Bibliographic record
Abstract
Deleuze relevait chez Beckett des « disjonctions inclusives », soit des sélections paradigmatiques logiquement incompatibles qu’une langue « bégayante » fait cependant cohabiter. La prose d’Éric Chevillard travaille cette limite de la langue. Ainsi, le protagoniste de Palafox (1990) est à la fois papillon, reptile et éléphant ; Crab (Un fantôme, 1995) se distingue à la fois par « sa laideur effrayante » et « la beauté irrégulière de ses traits ». Une taxinomie fantaisiste sur le plan des mots entraîne une ontologie irréconciliable au niveau du monde-référent. Nous étudions ici les modalités par lesquelles ces corps irrationnels parasitent les structures du discours et, partant, celles du « réel ».AbstractDeleuze had noted Beckett’s “inclusive disjunctions”, that is, logically incompatible paradigmatic choices which could nonetheless coexist in a “stammering” language. Éric Chevillard’s prose works this limit of language. Thus the protagonist of Palafox (1990) is at the same time butterfly, reptile and elephant, Crab (Un fantôme, 1995) is distinguished both by his “frightening ugliness” and the “irregular beauty of his features”; a fantastical taxonomy of words engages an irreconcilable ontology on the level of world-referent. I reflect here on the modalities whereby such irrational bodies parasitically occupy the structures of discourse and, thereby, of the “real”.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".