Transparency of Biobank Access in Canada: An Assessment of Industry Access and the Availability of Information on Access Policies and Resulting Research
Bibliographic record
Abstract
A key issue impacting public trust in biobanks is how these resources are utilized, including who is given access to biobank data and samples. To assess the conditions under which researchers are given access to Canadian biobanks, we reviewed websites and contacted Canadian biobanks to determine the availability of information on access policies and procedures; research resulting from access biobank data and samples; and conditions on private industry access to biobanks. We also conducted expert interviews with key Canadian stakeholders (n = 11) to obtain their perspectives on biobank transparency and access policies. Among 21 Canadian biobanks, there was wide variation in the access information made publicly available, and the majority of the biobanks allowed access by industry applicants. The paper further discusses the implications of our findings. We argue that biobanks should be governed by the principles of transparency, accountability, and accessibility, and attention must be given to the conditions around the commercialization of biobank-based research.
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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 | 0.041 | 0.129 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.016 |
| Science and technology studies | 0.016 | 0.009 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".