Bibliographic record
Abstract
Certaines approches stylistiques, vouees a l’analyse des textes litteraires, se sont investies d’une pretention scientifique de description linguistique qui a eu pour effet une presentation technique et normative des faits de la langue. Le dogmatisme de cette posture analytique, qui d’ailleurs est inseparable des proprietes phonetique, morphologique et syntaxique de la surface textuelle, a confine la reflexion sur le style a une sorte de techne positive de la « forme ». Mais quel sens et quelle pertinence le terme de « forme » peut-il recouvrir en stylistique? Et dans quelle mesure la stylistique gagne-t-elle a integrer la notion d’« informe » a son cadre theorique? Afin de repondre a ces questions, j’ai pour objectif avec cet article de susciter une reflexion en deux temps. Premierement, je reexaminerai certaines conceptions de la « forme », qui ont contribue a eriger les approches stylistiques tout au long de l’histoire, et, deuxiemement, de facon a reclamer un elargissement de l’horizon theorique, je chercherai a montrer comment la categorie de l’« informe » peut ouvrir de nouvelles perspectives pour l’etude du style en litterature.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.021 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".