Bibliographic record
Abstract
Entre 1950 et 1970, les lancements de livres sont fréquents aux Éditions Fides. À chaque événement, le père Paul-Aimé Martin, fondateur de la maison, ne manque pas de prendre la parole. Éditeur aguerri, grand érudit et fin publiciste, le père Martin manifeste une énonciation éditoriale particulière à travers ses allocutions de lancement. Censé s’effacer devant l’auteur, de quoi parle exactement l’éditeur à ce moment où il chante les louanges de telle nouveauté? Cet article vise à jeter les prémisses d’une réflexion sur un type particulier de « discours » d’éditeur, soit l’allocution prononcée lors de lancements. Au-delà d’une certaine part de flagornerie consubstantielle à ce type d’énoncé, comment l’éditeur parvient-il à mettre en valeur son propre catalogue? Il s’agit d’observer quelles stratégies discursives déploie l’éditeur dans ce type d’énoncé, et quels rapports de force le sous-tendent.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".