Aboriginalising the parole process: ‘Culturally appropriate’ adaptations and the Canadian federal parole system
Bibliographic record
Abstract
The increasing ‘diversity’ of penal populations in most western countries over the past three decades raises questions as to the fairness and appropriateness of established penal programmes and practices. In some jurisdictions, penal policy-makers and administrators are being forced to deal with the implications of offender diversities, including race, ethnicity, gender, culture and religion, in policy and planning. In Canada, the pervasive over-representation of Aboriginal individuals in prisons has led to calls for change in how the corrections and parole systems deal with Aboriginal prisoners. This article examines the advent of one ‘culturally appropriate’ adaptation of the parole process, the Elder assisted hearing, introduced in 1992 by the Parole Board of Canada as a means of (1) addressing the problem of over-representation and (2) being responsive to Aboriginal difference. It shows that the ‘Aboriginalisation’ of parole hearing formats is by no means a straightforward process, and is illustrative of the broader challenges that racial, cultural and gender differences pose to contemporary penality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.033 | 0.020 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".