Constitutional Cases 2024 (Pt 5) | The Criminal Law Power and the Evolution of Federalism
Bibliographic record
Abstract
Since confederation, the federal criminal law power has been central to both the vision and operation of the Canadian constitutional order. It is arguably the true “plenary” federal power and has always — since early debates about its nature and purpose — had a rights-adjacent character. As we watch the Court preside over a significant evolution in the nature of contemporary federalism, this Panel takes the Court’s decision in Murray-Hall as a touchstone for reflecting on the role and future of the criminal law power.\nPanelists:\nAsha Kaushal (Peter A Allard School of Law, University of British Columbia) and Robert Danay (Ministry of Attorney General of British Columbia)\nBenjamin Perryman (Faculty of Law, University of New Brunswick)\nYashoda Ranganathan (Crown Law Office – Constitutional)\nColton Fehr (College of Law, University of Saskatchewan)\nChair: Vanessa MacDonnell (Faculty of Law, University of Ottawa)\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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.034 | 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".