Communities Setting the Direction for Their Right to Nutritious, Affordable Food: Co-Design of the Remote Food Security Project in Australian Indigenous Communities
Bibliographic record
Abstract
Despite long histories of traditional food security, Indigenous peoples globally are disproportionately exposed to food insecurity. Addressing this imbalance must be a partnership led by Indigenous peoples in accordance with the UN Declaration of the Rights of Indigenous Peoples. We report the co-design process and resulting design of a food security research project in remote Australia and examine how the co-design process considered Indigenous peoples' ways of knowing, being, and doing using the CREATE Tool. Informed by the Research for Impact Tool, together Aboriginal Community Controlled Health Organisation staff, Indigenous and non-Indigenous public health researchers designed the project from 2018-2019, over a series of workshops and through the establishment of research advisory groups. The resulting Remote Food Security Project includes two phases. Phase 1 determines the impact of a healthy food price discount strategy on the diet quality of women and children, and the experience of food (in)security in remote communities in Australia. In Phase 2, community members propose solutions to improve food security and develop a translation plan. Examination with the CREATE Tool showed that employing a co-design process guided by a best practice tool has resulted in a research design that responds to calls for food security in remote Indigenous communities in Australia. The design takes a strengths-based approach consistent with a human rights, social justice, and broader empowerment agenda. Trial registration: The trial included in Phase 1 of this project has been registered with Australian New Zealand Clinical Trials Registry: ACTRN12621000640808.
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.
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 | 0.123 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 0.004 |
| 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".