The Language Fluency Paradox During Cultural Faux Pas: Poor Language Fluency Boosts Likability but Undermines Competence in Nonnative Professionals
Bibliographic record
Abstract
This research examines the paradoxical effects of nonnative speakers’ language fluency on how they are perceived by native speakers, focusing on likability and competence. Although poor fluency has been shown to shield nonnative speakers from negative evaluations of culturally inappropriate behavior, our findings indicate that this effect is confined to likability and does not extend to competence. Specifically, our results show that Russian professionals with lower English fluency were rated as more likable (Studies 1 and 2) but less competent (Study 2). Mediation analyses (Study 2) revealed that perception of effort and felt sympathy, rather than lack of cultural knowledge or intentional rudeness, mediated likability ratings, demonstrating the “effort-sympathy heuristic,” where poor fluency enhances likability by triggering greater sympathy and perceived effort. Overall, these findings highlight the dual-edged nature of language fluency in professional and social contexts, providing insights into how perceptions of nonnative speakers shape interpersonal and professional evaluations.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".