Genetic and Environmental Contributions to Humor Styles: A Replication Study
Bibliographic record
Abstract
One thousand and seventy three pairs of adult monozygotic (MZ) twins and 895 pairs of same sex adult dizygotic (DZ) twins from the United Kingdom (UK) completed the Humor Styles Questionnaire: a 32-item measure which assesses two positive and two negative styles of humor. MZ correlations were approximately twice as large as DZ correlations for all four humor styles, and univariate behavioral genetic model fitting indicated that individual differences in all of them can be accounted for entirely by genetic and nonshared environmental factors, with heritabilities ranging from .34 to .49. These results, while perhaps not surprising, are somewhat at odds with a previous study that we conducted in North America (Vernon et al., in press) in which genetic factors contributed significantly to individual differences in the two positive humor styles, but contributed far less to the two negative styles, variance in which was instead largely due to shared and nonshared environmental factors. We suggest that differences between North American and UK citizens in their appreciation of different kinds of humor may be responsible for the different results obtained in these two studies.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".