Understanding Sentencing under the Youth Criminal Justice Act
Bibliographic record
Abstract
The authors provide an analysis of the complicated sentencing regime found in Canada's Youth Criminal Justice Act (YCJA) and compare the new Act to the previous Young Offenders Act In comparison to the provisions of the Criminal Code that govern adult sentencing, the YCJA makes no reference to deterrence, has more focus on rehabilitation, and calls for lesser penalties than for adults. The authors point out that proportionality is a key principle for both sentencing youths and adults, but the aggravating elements enumerated in the YCJA are not the same as those in the Criminal Code. They further note that situations in which youth custody may be used are limited and that judges are directed to treat custody as a last resort and consider all alternatives. The authors conclude that the YCJA facilitates a more uniform treatment of young offenders, though the courts will continue to exercise considerable discretion. While it is clear that the use of custodial sanctions will decrease even without more community resources, in some places the coming into force of the new Act was accompanied by increased community resources which will also affect sentencing practices. The article concludes with a survey of some of the first cases decided under the YCJA, which reveal that custodial sanctions were avoided and rehabilitative principles played a major role in sentencing decisions.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".