Gender Differences in the Prevalence and Predictive Validity of Protective Factors in a Sample of Justice-Involved Youth
Bibliographic record
Abstract
Research on strengths and violent behavior in justice-involved youth suggests that the prevalence and predictive validity of strength factors vary as a function of gender. Interviews conducted between 2009 and 2012 with 185 justice-involved Canadian youth ( N female = 84, N male = 101; 67% violent index offence) were coded retrospectively using two strength measures for violence prediction: the protective domain of the Structured Assessment of Violence Risk in Youth (SAVRY), and the Structured Assessment of Protective Factors-Youth Version (SAPROF-YV). Males exhibited more protective factors than females across measures. Both tools were strong predictors of general recidivism in males but not females. The SAVRY protective domain was predictive of violent recidivism in males, but the SAPROF-YV was not; neither was predictive of violent recidivism in females. This study demonstrates gender differences in the prevalence and predictive validity of strengths in justice-involved youth and highlights the need for more female-focused research and measures.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".