Translating idiomatically into French in Quebec: Caught in the crossfire
Bibliographic record
Abstract
In translation theory, a translation is said to be“idiomatic”when it reads fluently, when it does not bear any linguistic or cultural features that are reminiscent of the source language and culture.“Idiomatic”translation thus stands in sharp contrast to the notion of interference, which is generally viewed as one of the worst linguistic mistakes in translation. However, the tendency to resort to interference, knowingly or unknowingly, is usually high among speakers who are bilingual or live in bilingual settings (for example speakers of French in North America). For some of these speakers, interference is not always a mistake, but an integral part of communication strategies as well as a marker of a distinct and distinctive linguistic identity. For others, interference is nothing less than a plague that threatens the integrity of the language, of the culture, and therefore of the group identity. In such a sociolinguistic environment, translating idiomatically or counteridiomatically becomes quickly coloured by ideology. What are these ideologies? How do they impact translation as a product? To tackle these questions, the paper will examine the impact of two types of ideological discourse relating to French spoken in Quebec and their impact on translation. It will argue that French Quebecker translators are, as it were, torn between the requirement to protect the quality of the French language in Quebec and the imperative to adapt their translations to their target audience whose workaday idiom bear the features of English (anglicisms).
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".