Effectiveness of 12 Types of Interventions in Reducing Juvenile Offending and Antisocial Behaviour
Bibliographic record
Abstract
The main aim of this article is to summarize the best available evidence (from systematic reviews) of the effectiveness of 12 types of interventions in reducing juvenile offending and antisocial behaviour. In the interests of making the results widely understandable to researchers, practitioners, policy makers, and the general public, all effect sizes are converted into percentage decreases in antisocial behaviour or offending. Based on the most important systematic review in each category, the most effective interventions are parent training, focused deterrence, child skills training, cognitive–behavioural therapy, mentoring, and family therapy. Anti-bullying programs, anti-cyberbullying programs, and pre-court diversion programs are quite effective, while school exclusion reduction, after-school programs, and boot camps are least effective. The good news is that, based on estimated reductions in offending, intervention programs are usually found to be much more effective than is commonly believed (based on other measures).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".