Two-tiered violence risk estimates: A validation study of an integrated-actuarial risk assessment instrument.
Bibliographic record
Abstract
This study is an initial validation study of the Two-Tiered Violence Risk Estimates instrument (TTV), a violence risk appraisal instrument designed to support an integrated-actuarial approach to violence risk assessment. The TTV was scored retrospectively from file information on a sample of violent offenders. Construct validity was examined by comparing the TTV with instruments that have shown utility to predict violence that were prospectively scored: The Historical-Clinical-Risk Management-20 (HCR-20) and Lifestyle Criminality Screening Form (LCSF). Predictive validity was examined through a long-term follow-up of 12.4 years with a sample of 78 incarcerated offenders. Results show the TTV to be highly correlated with the HCR-20 and LCSF. The base rate for violence over the follow-up period was 47.4%, and the TTV was equally predictive of violent recidivism relative to the HCR-20 and LCSF. Discussion centers on the advantages of an integrated-actuarial approach to the assessment of violence risk.
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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 | 0.052 | 0.149 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".