Legal Rights in the Supreme Court of Canada in 2000: Seeing the Big Picture
Bibliographic record
Abstract
In 2000, the Supreme Court of Canada decided four cases which raised claims concerning some of the legal rights provisions of the Charter. Two of the cases were criminal: R. v. Darrach, [2000] 2 S.C.R. 443; R. v. Morrisey, [2000] 2 S.C.R. 90. The other two cases involved a human rights investigation (Blencoe v. British Columbia (Human Rights Commission), [2000] 2 S.C.R. 307), and a child protection proceeding (Winnipeg Child and Family Services v. K.L.W., [2000] 2 S.C.R. 519). This comment focuses on two of these decisions (Blencoe and Darrach) where the SCC considered claims under section 7 of the Charter in the context of proceedings important to women's equality. Both of these cases demonstrate a commitment on the part of the Court to contextualize the interpretation of legal rights to take into account interests beyond those of the immediate parties to the case. In this paper, the author argues that this trend is justifiable in both the human rights and the criminal contexts at issue in these appeals.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.035 | 0.020 |
| Scholarly communication | 0.026 | 0.008 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.010 | 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".