Assisted Human Reproduction in Common Law Canada after the Supreme Court of Canada Reference: Moving beyond Regulation by Colleges of Physicians and Surgeons
Bibliographic record
Abstract
The Supreme Court of Canada’s opinion in Reference re Assisted Human Reproduction Act effectively decided that it was for provinces and territories to regulate most aspects of assisted human reproduction. Since the 2010 ruling, only Québec has passed legislation to govern the field. Although two colleges of physicians and surgeons have adopted medical practice guidelines, approximately forty-two fertility clinics in common law Canada lack detailed regulatory oversight. This article argues that such lack of specific regulation of assisted human reproduction in common law provinces is a waste of the public money and effort invested since the 1980s. Further, physician colleges are ill positioned to be the sole provincial regulator of practices and procedures conducted primarily on women’s bodies that aim to bring new humans to life. Provincial legislatures in common law Canada should urgently adopt the values expressed both by the Royal Commission on New Reproductive Technologies and by the Canadian Parliament and use similarly open and transparent processes. They ought to collaborate to adopt a regulatory mechanism (similar to that pioneered by the Uniform Conference of Canada or adopted in securities regulation) to govern assisted human reproduction in common law Canada primarily in the interests of women and the children to be created.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.014 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.017 | 0.016 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".