Predictive validity despite social desirability: evidence for the robustness of self‐report among offenders
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
INTRODUCTION: Many professionals believe that self-report questionnaires used to predict recidivism have a low validity. The aim of the present study was to investigate the assumption that the validity of self-report is vulnerable to self-presentation biases in offender samples. METHOD: The participants consisted of 124 male offenders who volunteered to complete the Self-Appraisal Questionnaire (SAQ). RESULTS: Lower scores on measures of social desirability were significantly associated with higher levels of risk (as measured by self-report and a rated actuarial instrument) and a higher likelihood to re-offend. Further, stepwise regression analysis revealed that social desirability added significantly unique variance in the prediction of violent recidivism. DISCUSSION: The authors propose that impression management may be an enduring person-based characteristic within an offender sample rather than a situationally determined response style. The variance associated with this characterological information is proposed to be the source of the unique predictive variance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 it