Predicting recidivism amongst sexual offenders: A multi-site study of Static-2002.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The predictive accuracy of Static-2002 (Hanson & Thornton, Notes on the development of Static-2002 (Corrections Research User Report No. 2003-01), 2003) was examined in eight samples of sexual offenders (five Canadian, one U.S., one U.K., one Danish; total sample of 3,034). Static-2002 showed moderate ability to rank order the risk for sexual, violent and general (any) recidivism (AUCs of .68, .71, and .70, respectively), and was more accurate than Static-99. These findings support the use of Static-2002 in applied assessments. There were substantial differences across samples, however, in the observed sexual recidivism rates. These differences present new challenges to evaluators wishing to use actuarial risk scores to estimate absolute recidivism rates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 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 it