Bibliographic record
Abstract
Depuis quelque vingt ans, Dominique Maingueneau, linguiste et professeur à l’Université Paris XII, s’applique à théoriser l’analyse du discours littéraire tout en cherchant à la faire reconnaître comme discipline des études littéraires, en invoquant une « rectification des frontières » épistémologiques dans ce domaine. Au centre de cette théorie se trouve une notion clé, un principe invariant appelé paratopie . Malgré un succès relatif, cette notion présenterait un problème de taille : celui de placer, dans la même catégorie, l’analyse du discours littéraire et l’objet de son analyse. À partir de ce constat, que Maingueneau souligne lui-même, ce sont les implications épistémologiques et la valeur opératoire de la paratopie que cet article tente de mettre en lumière afin de comprendre la réticence des spécialistes d’autres orientations critiques à reconnaître le bien-fondé de la démarche de Maingueneau.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.052 | 0.010 |
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".