The influence of actuarial risk assessment in clinical judgments and tribunal decisions about mentally disordered offenders in maximum security.
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
Research has shown that actuarial assessments of violence risk are consistently more accurate than unaided judgments by clinicians, and it has been suggested that the availability of actuarial instruments will improve forensic decision making. This study examined clinical judgments and autonomous review tribunal decisions to detain forensic patients in maximum security. Variables included the availability of an actuarial risk report at the time of decision making, patient characteristics and history, and clinical presentation over the previous year. Detained and transferred patients did not differ in their actuarial risk of violent recidivism. The best predictor of tribunal decision was the senior clinician's testimony. There was also no significant association between the actuarial risk score and clinicians' opinions. Whether the actuarial report was available at the time of decision making did not alter the statistical model of either clinical judgments or tribunal decisions. Implications for the use of actuarial risk assessment in forensic decision making are discussed.
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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 | 0.001 | 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 | 0.001 |
| 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