Next Steps in Decolonising Aboriginal and Torres Strait Islander Primary Health Care Policy in Australia: An Analysis of Key Stakeholder Views
Bibliographic record
Abstract
Following a failed 2023 referendum on constitutional recognition of Aboriginal and Torres Strait Islander people, Australian governments must work with Indigenous leaders to chart a new way forward in policy to support Indigenous health and wellbeing. Here we report on key stakeholder views on what is required to decolonise Indigenous primary health care (PHC) policy. This article reports on qualitative research conducting yarns with 20 senior staff working in key government and non-government organisations comprising the Indigenous PHC sector (‘stakeholders’). Stakeholders see the sector as exemplifying decolonisation, motivated through Indigenous leadership. However, further changes are needed in mainstream health services, workforce development, intersectoral policy, and determinants of health. We discuss how the Indigenous PHC sector can inform decolonising policy in other sectors and reflect on the international implications of our findings. We conclude that the sector provides important lessons for decolonising Australian public policy.
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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 | 0.033 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| 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".