Cross-cultural Comparison of Gratitude Expressions in Persian, Chinese and American English
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Granted the fact that different cultures have different speaking styles, knowledge of these styles can help people grasp the essence of social cultural knowledge to communicate with others more successfully. In this regard, the present paper aims at comparing the use of speech act of gratitude in Persian and Chinese EFL learners and English native speakers performances to identify the existing pattern among them. For this purpose, the participants were asked to complete a Discourse Completion Task (DCT) designed by Eisenstein and Bodman (1993). The results revealed that although thanking is regarded as the most favorite strategy among all three groups, there are significant differences in the ways Persian and Chinese learners of English, and also native speakers of English use the speech act of thanking.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it