Development of male proactive and reactive physical aggression during adolescence
Bibliographic record
Abstract
BACKGROUND: Different developmental courses have been postulated for proactive and reactive aggression. OBJECTIVE: Investigated the developmental course of proactive and reactive aggression in a large sample of adolescent boys from low socioeconomic areas. METHOD: A dual group-based joint trajectory method was used to identify distinct trajectories as well as similarities and differences in intra-individual changes. RESULTS: The trajectories for proactive and reactive aggression were similar: the majority of individuals followed infrequent and desisting trajectories. Contrary to expectations, very few adolescents followed trajectories of increasing proactive aggression. Reactive aggression was more common than proactive aggression. The overlap in trajectory group membership of individuals following trajectories of high peaking proactive and reactive aggression was nearly 100%. Across a period of 5 years, the boys on the high peaking trajectories were twice as likely to have affiliated with gangs. CONCLUSIONS: The developmental courses of proactive and reactive aggression are similar during adolescence. Males who tend to frequently use one form of aggression throughout adolescence also tend to frequently use the other and are at an increased risk for contemporaneous delinquent lifestyles.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".