Rethinking French‐as‐a‐second‐language education as a space for supporting Indigenous language work on xʷməθkʷəyəm (Musqueam) land
Bibliographic record
Abstract
Abstract In Canada, growing awareness of multilingualism in language teacher education requires educators to rethink how we practice language education. Many are increasingly questioning how established English–French official language programming can be reconciled with the reviving and reclaiming of Indigenous languages, and how we might think across Indigenous and Western worldviews in ethical, relational, and responsible ways. One such example is the redesign of a course that familiarizes future elementary teachers with a multilingual, place‐based approach to teaching French that incorporates knowledge of local ancestral and immigrant languages. Classroom discussions made evident ideological tensions as students and instructors navigated conflicting priorities, often pitting the need to learn instructional strategies for teaching official languages against the urgency to support local First Nations languages. By engaging our respective settler (European) and Indigenous (Hawaiian) perspectives, we identify moments of critical reflection to better understand how differently conceptualized approaches to language learning and teaching can coexist across language education programs in Canada and beyond.
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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 | 0.006 | 0.005 |
| 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 | 0.018 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".