Violence Risk Assessment Tools and Indigenous Peoples: Colonialism as an Underlying Cause of Risk Ratings on the SAVRY
Bibliographic record
Abstract
Violence risk assessment tools are used around the world with people who have committed crimes to determine the risk factors that may have contributed to their offending. These tools can carry great consequences for people’s liberty. Violence risk assessment tools are also used with Indigenous people who are overrepresented in the Canadian justice system. A major issue with these risk assessment tools is that they do not use a colonial lens to understand the underlying mechanisms of violence. Using the Structured Assessment of Violence Risk in Youth (SAVRY) as an example, we examined how colonialism underlies risk and protective ratings. Colonialism increases the probability that Indigenous youth will be rated higher on some risk factors on the SAVRY. Novel interventions to reduce Indigenous overrepresentation include addressing the colonial factors behind violence risk and protective factors. Given that colonialism underlies scores on risk assessment tools, service providers need to link risk ratings to colonialism in their service formulations, carefully attend to culturally relevant factors, and provide interventions and support that specifically address colonialism. Suggestions for future research that include Indigenous community involvement are also provided. A short case analysis, cultural formulation and treatment suggestions are provided as an illustration.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".