The Role of Preschool Relational and Physical Aggression in the Transition to Kindergarten: Links With Social-Psychological Adjustment
Bibliographic record
Abstract
RESEARCH FINDINGS: The transition to kindergarten has important ramifications for future achievement and psychosocial outcomes. Research suggests that physical aggression may be related to difficulty during school transitions, yet no studies to date have examined the role of relational aggression in these transitions. This paper examined how engagement in preschool physical and relational aggression predicted psychosocial adjustment during the kindergarten school year. Observations and teacher reports of aggression were collected in preschool, and kindergarten teachers reported on student-teacher relationship quality, child internalizing problems, and peer acceptance in kindergarten. Results suggested that preschool physical aggression predicted reduced peer acceptance and increased conflict with the kindergarten teacher. High levels of relational aggression, when not combined with physical aggression, were related to more positive transitions to kindergarten in the domains assessed. PRACTICE OR POLICY: These data lend support to the need for interventions among physically aggressive preschoolers to target not only concurrent behavior but also future aggression and adjustment in kindergarten. Thus, educators should work to encourage social influence in more prosocial ways amongst aggressive preschoolers.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".