Beyond policy and planning to practice: getting sexual health on the agenda in Aboriginal communities in Western Australia
Bibliographic record
Abstract
BACKGROUND: Indigenous Australians have significantly poorer status on a large range of health, educational and socioeconomic measures and successive Australian governments at state and federal level have committed to redressing these disparities. Despite this, improvements in Aboriginal health status have been modest, and Australia has much greater disparities in the health of its Indigenous people compared to countries that share a history characterised by colonisation and the dispossession of indigenous populations such as New Zealand, Canada and the United States of America. Efforts at policy and planning must ultimately be translated into practical strategies. This article outlines an approach that was effective in Western Australia in increasing the engagement and concern of Aboriginal people about high rates of sexually transmissible infections and sexual health issues. Many aspects of the approach are relevant for other health issues. RESULTS: The complexity of Indigenous sexual health necessitates inter-agency and cross-governmental collaboration, in addition to Aboriginal leadership, accurate data, and community support. A recent approach covering all these areas is described. This has resulted in Aboriginal sexual health being more actively discussed within Aboriginal health settings than it once was and additional resources for Indigenous sexual health being available, with better communication and partnership across different health service providers and sectors. The valuable lessons in capacity building, collaboration and community engagement are readily transferable to other health issues, and may be useful for other health professionals working in the challenging area of Aboriginal health. CONCLUSION: Health service planners and providers grapple with achieving Aboriginal ownership and leadership regarding their particular health issue, despite sincere concern and commitment to addressing Aboriginal health issues. This highlights the need to secure genuine Aboriginal engagement. Building capacity that enables Indigenous people and communities to fulfill their own goals is a long-term strategy and requires sustained commitment, but we argue is a prerequisite for better Indigenous health outcomes.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| 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".