The Predictive and Incremental Validity of Two Self-Report Risk Assessment Measures With Adult Male Offenders Who Have Mental Health Problems
Bibliographic record
Abstract
We examined the predictive and incremental validity of two self-report risk assessment measures—the Self-Appraisal Questionnaire (SAQ) and the Measure of Criminal Attitudes and Associates (MCAA)—in a sample of 121 adult male offenders, with mental health problems in a correctional treatment setting. Both the SAQ and MCAA were significantly and positively correlated with a standard risk/need assessment currently used in corrections, the Level of Service Inventory–Ontario Revision (LSI-OR). All three risk measures significantly predicted general recidivism within 1 year of follow-up. The SAQ and LSI-OR also significantly predicted institutional incidents (threat, verbal aggression, or assault). In addition, the MCAA significantly added to the prediction of general recidivism provided by the LSI-OR, whereas the SAQ did not, likely reflecting the relatively high content overlap of the SAQ and LSI-OR. Neither self-report measure added to the ability of the LSI-OR to predict institutional incidents involving aggression.
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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 | 0.001 | 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 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".