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Record W7070903448

A Review of Findings from the\n“Gender and Aggression Project”\nInforming Juvenile Justice Policy\nand Practice Through\nGender-Sensitive Research

2010· article· en· W7070903448 on OpenAlexaboutno aff

Bibliographic record

VenueInsecta mundi · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic JusticeAggressionJuvenileJuvenile delinquencyPopulationPoison controlNormativeSuicide prevention
DOInot available

Abstract

fetched live from OpenAlex

Adolescent girls comprise nearly a third of juvenile arrests, and rates of incarceration among young females have been rising rapidly. Yet, young women continue to be a neglected population in juvenile justice research and service delivery. This special issue is devoted to describing the critical issues that arise when young women come into contact with the juvenile justice system. Over the last decade, our research team has been working together to better understand the lives of justice-involved youth. To this end, we have conducted a multisite longitudinal study that has followed adolescents as they have moved through the juvenile justice system, with our most recent wave of assessments occurring as these young people made the transition back into their communities and into young adulthood. This special issue represents a collection of key findings from the Gender and Aggression Project, with a special emphasis on pathways that young women follow both into and out of the juvenile justice system.\nThe Gender and Aggression Project (GAP) involved a partnership of researchers from across diverse disciplines who came together to build a common research instrument that could be used within both normative and high-risk populations. The findings reviewed in this special issue are derived from two longitudinal studies that used this common assessment instrument to assess the profiles, risk factors, and outcomes of justice-involved youth in the United States and Canada. Study One, the Gender and Aggression Project— Virginia Site, recruited an entire population of females sentenced to secure custody during a 14-month period in a large southeastern state (93% of all admissions). Participants included 141 adolescent females who were, on average, 16 to 17 years of age at the time of the first assessment. The sample was racially/ethnically diverse, with 50.0% self-identifying as African-American, 2.2% as Native American, 1.4% as Hispanic and 8.0% as “Other”: the remaining 38.4% identified as Caucasian. Following their sentencing, each participant underwent a 30-day assessment, which included psychological and educational testing, in addition to a full medical examination completed by a physician. Each participant also completed approximately 6-8 hours of individual assessments, including semi-structured clinical interviews, computerized diagnostic assessments, and a self-report protocol. Approximately two years after the initial interview, 78.5% (N=102) of eligible study members who had been released into the community for at least six months completed a 2-3 hour in-person assessment focused on reentry into the community and on mental and physical health functioning. The third wave of in-person assessments has just been completed with 120 of the study members being followed into young adulthood. To our knowledge, this is one of the largest in-depth studies of girls who have reached the deep-end of the juvenile justice system for which there is now longitudinal assessments available.

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)0.023
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.031
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0150.026
Science and technology studies0.0030.003
Scholarly communication0.0060.004
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.136
GPT teacher head0.469
Teacher spread0.333 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations0
Published2010
Admission routes1
Has abstractyes

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