R. Karl Hanson and Kelly Morton-Bourgon Public Safety and Emergency Preparedness Canada Predictors of Sexual Recidivism: An Updated Meta-Analysis
Why this work is in the frame
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Bibliographic record
Abstract
This quantitative review examined the research evidence concerning recidivism risk factors for sexual offenders. A total of 95 different studies were examined, involving more than 31,000 sexual offenders and close to 2000 recidivism predictions. The results confirmed deviant sexual interests and antisocial orientation as important predictors of sexual recidivism. Antisocial orientation (e.g., unstable lifestyle, history of rule violation) was a particularly important predictor of violent non-sexual recidivism and general recidivism. The study also identified a number of new predictor variables, some of which have the potential of being useful targets for intervention (e.g., sexual preoccupations, conflicts in intimate relationships, emotional identification with children, hostility). Actuarial risk instruments were consistently more accurate than unguided clinical opinion in predicting sexual, violent nonsexual and general recidivism. For the prediction of sexual recidivism, there were no significant differences in the predictive accuracy of the various actuarial measures (e.g., SORAG, Static-99). Actuarial measures designed to predict general (any) criminal recidivism were strong predictors of general recidivism among sexual offenders. 1 Predictors of Sexual Recidivism: An Updated Meta-Analysis Sex offences are among the crimes that invoke the most public concern. Consequently, it is not
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it