SERIOUS CONDUCT PROBLEMS AMONG GIRLS AT RISK: TRANSLATING RESEARCH INTO INTERVENTION
Bibliographic record
Abstract
<span style="font-size: small; font-family: Times New Roman;">Until recently, research on serious conduct problems focused primarily on boys and men. In the past decade, however, we have gained a better understanding of the unique and shared risk and protective factors for girls and boys, and the role of gender in relation to developmental pathways associated with such problems. In this paper we discuss findings from the Gender and Aggression Project on risk and protective factors for girls who are perpetrators but also victims of violence. We discuss our findings from a developmental perspective, with the goal of understanding how exposure to adversity and violence early in life places girls at risk for aggression and violence, among other problems, and how continued exposure to trauma and the disruption of interpersonal and self-regulatory developmental processes cascades into ever deeper and broader problems. This research points more clearly to the need for accessible, evidence-based, and developmentally sensitive intervention.</span>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".