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Record W2930471066 · doi:10.5539/ass.v15n4p49

Refusal Strategy Used by Malay and German Native Speakers to Refuse Requests

2019· article· en· W2930471066 on OpenAlexvenueno aff
Farhana Muslim Mohd Jalis, Mohd Azidan Abdul Jabar, Hazlina Abdul Halim, Jürgen Martin Bukhardt

Bibliographic record

VenueAsian Social Science · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsMalayGermanLinguisticsPsychologyUniversality (dynamical systems)Speech actSocial psychology

Abstract

fetched live from OpenAlex

This study investigates similarities and differences in Malay and German refusal speech acts realised by their respective mother tongue languages, which are the Malay and German languages. This study analysed situations in which refusal could occur and examined the refusal strategies and corresponding linguistic forms used by the two groups when refusing requests made by higher, equal, and lower relationship status interlocutors. A Discourse Completion Test (DCT) was utilised to obtain data on the types and content of refusal strategies. The data gathered from the DCT was analysed and coded according to a combined taxonomy of refusal strategies proposed by Beebe et al. (1990) and Al-Issa (2003). The findings will provide future insights on the cross-cultural complexity of refusal interaction patterns used by both Malay and German speakers in order to understand and also avoid creating stereotypes of foreign culture. In addition, speakers may also adopt socially appropriate strategies for future situations that might be encountered in order to engender successful communication when dealing with refusals. The results are then discussed from the universality and cultural-specificity perspectives.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.795
Threshold uncertainty score0.633

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.028
GPT teacher head0.330
Teacher spread0.302 · 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 designTheoretical or conceptual
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

Citations3
Published2019
Admission routes1
Has abstractyes

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