From Ta’ārof to Ostensible Speech Acts: A Cross-cultural Analysis of Persian and American Apology Practices
Bibliographic record
Abstract
While genuine apologies have been widely studied across various cultural and linguistic contexts, ostensible apologies—those used not to express sincere regret but to maintain social harmony—remain underexplored. These speech acts can lead to misinterpretations and communication challenges, particularly in Persian-American interactions, where cultural expectations around politeness differ significantly. In Persian, ostensible apologies are deeply embedded in the cultural practice of ta’ārof, influencing how politeness and social hierarchy are negotiated. Despite their prevalence, Persian ostensible apologies (POAs) have not been systematically analyzed in relation to their American counterparts. Previous research on ostensible speech acts (OSAs), introduced by Isaacs & Clark (1990) and later refined by Link & Kreuz (2005), primarily focuses on English contexts, leaving a gap in understanding their function in Persian discourse. This study addresses this gap by integrating American English-based OSA features with the Persian meta-implicature framework of ta’ārof, as outlined by Yaqubi (2021). Through a cross-cultural analysis, this research offers a unified framework for interpreting Persian ostensible apologies, emphasizing their implications for intercultural communication, second-language learning, diplomatic discourse, and translation studies. By bridging theoretical and cultural perspectives, this study enhances understanding of Persian-English pragmatic differences and provides practical insights for fostering cross-cultural awareness in academic and professional settings.
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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 | 0.001 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".