Comparison of Interpersonal Consideration in Refusal in Business Communication between Japanese and English : Focusing on Facework and Linguistic Analysis
Bibliographic record
Abstract
In this study, I compare English and Japanese speech acts of refusal observed in business communications at multinational companies. Participants to this research are businesspeople, in Japan, who are native Japanese speakers （JS for Japanese speakers）and businesspeople, in Canada and the United States of America, who are native English speakers （ES for English speakers）. Since refusal is one of the most delicate speech acts which might spoil human relations, people carefully choose polite expressions to avoid misunderstandings and friction. I focus on the contents of a request that affect refusal speech acts as a factor, in addition to hierarchical relationships and intimacy. I set two different load levels of request: one is a light load request i.e., a request typical of everyday life at a workplace and the other is a heavy load request i.e., a request in which the listener might have to violate company policies. This study seeks to clarify how JS and ES maintain the human relations in refusal speech acts, and to make comparison between Japanese and English languages in terms of Facework and the words and phrases used.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".