Common Practices in the Quebec Translation Milieu with Respect to Canadian English Usage
Bibliographic record
Abstract
The widespread adoption of translation technologies and the availability of online tools has reshaped not only the translation process, but also research methods, as translators gradually abandon print resources in favour of online ones. What happens when reference materials like dictionaries—generally seen as authoritative in matters of spelling and style—are infrequently updated, or if translators become less reliant on them? Given that one of the major Canadian English reference books, The Canadian Oxford Dictionary (COD) , was last published in 2004, translators who work from French and other languages into English have had to complement their research with other sources. What has been the impact on their common practices? In 2022, the author carried out a study composed of a survey, which had 60 respondents, and 11 semi-directed interviews. It sought to ascertain the impact of evolving research methods and the lack of up-to-date reference materials on the habits of working translators in Quebec and Canada and in particular, on how they follow the spelling, style and vocabulary of Canadian English as a language variety. Given that Canadian English is notable in two ways—for the presence of French as a co-official language, leading to numerous borrowings and influences, and for its position as a settler colonial variety of English, whose vocabulary reflects contact with Indigenous languages, particularly with regard to toponymy—one might expect those aspects to provide ongoing challenges to translators in the current environment. The results show that while the role of dictionaries is in transition, respondents consider it a matter of responsibility and a point of identity to follow Canadian spelling and style, and they view linguistic variation more broadly as a source of cultural richness and diversity.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".