Gender Differences in Physical Aggression and Associated Developmental Correlates in a Sample of Canadian Preschoolers
Bibliographic record
Abstract
Recent studies have indicated that gender differences in children's aggressive behavior emerge during the preschool years and that these differences are relatively stable during childhood. The current study assesses whether these gender differences can be observed when a multidimensional measure of aggression from the ongoing Vancouver Longitudinal Study on the psychosocial development of children is utilized. Specifically, the level of physical aggression (PA) in three cohorts of children (aged three, four, and five years) from the initial 338 families in the Wave I data recruited for this study was analyzed using a series of constrained and unconstrained latent class models. Three latent classes of physically aggressive children were identified (low, moderate, and high level), with boys being over-represented in the highly aggressive group and being five times more likely than girls to show high levels of aggression. No age effects were detected, suggesting gender differences from the age of three years onward. The correlates of PA were similar for both boys and girls. Particularly important, a small subgroup of highly aggressive boys emerged from the study showing a clinical profile similar to Moffitt's life-course-persistent antisocial pattern. Such a group was not identified for 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".