What does ‘respect for persons’ require? Attitudes and reported practices of genetics researchers in informing research participants about research
Bibliographic record
Abstract
BACKGROUND: It has been suggested that researchers are obliged to offer summary findings to research participants to demonstrate respect for persons, and that this may increase public trust in, and awareness of, the research enterprise. Yet little research explores researchers' attitudes and practices regarding the range of initiatives that might serve these ends. METHODS: Results of an international survey of 785 eligible authors of genetics research studies in autism or cystic fibrosis are reported. RESULTS: Of 343 researchers who completed the survey (44% response rate), the majority agreed that their team should (i) inform participants of summary findings (90.7%) and (ii) ensure they gain an awareness of developments in the field (86.9%). Additionally, the majority reported that in practice, their team (i) informs participants of summary findings (69.4%) and (ii) provides other types of relevant non-results information (eg, state of science in the field, opportunities for research participation) (67.9%). CONCLUSION: Researchers endorsed the obligation of communicating with research participants by providing summary findings and other research-related information in equal measure. In light of these findings, it is suggested that while the provision of summary results may contribute to efforts to discharge the obligation of respect for persons, it may be neither a necessary nor a sufficient means to this end.
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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 | 0.167 | 0.324 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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".