Returning individual research results in international direct-to-participant genomic research: results from a 31-country study
Bibliographic record
Abstract
This paper summarizes the results of a 31-country qualitative study of expert perspectives on the regulation of international "direct-to-participant" (DTP) genomic research. We outline how the practice of directly recruiting participants for genomic studies online complicates ethics and regulatory considerations for the return of individual research results. As part of a larger project supported by the National Human Genome Research Institute, National Institutes of Health, we prepared and distributed to 31 global legal experts a questionnaire intended to ascertain opinions and perspectives on the way international DTP genomic research is likely to be regulated. We found significant disagreement across jurisdictions on the most favorable approach to managing such results, with some countries favoring return by default and others preferring to return only with the express consent of research participants. We conclude by outlining policy considerations that should guide researcher practices in this context. As international DTP genomic research evolves, jurists and ethicists should be attentive to the ways novel approaches to subject recruitment align with existing ethical and regulatory norms in research with human participants. This paper is a preliminary step toward documenting such alignment in the context of the return of individual research results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.128 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.012 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".