Une application contemporaine de l’échiquier cailloisien en médiation muséographique
Bibliographic record
Abstract
Une certaine après-midi de l’été 2006 où une petite dizaine de personnes se perdaient dans ce qui n’avait forme ni de labyrinthe, ni d’oubliettes, encore moins de salle de musée mais peut-être, tout au plus, de caverne d’Ali Baba, Dominique Autié fait comme celui qui retrouve un morceau de ficelle dans le fond de sa poche à l’instant critique. Cases d’un échiquier lui avait déjà fourni, deux ans auparavant, la structure parfaitement adaptée au cahier des charges établi pour la médiation muséographique du hall introductif aux expositions permanente et temporaires du muséum d’histoire naturelle de Toulouse refondé. À aucun moment, l’approche diagonale conduite par Roger Caillois n’a été plaquée sur la problématique muséographique : celle-ci, tout au contraire, appelait d’emblée les concordances, les ponts de discipline à discipline, conçus par Caillois il y a un demi-siècle, dont Cases d’un échiquier offre un précieux précipité.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".