School Outcomes of Aggressive‐Disruptive Children: Prediction From Kindergarten Risk Factors and Impact of the Fast Track Prevention Program
Bibliographic record
Abstract
A multi-gate screening process identified 891 children with aggressive-disruptive behavior problems at school entry. Fast Track provided a multi-component preventive intervention in the context of a randomized-controlled design. In addition to psychosocial support and skill training for parents and children, the intervention included intensive reading tutoring in first grade, behavioral management consultation with teachers, and the provision of homework support (as needed) through tenth grade. This study examined the impact of the intervention, as well as the impact of the child's initial aggressive-disruptive behaviors and associated school readiness skills (cognitive ability, reading readiness, attention problems) on academic progress and educational placements during elementary school (Grades 1-4) and during the secondary school years (Grades 7-10), as well as high school graduation. Child behavior problems and skills at school entry predicted school difficulties (low grades, grade retention, placement in a self-contained classroom, behavior disorder classification, and failure to graduate). Disappointingly, intervention did not significantly improve these long-term school outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".