Workplace Assessment of Targeted Violence Risk: The Development and Reliability of the<scp>WAVR</scp>‐21
Bibliographic record
Abstract
This study describes the development of the WAVR-21, a structured professional judgment guide for the assessment of workplace targeted violence, and presents initial interrater reliability results. The 21-item instrument codes both static and dynamic risk factors and change, if any, over time. Five critical items or red flag indicators assess violent motives, ideation, intent, weapons skill, and pre-attack planning. Additional items assess the contribution of mental disorder, negative personality factors, situational factors, and a protective factor. Eleven raters each rated 12 randomly assigned cases from actual files of workplace threat scenarios. Summary interrater reliability correlation coefficients (ICCs) for overall presence of risk factors, risk of violence, and seriousness of the violent act were in the fair to good range, similar to other structured professional judgment instruments. A subgroup of psychologists who were coders produced an ICC of 0.76 for overall presence of risk factors. Some of the individual items had poor reliability for both clinical and statistical reasons. The WAVR-21 appears to improve the structuring and organizing of empirically based risk-relevant data and may enhance communication and decision making.
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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 | 0.047 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".