La représentation littéraire des animaux : des limites langagières aux possibilités poétiques chez Lamartine et Ponge
Bibliographic record
Abstract
En s’arrêtant à la représentation des animaux non humains dans les écrits d’Alphonse de Lamartine et de Francis Ponge, deux poètes dont la production littéraire couvre les deux derniers siècles et qui s’intéressent clairement aux vies animales, cet article cherche à mettre en relief les limites de la représentation littéraire des animaux. Comme dans la plupart des productions culturelles de l’Occident moderne, chez Lamartine et Ponge, les animaux sont généralement réduits au symbolique. Malgré la bonne volonté des poètes, la poésie n’échappe pas à l’anthropocentrisme. Or, plutôt que de signaler la faillite de la poésie en ce qui concerne la représentation des animaux, ces limites constituent un point d’accès à des réalités hybrides dont il faut encore rendre compte.
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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 | 0.004 |
| 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 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".