The Effectiveness of the Self-Appraisal Questionnaire in Predicting Offenders' Postrelease Outcome
Bibliographic record
Abstract
The goal of the present research was to examine the effectiveness of the Self-Appraisal Questionnaire (SAQ) in predicting release outcome as compared to other well-established risk prediction measures. The SAQ is a self-report measure designed to predict offenders' postrelease out-come. The SAQ was administered along with four similar, but clinician-administered, measures to 68 federally sentenced Canadian male offenders prior to their release into the community. Data were collected for a 2-year follow-up period at six 4-month intervals. Outcome criteria measures were general recidivism, violent recidivism, and any failure (a composite measure recording failure on any of the following variables: negative parole reports, violation of parole conditions, incurring new charges, or a new conviction). Although the SAQ was the most economical of the comparable tools, results demonstrated that it was at least as effective as the four other measures in predicting postrelease outcome.
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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".