Does criticism in a foreign accent hurt less?
Bibliographic record
Abstract
Evaluative statements are routine in interpersonal communication but may evoke different responses depending on the speaker’s identity. Here, thirty participants listened to compliments and criticisms spoken in native or foreign accents and rated the speaker's friendliness as their electroencephalogram was recorded. Event-related potentials (ERPs) were examined for (1) vocal speech cues time-locked to statement onset and (2) emotive semantic attributes at the sentence-final word. Criticisms from native speakers were rated as less friendly than from foreign speakers, whereas compliments did not differ. ERPs revealed listeners rapidly used acoustic information to differentiate speaker identity and evaluative attitude (N100, P200), then selectively monitored vocal attitude of native speakers in the Late Positive Potential (LPP) time window. When the evaluative word was heard, native accents contextually modulated early semantic processing (N400). Words of criticism increased the LPP irrespective of accent. Our data showcase unique neurocognitive and behavioural effects of speaker accent on communication.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".