Eugène Morel : l’odyssée d’un polygraphe au pays de la classification décimale
Bibliographic record
Abstract
Pourquoi Eugène Morel, bibliothécaire « à la Nationale », choisit-il d’introduire de manière précoce, avant la Première Guerre mondiale, la classification Dewey dans la bibliothèque populaire de Levallois-Perret ? Cette expérimentation visionnaire, peu encouragée par les pionniers de la classification universelle, trouve ses racines dans la propre histoire de Morel, artiste, écrivain expérimentant une forme de polygraphie, entre romans, articles, pièces de théâtre et écriture qui se voulait scientifique et « bibliothéconomique ». En adaptant la classification Dewey aux besoins d’une bibliothèque populaire, Morel poursuit son rêve de mettre la culture à la portée de tous, et la lutte qu’il s’est assignée de lutter contre les « cimetières de livres » non classés.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".