Validating the Hamilton Anatomy of Risk Management–Forensic Version and the Aggressive Incidents Scale
Bibliographic record
Abstract
The Hamilton Anatomy of Risk Management–Forensic Version (HARM-FV) is a structured professional judgement tool of violence risk developed for use in forensic inpatient psychiatric settings. The HARM-FV is used with the Aggressive Incidents Scale (AIS), which provides a standardized method of recording aggressive incidents. We report the findings of the concurrent validity of the HARM-FV and the AIS with widely used measures of violence risk and aggressive acts, the Historical, Clinical, Risk Management–20, Version 3 (HCR-20 V3 ) and a modified version of the Overt Aggression Scale. We also present findings on the predictive validity of the HARM-FV in the short term (1-month follow-up periods) for varying severities of aggressive acts. The results indicated strong support for the concurrent validity of the HARM-FV and AIS and promising support for the predictive accuracy of the tool for inpatient aggression. This article provides support for the continued clinical use of the HARM-FV within an inpatient forensic setting and highlights areas for further research.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".