National survey on the opinions of French specialists in assisted reproductive technologies about social issues impacting the future revision of the French Bioethics laws
Bibliographic record
Abstract
INTRODUCTION: France is known for its conservative and unique position in assisted reproductive technologies (ARTs). At the eve of the future revision of French Bioethics laws, we decided to conduct a national survey to examine the opinions of French specialists in ARTs about social issues. MATERIAL AND METHODS: Descriptive study conducted in May 2017 in a university teaching hospital using an anonymous online questionnaire on current issues in ARTs. The questionnaire was sent by email to 650 French ARTs specialists, both clinicians and embryologists. RESULTS: After 3 reminders, 408 responses were collected resulting in a participation rate of 62.7% (408/650). Concerning pre-implantation genetic testing, 80% of the physicians were in favor of expanding the indications, which in France are presently limited to incurable genetic diseases. Authorizing elective Fertility Preservation was supported by 93.4% of the specialists, but without social coverage for 86.3% of them. Concerning gamete donation, 77.4% of the French ARTs specialists were in favor of giving a financial compensation to donors, 92% promoted preserving their anonymity and 80.9% were against a directed donation. ARTs for single heterosexual women were supported by 63.4% of the French specialists and by 72.5% for lesbian couples. The legalization of surrogacy was requested by 55.2%. DISCUSSION: Pending the revision of the French Bioethics laws, this survey provides an overview of the opinion of the specialists in ARTs on expanding ARTs for various social indications.Because of the evolution of social values, a more liberal and inclusive ART program is desired by the majority of ART specialists in France.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".