Constitutional Cases 2024 (Pt 3B) | Punishment and Policing
Bibliographic record
Abstract
In a year of surprising quiescence in the criminal/constitutional jurisprudence, there was nevertheless a series of cases that advanced the Court’s thinking on persistently challenging issues. This panel will consider the effects of Hills and Hilbach on s 12, McGregor’s impact on s 8, and what Zacharias will mean for s 24(2).\nPanelists:\nSteve Coughlan (Schulich School of Law, Dalhousie University)\nLisa Kerr (Faculty of Law, Queen’s University)\nGerald Chan (Stockwoods LLP)\nMichael Perlin (Ministry of the Attorney General)\nChair: Palma Paciocco (Osgoode Hall Law School)\nThe 27th iteration of the Constitutional Cases conference was held on Friday, April 12, 2024. Osgoode Hall Law School’s Annual Constitutional Cases Conference, recognized as the leading constitutional law conference in Canada, brings together many highly respected constitutional scholars, lawyers, students, and experts for an insightful and practical analysis of the Supreme Court’s significant constitutional judgments of the past year.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.033 | 0.004 |
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".