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Record W3209211389 · doi:10.5539/ijel.v11n6p98

A Review of Pragmatic Competence in BELF Interactions

2021· review· en· W3209211389 on OpenAlexvenueno aff
Jialiang Chen

Bibliographic record

VenueInternational Journal of English Linguistics · 2021
Typereview
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsEnglish as a lingua francaPragmaticsLingua francaConceptualizationLinguisticsInterpersonal communicationCompetence (human resources)Communicative competencePsychologySociologyPedagogySocial psychology

Abstract

fetched live from OpenAlex

Globalization has transformed English from a foreign language into a lingua franca. The pragmatic paradigm and pragmatic features of English as a lingua franca (ELF), are different from those of native English, especially in the business context, defined as English as a business lingua franca (BELF), which has contributed to a series of studies on pragmatic competence, pragmatic strategies and pragmatic awareness in the (B)ELF context. Relevant studies offer insights into the pragmatic competence of BELF users, which is crucial in the accomplishment of communicative goals in business settings. This paper first reviews relevant theoretical studies on (B)ELF and evaluates their characteristics from the perspective of pragmatics. Then, the focus is placed upon the diversified features of interpersonal pragmatic competence and intercultural pragmatic competence in the BELF context, revealing that the traditional paradigm of pragmatic competence based on native English does not apply to this diversified intercultural context. This paper argues for a re-conceptualization of pragmatic competence in the BELF context and a re-examination of the institutional features of BELF interactions and the dynamics of pragmatic competence, pragmatic strategies, and pragmatic awareness in this context.

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)0.001
metaresearch head score (Gemma)0.051
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.750
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.051
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.079
GPT teacher head0.400
Teacher spread0.321 · 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
GenreReview

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
Published2021
Admission routes1
Has abstractyes

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