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Record W1932480158 · doi:10.1177/1541204015585173

Prospective Childhood Risk Factors for Gang Involvement Among North American Indigenous Adolescents

2015· article· en· W1932480158 on OpenAlexaboutno aff
Dane Hautala, Kelley J. Sittner, Les B. Whitbeck

Bibliographic record

VenueYouth Violence and Juvenile Justice · 2015
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
FundersNational Institute on Drug AbuseNational Institute of Mental HealthNational Institute on Alcohol Abuse and Alcoholism
KeywordsJuvenile delinquencyLongitudinal studySuicide preventionPoison controlInjury preventionHuman factors and ergonomicsOccupational safety and healthIntervention (counseling)IndigenousDemographyReservationMedicinePsychologyEnvironmental healthDevelopmental psychologyPsychiatryPolitical scienceSociology

Abstract

fetched live from OpenAlex

The purpose of the study was to examine prospective childhood risk factors for gang involvement across the course of adolescence among a large eight-year longitudinal sample of 646 Indigenous (i.e., American Indian and Canadian First Nations) youth residing on reservation/reserve land in the Midwest of the United States and Canada. Risk factors at the first wave of the study (ages 10-12) were used to predict gang involvement (i.e., gang membership and initiation) in subsequent waves (ages 11-18). A total of 6.7% of the participants reported gang membership and 9.1% reported gang initiation during the study. Risk factors were distributed across developmental domains (e.g., family, school, peer, and individual) with those in the early delinquency domain having the strongest and most consistent effects. Moreover, the results indicate that the cumulative number of risk factors in childhood increases the probability of subsequent gang involvement. Culturally relevant implications and prevention/intervention strategies are discussed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.039
GPT teacher head0.338
Teacher spread0.299 · 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.

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

Citations25
Published2015
Admission routes1
Has abstractyes

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