Bibliographic record
Abstract
La rencontre intitulée « Exposer les migrations », organisée par la Fédération des écomusées et des musées de société (FEMS) le 14 novembre 2024 dans le cadre de ses « JE-DIS », visait à réfléchir aux collections, aux collectes, aux projets de médiation et à la pérennité du patrimoine des migrations humaines au sein de différentes institutions muséales. Animée par Élisabeth Jolys-Shimells, vice-présidente de la FEMS et responsable des collections du Musée national de l’histoire de l’immigration, elle réunissait Mathilde Beaujean, cheffe de projet expositions au musée de l’Homme, exposition Migrations, une odyssée humaine ; Florence Borel, chargée de projets de médiation au Louvre-Lens ; Marco Zanni, chargé d’expositions au Louvre-Lens, exposition Exils – Regards d’artistes ; Camille Faucourt, conservatrice du patrimoine, responsable du département Mobilité, métissage et communication du Mucem, exposition Revenir ; Émilie Gandon, conservatrice du patrimoine au Musée national de l’histoire de l’immigration, exposition Chaque vie est une histoire ; Nathalie Mémoire, directrice du Muséum - sciences et nature et du Jardin botanique de la ville de Bordeaux, exposition Migrations du vivant.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.077 | 0.017 |
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".