Utility of the Static-99 and Static-99R With Latino Sex Offenders
Bibliographic record
Abstract
The predictive validity of the Static-99 measures with ethnic minorities in the United States has only recently been assessed with mixed results. We assessed the predictive validity of the Static-99 and Static-99R with a sample of Latino sex offenders ( N = 483) as well as with two subsamples (U.S.-born, including Puerto Rico, and non-U.S.-born). The overall sexual recidivism rate was very low (1.9%). Both the Static-99 measures were able to predict sexual recidivism for offenders born in the United States and Puerto Rico, but neither was effective in doing so for other Latino immigrants. Calibration analyses ( N = 303) of the Static-99R were consistent with the literature and provided support for the potential use of the measure with Latinos born in the United States and Puerto Rico. These findings and their implications are discussed as they pertain to the assessment of Latino sex offenders.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".