Concurrent Cross-Validation of the Self-Appraisal Questionnaire: A Tool for Assessing Violent and Nonviolent Recidivism and Institutional Adjustment on a Sample of North Carolina Offenders
Bibliographic record
Abstract
The aim of this study was to determine whether the Self-Appraisal Questionnaire (SAQ), a tool that was found to be reliable and valid for assessing violent and nonviolent recidivism and institutional adjustment for Canadian offenders, would also be valid for the same purposes with a demographically different population of North Carolina offenders. The internal consistency alphas and SAQ total and subscale scores' correlations were high. Offenders with high SAQ total scores had significantly more violent offenses, had more total number of past offenses, had higher numbers of past arrests, and had more institutional infractions than those with low SAQ scores. There were no significant differences between the responses of the African American and Caucasian offenders on the SAQ scales. These results support previous findings regarding the reliability and validity of the SAQ for assessing recidivism and institutional adjustment and suggest that the SAQ could be used with diverse populations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".