Bibliographic record
Abstract
Cet entretien entre Nathalie Bondil, directrice générale et conservatrice en chef du Musée des beaux-arts de Montréal et Anik Meunier, professeure titulaire en éducation et muséologie et directrice du Groupe de recherche sur l’éducation et les musées (GREM) de l’Université du Québec à Montréal (UQAM), a eu lieu le 1er novembre 2018 à l’occasion du lancement du livre Culture et éducation non formelle. Cet ouvrage collectif dirigé par Daniel Jacobi est le dixième titre de onze publiés dans la collection « Culture et publics », dirigée par Anik Meunier et Jason Luckerhoff, professeur titulaire en culture et communications de l’Université du Québec à Trois-Rivières (UQTR). L’animation a été assurée par Julie Rose, étudiante à la maîtrise en muséologie et assistante de recherche au sein du GREM de l’UQAM.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.025 | 0.033 |
| Scholarly communication | 0.018 | 0.010 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.029 | 0.005 |
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".