Empathy and Observed Anger and Aggression in Five‐Year‐Olds
Bibliographic record
Abstract
Abstract In Roberts and Strayer (1996 ), we reported that emotional expressiveness and anger were important predictors of empathy for school‐age children, and that empathy strongly predicted prosocial behaviors aggregated across methods and sources. In this paper, we report how empathy was associated with direct observations of anger and aggression in peer play groups. Twenty‐four initially unacquainted five‐year‐old children (50% girls) were randomly assigned to six same‐sex groups; each group met for three one‐hour play sessions. Physical and verbal aggression, object struggles and anger were coded from videotapes, as were prosocial and social behaviors. As expected, empathy (aggregated across methods and sources) was negatively associated with aggression and anger, and positively associated with prosocial behaviors. Although children who were more angry were also more aggressive, anger and aggression did not covary across play sessions as a simple causal model requires. These results suggest further directions for research in emotions and aggression.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".