Access and use of human tissues from the developing world: ethical challenges and a way forward using a tissue trust
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Scientists engaged in global health research are increasingly faced with barriers to access and use of human tissues from the developing world communities where much of their research is targeted. In part, the problem can be traced to distrust of researchers from affluent countries, given the history of 'scientific-imperialism' and 'biocolonialism' reflected in past well publicized cases of exploitation of research participants from low to middle income countries. DISCUSSION: To a considerable extent, the failure to adequately engage host communities, the opacity of informed consent, and the lack of fair benefit-sharing have played a significant role in eroding trust. These ethical considerations are central to biomedical research in low to middle income countries and failure to attend to them can inadvertently contribute to exploitation and erode trust. A 'tissue trust' may be a plausible means for enabling access to human tissues for research in a manner that is responsive to the ethical challenges considered. SUMMARY: Preventing exploitation and restoring trust while simultaneously promoting global health research calls for innovative approaches to human tissues research. A tissue trust can reduce the risk of exploitation and promote host capacity as a key benefit.
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.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it