The living experience of First Nations Peoples and Forensic Mental Health systems: listening to the deep stories behind the numbers
Bibliographic record
Abstract
While First Nations Peoples in Australia experience high rates of criminal justice contact, there is limited research on their experiences of the forensic mental health system. This study aims to develop new understandings of how First Nations Peoples experience and understand the forensic mental health system in NSW. Interviews were conducted with ten First Nations Peoples in contact with the forensic mental health system, including forensic patients and their family members. Participants described challenging life experiences prior to their contact with the forensic mental health system, with community services often failing to respond to their mental health needs. While participants reported some positive experiences with the forensic mental health system, they ultimately described an urgent need for culturally appropriate programs that facilitate connections to family and Community. Forensic mental health services should be co-designed alongside First Nations Peoples and communities to improve outcomes and avoid re-traumatisation through contact with services.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.019 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".