In a group, “we’re not just a number”: what we learnt from an accidental hybrid health and well-being group programme for First Nations Australians with diabetes
Bibliographic record
Abstract
First Nations peoples in Australia are disproportionately affected by diabetes. We report on a qualitative evaluation of a healthy lifestyle group programme at an Aboriginal Community Controlled Health Service. The programme was designed by an Aboriginal Health Worker and took place in a regional community. Yarning interviews of five participants and four facilitators were conducted followed by a collaborative analysis. The group context provided connecting and relationship-building opportunities, allowing participants to feel that they were seen as an individual. The accidental hybrid approach adopted due to the impact of COVID-19 pandemic lockdown supported transition of healthy activities into the home context while still accessing support and motivation from the group. This paper concluded that the unintentional hybrid programme found promising individual and cross-generational health and wellbeing benefits for First Nations families which suggests that intentional hybrid frameworks may show promise in improving First Nations peoples’ health and well-being.
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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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.008 |
| 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".