RESEARCH ARTICLE Fair Shares and Sharing Fairly: A Survey of Public Views on Open Science, Informed Consent and Participatory Research in
Bibliographic record
Abstract
Context Biobanks are important resources which enable large-scale genomic research with human samples and data, raising significant ethical concerns about how participants ’ information is managed and shared. Three previous studies of the Canadian public’s opinion about these topics have been conducted. Building on those results, an online survey representing the first study of public perceptions about biobanking spanning all Canadian provinces was con-ducted. Specifically, this study examined qualitative views about biobank objectives, gover-nance structure, control and ownership of samples and data, benefit sharing, consent practices and data sharing norms, as well as additional questions and ethical concerns expressed by the public. Results Over half the respondents preferred to give a one-time general consent for the future shar-ing of their samples among researchers. Most expressed willingness for their data to be shared with the international scientific community rather than used by one or more Cana-
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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 | 0.115 | 0.133 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.019 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.006 |
| 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".