A multisite examination of sexual violence risk and therapeutic change.
Bibliographic record
Abstract
OBJECTIVE: We conducted a prospective multisite examination of sexual offender risk and treatment change on a large federal Canadian sample of 676 treated sex offenders followed up for an average of 6.31 years post release. METHOD: The present study featured the clinical application of a risk assessment and treatment planning tool, the Violence Risk Scale-Sexual Offender version (VRS-SO; Wong, Olver, Nicholaichuk, & Gordon, 2003). The VRS-SO was rated pre- and posttreatment by sex offender treatment providers on the sample of men who were attending institutionally based sex offender programs across the 5 regions of the Correctional Service of Canada. The Static-99 (Hanson & Thornton, 1999) was also rated as part of routine services, and the Static-99R was used for substantive analyses. RESULTS: The VRS-SO dynamic factors and the Static-99R demonstrated significant predictive accuracy for sexual, violent, and general recidivism (area under the curve = .65 to .78). Significant pre-post changes on the VRS-SO dynamic factors were observed, ranging from small to moderate in magnitude (d = 0.22 to 0.62) across low, moderate, and high intensity programs. The change scores, in turn, were associated with decreases in the 3 recidivism outcomes; the majority of relationships examined attained significance after partialing out of pretreatment scores. Cox regression survival analyses, controlling for pretreatment risk, further demonstrated change scores to have associations with postrelease recidivism outcomes to varying degrees. CONCLUSIONS: The results are consistent with the dynamic nature of sexual violence risk and suggest that risk-relevant changes associated with participation in sexual offender treatment are linked to reductions in sexual offender recidivism.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".