When to Laugh, When to Cry: Display Rules of Nonverbal Vocalisations Across Four Cultures
Bibliographic record
Abstract
Nonverbal vocalisations like laughter, sighs, and groans are a fundamental part of everyday communication. Yet surprisingly little is known about the social norms concerning which vocalisations are considered appropriate to express in which context (i.e., display rules). Here, in two pre-registered studies, we investigate how people evaluate the appropriateness of different nonverbal vocalisations across locations and relationships with listeners. Study 1, with a U.S. sample (n = 250), showed that certain vocalisations (e.g., laughter, sighs, cries) are consistently viewed as more socially acceptable than others (e.g., roars, groans, moans). Additionally, location (private vs. public) and interpersonal closeness (close vs. not close) significantly influenced these perceptions, with private locations and close relationships fostering greater expressive freedom. Study 2 extended this investigation across four societies with divergent cultural norms (n = 1120 in total): the U.S. (for direct replication), Türkiye, China, and the Netherlands. Findings largely replicated those from Study 1 and supported the existence of cross-culturally consistent patterns in display rules for nonverbal vocalisations, though with some variation across cultures. This research expands our understanding of how social norms affect auditory communication, extending beyond the visual modality of facial expressions to encompass the rich world of nonverbal vocalisations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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; both teacher heads agree on what is shown here.
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".