Instrumentos para la valoracion del riesgo de violencia sexual en ofensores sexuales adolescentes evidencias de validez en paises de America Latina
Bibliographic record
Abstract
Este articulo de revision tiene por objeto conocer la evidencia de validez disponible en America Latina de los principales instrumentos en el ambito internacional para la valoracion del riesgo de reincidencia sexual en ofensores sexuales adolescentes Para ello se realizo una revision bibliografica descriptiva en la que se utilizaron palabras claves afines con la materia analizada a traves de las bases de datos ISI Web of Science y Scopus y del metabuscador Google Scholar Los resultados destacan como paises principales en la creacion de este tipo de herramientas a Canada y Estados Unidos con herramientas como JSOAPII ERASOR 20 JSORRATII JRAT MEGA y DASH13 Asimismo se constata escasez de investigaciones que exploren las propiedades psicometricas de estos instrumentos en Latinoamerica y carencia de indicios en torno a la construccion de instrumentos de valoracion del riesgo de violencia sexual dentro de dicha zona geografica Se discuten las implicancias de estos efectos para la evaluacion e intervencion en ofensores sexuales adolescentes y se reconocen las dificultades relativas a la sobreutilizacion del procedimiento de juicio clinico en la valoracion del riesgo yo el uso de herramientas carentes de evidencias de validez para esta poblacion
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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 | 0.045 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".