Towards attainment of Indigenous health through empowerment: resetting health systems, services and provider approaches
Bibliographic record
Abstract
Colonial policies and practices have introduced significant health challenges for Indigenous populations in commonwealth countries. Health systems and models of care were shaped for dominant society, and were not contextualised for Indigenous communities nor with provision of Indigenous cultural approaches to maintain health and wellness. Shifts to support Indigenous health outcomes have been challenged by debate on identifying which system and service components are to be included, implementation approaches, the lack of contextualised evaluation of implemented models to justify financial investments, but most importantly lack of effort in ensuring equity and participation by affected communities to uphold Indigenous rights to health. Prioritising the involvement, collaboration and empowerment of Indigenous communities and leadership are critical to successful transformation of healthcare in Indigenous communities. Locally determined priorities and solutions can be enacted to meet community and individual needs, and advance health attainment. In this paper, existing successful and sustainable models that demonstrate the empowerment of Indigenous peoples and communities in advocating for, designing, delivering and leading health and wellness supports are shared.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".