Redefining marriage or deconstructing society: A Canadian case study
Bibliographic record
Abstract
In this article, we examine the pivotal Canadian cases that led to the legalization of same-sex marriage in 2005. Using historical, cross-cultural, ethical, and existential arguments, our aim is to alert countries still struggling with this topic to the rational and substantial grounds for maintaining the historic definition of marriage – specifically, the rational connection between heterosexuality and the purposes of marriage – and how to do this with minimal impairment to gay couples and their children. Toward this end, we answer six questions: (1) Was the court’s redefinition of marriage in line with international law? (2) Did its definition of (straight) marriage do justice to the historical and cross-cultural evidence? (3) Was the exclusion of gay couples from marriage discriminatory according to s. 15(1) of the (Canadian) Charter of Rights and Freedoms? (4) Even if the historic definition of marriage really had discriminated against gay couples, could it have been justified according to s. 1 of the Charter? (5) What risks are involved in severing the historic connection between the purpose of marriage and its exclusively heterosexual definition? (6) To maintain the historic definition of marriage, could we have discriminated with only ‘minimal impairment’ to gay couples? (7) What were the underlying judicial strategies used by the Canadian courts? (8) Was there a problem of judicial activism is the Canadian cases?
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.054 | 0.014 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| 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".