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Record W2100687755 · doi:10.5539/ass.v8n7p139

A Cross-Cultural Comparative Study of Gratitude Strategies between Iranian and Malaysian Postgraduate Students

2012· article· en· W2100687755 on OpenAlexvenueno aff
Atieh Farashaiyan

Bibliographic record

VenueAsian Social Science · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsGratitudePsychologyAffect (linguistics)Social psychologyMathematics educationMedical educationCommunicationMedicine

Abstract

fetched live from OpenAlex

This study describes and compares the gratitude strategies utilized by Iranian EFL and Malaysian ESL learners in facing different situations. Data were cumulated from 20 Iranian and 20 Malaysian postgraduate university students having the same language proficiency through a Discourse Completion Tasks Questionnaire. Social status, size of imposition and gender are contextual and social variables which were investigated for two groups of learners in this study. Results of the study illustrated certain commonalities and differentials in terms of the strategies and type of gratitude used by Iranian and Malaysian students. A detailed analysis of the use of the gratitude strategies revealed significant differences in communicative ways of Iranian and Malaysian postgraduate students reflecting insights into understanding the differences in cultural values and norms in two non-western cultures. The results also illustrated that the two contextual factors and gender affect significantly on the type and frequency of the strategies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.103
GPT teacher head0.424
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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations19
Published2012
Admission routes1
Has abstractyes

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