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Record W2595600573 · doi:10.1515/jelf-2017-0004

Using stimulated recall to explore the use of communication strategies in English lingua franca interactions

2017· article· en· W2595600573 on OpenAlexaff
Sara Kennedy

Bibliographic record

VenueJournal of English as a Lingua Franca · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsConcordia University
Fundersnot available
KeywordsRecallPsychologyFeelingEnglish as a lingua francaContext (archaeology)Cognitive psychologyRelation (database)Lingua francaSocial psychologyLinguisticsComputer science

Abstract

fetched live from OpenAlex

Abstract In this study, the communication strategy use of two pairs of English as a lingua franca (ELF) users was explored in relation to two contextual factors, the communicative goal and the ELF users’ thoughts and feelings about the interactions. The ELF users were video-recorded engaging in researcher-designed tasks which required sharing information to achieve a joint goal. Subsequent stimulated recall with individual speakers targeted instances of potential or actual difficulties in understanding. Recordings and transcripts of the paired tasks and stimulated recall were used to identify communication strategies used to address difficulties in understanding. Results showed that overall, 11 different strategy types were seen across both pairs of speakers. However, the pair which achieved the shared goal showed a different pattern of strategy use and of interaction than the pair which did not achieve the shared goal. The two pairs also differed in how they attributed responsibility for successful communication. These findings, discussed in the context of previous ELF communication strategy research, highlight benefits of investigating interlocutors’ contemporaneous thoughts and feelings and the ways in which communication strategies are used during interactions.

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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.837
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.212
GPT teacher head0.369
Teacher spread0.157 · 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 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

Citations18
Published2017
Admission routes1
Has abstractyes

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