Comment capturer le patrimoine culturel immatériel : réflexions autour de la patrimonialisation de la fauconnerie
Bibliographic record
Abstract
Cet article aborde la patrimonialisation d’un item protégé par la « Convention pour la sauvegarde du patrimoine culturel immatériel de l’humanité » de l’UNESCO depuis 2010 : « La fauconnerie, un patrimoine humain vivant ». Suivant une brève description de la fauconnerie, au moyen de laquelle est notée son essence immatérielle, l’auteur poursuit l’analyse du processus conduisant à son intégration dans la sphère du patrimoine mondial. Ce faisant, il semble que la réussite d’un tel projet demeure compromise en raison de difficultés que présente sa médiatisation dans l’espace public. Cette investigation débouche alors sur l’identification de trois enjeux sémiotiques sous-jacents à ces problèmes et espère, par là, mener une réflexion dans le domaine de la muséologie désireuse d’accueillir l’immatériel au rang de ses principales préoccupations de recherche.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.030 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".