Pourquoi la reprise après la Covid-19 doit être sexospécifique
Bibliographic record
Abstract
Cette synthèse met en évidence les principaux enseignements tirés de la recherche menée dans le cadre de l’initiative Covid-19 Responses for Equity (CORE) axée sur l’impact de la pandémie sur différents groupes vulnérables et sur la façon dont le genre recoupe et exacerbe souvent ces conséquences. Soutenu par le Centre de recherches pour le développement international (CRDI), CORE réunit 21 projets visant à comprendre les impacts socio-économiques de la pandémie, améliorer les interventions existantes et générer de meilleures options stratégiques pour la reprise. La recherche est principalement dirigée par des chercheurs locaux, des universités, des groupes de réflexion et des organisations de la société civile dans 42 pays d’Afrique, d’Asie, d’Amérique latine et du Moyen-Orient.
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 | 0.015 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 0.004 |
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".