Humor use, reactions to social comments, and social anxiety
Bibliographic record
Abstract
Abstract This study investigated how the use of different humor styles by individuals described as being either socially anxious or non-anxious can have an impact on the perceptions and evaluations made by others about these individuals. Participants read a set of scenarios describing brief interactions with a casual acquaintance (either socially anxious or non-anxious) who made four different types of social comments (affiliative, self-enhancing, aggressive or self-defeating). When the affiliative and self-enhancing comments were delivered humorously, participants indicated more positive evaluations and less social rejection of the casual acquaintance. This finding was obtained for both the socially anxious and non-anxious casual acquaintances. In contrast, the use of self-defeating comments, both with or without humor, was particularly detrimental to evaluations of the socially anxious acquaintance. In addition, participants were generally less interested in future interactions with a socially anxious acquaintance, and rated themselves more negatively when this acquaintance was portrayed as being socially anxious. Discussion focused on the pervasive role of humor in facilitating more positive reactions and responses to social comments made by both socially anxious and non-anxious individuals.
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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 | 0.016 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".