Bibliographic record
Abstract
Dans cet article, nous déchiffrons le début de la littérature de l’himalayisme à travers une analyse de Mont Everest (1942) de Joseph Peyré, et étudions comment ce roman s’articule sur un certain nombre de publications précédentes : entre autres, récits des premières expéditions britanniques à l’Everest, textes de David-Néel, et Matterhorn (1939) également de Peyré, puisque l’un des personnages principaux, le guide suisse Jos-Mari, figure aussi dans Mont Everest.Notre étude s’appuie sur la notion de « complexe scientifico-ludique » développée par Nicolas Giudici dans La Philosophie du mont Blanc (2000) et qui se définit comme le fondement du regard occidental sur la montagne depuis la fin du XVIIIesiècle. Nous examinons comment les aspects mystiques traditionnellement associés aux montagnes himalayennes entrent en rapport, et en conflit, avec ce « complexes cientifico-ludique », et finissent par définir ce que nous appellerons un « complexe mystico-ludique ».
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".