Bibliographic record
Abstract
Biobanks are controversial due to their ethical, legal, and social implications. Recent discussion has highlighted a central role for governance in helping to address these controversies. We argue that sustainable governance of biobanks needs to be informed by public discourse. We present an analysis of a deliberative public engagement to explore the public values, concerns, and interests underlying recommendations pertaining to biobank governance. In particular, we identify five themes underlying expressed goals and concerns of participants regarding the development, operation and application of biobank research. Ultimately, we argue that, for the deliberants, governance represented a way to achieve trust in biobanks through accountability, transparency and control. As discussion of biobank governance moves the conceptual to the specific, policy makers and researchers should acknowledge the importance of the public viewpoint in maintaining trust; this acknowledgement is of importance to the ultimate success and longevity of biobanks.
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 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 | 0.055 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.079 |
| Scholarly communication | 0.021 | 0.043 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.018 | 0.020 |
| Insufficient payload (model declined to judge) | 0.004 | 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".