Children’s Moral Emotions and Negative Emotionality: Predictors of Early-onset Antisocial Behaviour
Bibliographic record
Abstract
This study examined links between antisocial behaviour, moral emotions (i.e., sympathy and guilt), and negative emotionality in an ethnically diverse sample of 4- and 8-year-old children (N = 79). Primary caregivers reported their children’s antisocial behaviour, sympathy, and negative emotionality through a questionnaire and across a 10-day span via daily diary entries (n = 474 records). In a semi-structured interview, children reported their sympathy levels and guilt feelings. Children with high guilt in harm contexts and low negative emotionality were rated as less antisocial in both questionnaire and diary reports. For children with low guilt in exclusion contexts, low sympathy ratings predicted higher questionnaire-reported antisocial behaviour. For children with high guilt in prosocial omission contexts, high sympathy ratings predicted lower diary-reported antisocial behaviour. Lastly, high sympathy ratings predicted lower questionnaire-reported antisocial behaviour for children with low negative emotionality.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".