Preconception care and genetic risk: ethical issues
Bibliographic record
Abstract
Preconception care to address genetic risks in reproduction may be offered either individually to couples with a known or suspected increased risk of having a child with a genetic disorder, or systematically to couples or individuals of reproductive age. The identification of couples at risk of transmitting a (serious) genetic disorder allows those couples to refrain from having children or to adapt their reproductive plans (using prenatal or preimplantation diagnosis, donor gametes, or adoption). Ethical issues concern the possible objectives of providing these options through preconception genetic counseling or screening, objections to abortion and embryo-selection, concerns about eugenics and medicalization, and issues arising in the professional-client relationship and/or in the light of the normative framework for population screening. Although enhancing reproductive autonomy rather than prevention should be regarded as the primary aim of preconception care for genetic risks, directive counseling may well be acceptable in exceptional cases, and prevention in the sense of avoiding serious suffering may be an appropriate objective of specific community-based preconception screening programmes. The seemingly unavoidable prospect of comprehensive preconception screening raises further ethical issues.
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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 | 0.077 | 0.107 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.036 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.022 | 0.023 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".