Reactive aggression and peer victimization from pre‐kindergarten to first grade: Accounting for hyperactivity and teacher–child conflict
Bibliographic record
Abstract
BACKGROUND: The role of reactive aggression in the development of peer victimization remains unclear due in part to a failure to account for confounding problems of behavioural undercontrol (e.g., hyperactivity). As well, the school social context has rarely been examined to see whether these risks are mediated by relationships with teachers. AIMS: This study tests the prospective relations between reactive aggression, hyperactivity, victimization, and teacher-child (T-C) relationship, to determine whether conflict mediates the relationships between externalizing problems and victimization. SAMPLE: A sample of 1,114 Australian students were followed from pre-kindergarten through first grade. METHODS: Cross-lagged path analyses were conducted, with comparison of gender-moderating models and autocorrelation models. Full-information maximum likelihood was deployed to account for missingness. RESULTS: Best fitting models found that the relationship of early externalizing problems to later victimization was mediated by T-C conflict. No evidence of victimization increasing externalizing problems nor gender differences were observed. T-C conflict in kindergarten predicted subsequent increases in victimization, reactive aggression, and hyperactivity. CONCLUSIONS: Understanding the processes whereby externalizing problems confer risk of victimization involves understanding the whole social context of classrooms, including relationships with teachers. Finer-grained research is needed to better understand how peer dynamics may be influenced by observation of T-C relationships. Pre-service teacher education needs to ensure a focus on the potential social impact of teacher's relationships with students.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".