Should Actuarial Risk Assessments be Used with Sex Offenders who are Intellectually Disabled?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background Objective actuarial assessments are critical for making risk decisions, determining the necessary level of supervision and intensity of treatment ( Andrews & Bonta 2003 ). This paper reviews the history of organized risk assessment and discusses some issues in current attitudes towards sexual offenders with intellectual disabilities. Method We present two risk assessment tools (RRASOR and STABLE‐2000) that appear to have practical utility with this population. Data are presented from a community sample of 81 sexual offenders who are intellectually disabled suggesting that the RRASOR may provide a useful metric of risk for this population. Dynamic risk is assessed using the STABLE‐2000. This tool, based on 16 areas empirically associated with sexual recidivism, samples the individuals’ current behaviour, skill deficits and personality factors. Change in these factors serves to flag the supervisor to changing risk levels. Conclusions In addressing the question of whether we should seek special risk measures normed on people with intellectually disabilities, given the current lack of alternative tools, we conclude that it is reasonable to make use of the risk assessments that have been validated on the general sex offender population.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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