Crooked ol' maids - all in de family: traduction de Les Belles Soeurs de Michel Tremblay - Les rapprochements entre le > du Quebec et l'anglais dialectal de Terre Neuve dialectal de Terre Neuve
Bibliographic record
Abstract
Michel Tremblay est un des dramaturges les plus reconnus et les plus traduits au Canada. Les traductions de ses pieces produisent des qualites variantes, puisque Tremblay emploie souvent le franyais populaire (le « joual » ou le franyais quebecois), ce qui pose particulierement des difficultes pour le traducteur. Je propose la traduction de la piece Les Belles Soeurs dans I'anglais dialectal de Terre Neuve pour plusieurs raisons, y compris: les rapprochements culturels, linguistiques, politiques et historiques, aussi bien que la situation de la femme et les stereotypes negatifs associes a la langue populaire de ces deux provinces au Canada. Les dramaturges des deux provinces se servaient du theatre surtout altematif' comme outil de contestation contre la societe et le gouvemement canadien pour reaffirmer leur identite culturelle qu'ils croyaient menacee par la modernisation rapide imposee par le reste du Canada. Les similarites entre les deux provinces et la ressemblance entre les themes traites dans leurs theatres sont plus qu' evidentes, ce qui convient le plus a exprimer la realite de la situation quebecoise de Les Belles Soeurs.
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 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 | 0.001 |
| Science and technology studies | 0.027 | 0.013 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".