Innovations in research ethics governance in humanitarian settings
Bibliographic record
Abstract
BACKGROUND: Médecins Sans Frontières (MSF) is one of the world's leading humanitarian medical organizations. The increased emphasis in MSF on research led to the creation of an ethics review board (ERB) in 2001. The ERB has encouraged innovation in the review of proposals and the interaction between the ERB and the organization. This has led to some of the advances in ethics governance described in this paper. DISCUSSION: We first update our previous work from 2009 describing ERB performance and then highlight five innovative practices: • A new framework to guide ethics review • The introduction of a policy exempting a posteriori analysis of routinely collected data • The preapproval of "emergency" protocols • General ethical approval of "routine surveys" • Evaluating the impact of approved studies. The new framework encourages a conversation about ethical issues, rather than imposing quasi-legalistic rules, is more engaged with the specific MSF research context and gives greater prominence to certain values and principles. Some of the innovations implemented by the ERB, such as review exemption or approval of generic protocols, may run counter to many standard operating procedures. We argue that much standard practice in research ethics review ought to be open to challenge and revision. Continued interaction between MSF researchers and independent ERB members has allowed for progressive innovations based on a trustful and respectful partnership between the ERB and the researchers. In the future, three areas merit particular attention. First, the impact of the new framework should be assessed. Second, the impact of research needs to be defined more precisely as a first step towards being meaningfully assessed, including changes of impact over time. Finally, the dialogue between the MSF ERB and the ethics committees in the study countries should be enhanced. SUMMARY: We hope that the innovations in research ethics governance described may be relevant for other organisations carrying out research in fragile contexts and for ethics committees reviewing such research.
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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 | 0.202 | 0.933 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.070 |
| 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 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".