Response to Commentary: Cross-Examining Risk “Knowledge”
Notice bibliographique
Résumé
Proportionality, as stipulated in the 2003 Youth Criminal Justice Act (YCJA), sets out the parameters within which we examine the implications of embedding assessments within youth pre-sentence reports (PSRs). Our article raises questions for academic and legal professionals and, ultimately, judges, who may or may not elect to consider risk/need assessments in the determination of a sentence. The sentencing principles contained in section 38(2) stipulate that (c) the sentence must be proportionate to the of the offence and the of of the young person for that offence; and that (e) subject to [the aforementioned] paragraph (c), the sentence must (ii) be the one that is most likely to rehabilitate the young person and reintegrate him or her into society. (emphasis added) The YCJA is unequivocal in the priority afforded to proportionality. By contrast, rehabilitation, albeit important, is of less relevance to sentencing. We do not dispute the importance or impact of treatment and rehabilitative approaches in the management of offenders. Our concern is with whether the use of risk-assessment information sentencing contravenes the principle of proportionality and/or disparity. The seriousness of the the of harm caused, and the youth's degree of responsibility are central to proportionality, but not to the assessment of risk. Risk assessments are designed to identify factors and criminogenic needs that can be targeted through treatment in an effort to prevent, or more accurately, to minimize a predicted of re-offence. Risk introduces a future-oriented model, wherein punishment is determined on the calculation of scores and the predicted likelihood that the accused will recidivate. Risk scores may well be able to identify a group of offenders who are more likely to recidivate, but not everyone in the group will with certainty do so. Prediction of recidivism is not definitive. There is no absolute certainty that an offender will re-offend, or re-offend with the same of seriousness. In fact, our research indicates that assessments are more likely to target those most likely to breach conditions, a relatively minor criminal offence, and are less reliable in predicting who will commit a serious violent offence. Further, not all of the risk-assessment practices used in Canada rely on empirically tested tools (Hannah-Moffat and Maurutto 2003). The prediction of in the medical context is quite distinct from in the criminal-justice sphere. In the medical context, where patients have the choice to determine their course of treatment, pre-emptive interventions may be the optimal course of action, even though there is no certainty of disease. By contrast, in the legal system, such pre-emptive intervention would contravene the YCJA, as well as our collective rights as set out in the Canadian Charter of Rights and Freedoms. Both sets of legislation restrict the ability of the courts to impose punishment on the anticipation of a threat or on the basis of an offender's criminogenic needs. Moreover, information can result in more punitive dispositions for those youth exhibiting greater needs. Marginalized youth, whose lives tend to be mired in a range of criminogenic and other needs, are more likely to score as high-risk. As a result, they are at risk of receiving longer custodial sentences and/or a greater number of conditions attached to their disposition, making them more vulnerable to breach, increased surveillance, and further criminalization. Risk assessments are not as transparent or as objective as presumed. Risk assessments include a range of discretionary and arbitrary decisions that are obscured in the presentation of PSRs (cf., Rose 1998; Maurutto and Hannah-Moffat 2006). Crowns, defence and duty counsel, judges, and many writers of PSRs are rarely attuned to how far subjective judgements frame PSRs and, consequently, rarely contest this information. …
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.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,079 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,007 | 0,008 |
| Communication savante | 0,005 | 0,006 |
| Science ouverte | 0,010 | 0,005 |
| Intégrité de la recherche | 0,092 | 0,076 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,017 | 0,013 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».