Bibliographic record
Abstract
Condamné à disparaître après la prise du pouvoir par les talibans en 2021, l’Institut national de musique d’Afghanistan (Anim) a pu renaître au Portugal grâce aux deux ans d’efforts déployés par son fondateur, le Dr Ahmad Naser Sarmast. Créée à Kaboul en 2010, cette école de musique s’opposait aux valeurs imposées par les islamistes. Elle prônait la mixité sociale comme celle des genres, et enseignait les répertoires de tradition afghane et de musique classique occidentale. L’irruption des talibans, réfractaires à toute forme de musique et de mixité, imposait de mettre en sécurité les près de 600 élèves, employés et professeurs de l’institut avec leurs familles ; de leur faire quitter l’Afghanistan ; de permettre à l’Anim de poursuivre son activité en assurant que la musique afghane continue de se transmettre en exil. Autant de défis relevés par le Dr Sarmast. Retour sur cette épopée contre l’obscurantisme.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.652 | 0.291 |
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".