Bibliographic record
Abstract
In the wake of the killing of George Floyd in 2020, global protests generated public scrutiny about policing in our communities. Between 2020 and 2022, many school boards in Canada began to re-evaluate the value of having police in schools, as school resource officers or school liaison officers, with many boards eventually electing to end these programs altogether. Interactions with police in and through schools can facilitate a process by which youth are pushed out of the school system and into the criminal justice system, commonly known as the school to prison pipeline. The Youth Criminal Justice Act (YCJA), which governs youth in conflict with the law, specifically in their interactions with the justice system and information that is permitted to be shared with other entities like schools. In part, these protections are provided to prevent stigmatization and promote rehabilitation. However, the YCJA had been amended to allow more information disclosures between police and school administrations. This article looks at the legislative history of the YCJA to provide context to these amendments. This article also explores how the court has interpreted privacy for youth under the Act, and how the privacy provisions operate in practice. Finally, it provides empirical research that relies upon interviews with key informants that shed light on the impacts of information sharing between police and schools on 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 | 0.020 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.038 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 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".