Sentencing Aboriginal offenders : progressive reforms or maintaining the status quo?cby Andrew Welsh.
Bibliographic record
Abstract
As of March 3 1,2003, Aboriginal offenders represented 18.3% of the incarcerated population, but accounted for only 2.7% of the Canadian population.Bill C-41 was introduced by Parliament to amend Criminal Code sentencing practices, and to encourage judicial consideration of alternatives to incarceration, with particular attention to the circumstances of Aboriginal offenders.To investigate the extent to which the Bill C-41 sentencing reforms have been effective in addressing Aboriginal over-representation, two separate studies were conducted.The first study examined sentencing admissions to incarceration, probation, or a conditional sentence for all male offenders in British Columbia from April 1993 to April 2000.Analyses demonstrated that neither overall incarceration rates nor Aboriginal incarceration rates in British Columbia have declined significantly since the introduction of Bill C-41.There was also no significant decline in Aboriginal incarceration rates when controlling for offence seriousness and criminal history.The second study examined judges' reasons for sentencing in a sample of Canadian sentencing cases to determine the role of Aboriginal status relative to other legally relevant factors.The Quicklaw dataset was used to identify 713 reported sentencing decisions from 1990 to 2002.Results indicated that Aboriginal offenders were not more likely to be incarcerated than non-Aboriginal offenders.Finally, Aboriginal status did not significantly predict the likelihood of receiving a custodial or non-custodial disposition relative to aggravating and mitigating factors cited by judges.Thus, it appears that the Bill C-41 sentencing reforms have underestimated the true complexity of the overrepresentation problem and, regardless of recent common law developments, sentencing judges alone cannot significantly reduce the current disproportionate rates of Aboriginal incarceration.The implications of these findings in light of the goals of Bill C-41 are discussed. DEDICATIONTo Jen.Thank you for all your love and support.I could not have made that last push to finish this dissertation without you.And to my parents who provided me with the love and encouragement to pursue my dreams and fulfill my goals.This is for you
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.033 | 0.007 |
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".