Women as Patients, Not Spare Parts: Examining the Relationship between the Physician and Women Egg Providers
Bibliographic record
Abstract
Egg donation in Canada is shrouded in secrecy. Although much of the evidence is anecdotal, there are reports of women who are stimulated to produce many more eggs than is safe; women who receive little to no follow-up care from their treating physician when they suffer from serious complications; and women who are denied or receive inadequate records of their medical care leading them to question whether they have received substandard care from their physicians. Their stories give rise to serious concerns about the medical treatment of women who donate their eggs and are a sign that greater scrutiny of egg donation in Canada is warranted. The objective of this article is to examine the role of the physician who treats a woman who is donating her eggs; to highlight instances of substandard care; to examine the legal, ethical, and professional requirements of the physician; and to offer recommendations to ensure that all women who donate their eggs receive the best possible medical care available.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.025 | 0.017 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 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".