Bibliographic record
Abstract
L’Organisation mondiale de la santé (OMS) a fait l’objet de critiques parfois virulentes sur sa gestion initiale de la crise du Covid-19 et sur son attitude à l’égard du gouvernement chinois lors des premières semaines de l’épidémie. Contribuant à la réflexion sur l’autorité des organisations internationales en période de crise, cet article démontre que la réponse de l’OMS n’a pas tant été contrainte par une supposée « influence » de la Chine, que par la nécessité de prévenir une contestation de l’autorité d’expertise de l’organisation. Ainsi, dans un premier temps, le choix d’une stratégie de conciliation à l’égard de Pékin a permis à l’OMS de s’assurer un accès aux informations épidémiologiques en provenance de Chine. Néanmoins, cette approche a, dans un second temps, nourri la contestation de l’administration Trump et entraîné une forte politisation des débats, nuisant in fine à l’autorité de l’organisation dans la coordination de la lutte contre la pandémie.
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.
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 | 0.042 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.032 |
| Scholarly communication | 0.018 | 0.011 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.014 | 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; 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".