Development of Vermont Assessment of Sex Offender Risk-2 (VASOR-2) Reoffense Risk Scale
Bibliographic record
Abstract
The present study aimed to revise the Vermont Assessment of Sex Offender Risk (VASOR) Reoffense Risk Scale, a commonly used sex offender risk assessment tool. The revised tool was named the VASOR-2. Among models tested to revise the scale, a logistic regression model showed the best balance between simplicity of use, goodness of fit, and internal validity (as tested with K-10 cross-validation), and maximized predictive accuracy. Predictive accuracy was tested using four meta-analytically combined data sets drawn from Canada and Vermont (N = 1,581). At 5-year fixed follow-up, the predictive accuracy for sexual recidivism for VASOR-2 (AUC = .74) was similar to the VASOR (AUC = .71). The findings show the VASOR-2 is well calibrated with observed recidivism rates for all but the highest risk sex offenders. The instrument showed good interrater reliability (ICC = .88). An advantage of the VASOR-2 is that it has fewer items and simpler scoring instructions than the VASOR. Norms are presented for a contemporary, nonselected, routine sample of Vermont sex offenders (n = 887).
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".