Choosing Prison over Parole: Factors Associated with Prisoners’ Decision to Waive Their Conditional Release Hearing
Bibliographic record
Abstract
Parole review waivers have serious implications on correctional systems, prisoners’ rehabilitation, and public safety. However, studies on this topic are scarce, have limited scopes and methodologies, and lack in-depth analysis about women and Indigenous people. The purpose of this study was to examine the characteristics of prisoners who forgo parole review. Quebec’s correctional services provided us with the correctional records of all parole-eligible prisoners in the province in 2014–15 (N = 3,675). A sample of men, women, Indigenous people, and non-Indigenous people assessed with the LS/CMI (n = 2,595) was selected. Hierarchical logistic regressions showed that recidivism risk and parole officers’ recommendations for release have a strong statistical relationship with waivers. In addition, Indigenous people are more likely to waive a parole hearing. Moderation analyses also showed that sex and Indigenous ethnicity each moderate the effect of one factor. Results suggest that the combination of statistically significant factors, as represented by recidivism risk, explains waivers better than the specific effects of these factors viewed separately.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".