Evaluación del riesgo y manejo del riesgo clínico en jóvenes antisociales: el grupo olvidado
Bibliographic record
Abstract
En el Centro para Niños Infractores (CCCO), del Instituto de Desarrollo Infantil (CDI) en Toronto (Canadá), se desarrollaron las Listas de Evaluación de Riesgos Tempranos (EARL-20B para niños; EARL-21G para niñas), para niños en riesgo de desarrollar criminalidad. En este primer estudio longitudinal de las EARL, 573 niños y 294 niñas que participaron en SNAP, un modelo basado en evidencia de género específico para riesgo\nen niños (6-11 años), 8.2 % de niños y 3.1 % de las niñas registraron delitos criminales durante el seguimiento (M = 14.9 y 14.6, respectivamente). Los puntajes de EARL Total, Familia, Niños y Responsividad, incluyendo dos ítems de riesgo específicos de género, y el Juicio Clínico General predicen el inicio temprano de actividad criminal. Los resultados sugieren que la evaluación del riesgo clínico sensible al género y el manejo de herramientas son importantes para la identificación efectiva y potencialmente reducen los resultados criminales.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| 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; both teacher heads agree on what is shown here.
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".