Canadian Same Sex Relationship Recognition Struggles and the Contradictory Nature of Legal Victories
Bibliographic record
Abstract
I want to pick up on one of the themes running through virtually all of the papers in this symposium-the contradictory nature of law. Legal victories-and defeats-are always fragile, partial and contradictory. The perspective I bring to this theme is a Canadian one, where in the context of gay and lesbian struggles, legal victories now outweigh legal defeats. I will tell a story of these legal victories, which resulted in a much celebrated case in 1999 known as M v. H., in which the Supreme Court of Canada recognized the equality rights of same sex couples, and struck down a law with an opposite sex definition of spouse? This may sound like an unequivocal legal victory for gays and lesbians. But, the story that I want to tell teases out a more complicated understanding of the case, which will illustrate the contradictory nature of legal strategies and legal victories. Legal victories are never only legal victories, just as legal defeats are never only legal defeats.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.071 | 0.039 |
| Scholarly communication | 0.017 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.011 | 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".