Predictors of childhood trajectories of overt and indirect aggression: An interdisciplinary approach
Bibliographic record
Abstract
The aim of this study was to advance our understanding of the development of aggression in boys and girls by testing a model combining insights from both evolutionary theory and developmental psychology. A sample of 744 children (348 girls) between six and 13 years old was recruited in schools with high deprivation indices. Half of the sample (N = 372; 40.1% girls) had received special educational services for behavioral and/or socio-emotional problems. Two trajectories for overt aggression and two trajectories for indirect aggression were identified and binomial logistic regressions were used to identify environmental predictors and sex-specific patterns of these trajectories. Results indicated that peer rejection predicted overt aggression and indirect aggression and that extraversion and male sex predicted overt aggression. The results also showed that interaction between parental practices and some child temperament traits predicted overt aggression (coercion and lack of supervision associated with extraversion or low effortful control) or indirect aggression (coercion and neglect associated with negative affect or low effortful control), and the absence of a father figure predicted high indirect aggression in girls.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".