Uncovering the gaps: Violence risk assessment tools and their validity among Australian First Nations adults with mental disorders
Bibliographic record
Abstract
BackgroundThere is ongoing debate on the cultural appropriateness of violence risk assessment tools, particularly for marginalised populations such as Australian First Nations peoples, in determining court outcomes.ObjectiveThis scoping review aims to evaluate existing validated violence risk assessment tools for use among Australian First Nations adults with diagnosed mental disorders.DesignA search across databases, including PsycINFO, MEDLINE and Web of Science, identified 1202 studies, of which 31 met eligibility criteria. Two studies were ultimately included.ResultsThe review found two studies examining the cultural appropriateness of these tools, both highlighting a significant lack of cultural validation. Existing instruments were criticised for potentially misidentifying violence risk in First Nations populations.ConclusionsThe scarcity of studies underscores the urgent need for culturally sensitive research and validation of risk assessment tools for Australian First Nations adults. This review questions the ethics of using unvalidated tools in sentencing and advocates for developing culturally appropriate methodologies for First Nations populations.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".