Not Worth the Wait: Why the Long-Awaited Regulations Under the AHRA Don’t Address Egg Donor Concerns
Bibliographic record
Abstract
The Assisted Human Reproduction Act seeks to protect egg donors’ health and well-being and prevent trade in their reproductive capabilities. In order to fulfill these objectives, the Act prohibits the buying and selling of ova, and only allows for egg donors to be reimbursed for their expenses. However, no regulations setting out what expenses can be reimbursed were promulgated. Sixteen years later, these long-awaited regulations finally came into force in June 2020. In this study, I rely on data from interviews with sixteen egg donors in order to assess how the new regulations might help or hinder concerns that egg donors have with how egg transactions are regulated in Canada. I argue that the new regulations might hinder, more than help with, addressing current concerns related to egg transactions in Canada. The most likely result is that they will not change the current state of affairs. La loi sur la procréation assistée vise à protéger la santé et le bien-être des donneuses d’ovules et à empêcher le commerce de leurs capacités reproductives. Afin d’atteindre ces objectifs, la loi interdit l’achat et la vente d’ovules et permet uniquement aux donneuses d’ovules de se faire rembourser leurs dépenses. Toutefois, aucune réglementation précisant les dépenses pouvant être remboursées n’avait été officiellement promulguée. Seize ans plus tard, ces réglementations tant attendues sont finalement entrées en vigueur en juin 2020. Dans cette étude, je m’appuie sur des données issues d’entretiens avec seize donneuses d’ovules afin d’évaluer comment la nouvelle réglementation pourrait aider ou entraver les préoccupations des donneuses d’ovules concernant la façon dont les transactions sont réglementées au Canada. Je soutiens que les nouvelles réglementations pourraient empêcher de répondre aux préoccupations actuelles liées aux transactions d’ovules au Canada, plutôt qu’aider à trouver une solution. Le résultat le plus probable de ces réglementations est qu’ils ne changeront pas l’état actuel des choses.
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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 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".