Global Second Language Proficiency Predicts Self-Perceptions of General Sarcasm Use Among Bilingual Adults
Bibliographic record
Abstract
Each culture has a distinct set of features that contribute to a unique communication style. For example, bilinguals often balance multiple social contexts and may undergo cognitive changes that consequently support different communication styles. The present work examines how individual differences in bilingual experience affect one form of communication style: sarcastic and indirect language. A diverse sample of largely bilingual adults (first language English) rated their likelihood of using sarcastic and indirect language across different daily settings. They also rated their second language experience. There were two key findings: Bilinguals use sarcasm for similar social functions as do monolinguals (general sarcasm, frustration diffusion, and embarrassment diffusion) and greater global second language proficiency linked to greater usage of general sarcasm in daily life. These results suggest that bilinguals may use sarcasm to achieve various communicative goals and bilingual experience may affect general cognitive capacities that support sarcasm use across real-world contexts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".