Fake It Till You Make it: Policymaking and Assisted Human Reproduction in Canada
Bibliographic record
Abstract
The Assisted Human Reproduction Act (AHR Act) came into effect in 2004. The AHR Act stipulates in s.12 that no reimbursement of expenditures incurred in the course of donating gametes, maintaining or transporting in vitro embryos, or providing surrogacy services is permitted, except in accordance with the regulations and with receipts. Ten years later, Health Canada still has not drafted the regulations governing reimbursement. Section 12 is therefore still not in force. Health Canada and others have asserted that there is a Health Canada policy on reimbursement and that reimbursement with receipts is legally permissible. We dispute the existence of such a policy and its legitimacy (if it exists). We also challenge the decision by Health Canada not to produce regulations and thereby make it possible for Parliament to bring s.12 into force. This intentional lack of action is worrisome on at least two fronts. First, it sidesteps the processes required for regulations and thereby ducks the Parliamentary oversight very deliberately built into the AHR Act. Second, it leaves Canadians who provide and who access assisted human reproduction uncertain about what is and is not permitted, and therefore fearful of, or at risk of, prosecution. We conclude that Health Canada should take the steps necessary to put regulations in front of Parliament so that Parliament will then be able to pass regulations and bring s.12 into force. Canadians should demand no less.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.043 | 0.023 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".