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Record W2803091408 · doi:10.1111/weng.12305

Unpacking research and practice in world Englishes and Second Language Acquisition

2018· article· en· W2803091408 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

VenueWorld Englishes · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsCentre for Advancing Health OutcomesUniversity of British Columbia
Fundersnot available
KeywordsUnpackingMacroIdeologySociologyWorld EnglishesSecond-language acquisitionLanguage educationNeoliberalism (international relations)LinguisticsLanguage acquisitionPedagogyPoliticsPolitical scienceMathematics educationSocial sciencePsychologyComputer science

Abstract

fetched live from OpenAlex

Abstract Research on world Englishes and Second Language Acquisition has conceptualized language, language users, and language learning as diverse and dynamic, broadening conventional knowledge. Yet, research outputs have not influenced language education policies in Expanding Circle countries, which favor Inner Circle standardized English, promote teaching English to young learners, and require monolingual teaching of English, as seen in the case of Japanese primary and secondary education. These activities are perpetuated by macro‐level language ideology and broader political, historical, and economic forces including neoliberalism that exist at a super macro level. Examining the roots of these practices directs our attention to both macro and super‐macro issues as well as to complicities between research/researchers and broader ideological and structural issues. Recommendations are offered to invite researchers to begin exploring how research can make impacts on real‐world issues.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.043
GPT teacher head0.321
Teacher spread0.278 · 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