IN THE MATTER OF THE FEMALE MIND: AN ANALYSIS OF THE SUPREME COURT OF CANADA’S APPROACH TO WOMEN AND MENTAL HEALTH
Bibliographic record
Abstract
According to the Supreme Court of Canada’s most recent equality law ruling in Withler v. Canada (Attorney General) (2011), considerations of context must be central to a discrimination analysis. As the jurisprudence evolves, discrimination cases in Canadian courts are becoming increasingly complex and some legal experts predict that we will see a rise in the number of disability rights claims. To date, very few cases involving women and mental health have made their way up to Canada’s highest court. This paper uses a gendered analysis of disability to examine three Supreme Court of Canada decisions: University of British Columbia v. Berg (1993), Winnipeg Child and Family Services (Northwest Area) v. G. (D.F.) (1997), and Gosselin v. Québec (Attorney General) (2002). The results indicate that in cases where gender and mental health intersect, the Court is unwilling or unable to deal with issues of intersectionality in order to recognize the gendered experience of mental illness. Yet, the Court continues to point to one of these cases, Gosselin, as an example of how to get the contextual analysis right. When it comes to women and mental health, it appears that equality and justice may continue to give way to decontextualization and stereotype.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.060 | 0.035 |
| Scholarly communication | 0.015 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".