Comment valoriser le patrimoine culturel immatériel via un musée numérique ?
Bibliographic record
Abstract
Avec l’introduction du numérique dans le milieu muséal et l’émergence du patrimoine culturel immatériel, les pratiques muséographiques sont réinventées. L’article présente la méthode mise en œuvre pour valoriser les fêtes du feu du solstice d’été dans les Pyrénées centrales inscrites sur la Liste représentative du patrimoine immatériel de l’humanité depuis 2015. Il rend compte des défis et de la démarche d’écriture muséographique pour concevoir le modèle d’un musée numérique et élaborer son programme communicationnel. L’enjeu du projet est d’articuler les spécificités de ce PCI avec les potentialités offertes par le numérique pour développer un musée le plus complet possible dans ses fonctions traditionnelles de conservation, d’étude et de communication.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".