Humor styles are related to loneliness across 15 countries
Bibliographic record
Abstract
The relationships between self-report loneliness and the four humor styles of affiliative, aggressive, self-defeating, and self-enhancing were investigated in 15 countries (N = 4,701). Because loneliness has been suggested to be both commonly experienced and detrimental, we examine if there are similar patterns between humor styles, gender, and age with loneliness in samples of individuals from diverse backgrounds. Across the country samples, affiliative and self-enhancing humor styles negatively correlated with loneliness, self-defeating was positively correlated, and the aggressive humor style was not significantly related. In predicting loneliness, 40.5% of the variance could be accounted. Younger females with lower affiliative, lower self-enhancing, and higher self-defeating humor style scores had higher loneliness scores. The results suggest that although national mean differences may be present, the pattern of relationships between humor styles and loneliness is consistent across these diverse samples, providing some suggestions for mental health promotion among lonely individuals.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".