Instrumentos para la valoración del riesgo de violencia sexual en ofensores sexuales adolescentes: evidencias de validez en países de América Latina
Bibliographic record
Abstract
The objective of this review article consist of getting to know the validity evidence available in Latin America of the main instruments existing in the international sphere for the appreciation of the sexual recidivism risk in adolescent sexual offenders. For this purpose, a descriptive bibliographical review was carried out where similar or associated key words were used with the matter being analyzed, through the ISI Web of Science and Scopus databases and the Google Scholar metasearch. The results point at Canada and the United States as the major countries in the creation of this type of mechanisms, with tools such as J-SOAP-II, ERASOR 2.0, JSORRAT-II, J-RAT, MEGA and DASH-13. Likewise, a scarcity of researches serving to explore the psychometric properties of these instruments in Latin America and the lack of signs around the construction of those serving for the assessment of sexual violence within this geographical zone. The implications of these effects for evaluation and intervention in adolescent sexual offenders are discussed and the difficulties relating to the overutilization of clinical judgment in risk assessment and/or the use of tools deprived of validity for this population are duly acknowledged
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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 | 0.076 | 0.150 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".