Scientific Advisory Committees at the World Health Organization: A Qualitative Study of How Their Design Affects Quality, Relevance, and Legitimacy
Bibliographic record
Abstract
Governments and international organizations frequently convene scientific advisory committees (SACs) to support decision-making with scientific advice. In this study, thematic analysis of interviews with 35 senior WHO staff identified five main themes characterizing WHO's experience with designing SACs to ensure quality, relevance, and legitimacy of scientific advice. First, in addition to technical matters, SACs are established to serve broader strategic objectives, including consensus building to promote high-level political messages. Second, for SACs to be fully independent, they must have autonomy from the institutions convening or funding them, from the institutions from where SAC members are recruited, and from the institutions to whom the advice is directed. Third, since choices affecting quality, relevance, and legitimacy are closely linked, designing SACs often require trade-offs among these three attributes. Fourth, staff supporting SACs need to balance between safeguarding SACs from external influence and being receptive to the external political environment. Fifth, the design of SACs need to balance the involvement of stakeholders with the power to act on recommendations against the need to protect the independence and integrity of the scientific process. Overall, this study highlights key choices conveners of SACs must make when seeking to promote quality, relevance, and legitimacy of scientific advice.
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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 | 0.065 | 0.087 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.012 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".