Who is respectful? Effects of social context and individual empathic ability on ambiguity resolution during utterance comprehension
Bibliographic record
Abstract
Verbal communication is often ambiguous. By employing the event-related potential (ERP) technique, this study investigated how a comprehender resolves referential ambiguity by using information concerning the social status of communicators. Participants read a conversational scenario which included a minimal conversational context describing a speaker and two other persons of the same or different social status and a directly quoted utterance. A singular, second-person pronoun in the respectful form (nin/nin-de in Chinese) in the utterance could be ambiguous with respect to which of the two persons was the addressee (the "Ambiguous condition"). Alternatively, the pronoun was not ambiguous either because one of the two persons was of higher social status and hence should be the addressee according to social convention (the "Status condition") or because a word referring to the status of a person was additionally inserted before the pronoun to help indicate the referent of the pronoun (the "Referent condition"). Results showed that the perceived ambiguity decreased over the Ambiguous, Status, and Referent conditions. Electrophysiologically, the pronoun elicited an increased N400 in the Referent than in the Status and the Ambiguous conditions, reflecting an increased integration demand due to the necessity of linking the pronoun to both its antecedent and the status word. Relative to the Referent condition, a late, sustained positivity was elicited for the Status condition starting from 600 ms, while a more delayed, anterior negativity was elicited for the Ambiguous condition. Moreover, the N400 effect was modulated by individuals' sensitivity to the social status information, while the late positivity effect was modulated by individuals' empathic ability. These findings highlight the neurocognitive flexibility of contextual bias in referential processing during utterance comprehension.
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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 | 0.008 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".