The validity of the Violence Risk Appraisal Guide (VRAG) in predicting criminal recidivism
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: The VRAG is an actuarial risk assessment instrument, developed in Canada as an aid to estimating the probability of reoffending by mentally ill offenders. AIM: To test the predictive validity of the VRAG with a German sample. METHOD: The predictive validity of the VRAG was tested on a sample of 136 people charged with a criminal offence and under evaluation for criminal responsibility in the forensic psychiatry department at the University of Munich in 1994-95. The predicted outcome was tested by means of ROC analysis for correlation with the observed rate of recidivism between discharge after the 1994-95 assessment and the census date of 31 March 2003. Recidivism rate was calculated from the official records of the National Conviction Registry. RESULTS: Just over 38% of the sample had reoffended by 2003. Their mean time-at-risk was 58 months (SD 3.391; range 0-115 months). The VRAG yielded a high predictive accuracy in the ROC analysis with an AUC of 0.703. For a constant time-at-risk < = 7 years, the predicted probability and observed rates of recidivism correlated significantly with Pearson's r = 0.941. CONCLUSIONS: The validity of the VRAG was replicated with a German sample. The VRAG yielded good predictive accuracy, despite differences in sample and outcome variables compared with its original sample.
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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 | 0.004 | 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 | 0.001 |
| 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