Yarning about river safety: A qualitative study exploring water safety beliefs and practices for First Nations People
Bibliographic record
Abstract
ISSUE ADDRESSED: Water is vital to Australian First Nations Peoples' connection to country and culture. Despite this cultural significance, and epidemiological studies identifying elevated drowning risk among Australian First Nations Peoples, extremely limited qualitative research explores water safety beliefs and practices of First Nations Peoples. This study addressed this knowledge gap via qualitative research with Wiradjuri people living in Wagga Wagga, New South Wales. METHODS: Under Aboriginal Reference Group guidance, a local researcher recruited participants using purposive sampling for yarning circles across four groups: young people aged 18-30 years, parents of children under 5, parents of older children and adolescents and Elders. Yarning circles were audio recorded, transcribed and thematically coded using an inductive approach. RESULTS: In total, 10 First Nations individuals participated. Yarning led to rich insights and yielded five themes: families as first educators; importance of storytelling, lived experience and respect for knowledge holders; the river as a place of connection; historical influence on preference for river over pool and river is unpredictable and needs to be respected. CONCLUSIONS: This study demonstrates the importance of First Nations culture to water safety practices, particularly around the river. To reduce drowning risk among First Nations populations, knowledge holders need to be embedded in the design and delivery of community water safety education. SO WHAT?: Co-designing water safety initiatives with First Nations Peoples will have dual benefits; developing culturally appropriate and locally relevant water safety education, while also continuing First Nations culture across generations.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".