The right to know one’s genetic origins and cross-border medically assisted reproduction
Bibliographic record
Abstract
The use of donor sperm or egg for reproduction raises the issue of the right of donor-conceived individuals to know their genetic origins. This paper argues in favor of acknowledging such a right and explores the challenges that cross-border medically assisted reproduction would raise in relation to it. It first explores possible justifications for such a right by discerning its possible conceptual and empirical groundings. It describes some key ethical and policy implications of the removal of donor anonymity. It then argues that novel technologies such as mitochondrial replacement and gene editing raise new concerns in this area and may expand the scope of such a right. Finally, it argues that while many barriers to accessing information about genetic origins already exist at national levels, cross-border medically assisted reproduction may exacerbate a reality in which many individuals conceived through third-party participation are deprived of information that may be crucial to their future well-being for medical or psycho-social reasons.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.054 | 0.040 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".