Parental and Early Childhood Predictors of Persistent Physical Aggression in Boys From Kindergarten to High School
Bibliographic record
Abstract
BACKGROUND: In a prior study, we identified 4 groups following distinct developmental courses, or trajectories, of physical aggression in 1037 boys from 6 to 15 years of age in a high-risk population sample from Montréal, Québec. Two were trajectories of high aggression, a persistently high group and a high but declining group. The other 2 trajectories were a low group and a moderate declining group. This study identified early predictors of physical aggression trajectories from ages 6 to 15 years. METHODS: In this study, logistic regression analysis was used to identify parental and child characteristics that distinguished trajectory group membership. RESULTS: For boys displaying high hyperactivity and high opposition in kindergarten, the odds of membership in the 2 high aggression groups were increased by factors of 3.0 (95% confidence interval [CI], 2.0-4.3) and 2.7 (95% CI, 1.9-3.8), respectively, compared with boys without these risks. Counterpart odds ratios for the risk factors of mothers' teen-onset of parenthood and low educational attainment were 1.6 (95% CI, 1.1-2.2) and 1.8 (95% CI, 1.3-2.4), respectively. Only the maternal characteristics distinguished between the trajectory of persistently physical high aggression and the trajectory starting high but subsequently declining. For the 2 maternal risk factors combined, the odds ratio of persisting in high level physical aggression was 9.4 (95% CI, 2.9-30.4). CONCLUSIONS: Kindergarten boys displaying high levels of opposition and hyperactivity are at high risk of persistent physical aggression. However, among kindergarten boys who display high levels of physical aggression, only mothers' low educational level and teenage onset of childbearing distinguish those who persist in high levels of physical aggression.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".