Maria Chapdelaine vue dâailleurs: les agents et les enjeux derrière la traduction espagnole et catalane dâun classique de la littérature canadienne-française
Bibliographic record
Abstract
Le prsent article vise analyser les diffrentes rditions des traductions espagnole et catalane d'un classique de la littrature canadienne-franaise, soit Maria Chapdelaine. partir des prfaces conues en tant que prises de position (au sens bourdieusien), sont analyss les diffrents agents derrire l'initiative de faire traduire ce roman en Espagne et en Catalogne, ainsi que le rapport de ces agents envers l'altrit canadienne-franaise du texte source.Est rvle la fonction idologique des prfaces en tant que dispositifs discursifs qui permettent aux agents des champs cibles de rveiller certains dbats qui vont (thmatiquement et chronologiquement) bien au-del des questions lies au texte original.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".