Mapping international research output within ethical, legal, and social implications (ELSI) of assisted reproductive technologies
Bibliographic record
Abstract
PURPOSE: Research about ethical, legal, and social implications (ELSI) of assisted reproductive technologies (ART) is influenced by cultural and value-based perspectives. It impacts regulations, funding, and clinical practice, and shapes the perception of ART in society. We analyze trends in the global literature on ELSI of ART between 1999 and 2019. As most output is produced by North America, Western Europe, and Australia, we focus on international research, i.e., academic articles studying a different country than that of the corresponding author. METHODS: The corpus, extracted from PubMed, Web of Science, and Scopus, includes 7714 articles, of which 1260 involved international research. Analysis is based on titles, abstracts and keywords, classification into ART fields and Topic Modeling, the countries of corresponding author, and countries mentioned in abstracts. RESULTS: An absolute increase in the number of international studies, and their relative proportion. Trends of decentralization are apparent, yet geographic centralization remains, which reflects an unequal distribution of research funds across countries and may result in findings that do not reflect global diversity of norms and values. Preference for studying conceptual challenges through philosophical analysis, and for fields that concern only a portion of ART cycles. Less attention was dedicated to economic analysis and barriers to access, or to knowledge of and attitudes. International studies provide an opportunity to expand and diversify the scope of ELSI research. CONCLUSION: We call on the research community to promote international collaborations, focus on less explored regions, and divert more attention to questions of cost, access, knowledge, and attitudes.
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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 | 0.061 | 0.221 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.066 | 0.095 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".