A Comprehensive Review of Optimal Approaches to Co-Design in Health with First Nations Australians
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Australia’s social, structural, and political context, together with the continuing impact of colonisation, perpetuates health care and outcome disparities for First Nations Australians. A new approach led by First Nations Australians is required to address these disparities. Co-design is emerging as a valued method for First Nations Australian communities to drive change in health policy and practice to better meet their needs and priorities. However, it is critical that co-design processes and outcomes are culturally safe and effective. Aims: This project aimed to identify the current evidence around optimal approaches to co-design in health with First Nations Australians. Methods: First Nations Australian co-led team conducted a comprehensive review to identify peer-reviewed and grey literature reporting the application of co-design in health-related areas by and with First Nations Australians. A First Nations Co-Design Working Group (FNCDWG) was established to guide this work and team.A Collaborative Yarning Methodology (CYM) was used to conduct a thematic analysis of the included literature. Results: After full-text screening, 99 studies were included. Thematic analysis elicited the following six key themes, which included 28 practical sub-themes, relevant to co-design in health with First Nations Australians: First Nations Australians leadership; Culturally grounded approach; Respect; Benefit to First Nations communities; Inclusive partnerships; and Evidence-based decision making. Conclusion: The findings of this review provide a valuable snapshot of the existing evidence to be used as a starting point to guide appropriate and effective applications of co-design in health with First Nations Australians.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it