Humor Use in Romantic Relationships: The Effects of Relationship Satisfaction and Pleasant Versus Conflict Situations
Bibliographic record
Abstract
In this study, the authors explored the use of positive, negative, and avoiding humor in 2 types of situations by individuals in romantic relationships. Participants (N = 154) rated their frequency of humor use in either a typical conflict scenario with their partner or a typical pleasant event. Participants also indicated their overall degree of romantic relationship satisfaction. Hierarchical regression analyses revealed that individuals who were more satisfied with their relationship reported higher levels of positive humor use and lower levels of negative and avoiding humor use. Furthermore, lower levels of negative and avoiding humor use were reported for the conflict situation. Last, a significant 2-way interaction revealed that individuals who were high in relationship satisfaction reported significantly lower levels of negative humor use in a conflict situation as compared with a pleasant encounter. In contrast, individuals who were low in relationship satisfaction reported the same high levels of negative humor use regardless of whether they were in a conflict situation or a pleasant encounter. The authors discuss these findings in terms of the need for further research to clearly delineate the factors that may influence the complex use of humor in romantic relationships.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".