The Predictive Validity of a General Risk/Needs Assessment Inventory on Sexual Offender Recidivism and an Exploration of the Professional Override
Why this work is in the frame
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Bibliographic record
Abstract
This study examines the predictive validity of the Level of Service/Case Management Inventory (LS/CMI) on a sample of sexual offenders extracted from a large cohort of offenders and compares predictive validities with nonsexual offenders from the same cohort. The LS/CMI predicted sex offenders’ general recidivism, which occurred at a rate of 44.1%, with about the same accuracy as less frequently occurring violent (12.34%) and sexual recidivism (3.73%; AUC = .77, .74, and .74, respectively) and with nonsexual offenders. The study revealed that allowing assessors to override the numerically derived risk level with their professional judgment, a practice that increased risk level much more often than it decreased it, reduced the predictive validity of the scale and did so particularly for sex offenders by increasing risk excessively. An exploration of factors related to these adjustments revealed that non-risk-related characteristics were used in judgments to modify risk ratings. Implications for policy and practice are considered.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it