Punishment in Canada: Extending Gladue-Like Procedures to Non-Indigenous Offenders
Bibliographic record
Abstract
In the Canadian criminal justice system, there is a procedure which provides additional protections to Indigenous offenders during sentencing and its related events. This procedure is commonly referred to as the Gladue process. This thesis defends the plausibility of extending Gladue-like procedures to non-Indigenous offenders on the grounds that failing to do so would be a failure of consistency of the law. The law must be consistent in the sense that it must treat like cases alike. It will be argued in this thesis that there are other individuals and groups who may be similarly deserving of additional protections during sentencing because of their significant circumstances of vulnerability. This includes black individuals, LGBTQIA+, and mentally ill persons, but this is by no means an exhaustive list. This thesis does not aim to diminish the unique experience of Indigenous persons, but rather, it suggests that extending Gladue-like processes to particular non-Indigenous persons and groups may be required based on consistency of the law and attention to intersectionality. It is my hope that this thesis brings about greater awareness to the sentencing procedures pertaining to both Indigenous and non-Indigenous offenders alike, and that it may spark discussion on the subject of extending additional legal protections to vulnerable persons. This thesis relies heavily on the hybrid theory of punishment, as presented by H.L.A. Hart, which combines both utilitarian and retributivist elements in justifying the act of punishment. Hart’s theory aligns with the Canadian legislation on sentencing and provides a convincing justification for punishment while allowing the inclusion of restorative punishment practices for vulnerable persons. It will be argued that extending restorative practices to non-Indigenous offenders is, in some cases, plausible, and at times, necessary.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".