Goodbye Sékou : Perdre un esprit engagé dans les politiques de développement et la recherche en santé globale
Bibliographic record
Abstract
Tout en rendant hommage à Sékou, un des collaborateurs importants de Global Vaccine Logics, qui nous a quittés en décembre 2020, nous voulons mettre en exergue la place importante que jouent les assistants de recherche et les jeunes chercheurs africains dans les projets de santé globale. Une partie de la trajectoire de Sékou tout en révélant par-delà les réflexions, les entrelacements entre santé, extraction et engagement, ramène à faire un appel vibrant pour améliorer les conditions de recherche dans les universités africaines et favoriser la décolonisation des conditions de production des connaissances pour frayer le chemin, laisser la place et donner parole et crédit à l’expertise de la jeune génération africaine qui prend la relève.
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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.015 | 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".