De l’image animalière à la banalité zoologique : le bestiaire sarrautien
Bibliographic record
Abstract
De la bête sauvage, à l’animal de ferme jusqu’à la bestiole, l’œuvre de Nathalie Sarraute abonde en renvois zoologiques. Hormis l’image animalière, cet impressionnant bestiaire est également parsemé de clichés zoologiques, une composante de cette collection d’animaux qui, jusqu’à présent, n’a pas fait l’objet de recherches poussées. Optant pour une étude intratextuelle, plutôt qu’une analyse générale de la locution figée animale, ce travail vise notamment à cerner le rôle que joue ce type de cliché tant à l’intérieur du bestiaire, qu’au sein du fonctionnement et de la structure de l’œuvre. Par le biais d’études de cas, dont les extraits sont puisés de Portrait d’un inconnu (1948), Martereau (1953) et Le planétarium (1959), il est question dans cet article de sonder le rapport entre l’humain et l’animal tel qu’il est exprimé par le langage, à l’intérieur ainsi que, de manière plus générale, à l’extérieur de l’œuvre sarrautienne. From wild beasts, to farm animals and even insects, the zoological references in Nathalie Sarraute’s works are numerous. Aside from animal imagery, there are also many zoological clichés in this impressive bestiary, components of this assortment of animals that have yet to be studied in depth. In this article, instead of studying the zoological cliché in a general manner, we have chosen to take an intratextual approach, in order to identify the workings of this figure of banality inside the bestiary as well as within the logic and the structure of the corpus. Through case studies of excerpts taken from Portrait d’un inconnu (1948), Martereau (1953) and Le planétarium (1959), we will examine the relationship between man and beast as expressed through language, both inside and, on a broader scale, outside the works of Nathalie Sarraute.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.030 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".