MétaCan
Menu
Back to cohort
Record W4307269972 · doi:10.3138/cjccj.2022-0022

Effectiveness of 12 Types of Interventions in Reducing Juvenile Offending and Antisocial Behaviour

2022· article· en· W4307269972 on OpenAlexvenueno aff
David P. Farrington, Hannah Gaffney, Howard White

Bibliographic record

VenueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénale · 2022
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionIntervention (counseling)PsychologyJuvenile delinquencyJuvenileBest practiceDeterrence (psychology)Parent trainingDeterrence theoryCrime preventionApplied psychologyCriminologyClinical psychologyMedical educationMedicinePsychiatryPolitical science

Abstract

fetched live from OpenAlex

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).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.092
GPT teacher head0.338
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénaleSame topicBullying, Victimization, and AggressionFrench-language works237,207