Breaking ground in cross-cultural research on the fear of being laughed at (gelotophobia): A multi-national study involving 73 countries
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The current study examines whether the fear of being laughed at (gelotophobia) can be assessed reliably and validly by means of a self-report instrument in different countries of the world. All items of the GELOPH (Ruch and Titze, GELOPH〈46〉, University of Düsseldorf, 1998; Ruch and Proyer, Swiss Journal of Psychology 67:19–27, 2008b) were translated to the local language of the collaborator (42 languages in total). In total, 22,610 participants in 93 samples from 73 countries completed the GELOPH. Across all samples the reliability of the 15-item questionnaire was high (mean alpha of .85) and in all samples the scales appeared to be unidimensional. The endorsement rates for the items ranged from 1.31% through 80.00% to a single item. Variations in the mean scores of the items were more strongly related to the culture in a country and not to the language in which the data were collected. This was also supported by a multidimensional scaling analysis with standardized mean scores of the items from the GELOPH〈15〉. This analysis identified two dimensions that further helped explaining the data (i.e., insecure vs. intense avoidant-restrictive and low vs. high suspicious tendencies towards the laughter of others). Furthermore, multiple samples derived from one country tended to be (with a few exceptions) highly similar. The study shows that gelotophobia can be assessed reliably by means of a self-report instrument in cross-cultural research. This study enables further studies of the fear of being laughed at with regard to differences in the prevalence and putative causes of gelotophobia in comparisons to different cultures.
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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 | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it