Human Rights, Transsexed Bodies, and Health Care in Canada: What Counts as Legal Protection?
Bibliographic record
Abstract
Abstract Antidiscrimination legislation is the vehicle most commonly used by communities to demand equality, but how should such law best be employed? In this article, the Ontario Human Rights Tribunal decision inHogan v. Ontario (Health and Long-term Care)is examined in relation to the removal of sex reassignment surgery from the Alberta Healthcare Insurance Plan in order to better understand the legal strategies designed to remedy different kinds of discrimination. This article argues that trans issues (involving people who identify as transgender, transsexual, or trans) ought not to be seen as additions to gay and lesbian issues legally or politically. Moreover, this article demonstrates that the fight for formal inclusion in legislation as a discrete or insular minority should be rejected by trans activists, as other legal strategies are better positioned to combat the processes of transphobia, thus potentially offering important steps towards substantive equality.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.028 | 0.028 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".