The Serendipitous Solution to the Problem of Supreme Court Appointments
Bibliographic record
Abstract
Judges matter.In the age of the Charter, 1 there can be no question about this 2 -the role of courts and judges has expanded to include a wider range of legal and policy issues, invoked by a wider universe of groups and individuals, than anyone would have imagined possible even a few decades ago.There was a time when most political science textbooks did not include a chapter on the courts; today, such an omission would be unthinkable.We are all court-watchers now.The logical corollary is that who the judge is also matters: when a vacancy must be filled, especially on the Supreme Court of Canada, it makes a difference whether it is filled by person X or person Y.Some find this observation unpalatable-others would even suggest it is insulting to the judges-but every time the Supreme Court hands down a 5-4 decision, it makes the argument for me. 3 And there have been some very important 5-4 decisions recently: Doucet-Boudreau 4 on judicial remedies for Charter violations, Amselenf on freedom of
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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 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.022 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.017 | 0.023 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".