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Record W4393157966 · doi:10.5539/ijel.v14n2p50

ELF and Transcultural Communicative Practices in Multilingual and Multicultural Settings: A Theoretical Appraisal of Recent Advances

2024· article· en· W4393157966 on OpenAlexvenueno aff
Antonio Taglialatela

Bibliographic record

VenueInternational Journal of English Linguistics · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismPsychologyLinguisticsSociologyPedagogyPhilosophy

Abstract

fetched live from OpenAlex

Transcultural communicative practices (TCPs) have become increasingly important in English language pedagogy owing to the growing number of multilingual and multicultural settings. In this study, I theoretically appraise these practices and place them in the context of English as a lingua franca (ELF) and transcultural communication in the English language classroom. Drawing on Takkula et al.’s (2008) claim that all people are products of their native culture and mother tongue from the moment of birth, the paper argues that language students must be educated to overcome their culture-bound assumptions and beliefs and acquire the necessary skills for transcultural exchanges and that to this end, ELF is a valuable transcultural communication tool. The benefits and challenges of such practices are also discussed. The benefits for students include increased cultural sensitivity, improved communication skills, and enhanced critical thinking, whereas the challenges include language barriers, cultural differences, and class time constraints. The study concludes with hints for English language teachers and practitioners to effectively implement TCPs in classrooms to promote transcultural understanding and communication among students.

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)0.000
metaresearch head score (Gemma)0.045
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.846
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.045
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.350
Teacher spread0.323 · 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; a candidate call from one teacher head, not a consensus.

Study designNot applicable
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

Citations7
Published2024
Admission routes1
Has abstractyes

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