Le Picaresque dans la construction du roman hispano-américain. Le Cas du Periquillo
Bibliographic record
Abstract
Cet article examine le rôle que joua le modèle picaresque dans la formation du roman hispano-américain. L'exploration des relations intertextuelles entre le Periquillo Sarniento (1816) et la forme picaresque traditionnelle permet de repérer les processus de déconstruction à l'oeuvre dans ce roman mexicain et par la suite de déterminer comment les conditions sociohistoriques particulières et les caractéristiques discursives propres à l'Amérique latine ont mené à la transformation des traits picaresques, même fondamentaux. Le roman picaresque apparaît ainsi jouer un rôle majeur dans la naissance du roman hispano-américain en contribuant à produire, malgré et grâce à des modifications profondes de ses composantes, une forme narrative nouvelle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".