Culture, Health and Wellbeing: Yarning with the Victorian Indigenous community
Bibliographic record
Abstract
Indigenous young people around the world suffer poorer mental health outcomes than their non-Indigenous counterparts. Currently, how culture matters for health, what cultural practices are used in community to support health and wellbeing, and how culture is passed on in Aboriginal contemporary life in south east Australia – a region most affected by settler-colonisation – is not well understood. This paper presents findings from yarns with a representative sample of 45 Indigenous participants working in the field of health and wellbeing that explored how culture interleaves with health and wellbeing. It used Grounded Theory as the overarching methodology with community participation in all aspects of the project. Participants were nominated through snowballing and screened by a governing Board of Elders. They included men and women of varied ages, half residing in urban areas and half from rural Victoria, Australia. They had declared affiliations to 31 Traditional tribal groups. The yarns were held over zoom between a FN research assistant who was part of the community, and each participant. Each was recorded, transcribed, coded and analysed by a multi-perspectival team. Culture was viewed as central to individual and communal life, and passed on through relationships with people and Country itself. A wide variety of cultural practices were used by community members to aid and maintain health and wellbeing in profound ways. Myriad obstacles to health and wellbeing exist were also described, from experiences of disconnection through to barriers for accessing services. These findings have the potential to shape future holistic care and 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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.011 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| 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".