Working right ways in foot health with and for First Nations Peoples: research method guided and governed by First Nations ways of knowing, being, and doing in cross-sectional qualitative study design.
Bibliographic record
Abstract
Background: Underpinning ongoing colonisation of the lands now known as Australia, scientific racism in colonial research delivered flawed results by building Indigenous inferiority into methodology to produce dehumanising conclusions of First Nations Peoples. Scientific racism facilitated exclusion of First Nations Peoples from systems design and development; foregrounding ways exclusive and enforced colonial health systems cause First Nations health and wellbeing inequality. Inequities in foot health contribute to this inequality. This work describes and documents a process of First Nations-led authentic co-design for foot health research. This study represents ways and means to develop culturally responsive foot health research as judged by First Nations Peoples which will translate into improved and more responsive ways of delivering foot care. Methods: Non-Indigenous and First Nations Peoples sought authentic First Nations-led co-design process in foot health research methods, a governing First Nations Advisory Group, and broader First Nations governance and ethics approvals. Indigenous methodology, data sovereignty, and redistribution of power were imperative in ways of working. First Nations-led co-design developed culturally responsive semi-structured interviews to collect data. Talking with ten registered health practitioners who work closely with lower limb and foot health represented the right mix of participants and enough data to convey a more complicated mosaic of multi-faceted stories. First Nations expertise informed analytic induction and the use of inductive reasoning and constant comparison to identify common and overarching themes, and to perform thematic analysis. Results: Authentic First Nations-led ways of working in cross-sectional qualitative study design are documented. Results of data analysis following these ways of working will be published subsequently. Conclusion: This work provides insights into working right ways in research which will underpin good foot health services with and for First Nations Peoples. The paper highlights ways of working that empowers First Nations Peoples in authentic co-design. First Nations-led foot health research changes ways of working to counter inequities in foot health caused and maintained by ongoing colonisation and systemic racism. This study provides qualified voiced lived experience which foot health researchers must listen to and receive learning and direction from.
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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 | 0.182 | 0.118 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".