Le Musée des Beaux-Arts de Dunkerque. Reflets d’une collection plurielle
Bibliographic record
Abstract
Dans la continuité des voyages scientifiques et de la philosophie des Lumières du xviiie siècle, la France voit émerger sous la Révolution, la création de musées et de muséums. Ces derniers poursuivent la vocation d’instruments pédagogiques incarnant le « Républicanisme des arts » – Georges Monnier, « L’art et ses institutions en France. De la Révolution à nos jours », Gallimard, Paris, 1995, p. 33 – sous-entendu un musée idéal, encyclopédique, accessible à tous. Parallèlement les cabinets de curiosités se développent, les sociétés savantes se multiplient. Parmi ses membres, des collectionneurs, des propriétaires aisés, des fonctionnaires civils et militaires qui souvent, sont à l’origine de la création des musées locaux et régionaux. C’est ainsi que naît celui de Dunkerque. Constitué comme un muséum dès 1829, inauguré en 1841 sous l’appellation musée communal, transformé en 1877 en musée-bibliothèque, l’après-guerre voit se reconstruire la ville et son musée des Beaux-Arts, en 1973.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.002 |
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".