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Record W2131823518 · doi:10.1002/bsl.868

Racial differences in the associations of neighborhood disadvantage, exposure to violence, and criminal recidivism among female juvenile offenders

2009· article· en· W2131823518 on OpenAlexaff
Preeti Chauhan, N. Dickon Reppucci, Eric Turkheimer

Bibliographic record

VenueBehavioral Sciences & the Law · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsCanadian Institutes of Health Research
FundersCenters for Disease Control and Prevention
KeywordsRecidivismJuvenileDisadvantageJuvenile delinquencyHuman factors and ergonomicsPoison controlCriminologyPsychologyInjury preventionSuicide preventionOccupational safety and healthMedical emergencyMedicinePolitical scienceBiologyEcologyLaw

Abstract

fetched live from OpenAlex

The current study examined the impact of exposure to violence and neighborhood disadvantage on criminal recidivism among Black (n = 69) and White (n = 53) female juvenile offenders. Participants were girls between the ages of 13 and 19 (M = 16.8; SD = 1.2) who were sentenced to secure custody. Using a multi-method research design, the study assessed neighborhood disadvantage through census level data, exposure to violence through self-report, and criminal recidivism through official records. Results indicated that Black girls were significantly more likely than White girls to live in disadvantaged neighborhoods, but both reported similar levels of parental physical abuse and witnessing neighborhood violence. In structural equation models, neighborhood disadvantage and witnessing neighborhood violence were indicative of future recidivism for the group as a whole. However, multiple group analyses indicated the existence of race specific pathways to recidivism. Witnessing neighborhood violence was associated with recidivism for Black girls while parental physical abuse was associated with recidivism for White girls. Results suggest that characteristics within the neighborhood play a considerable role in recidivism among female juvenile offenders generally and Black female juvenile offenders, specifically. Race specific risk models warrant further investigation, and may help lawmakers and clinicians in addressing racial disparities in the justice system.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.077
GPT teacher head0.368
Teacher spread0.291 · 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

Citations39
Published2009
Admission routes1
Has abstractyes

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