Full parole and the aboriginal experience: Accounting for the racial discrepancies in release rates
Bibliographic record
Abstract
Aboriginal people comprise 2% of Canada's general population, yet they account for approximately 17% of all federal offenders This overrepresentation of aboriginals in corrections has been attributed, in part, to racial disparities in the granting of full parole. To date, studies of full parole and aboriginal offenders have been descriptive and controls for other causal factors besides race have not been introduced. The purpose of the present study was to investigate the extent to which race group differences accounted for differences in the granting of full parole in comparison to factors normally considered in evaluating release potential. All male federal offenders who reached their full parole eligibility date in 1996 (N = 2479) were followed across four stages of the parole process as provided for by the Corrections and Conditional Release Act. Results indicated that aboriginal offenders were significantly less likely to apply for and be granted full parole as compared to non-aboriginal offenders. Logistic regression analyses, however, found that race group differences did not predict either full parole application rates or parole board decisions.
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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 | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".