Developing Appreciation for Sarcasm and Sarcastic Gossip: It Depends on Perspective
Bibliographic record
Abstract
Background: Speakers use sarcasm to criticize others and to be funny; the indirectness of sarcasm protects the addressee's face (Brown & Levinson, 1987). Thus, appreciation of sarcasm depends on the ability to consider perspectives. Purpose: We investigated development of this ability from late childhood into adulthood and examined effects of interpretive perspective and parties present. Method: We presented 9- to 10-year-olds, 13- to 14-year-olds, and adults with sarcastic and literal remarks in three parties-present conditions: private evaluation, public evaluation, and gossip. Participants interpreted the speaker's attitude and humor from the addressee's perspective and, when appropriate, from the bystander's perspective. Results: Children showed no influence of interpretive perspective or parties present on appreciation of the speaker's attitude or humor. Adolescents and adults, however, shifted their interpretations, judging that addressees have less favorable views of criticisms than bystanders. Further, adolescents and adults differed in their perceptions of the social functions of gossip, with adolescents showing more positive attitudes than adults toward sarcastic gossip. Conclusions: We suggest that adults' disapproval of sarcastic gossip shows a deeper understanding of the utility of sarcasm's face-saving function. Thus, the ability to modulate appreciation of sarcasm according to interpretive perspective and parties present continues to develop in adolescence and into adulthood.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".