Understanding unintended and unsuccessful ironies among Chinese primary school children
Bibliographic record
Abstract
Abstract Despite the numerous studies on irony understanding, much remains unknown about how children comprehend unintended and unsuccessful ironies and the role of interlocutors’ social status in the recognition of ironic intention. The present study aimed to address this gap through randomly selecting 269 Chinese children in grades 3 and 6, with an average age of 9 and 12 years, respectively. The results indicate that: (1) both graders performed significantly better in the comprehension of regular irony than that of unintended and unsuccessful ironies; (2) there was no significant difference between 9 and 12 year-old children in the comprehension of unintended and unsuccessful ironies; (3) significant interaction between age and interlocutors’ social status was found in the understanding of unintended and unsuccessful ironies. 9-year-olds demonstrated a better understanding when both irregular types of irony happened between peers, while 12-year-olds showed a better performance under the teacher and students context. The above findings have valuable implications for figurative language teaching and research.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".