Sexual Offender Treatment | ISSN 1862−2941 Predictive Validity of the Static−99 and Static−2002 for Sex Offenders on Community Supervision
Bibliographic record
Abstract
The Static−99 is the most commonly used actuarial tool for sexual offenders. Although it has shown acceptable predictive accuracy in a large number of studies, all these studies involved researchers scoring the instrument retrospectively. Consequently, it is unclear whether similar results would be obtained when used in routine practice. The authors of the Static−99 have proposed a new scale, the Static−2002, but there has been insufficient research to determine whether it is an improvement over the Static−99. This study examined the predictive accuracy of the Static−99 in a prospective study of 706 Canadian sexual offenders on community supervision. All assessments were conducted by the probation and parole officers responsible for supervising the cases. The Static−99 was compared with the Static−2002, which was scored retrospectively from criminal history records. After an average 3 year follow−up, the Static−99 and Static−2002 were equally accurate in predicting sexual recidivism (ROC of.76 for both). The Static−2002, however, was better than the Static−99 at predicting violent and general recidivism. There were no significant differences in the accuracy of the measures for rapists, child molesters, or non−contact offenders. Overall, the Static−99 and Static−2002 are both reliable and valid measures of recidivism risk for sexual
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.007 | 0.001 |
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".