Qualitative study on custodianship of human biological material and data stored in biobanks
Bibliographic record
Abstract
BACKGROUND: Balancing the rights and obligations of custodians and applicants in relation to access to biobanks is of utmost importance to guarantee trust and confidence. This study aimed to reveal which issues divide different stakeholders in an attempt to determine the rights and/or obligations held on human biological materials (HBM) and data. METHODS: Twenty-eight informants in the Benelux and Scandinavia were interviewed in order to capture the perspectives of experts and stakeholders in relation to the rights and obligations held by custodians and applicants with respect to access to HBM and data. RESULTS: There was no consensus among the informants on whether the custodian of a biobank should decide upon the scientific merits and the utility of an access request. Nearly all informants agreed that a new request or an amendment to the initial request has to be submitted when an applicant wants to use leftover HBM in a new or follow-up project. Several informants felt that it might be justified to charge higher access fees to external or industrial applicants that did not contribute (directly or indirectly) to the collection of HBM and data. Most informants agreed that a custodian of a biobank could request the sharing and return of research results. It was furthermore argued that some of the benefits of research projects should be fed back into biobanks. CONCLUSIONS: The interviews revealed a rather complex web of rights and obligations allocated to the custodian and the applicant in relation to access to HBM and data stored in biobanks. Some rights and obligations are negotiated on a case-by-case basis, while others are stipulated in access arrangements. We did find a consensus on the attribution of certain general rights to the custodians and the applicant.
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 | 0.045 | 0.499 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| 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; 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".