A behavior genetic analysis of the relationship between humor styles and depression
Bibliographic record
Abstract
Abstract The present study examined the relationship between humor styles and depression using two methods of examination: (1) the mean humor style differences between individuals who reported that they had been diagnosed with depression versus those who did not report being depressed; and (2) the phenotypic, genetic, and environmental correlations between humor styles and a short scale assessing depressed affect created from preexisting measures in archival data. Participants were 1154 adult Australians, consisting of 339 monozygotic twin pairs and 238 dizygotic twin pairs. With respect to mean differences, depressed individuals were found to use self-defeating humor more and self-enhancing humor less than non-depressed adults. When the depressed affect scale score was analyzed, negative correlations were found with both affiliative and self-enhancing humor. A positive correlation was found between depressed affect and both aggressive and self-defeating humor. These phenotypic correlations were also found to have some significant genetic and environmental correlations.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".