French-Medium Instruction in Anglophone Canadian Higher Education: The Plurilingual Complexity of Students and Their Instructors
Bibliographic record
Abstract
In this article, we analyze the plurilingualism of instructors and their students in a program taught through the medium of French at a multilingual, Anglophone university in Western Canada. We employ the lenses of plurilingualism and plurilingual competence in the analysis of data from a one-year qualitative study of plurilingualism across the disciplines at the university. We analyze interview data and students’ writing samples, focusing on how French and other languages are used by instructors and students in classes, and on the professional dilemma that instructors face in such courses: are they disciplinary experts and/or French immersion teachers? In our discussion, we suggest that instructors’ and students’ classroom practices are the result of several factors, including institutional discourses around plurilingualism and the French language, personal beliefs and ideologies, experiences of mobility from France and Quebec to British Columbia (instructors), and normative practices previously experienced in French immersion schools (students).
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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; 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".