"Maria Chapdelaine" vue d'ailleurs: les agents et les enjeux derrière la traduction espagnole et catalane d'un classique de la littérature canadienne-française
Bibliographic record
Abstract
Le present article vise a analyser les differentes reeditions des traductions espagnole et catalane d’un classique de la litterature canadienne-francaise, soit Maria Chapdelaine. A partir des prefaces concues en tant que prises de position (au sens bourdieusien), sont analyses les differents agents derriere l’initiative de faire traduire ce roman en Espagne et en Catalogne, ainsi que le rapport de ces agents envers l’alterite canadienne-francaise du texte source. Est revelee la fonction ideologique des prefaces en tant que dispositifs discursifs qui permettent aux agents des champs cibles de reveiller certains debats qui vont (thematiquement et chronologiquement) bien au-dela des questions liees au texte original.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".