Between Here and There is Better Than Anything Over There: The Morass of Sauvé V. Canada (Chief Electoral Officer)
Bibliographic record
Abstract
In 1993, the Supreme Court of Canada was asked to decide on the constitutional legitimacy of legislation prohibiting all prisoners from voting in federal elections.1 Given that the case ended up in our highest court, the parties must have considered it a fairly thorny problem to resolve.Apparently they were mistaken.In a mere 95 words, fewer than the average grade two writing assignment, the Court pronounced that the solution should have been obvious.Here is the judgment in its entirety:We are all of the view that these appeals should be dismissed.The Attorney General of Canada has properly conceded that s. 51(e) of the Canada Elections Act, R.S.C., 1985, c.E-2, contravenes s. 3 of the Canadian Charter of Rights and Freedoms but submits that s. 51(e) is saved under s. 1 of the Charter.We do not agree.In our view, s. 51(e) is drawn too broadly and fails to meet the proportionality test, particularly the minimal impairment component of the test, as expressed in the s. 1 jurisprudence of the Court. 2 Cut to 2002, almost 10 years later, and the Court is faced with virtually the same problem.This time, however, the legislation has been tinkered with.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".