But Why Him? A Review of The Tenth Justice: Judicial Appointments, Marc Nadon, and the Supreme Court Act Reference, by Carissima Mathen and Michael Plaxton
Bibliographic record
Abstract
To the great benefit of the Canadian legal community and the Canadian public, the authors have created an extensive, concise, and highly readable account of the Nadon saga. Anyone unfamiliar with the purported appointment of Justice Nadon to the Supreme Court of Canada, the Reference re Supreme Court Act, ss 5 and 6 (also known as the Nadon Reference), and the aftermath will find this book invaluable. I expect this work will become the definitive and authoritative account of this saga and that it will be indispensable to future scholars.\nI begin this review with a brief overview of the content and organization of the book. Within that context, I then focus on the debates the book raises and provokes and on the mysteries that remain for future work.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".