Une arche de vanité ou le miroir ironique de la mélancolie. Éric Chevillard, un écrivain au Museum d’histoire naturelle1
Bibliographic record
Abstract
Lancée en 2018 par les éditions Stock (Paris), la collection « Ma Nuit au musée » repose sur un concept simple : un auteur ou une autrice passe une nuit, seul.e, dans un musée, et tire de cette expérience un récit. En novembre 2019, Éric Chevillard passe une nuit au Museum d’histoire naturelle à Paris et, en 2022, il publie un récit sur cette expérience d’enfermement nocturne parmi des spécimens empaillés : L’Arche-Titanic. Cet article propose une lecture de ce récit de Chevillard qui, conjuguant angoisse et désinvolture apparente par le biais d’un jeu illustrant, non sans ironie, la tension entre l’ambition préservatrice du musée et les sentiments de perte inspirés par les spécimens exposés, interroge le statut de l’écrivain ainsi que son rôle dans la sphère littéraire contemporaine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".