Bibliographic record
Abstract
This judgment of the Women's Court of Canada re-considers the reasons in the 2008 Supreme Court of Canada decision in R v Kapp, though it concurs in the result. The judgment takes particular issue with the Supreme Court's interpretation of section 15(2) of the Canadian Charter of Rights and Freedoms as an independent “saving” provision capable of exempting ameliorative laws and programs from scrutiny under section 15(1), identifying three reasons that this approach cannot stand: (1) the existing interpretation of section 15(2), which treats it as an interpretive provision informing the whole of section 15, is sufficient to protect ameliorative laws and programs from formal equality challenges like the one advanced in this case; (2) the novel approach to section 15(2) established in this case may be inconsistent with substantive equality in cases of under-inclusiveness and discriminatory effects; and (3) the Court's reading of section 15(2) in this case improperly displaces section 1 of the Charter in cases involving allegedly ameliorative laws or programs. The judgment concludes that the interpretive approach to section 15(2), which views this section as informing the overall section 15 promise of substantive equality, ought to be maintained. Finally, the judgment offers a brief critique of the Supreme Court's obiter comments on section 15(1) of the Charter, calling into question the narrow approach to discrimination suggested by the two-part test adopted in Kapp.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.017 | 0.014 |
| Insufficient payload (model declined to judge) | 0.013 | 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".