Women Gossip and Men Brag: Perceived Gender Differences in the Use of Humor by Romanian Older Women
Bibliographic record
Abstract
The present study investigates perceived gender differences in the producion and social use of humor in the interpersonal communication of Romanian older women, aged 60 and above. The study is a qualitative investigation, based on semi-structured interviews. The aim was to understand the perceptions and motivations that women have when using humor in social interactions, and to explore the functions that humor serves in their day-to-day communication. A previous quantitative investigation found statistically significant gender differences between Romanian older men and women on a sense of humor scale, and suggested that the use of humor in interpersonal communication had stronger social benefits for women (Schiau, 2016a). Drawing on these findings, and keeping in mind other studies that discuss the different use of humor by men and women, this study aims to investigate specific gender differences in the production of humor, as perceived by the participants.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".