Teacher–Child Relationship, Parenting, and Growth in Likelihood and Severity of Physical Aggression in the Early School Years
Bibliographic record
Abstract
This investigation used two-part growth modeling and cross-lagged panel analysis to examine the predictive function of parenting and teacher–child relationship on the likelihood of children showing problems with parent-rated physical aggression, and on the severity of problems, for 374 children followed from prekindergarten and first grade. Two-part modeling found that teacher–child relationship did not differentiate children who did or did not show aggression problems; parental warmth did, but only in prekindergarten. For children who showed problems with aggression, parental warmth predicted the severity of those problems in prekindergarten, and teacher–child conflict predicted severity of aggression problems in first grade. Cross-lagged panel analyses similarly indicated that parental warmth in prekindergarten predicted aggression in kindergarten, but that kindergarten teacher–child conflict predicted subsequent higher aggression in first grade. Shifts in the importance of specific microsystems over time on children’s social development (chronosystem) are discussed, as are the implications for teachers and preservice teacher training.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".