Emotional understanding, aggression, and social functioning among preschoolers.
Bibliographic record
Abstract
Evidence suggests that emotional understanding (EU) assists in the regulation of aggression, which in turn, predicts better social functioning. Although the links among EU, aggression, and social functioning have been preliminarily explored, significant gaps remain in our comprehension of the factors that could qualify these links (e.g., impact of developmental stage, type of aggression, type of social functioning, and different dimensions of EU). Here we conduct a multidimensional assessment of EU, aggression, and social functioning within a sample of aggressive preschoolers (n = 24) and a matched comparison group (n = 26; N = 50, 26 girls; Mage = 53.83 months, SDage = 3.73). We assessed EU using a behavioral assessment and social functioning via teacher-report. We conducted all analyses through the use of two measures of children's aggression-first, we compared children identified as aggressive by preschool teachers to those in the nonaggressive comparison group. Second, we used teacher-reported continuous measures of children's physical and relational aggression. Relative to the comparison group, the aggressive group demonstrated lower expressive EU, higher receptive EU, lower peer acceptance, and lower prosocial behavior. Analyses of continuous measures revealed a more complicated pattern of associations among aggression, EU, and social functioning. Higher physical aggression predicted greater peer victimization among females, and expressive EU was only associated with higher peer acceptance among the aggressive group. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".