Evolving values in ethics and global health research
Bibliographic record
Abstract
Over the past 25 years, the ethics of international health research have shifted from addressing narrow issues such as cultural differences in informed consent practices towards a greater emphasis on development and social justice. We anticipate that the next 'era' in international research ethics will involve an intensification of this focus on the role of research in achieving global justice. Three values, in particular, will shape how ethics considerations should evolve: solidarity; respect for Southern innovation; and commitment to action. We expect continuing debate on whether researchers and research sponsors should recognise more than a minimal set of obligations for the care and benefit of research participants and their communities. As the debate about the role of research in development intensifies, we expect to see new and more elaborate mechanisms for financing on-going access to beneficial interventions, ancillary care and other research-related benefits, as well as a greater involvement in research funding by developing country governments and private foundations. Ethics review and oversight need to reflect on these new values and on ways of operationalising them, or risk becoming marginalised in the research process.
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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 | 0.221 | 0.124 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.011 | 0.172 |
| Scholarly communication | 0.031 | 0.031 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.018 | 0.026 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier 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".