The dynamic prediction of criminal recidivism: A three-wave prospective study.
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
A three-wave, prospective panel design was used to assess the extent to which static and dynamic risk factors could predict criminal recidivism in a sample of 136 adult male offenders released from Canadian federal prisons. Static measures were assessed only once, prior to release while dynamic measures were assessed on three separate occasions: pre-release, 1 month, and 3 months post-release. Recidivism was coded during an average of 10.2-month follow-up period (SD=19.2). A series of Cox regression survival analyses with time-dependent covariates and Receiver Operator Characteristic (ROC) analyses were conducted to assess predictive validity. Although the combined static and time-dependent dynamic model (AUC=.89, CI=.81-.93) significantly (p<.01) outperformed the pure static model (AUC=.81, CI=.73-.87) the confidence intervals did overlap to some extent. Implications for dynamic risk assessment and management are discussed.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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