Preliminary Evidence of Adaptive Decision Making Techniques Used by Parole Board Members
Bibliographic record
Abstract
Given wide-ranging interest in the predictors of recidivism, it is surprising that relatively little research has focused on a major factor influencing offenders' ability to re-offend—conditional release decisions. Using a correlational design and hypothetical offender vignettes, this study examined conditional release decisions in a sample of 31 parole board members from Canada and New Zealand. Results revealed marked inter-individual differences, not related to demographic characteristics, in the parole decisions reached, as well as in the amount and types of file information considered. Results also demonstrated variation in decisions by offender type, as well as in the frequency with which different file information was accessed. These patterns offered preliminary evidence of the use of adaptive decision making techniques among board members, with case reviews focusing on specific information known to be related to parole outcome. Though useful in the face of time pressures, such techniques may be inconsistent with legislated requirements.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".