Notice bibliographique
Résumé
Cheryl Webster, Rosemary Gartner, and Anthony Doob have criticized as fatally flawed our study Lifetime Sex Offender Recidivism: A 25-Year Follow-Up Study, which appeared in this journal in October 2004. Their conclusions, however, are based on major omissions of facts, both from our study and from the world literature; careless and inappropriate comparisons of data; and what appears to be an unfamiliarity with the practice of forensic psychiatry and psychology as it applies to sex offenders. Following are some of the problems with the critique that led to their conclusions. Sexual offending as a temporary problem Webster et al. (2006) seem unaware of current pessimism among treatment providers of sex offenders and open their critique as follows: Despite the persistent notion that sex offenders have a lasting--perhaps even incurable--propensity to commit further sexual offences, this belief has not been borne out by empirical studies, and quote a number of short-term follow-up studies to suggest that reoffending rates are generally low for sex offenders (80). Interestingly, they quote work by R. Karl Hanson, Ian Broom, and Marylee Stephenson (2004) later in their critique but do not mention here that these authors reported a difference of less than 1% in recidivism rates for treated and untreated sex offenders in a 12-year follow-up study, a statistically non-significant finding. Relapse prevention therapy is the most commonly used treatment today; its major premise is that sexual offending can be managed, but there are no promises of cure. The work of Janice Marques, Mark Wiederanders, David M. Day, Craig Nelson, and Alice van Ommeren (2005), who conducted one of the longest follow-up treatment studies to date using a randomized design, is not mentioned; their conclusions indicate that current treatment is ineffective. Results of all treatment efforts with sex offenders over the past 40 years appear to suggest that sexual offending is a persistent problem. Our sample indicated that the problem persisted, on average, for almost two decades. It does not help offenders to promote the belief that their problem of sex offending will go away in short order. Convictions versus undetected crimes Our study examined lifetime recidivism rates among various sex offender groups and evaluated the effects of data sources and criterion measures used in calculating recidivism rates, irrespective of any treatment intervention. We examined seven indices of recidivism: (1) charges for all offences, (2) convictions for all offences, (3) charges for sexual offences, (4) convictions for sexual offences, (5) number of separate court appearances for all offences, (6) number of separate court appearances for sexual offences, and (7) all sex offences including undetected crimes. We examined the offenders from the earliest known crimes to the most recent. Webster et al. have selected only one recidivism measure from those presented in our article and make an inappropriate comparison to recidivism statistics reported by others. In particular, they emphasize the 88.3% recidivism rate for (7) all sex offences including undetected crimes, a category that includes all official crimes as well as undetected/unreported sexual offences. They compare this to a number of short-term follow-up studies that report reoffending or re-conviction rates ranging from 6% to 24%--statistics that do not include undetected crimes (see Hanson and Morton-Bourgon 2004). Because the rate including undetected crimes can only be greater than the rate for convictions, one cannot ask if it will be greater, only by how much. A more appropriate comparison from our data might be with (4), the 61.1% who recidivated based on a sex offence reconviction. Interestingly, Webster et al. later suggest that the 88.3% is too low based on the type of study we did. They quote a study by Roger Boe, Mark Nafekh, Ben Vuong, Roberta Sinclair, and Colette Cousineau (2003) that found that 91% of federal inmates in Canada have served prior youth and/or adult sentences within a five-year period! …
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 | 0,011 | 0,055 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,006 |
| Communication savante | 0,005 | 0,008 |
| Science ouverte | 0,005 | 0,004 |
| Intégrité de la recherche | 0,041 | 0,073 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,006 |
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 ».