Evaluation of a community-based program for young boys at-risk of antisocial behaviour: results and issues.
Bibliographic record
Abstract
OBJECTIVE: We assess the impact of a community-based intervention program for boys 6-11 years old at-risk of antisocial behaviour, and compare changes in behaviour and competence pre-post for intervention and wait-list comparison group. METHOD: Interested parents called for enrolment. Inclusion required police contact and/or clinical scores (T>69) on Child Behaviour Checklist (CBCL) or Teacher Report Form (TRF), no developmental delay and English speaking. The program included two core 12-week groups (children's, parents') and optional additional services. Twelve sessions (February 2002-December 2005) provide pre-post intervention data, boys waiting at least 6 months formed a comparison group (starting April 2005). Outcomes included CBCL and TRF behaviour scales (rule-breaking, aggression, conduct, total problems) and competence. Repeated measures analysis of variance was done. RESULTS: Pre-post outcome comparisons indicated improvements among all boys, with significant differences favouring intervention boys on CBCL behaviour scales, but not TRF outcomes. Effect sizes were small to medium. Persisting high post-behaviour levels, unmeasured variation in additional services, and other design and sampling issues are noted. CONCLUSIONS: More rigorously designed program evaluation is required.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".