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Record W4296389477 · doi:10.5539/elt.v15n10p1

A Developmental Study of Pragmatic Strategies of Refusals by Chinese English Majors

2022· article· en· W4296389477 on OpenAlexvenueno aff
Fenghua Zhang

Bibliographic record

VenueEnglish Language Teaching · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsnot available
FundersJiangsu Provincial Department of Education
KeywordsPsychologyPragmaticsLinguisticsMetalinguisticsMathematics educationTeaching methodVocabulary development

Abstract

fetched live from OpenAlex

This study investigates the pragmatic development of the refusal strategies to the four different stimulus types (1 request, 1 suggestion, 1 invitation, and 1 offer) by Chinese English major students with low-intermediate language proficiency. The data was collected through written discourse completion tasks, and coded based on the modified taxonomy by Beebe et al. (1990). Refusal strategies were analyzed in terms of frequency and contents of the semantic formulas. The results suggested on the whole a downward pattern was observed but statistically there was no significant development towards the learners’ refusal strategies (directness, indirectness and adjuncts). The findings also revealed that the Chinese English major students relied heavily on the indirectness and adjuncts to realize their refusals. Learners’ data displayed the tendency of being verbose and were also found with ungrammatical forms.

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)0.000
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.273
Teacher spread0.261 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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