Developing an empirical classification of violent offences for use in the prediction of recidivism in England and Wales

Abstract

PurposeThe classification of criminal acts as violent or nonviolent should be a keystone of actuarial predictors of violent recidivism, as it affects their outcome measure and scoring of criminal history, thus influencing many decisions about sentencing, release and treatment allocation. Examination of existing actuarial and clinical violence risk assessment tools and research studies reveals considerable variation in the classifications used. This paper aims to use large samples to develop an alternative, empirically grounded classification that can be used to improve actuarial predictive scores within the offender assessment system (OASys), the tool used by the National Offender Management Service of England and Wales to assess static and dynamic risk.Design/methodology/approachTwo analytical steps are implemented. First, to identify offences that frequently involve violent acts, 230,334 OASys cases are analyzed for indicators of violent content. Second, the ability of dynamic and static risk factors to predict reoffending for various offence types is investigated, analyzing 26,619 OASys cases that have official recidivism data.FindingsThe resulting empirical classification of violent offences adds public order, criminal damage, threats/harassment, robbery/aggravated burglary and weapon possession offences to the central group of homicide and assault offences. The need to assess risk of sexual recidivism separately is discussed.Originality/valueThis study has successfully produced an offence classification for use in a new predictor of violent recidivism. The use of empirical methods to select these offences helps to maximise predictive validity.