Interventions to address food insecurity among Aboriginal and Torres Strait Islander people: a rapid review
Bibliographic record
Abstract
Food insecurity disproportionately impacts Aboriginal and Torres Strait Islander Australians. This review sought to investigate research and evaluations of programs and interventions implemented to address food insecurity among Aboriginal and Torres Strait Islander communities. A rapid review was conducted to collate the available research from 6 databases. The search was conducted in May 2020. Search constructs related to food insecurity, Aboriginal and Torres Strait Islander people, and Australia. Twenty-five publications were included in this review, 24 reported on an intervention, while 9 were evaluations of an intervention. Interventions included behaviour change projects, including projects that sought to change purchasing and cooking behaviours, school-based education programs, and gardening programs. In general, the studies included in this sample were small and lacked a systematic consideration of the factors that shape the experience of food insecurity among Aboriginal and Torres Strait Islander people specifically. Based on the findings of this review, authors suggest greater consideration to the systematic determinants of food insecurity among Aboriginal and Torres Strait Islander communities to have lasting and sustainable impact on food insecurity. This review has been registered with the international prospective register of systematic reviews (PROSPERO: CRD42020183709). Novelty: Food insecurity among Aboriginal and Torres Strait Islander people poses significant risk to health and wellbeing. Small-scale food security interventions may not provide ongoing and sustained impact. Any intervention to promote food security will need to involve Aboriginal and Torres Strait Islander people and be sustained once external parties have left.
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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".