Difficulté des jeunes enfants à comprendre la dissimulation des émotions.
Bibliographic record
Abstract
The authors investigated the understanding of emotion dissimulation in school-age children. Sixty participants were read short stories in which a main character expressed an emotion or hid an emotion from other characters. The participants were asked to identify the emotion felt by the main characters and to indicate the facial expressions they would display. Then they were asked what emotions the main characters felt while they were displaying these expressions, and what the beliefs of the other story characters would be as to the emotion felt by the main characters. The results revealed that children from 5 to 6 years of age have a partial understanding of emotion dissimulation. They were accurate in finding the emotion felt by the main characters when questioned the first time. They were also accurate in choosing the expressions the main characters would display to hide their emotions. However, they were often inaccurate as to the felt emotions of the main characters when questioned the second time. Compared with 9- and 10-year-olds, the younger children had more difficulty understanding the simultaneous character of felt and displayed emotions. Five- and 6-year-olds were also less accurate than the older children when asked to indicate the beliefs of the other characters in stories where felt emotions were hidden.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".