Tuberculosis care designed with barramarrany (family): Participatory action research that prioritised partnership, healthy housing and nutrition
Bibliographic record
Abstract
ISSUE ADDRESSED: Ongoing tuberculosis (TB) transmission in Aboriginal communities in Australia is unfair and unacceptable. Redressing the inequity in TB affecting Aboriginal peoples is a priority in Australia's Strategic Plan for Tuberculosis Control. Improving TB care needs not to just identify barriers but do something about them. Privileging the voices of Aboriginal people affected by TB is essential to identify effective and enabling strategies. METHODS: A barramarrany (Aboriginal family) affected by recurring TB partnered with TB and Environmental Health teams using a participatory action research (PAR) methodology to improve housing health hardware and nutrition alongside biomedical TB prevention and care. A combination of the Ottawa Charter for Health Promotion; the International "End TB" Strategy; and Aboriginal barramarrany leadership, worldviews and traditional values guided actions to reduce TB transmission. RESULTS: Together the partners improved housing hardware and access to nutritious food, so the barramarrany could create a setting for good health and wellbeing. These actions supported the barramarrany to regain the physical, social and emotional wellbeing to deal with day-to-day challenges and stresses. The barramarrany were able to better sustain supportive relationships; grow, prepare and eat healthy food; and participate in health care activities. The barramarrany could better engage with medical approaches for TB and four barramarrany members completed TB treatment. The PAR action-project enabled and supported early TB diagnosis, treatment and prevention. CONCLUSION: Amplifying the voices of Aboriginal people and shared ownership of TB diagnosis, treatment and prevention by the barramarrany, was underpinned with principles of self-determination, capacity building and social justice. This PAR action-project provides further evidence that improving housing and nutrition can assist in Ending TB while improving wellbeing. SO WHAT?: Our action-research project undertaken within a PAR framework demonstrates the implementation of End TB Strategies by utilising the Ottawa Charter's five actions to promote health, by understanding and centralising the social determinants of health.
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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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".