Bibliographic record
Abstract
If at first you don't succeed, try, try again:" traditional folk wisdom that Parliament applied with great success throughout the 1990's. 1 Parliament avoided the majority ruling in O'Connor 2 by legislatively co-opting the minority's reasons, which the Court duly upheld in Mills; 3 so too the result in Seaboyer 4 was reversed by legislation subsequently upheld in Darrach.5 So when, in 1993, the Supreme Court released its cryptic, 100-odd word decision in Sauvé v. Canada (Attorney General) 6 striking down section 51(e) of the Canada Elections Act 7 which disqualified from voting in federal elections "every person undergoing punishment as an inmate in any penal institution for * Partner, Stikeman Elliott LLP (Toronto).I am indebted to the excellent research conducted by two of our articling students, Jessica Bookman and Owen M. Rees, without whose efforts this paper would not have been possible.I also wish to thank David Frayer, Q.C. and Gérald L. Chartier of the Department of Justice
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".