Indigenous Over-representation in Canada’s Youth Correctional System: An Assessment of Regional Variability
Bibliographic record
Abstract
Although Indigenous youth make up 8% of Canada’s population, they are over-represented in the youth correctional system – comprising 46% of admissions in the 2016/17 fiscal year. The Youth Criminal Justice Act (YCJA) of 2003 calls for attention to the unique needs of Indigenous youth at all points of justice system contact, yet despite these special considerations and emphasis on fair treatment, overrepresentation has grown steadily in recent years. Examination of the number of correctional admissions for Indigenous and non-Indigenous youth, as well as the percentage of Indigenous admissions, across the provinces and territories provides insight into this unexpected trend. By incorporating regional population data, this research uncovers the areas that report the greatest levels of over-representation and those which have successfully reduced the percentage of system-involved Indigenous youth or maintained proportionate representation. This information provides a starting point for future research to uncover the systemic causes of the over-representation problem. These findings also draw attention to issues with recording and reporting practices – a problem that must be addressed in order to act on the Truth and Reconciliation Commission’s call to reduce criminal justice disparities among Indigenous youth.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".