Critical multilingual language awareness: the role of teachers as language activists and knowledge generators
Bibliographic record
Abstract
My commentary initially sketches the evolution of academic discourse in the field of ‘language awareness’ (LA) from a dominant focus on knowledge about language to a focus on ‘critical language awareness’ (CLA) that highlighted the intersections of language and power. This evolution has more recently progressed to an inclusion of ‘multilingualism’ within the realm of CLA which is reflected in the label ‘critical multilingual language awareness’ (CMLA). On the basis of a review of the papers in this special issue, I highlight some of the major findings and claims. Then, I suggest some additional directions that teacher educators and educational leaders might pursue to build a focus on CMLA into the overall pedagogical practice of the school.ABSTRACT (FRENCH) Mon commentaire esquisse d’abord l’évolution du discours académique dans le domaine de la « conscience du langage » (CL), d’une focalisation dominante sur la connaissance du langage, à une focalisation sur la « conscience critique du langage » (CCL) qui met en évidence les intersections du langage et du pouvoir. Cette évolution a récemment progressé vers une inclusion du « multilinguisme » dans le domaine de la CCL, qui se reflète dans l‘appellation « conscience critique du langage multilingue » (CCLM). Basé sur une revue des articles de ce numéro spécial, je souligne certaines des principales conclusions et affirmations. Ensuite, je suggère quelques orientations supplémentaires que les formateurs d’enseignants et les leaders pédagogiques pourraient suivre pour mettre l’accent sur le CCLM dans la pratique pédagogique globale de l’école.
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 | 0.017 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.041 |
| Scholarly communication | 0.019 | 0.021 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".