Bibliographic record
Abstract
Starting in 1908 with a law based on welfare principles and finishing in 2003 with a law based on criminal law principles and proportionality, successive changes in Canada's youth justice legislation have provided additional structure in governing the key decisions involving youths. While criminal law in Canada, including youth justice laws, is a federal responsibility, the provinces administer the law. Interestingly, there are very large differences in the manner in which the provinces administer the single (federal) criminal law. Although most Canadians believe that the youth justice system is too lenient, the data show that many of the cases being processed through Canada's youth courts and many of the cases resulting in imprisonment for youth involve very minor offenses. Federal government concerns about the provincial overuse of the youth justice system and about the high rates of custodial sentences for minor offenses were important determinants of the shape of the most recent youth justice legislation-the Youth Criminal Justice Act (YCJA), which came into effect in 2003. For political reasons, these concerns were "balanced" with symbolically tough, but practically inconsequential, measures. It remains to be seen what the effects of the new law will be.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".