Bibliographic record
Abstract
Cet article étudie comment le recours à l’animalisation dans Les Mohicans de Paris d’Alexandre Dumas est l’espace d’une véritable réflexion sur les rapports entre l’humain et l’animal. Ceci apparaît de façon nette dans la fictionnalisation du chien qui induit un brouillage des limites séparant humain et animal, brouillage qui a pour fonction de permettre l’articulation des personnages canins aux enjeux fondamentaux du roman. De façon plus précise, la mise en scène du « meilleur ami de l’homme » sert à redoubler le projet politique au cœur des Mohicans de Paris. This paper examines how, in Les Mohicans de Paris, Alexandre Dumas assigns animalistic features to some characters to question the relations between humans and animals while portraying the various dogs in the novel in a way which blurs the limits between humans and animals. These seemingly accessory canine characters are actually closely associated with the fundamental elements of the novel. More precisely, the way “man’s best friend” is put in fiction actually repeats the political project at the heart of Les Mohicans de Paris.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.027 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".