Reproductive Genetics: Canadian and European Perspectives
Bibliographic record
Abstract
Unlike medically assisted conception, the issue of the impact on women of reproductive genetic testing has been characterized by the emergence of a more 'relativist' position. This relativist position is grounded in the understanding of the universality of problems arising from human genetics. An analysis of the major reports emanating from different European countries will demonstrate that the discussion regarding the impact of medically assisted conception and reproductive genetic testing on women is often incidental and secondary. There are similarities and differences in the issues raised in the evaluation of both these technologies. Similarities, in their experimental character, the concomitant social pressure, the myth of the perfect child and the increased medicalization. Differences, in the inherent responsibility or guilt accompanying genetic testing, the timing of choices, the possibility of sex selection, the use and control of genetic information, the sense of intergenerational responsibility and the current qualification of such genetic testing as medical and diagnostic as opposed to a technology of 'convenience' as was often the case with the treatment of infertility. In contrast to the European reports, the work of the Canadian Royal Commission on New Reproductive Technologies has as its primary focus the impact of both these technologies on women, children and society.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".