Pandémie de Covid-19 : appel à l’engagement des universitaires dans l’espace public
Bibliographic record
Abstract
Dès les débuts de la pandémie de COVID-19, les bouleversements engendrés par le numérique sur la diffusion et la consommation d’informations ont soulevé des enjeux majeurs pour la santé publique. En parallèle à la pandémie, le monde fait face à une véritable « infodémie » où les fausses informations se mêlent aux « faits » scientifiques. Devant cette situation problématique, quel rôle doivent jouer les universitaires ? Nous les invitons à adopter une posture d’engagement dans l’espace public pour contribuer à la démocratisation des connaissances.
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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 | 0.032 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.013 |
| Scholarly communication | 0.022 | 0.014 |
| Open science | 0.002 | 0.029 |
| Research integrity | 0.011 | 0.017 |
| Insufficient payload (model declined to judge) | 0.043 | 0.012 |
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".