The Relationship Between Risk, Criminogenic Need, and Recidivism for Indigenous Justice-Involved Youth
Bibliographic record
Abstract
The risk–need–responsivity framework is widely used to guide the case management of justice-involved youth, but little research is available on its applicability to Indigenous populations. In the present study, we examined how standardized risk assessment, identification of criminogenic needs, and receipt of need-targeted programming related to recidivism in a sample of 70 Indigenous and non-Indigenous youth. The two groups did not differ on overall level of risk, number of needs, match to services, or recidivism rates. However, Indigenous youth were evaluated as higher risk in peer and leisure functioning, more likely to have needs related to education and leisure, and less likely to receive adequate peer-specific intervention. In both groups, risk assessment predicted recidivism, while match to services predicted days to reoffense. High rates of mental health issues and associated services were observed in both groups. Implications of these findings for research and practice with Indigenous youth are discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.001 |
| 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".