Same-sex marriage beyond Charter dialogue: Charter cases and contestation within government
Bibliographic record
Abstract
In this article, I argue that the dialogue debate has obscured a much richer story that can be told about Halpern v Canada, same-sex marriage, and the complex relationship between courts and legislatures. The federal government was deeply divided on same-sex marriage. Parliament, the Liberal government, the federal Cabinet, and the liberal caucus were all deeply divided. From the outside, it may have appeared as a ‘courts versus government’ battle, with the federal government defending the opposite-sex definition of marriage right up until the Ontario Court of Appeal struck it down as unconstitutional in Halpern. But a closer look shows that the federal government’s about-face after Halpern had been in the making for years, with supporters trying to use court decisions as well as changing public opinion to wedge open the marriage issue. The same-sex marriage case study can be retold as a story not of dialogue between courts and Parliament but, rather, as a contestation within government. I argue that this story – of conflict and contestation within government and the use of court decisions by proponents of same-sex marriage – can provide a richer account of the evolution of the federal government and the adoption of the Civil Marriage Act.
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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 | 0.017 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.036 | 0.053 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".