Moral Evils v. Health and Safety Evils: The Case of an Ovum ‘Obtained’ From a ‘Donor’ and Used By the ‘Donor’ in Her Own Surrogate Pregnancy
Bibliographic record
Abstract
This paper critically examines the amendment made in 2012 to section 10(2)(c) of the Assisted Human Reproduction Act, 2004 mandating the screening and testing of “obtained” ovum “donated” by a “donor” and used in her own surrogate pregnancy. The amendment at section 10(1) of the Act cites the federal government’s obligation to reduce harm to human health and safety arising from use of sperm or ova for human reproduction, including the risk of disease transmission. This paper argues that the amendment mandating the screening and testing of surrogate ova when used by the surrogate in her own surrogate pregnancy creates a dangerous liminal regulatory space; one that transforms the surrogate into a third-party donor yet she incurs no health and safety risk to herself as she is the recipient of her own ova embryo. Genetic implications for the surrogate-born child makes a stronger case in support of mandatory testing, however the amendment imposes no similar screening and testing regime on the usual category of traditional surrogates: women who bear genetically-related children conceived through artificial insemination (IUI) rather than IVF. The paper questions the application of a health and safety evil that the amendment seeks to address. It suggests the real evil is a moral one whereby criminal code sanctions are being employed to discourage traditional surrogacy when practiced as a result of assisted reproduction techniques.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.034 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.015 | 0.015 |
| Insufficient payload (model declined to judge) | 0.002 | 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".