A Review of Findings from the“Gender and Aggression Project”Informing Juvenile Justice Policyand Practice ThroughGender-Sensitive Research
Bibliographic record
Abstract
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. The 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.035 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.017 | 0.027 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".