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Record W4390280739 · doi:10.1080/09658416.2023.2285361

Critical multilingual language awareness: the role of teachers as language activists and knowledge generators

2023· article· en· W4390280739 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLanguage Awareness · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMetalinguisticsMultilingualismPsychologyLinguisticsTeaching methodPedagogyVocabulary development

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.020
GPT teacher head0.317
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it