Interpreting multiple risk scales for sex offenders: Evidence for averaging.
Bibliographic record
Abstract
This study tested 3 decision rules for combining actuarial risk instruments for sex offenders into an overall evaluation of risk. Based on a 9-year follow-up of 940 adult male sex offenders, we found that Rapid Risk Assessment for Sex Offender Recidivism (RRASOR), Static-99R, and Static-2002R predicted sexual, violent, and general recidivism and provided incremental information for the prediction of all 3 outcomes. Consistent with previous findings, the incremental effect of RRASOR was positive for sexual recidivism but negative for violent and general recidivism. Averaging risk ratios was a promising approach to combining these risk scales, showing good calibration between predicted (E) and observed (O) recidivism rates (E/O index = 0.93, 95% CI [0.79, 1.09]) and good discrimination (area under the curve = 0.73, 95% CI [0.69, 0.77]) for sexual recidivism. As expected, choosing the lowest (least risky) risk tool resulted in underestimated sexual recidivism rates (E/O = 0.67, 95% CI [0.57, 0.79]) and choosing the highest (riskiest) resulted in overestimated risk (E/O = 1.37, 95% CI [1.17, 1.60]). For the prediction of violent and general recidivism, the combination rules provided similar or lower discrimination compared with relying solely on the Static-99R or Static-2002R. The current results support an averaging approach and underscore the importance of understanding the constructs assessed by violence risk measures.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".