The interconnected school context: Meta-analyses of the associations between peer aggression involvement and teacher-student relationship closeness
Bibliographic record
Abstract
A growing body of literature has documented the contribution of teacher-student relationship quality to both persistence and reduction in peer aggression incidents in the school context. The research literature indicates that students who are involved in peer aggression also tend to experience lower levels of closeness in their relationships with their teachers. However, these study results have not yet been aggregated, and the size and direction of effects remains unclear. In the present study we quantitatively synthesized 66 individual studies (Nstudents = 352,376) in two meta-analyses by aggregating cross-sectional associations between peer aggression involvement and teacher-student relationship closeness that have been reported in the literature over the last 20 years. A small, negative, and significant association was found between perpetration and victimization and teacher-student relationship closeness, indicating that students who experience greater involvement in peer aggression also have relationships with their teachers that are lacking in closeness. Three moderator analyses were also conducted. No moderating effect was found for school level or measure type; however, a significant moderating effect was found for informant type. The results from the meta-analyses lead to direct recommendations for practice regarding how we can best support students’ psychosocial development in the school context.
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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 | 0.027 | 0.058 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.045 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".