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Record W4401488009 · doi:10.37546/jalttlt48.5-1

JALT2024 Plenary Speaker: Toward Justice-Affirming Language Teaching

2024· article· en· W4401488009 on OpenAlexaff
Ryūko Kubota

Bibliographic record

VenueThe Language Teacher · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPlenary sessionLinguisticsEconomic JusticeSociologyPsychologyPolitical scienceComputer sciencePhilosophyLawLibrary science

Abstract

fetched live from OpenAlex

In the field of language education, there is an increased recognition that equity, diversity, inclusion, and social justice should be established in every aspect of teaching and learning. This trend exists against the backdrop of broader sociopolitical contexts that are becoming more volatile and threatening to human existence, requiring a greater promotion of sustainability of humankind and the non-human world. Under this circumstance, language education, with its aim to foster communicative competence, contributes to honoring human dignity and building solidarity across differences. Central to this vision is justice-affirming language teaching for raising critical consciousness of how oppressive forces affect the lives of individuals who are positioned differently in power hierarchies. Simultaneously, this framework requires praxis: critical reflection for unlearning and a commitment to putting relearned critical perspectives into action (Freire, 1998). In this essay, I will outline a conceptual foundation of justice-affirming language teaching, challenges that need to be overcome, and its applications to the context of Japan.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.034
GPT teacher head0.384
Teacher spread0.350 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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