MARKOV CHAIN ANALYSIS AND SPECIALIZATION IN CRIMINAL CAREERS

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Abstract
This paper investigates whether the longitudinal sequences of types of offences committed in criminal careers can be treated as a stationary first-order Markov chain. The sample consisted of 698 English male prisoners who had each been convicted of at least two standard list offences. In agreement with the Markov chain hypothesis, the probability of switching from one offence to another remained constant over successive convictions. However, contrary to this hypothesis, the past history of types of offences helped in predicting future types of offences, suggesting that there was some specialization in offending. The forward specialization coefficient confirmed and quantified this. Sex offenders were the most specialized, and the most persistent offenders became increasingly specialized in fraud. A study of the extent to which one sentence followed another revealed the stepping-stone nature of the sentencing tariff.

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