Co-designing health service evaluation tools that foreground first nation worldviews for better mental health and wellbeing outcomes
Bibliographic record
Abstract
It is critical that health service evaluation frameworks include Aboriginal people and their cultural worldviews from design to implementation. During a large participatory action research study, Elders, service leaders and Aboriginal and non-Aboriginal researchers co-designed evaluation tools to test the efficacy of a previously co-designed engagement framework. Through a series of co-design workshops, tools were built using innovative collaborative processes that foregrounded Aboriginal worldviews. The workshops resulted in the development of a three-way survey that records the service experiences related to cultural safety from the perspective of Aboriginal clients, their carer/s, and the service staff with whom they work. The surveys centralise the role of relationships in client-service interactions, which strongly reflect their design from an Aboriginal worldview. This paper provides new insights into the reciprocal benefits of engaging community Elders and service leaders to work together to develop new and more meaningful ways of servicing Aboriginal families. Foregrounding relationships in service evaluations reinstates the value of human connection and people-centred engagement in service delivery which are central to rebuilding historically fractured relationships between mainstream services and Aboriginal communities. This benefits not only Aboriginal communities, but also other marginalised populations expanding the remit of mainstream services to be accessed by many.
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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 | 0.285 | 0.301 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.011 | 0.005 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.019 | 0.015 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".