Emotional Expression and Socially Modulated Emotive Communication in Children with Traumatic Brain Injury
Bibliographic record
Abstract
Facial emotion expresses feelings, but is also a vehicle for social communication. Using five basic emotions (happiness, sadness, fear, disgust, and anger) in a comprehension paradigm, we studied how facial expression reflects inner feelings (emotional expression) but may be socially modulated to communicate a different emotion from the inner feeling (emotive communication, a form of affective theory of mind). Participants were 8- to 12-year-old children with TBI (n = 78) and peers with orthopedic injuries (n = 56). Children with mild-moderate or severe TBI performed more poorly than the OI group, and chose less cognitively sophisticated strategies for emotive communication. Compared to the OI and mild-moderate TBI groups, children with severe TBI had more deficits in anger, fear, and sadness; neutralized emotions less often; produced socially inappropriate responses; and failed to differentiate the core emotional dimension of arousal. Children with TBI have difficulty understanding the dual role of facial emotions in expressing feelings and communicating socially relevant but deceptive emotions, and these difficulties likely contribute to their social problems.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".