How Do Children Respond to Verbal Irony in Face-to-Face Communication? The Development of Mode Adoption Across Middle Childhood
Bibliographic record
Abstract
A number of studies have now examined the development of children's appreciation for verbal irony, typically by testing children's comprehension of the ironic speaker's belief and intent. This article examines a topic that has received much less attention: children's ability to produce irony in context-appropriate ways. The study presents 7- to 11-year-olds with brief stories that were each followed by an experimenter's literal or ironic remark. Of critical interest was whether children would show sensitivity to the convention of mode adoption by replying to irony with irony of their own. Results showed that children's overall rate of mode adoption was 8.67%. When ironic criticisms were presented (Experiment 1), irony was employed more frequently in the responses of older children than in the responses of younger children. When ironic compliments were presented (Experiment 2), no age effects were observed in children's ironic responses. Comprehension data show that the complimentary form of irony was more difficult for children to grasp.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".