Pt 5 The Legend of Two Textbooks - His Brilliant Legacy: A Conference in Honour of Peter W. Hogg
Bibliographic record
Abstract
His Brilliant Legacy: A Conference in Honour of Peter W. Hogg was held on January 10, 2024 at Osgoode Professional Development and co-hosted by Osgoode Hall Law School and Blake, Cassels & Graydon LLP.\nThis session includes: "Peter and the Legend of Two Textbooks" Peter Hogg's textbooks have been studied and relied on by students and all branches of the legal profession, including courts. Speakers on this panel will examine two of his principal texts - Constitutional Law and Taxation Law, considering their role, impact, and significance over time.\nChair: Professor Emily Kidd White, Osgoode Hall Law School\nSpeakers: Professor Adam Dodek, Faculty of Law, University of Ottawa, Professor Jinyan Li, Osgoode Hall Law School and Mr. Scott Wilkie, Blakes LLP, Professor Bruce Ryder, Osgoode Hall Law School, Professor Wade Wright, Western Law
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.314 | 0.156 |
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".