Offender Risk Assessment and Sentencing

I would like to thank the editors of this special issue of the Canadian Journal of Criminology and Criminal Justice examining risk assessment and sentencing for inviting me to comment on the three articles that form the basis of the issue. I was surprised that the editors asked someone who for years has collaborated with Don Andrews and is, therefore, likely to provide a commentary that may not be very much different than one Andrews would write. I did disclose to the editors my close working relationship with him, and I would like the readers to know of my bias. Nevertheless, the editors felt that I might have something substantive to contribute to the discussion and asked me to write this commentary. Differentiating offenders in terms of their risk to re-offend has been a major preoccupation of corrections ever since Burgess developed a simple, actuarial measure in 1928 to assess who is a good risk for parole and who is not. However, it was not until the 1970s that social scientists took the risk-assessment business seriously and began to develop objective assessment instruments that yielded predictive accuracies surpassing the judgements of psychiatrists, psychologists, and social workers. The most important advance in offender risk assessment came from the work of Don Andrews and his colleagues, first seen in the 1980s (Andrews 1982) and elaborated in the 1990s (Andrews, Bonta, and Hoge 1990; Andrews and Bonta 1994). This was the integration of dynamic risk factors (or criminogenic needs) with static risk factors in risk/need instruments such as the Level of Service Inventory--Revised (LSI-R; Andrews and Bonta 1995). The use of evidence-based risk/need-assessment instruments in corrections has exploded in the last decade. All but two Canadian provincial and territorial correctional systems use an empirically defensible offender risk/need instrument, and the remaining two jurisdictions (Alberta and Quebec) are in the process of implementing such instruments (a similar trend is seen in the United States and the United Kingdom as well as other countries around the world). The value of risk/need instruments is not limited to decisions around who should be supervised more closely or who should be kept in custody for the protection of the public. Because these instruments also sample criminogenic needs, they can be used to direct rehabilitation services in order to reduce offender risk. The value of objective risk/needs instruments is readily apparent to correctional agencies. The question that the three papers here raise is whether risk/needs instruments have a place in pre-sentencing decisions. Andrews and Dowden argue that there is value in the courts' considering risk/need assessments, whereas Maurutto, Hannah-Moffat, and Cole are much more wary of a role for these instruments in the sentencing process. An exercise in knowledge destruction Rational empiricists highly value and respect evidence. It is systematic, objective, replicable evidence that makes or breaks a theory. Without a strong respect for evidence, we are left with personal, ideological explanations of a phenomenon. It is difficult for people, and scientists, to give up on notions that they have cultivated for years, as empirical evidence to the contrary grows. Look at how we have dealt with the issue of climate change. Although the alarm bells were sounded more than 30 years ago, it was not until this year that a consensus report from scientists from around the world unequivocally concluded that human beings have had a hand in climate change. How does one remain committed to a viewpoint that is contrary to evidence? The answer is to engage in knowledge-destruction techniques (Andrews and Bonta 2006). That is, adopt only that knowledge that supports one's position and discard knowledge to the contrary. The Maurutto and Hannah-Moffat article questions the very validity of risk/needs instruments, thereby pre-empting consideration of whether there is a useful role for these instruments in the sentencing process. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.