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Record W2015899291 · doi:10.1177/0887403403255068

Drug and Alcohol Involvement among Minority and Female Juvenile Offenders: Treatment and Policy Issues

2004· article· en· W2015899291 on OpenAlexaff
Steven Belenko, Jane B. Sprott, Courtney A. Petersen

Bibliographic record

VenueCriminal Justice Policy Review · 2004
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsJuvenileEconomic JusticeJuvenile delinquencyPsychological interventionCriminologyRecidivismPsychologySubstance abuseCriminal justicePsychiatryPolitical scienceBiologyLaw

Abstract

fetched live from OpenAlex

Substance abuse and its consequences have had an important impact on the juvenile justice system, but relatively little attention has been paid to assessing and treating juvenile offenders for substance-related problems. Female and minority youth have been particularly affected: Most young female offenders have some substance involvement, yet juvenile justice–based treatment interventions are scarce. Second, minority overrepresentation occurs at all stages of the juvenile justice system; minority youth are treated more severely, and minority drug offenders in particular are at increased risk of formal handling, detention, and custody placement. Increased attention is needed to implement effective treatment and prevention programs that are gender and culturally specific and that target known risk factors. The authors describe some of the key elements and policies needed to reduce the impact of current juvenile justice policies on substance-involved girls and minorities and to overcome barriers to providing more effective treatment and related services for these populations.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.082
GPT teacher head0.379
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations42
Published2004
Admission routes1
Has abstractyes

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