The Will to Change: Lessons from Canada's Successful Decarceration of Youth
Bibliographic record
Abstract
In 1997, Canada's youth custodial facilities held 3825 sentenced youths. Eighteen years later, this number was 527—an 86 percent reduction. Overall youth imprisonment (sentenced + pretrial detention) decreased by approximately 73 percent. This paper uses Canada's successful decarceration of youths to understand what might be learned about decarceration more broadly. By examining the reforms that transpired in Canada's treatment of young offenders since the 1960s and the political/cultural shifts that occurred since the 1990s, we demonstrate that the decline resulted from changes occurring in various parts of the system. Finally, we contrast this decarceration with more than 60 years of relative stability of Canadian adult imprisonment rates as well as Canada's failure to substantially decrease youth pretrial detention in order to identify those factors seemingly necessary to reduce imprisonment more generally.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".