Orientations to French Language Varieties among Western Canadian French-as-a-Second-Language Teachers
Bibliographic record
Abstract
In Canada, official French-English bilingualism and the long-standing presence of Indigenous and immigrant languages has shaped how these languages and their varieties are learned, taught, and used in educational contexts. To date, there has been little inquiry into French-as-a-second-language (FSL) teachers’ orientations to the varieties of French they teach, in particular Canadian French language varieties (Arnott, Masson, and Lapkin 2019), despite studies showing that ideologies associated with different language varieties can impact teachers’ instructional choices. This article presents an analysis of the narrated experiences of FSL teachers from Western Canada, drawn from journal and interview accounts, about their encounters with different language varieties while on professional development in France. Thematic and discourse analytic perspectives bring to light complex negotiations of ideological meaning and representation related to language variation in French, as well as the discursive strategies employed by the participants in orientating to these meanings. These discursive actions make evident deeply embedded language ideologies that have significant implications for both French as a first and as a second language education, not only in terms of a prevailing linguistic insecurity among francophones but equally significant for FSL teachers’ professional identity construction, especially those who are themselves second language speakers of French. The analysis and discussion highlight the importance of integrating pluralistic perspectives into teacher education programs and ongoing teacher professional development initiatives.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.025 | 0.022 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".