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From Intercultural to Transcultural Communication: ELF in Multilingual Settings

2023· article· en· W4389685187 on OpenAlexaboutno aff
Anna Maria De Bartolo

Bibliographic record

VenueEL LE · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsIntercultural communicationLingua francaEnglish as a lingua francaLinguisticsIntercultural relationsFirst languageAffect (linguistics)PsychologyRelation (database)SociologyComputer sciencePedagogyCommunication

Abstract

fetched live from OpenAlex

The study centres around the idea that English is a global lingua franca for intercultural communication among multilingual speakers. Drawing on relevant literature in the field, the paper will highlight the intercultural and transcultural nature of English used as a multilingua franca (EMF). In particular, the study will explore learners’ attitudes with the purpose to identify how learners perceive the complex relation between culture and language and the factors which may affect intercultural communication through English. The study will analyse two sample groups. The first group is composed of students belonging to different first language backgrounds, mainly non-native speakers of English studying in an Italian university. The second group is composed of both native and non-native English speakers studying in the US and Canada. An online link to a questionnaire was sent via email to all participants and was used as a research instrument to collect quantitative data. It is highlighted that English used in multilingual settings cannot be analysed as a static and bounded entity with precise boundaries. On the contrary, English has transcended boundaries, in a fluid, dynamic and flexible process where borders are fuzzy and blurred and languages do not reflect well-defined national cultures. Therefore, it is suggested that language teaching practices should incorporate intercultural/transcultural oriented issues to provide learners with a more comprehensive knowledge of the multifaceted global English world and encourage a richer cultural and linguistic experience.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.027
GPT teacher head0.278
Teacher spread0.251 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2023
Admission routes1
Has abstractyes

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