Developmental Trajectories of Physical Aggression from School Entry to Late Adolescence
Bibliographic record
Abstract
The developmental perspective applied to psychopathology has led to the concept of early- and late-onset disorders. This study explores the application of the early- and late-onset concepts of antisocial behavior to physical aggression. Are there two categories of chronically physically violent adolescents: those who are physically aggressive throughout childhood and those who start being physically aggressive during adolescence? The estimation of developmental trajectories for repeated measures of two different response variables physical aggression in childhood as measured by teacher reports and physical aggression in adolescence as measured by self-reported violent delinquency is achieved with a semi-parametric, group-based method. This new method is applied to a large sample of males from Montreal who have been assessed repeatedly since kindergarten. Several salient findings emerge from the analysis. First, we find considerable change in the levels of childhood and adolescent physical aggression. Thus, there is little evidence of stability of behavior in an absolute sense. A second key finding concerns the connection of childhood aggression to adolescent aggression. Boys with higher childhood physical aggression trajectories are far more likely to transition to a higher-level adolescent aggression trajectory than boys from lower childhood physical aggression trajectories. However, for all childhood physical aggression trajectory levels the modal transition is to a relatively low-level adolescent aggression trajectory. Third, we find little evidence of "late onset" of high-level physical aggression. Specifically, the joint trajectory analysis finds no evidence of transition from a low physical aggression trajectory in childhood to a high trajectory in adolescence.
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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) | 0.000 | 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 | 0.000 | 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".