Formes d'expression et d'atténuation de l'évaluation dans les comptes rendus d'ouvrages en linguistique
Bibliographic record
Abstract
Ces dernieres annees, le discours scientifique a fait l’objet de nombreuses etudes. Examinant la mise en mots et texte des resultats de recherches, les auteurs de ces etudes analysent, entre autres, l’organisation textuelle, les choix lexicaux et leurs variations linguistiques, disciplinaires et socioculturelles. La presente etude s’inscrit dans le prolongement de ces travaux. Elle examine le compte rendu critique d’ouvrage, un type de discours scientifique dont la fonction ultime est de presenter une nouvelle publication et d’en evaluer la pertinence dans une discipline donnee. Cette visee evaluative va de pair avec la gestion des faces et rapports interpersonnels au sein de la communaute scientifique dont emane et ou circule ce type de discours. A partir d’un corpus de comptes rendus d’ouvrages tires de quelques revues specialisees en linguistique, l’etude met en exergue des strategies mobilisees par les evaluateurs pour emettre des jugements de valeur sur les travaux de leurs pairs et negocier des relations interpersonnelles au sein de leur communaute discursive.
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 | 0.017 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".