Health policy and systems research: towards a better understanding and review of ethical issues
Bibliographic record
Abstract
Given the focus on health systems in the post-millennium development goal era and moving towards the sustainable development goals, there is a compelling need for a common framework for health policy and systems research ethics to guide researchers and facilitate review by research ethics committees. A consultation of global health policy and systems research and ethics experts was convened to identify ethical considerations relevant to health policy and systems research based on existing knowledge and to identify knowledge gaps through a scoping review and further expert deliberation. Health policy and systems research is highly complex and, in the absence of guidance documents, there is significant variability in ethics review. Although fundamental ethical principles pertain to both traditional clinical research and health policy and systems research, the application of these principles requires a comprehensive understanding of the nature of health policy and systems research with its distinct challenges. Such awareness must be raised among researchers and research ethics committees. Current research ethics committees lack familiarity with health policy and systems research and because health policy and systems research is conducted in real-world contexts, committees often have difficulties in determining whether a project is indeed research and/or requires ethical review. Given the strong current focus on health policy and systems research to rapidly improve health and health systems functioning globally, greater engagement and dialogue around the ethical concerns is required to optimise research review and research conduct in this rapidly evolving field.
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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 | 0.306 | 0.474 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.019 | 0.024 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.017 | 0.021 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".