Bibliographic record
Abstract
In its 2008 decision in R v Kapp, the Supreme Court of Canada gave broad effect to the Canadian Charter of Rights and Freedom's ameliorative program provision, section 15(2). The Supreme Court's decision signalled that a government respondent's declaration that a program is “ameliorative” may shield it from further scrutiny under section 15(1). This Women's Court of Canada judgment takes the opportunity to reformulate the approach to section 15(2). Although the Charter provides express protection of ameliorative programs, such programs have sometimes been challenged by members of advantaged groups claiming “reverse discrimination.” We argue that such “equality regressive claims” should be caught by section 15(2). However, for challenges to “under-inclusive” programs, deference to the government on the development of ameliorative programs may perpetuate disadvantage experienced by excluded disadvantaged groups and should not be similarly shielded. This decision develops a contextual approach to section 15(2) that ensures that it does not become a loophole through which government respondents can avoid fulsome Charter scrutiny of claims of under-inclusivity. We outline a test that not only encourages government to take affirmative action but is also narrow enough to subject genuine equality claims to section 15(1) review.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.024 | 0.017 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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".