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