Humor in Persuasion on Threatening Topics: Effectiveness Is a Function of Audience Sex Role Orientation
Bibliographic record
Abstract
The hypothesis was that humor relative to no-humor appeals on threatening topics are effective for high-masculinity individuals because they seem particularly averse to experiencing distress (i.e., sadness and fear). Persuasive targets were sunscreen use to prevent melanoma (skin cancer) in Study 1 and condom use to prevent AIDS in Study 2. The humor and no-humor appeals presented the same substantive information. In both studies, high-masculinity men and women exhibited greater intent to adopt the preventive behaviors in response to the humor relative to the no-humor appeal; no difference emerged for low-masculinity individuals. Humor effects were not related to explicit responses to the ads (e.g., listed thoughts and feelings). In Study 2, threat intensity in the media context was manipulated (moderate vs. low) as experiential processing is likely favored under greater threat. Overall, the results seem attributable to experiential processing of humor appeals on threatening topics by high-masculinity participants.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".