Indicators of psychoses or psychoses as indicators: the relationship between Indigenous social disadvantage and serious mental illness
Bibliographic record
Abstract
OBJECTIVE: To explore the relationship between Indigenous social disadvantage and serious mental illness. CONCLUSIONS: Rapidly changing patterns of mental disorders in Indigenous populations indicate the importance of social determinants. Canadian research on Native American suicide has demonstrated a clear link between social control factors and one mental health issue - completed suicide - a finding with major social policy implications. This work has not been replicable in Australia, reflecting the particular political and social circumstances of Aboriginal and Torres Strait Islander populations. Recent research motivated by clinicians' observations of an increase in psychotic disorders in the Indigenous populations of Cape York and the Torres Strait has demonstrated that the prevalence is high and that there are within-population differences. Given similar exposure to social disadvantage, these findings raise the possibility of utilising Indigenous psychosis prevalence as a metric to inform a more nuanced understanding of the predictors of wider vulnerability and resilience at a setting level, and as a policy and service development lever.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".