Predicting Recidivism in Sex Offenders Using the SVR-20: The Contribution of Age-at-release
Bibliographic record
Abstract
Sex offenders (N = 468) were released from custody and recidivism outcome was recorded. The Sexual Violence Risk-20 (SVR-20) was scored for each offender and the relationship between age-at-release and SVR-20 item and total scores was examined. SVR-20 total scores were not correlated with age-at-release (r = .-057). SVR-20 scores were combined with a score representing the age of the offender at their release from custody. On the basis of ROC analysis, predictive accuracy was significantly enhanced when age-atrelease was included in the risk score. We suggest that the SVR-20, and perhaps other similar risk instruments, could be improved by including age-at-release information. We discuss the possibility that the advantage obtained by empirical actuarial instruments may be due in part to their close relation with age-at-release.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".