Recidivism and treatment attrition among persons who sexually offend (PSOs): applying the integrated risk assessment and treatment system (IRATS)
Bibliographic record
Abstract
The aim of this thesis was to investigate whether the Integrated Risk Assessment and Treatment System (IRATS; Looman & Abracen, 2013) can provide an explanatory framework for understanding persons who sexually offend (PSOs). The IRATS is comprised of several overarching components: Deviant Sexual Arousal, Psychological Vulnerability, and Criminality. Study 1 investigated whether the IRATS components predict the likelihood that an incarcerated sample of PSOs will engage in sexual recidivism. This sample consisted of convicted PSOs who were assessed at the Regional Treatment Centre High Intensity Sex Offender Treatment Program (RTCSOTP), provided by the Correctional Service of Canada (CSC). Study 2 investigated whether the IRATS components predict the likelihood that a community sample of PSOs will terminate their treatment prematurely. This sample consisted of PSOs who were assessed at the Sexual Behaviours Clinic (SBC) at the Centre for Addiction and Mental Health (CAMH). The results of both studies indicated that the three components, together, significantly predict the outcomes of interest, and the Criminality component appears to drive this relationship. Implications of these findings are discussed herein.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".