The Generalizability of the LSI-R and the Cat To the Prediction of Recidivism in Female Offenders
Bibliographic record
Abstract
The prediction of recidivism of female offenders has lagged behind that of their male counterparts. The present study was designed to extend the work of previous research on the Level of Service Inventory—Revised (LSI-R) and to examine the utility of another measure—the Childhood and Adolescent Taxon Scale (CAT)—in the prediction of recidivism among female offenders. Participants, 100 female offenders serving sentences of more than 2 years in Canada, completed a self-report version of both instruments. Results indicated acceptable reliability and predictive validity for both measures, and both measures distinguished recidivists from nonrecidivists. Results are discussed in light of previous research and future directions for the examination of the prediction of recidivism among female offenders.
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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 | 0.000 |
| 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 | 0.001 |
| 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 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".