Effectiveness of foodbank western australia’s food sensations® for adults food literacy program in regional australia
Bibliographic record
Abstract
Background: Food Sensations for Adults, funded by the Western Australian Department of Health, is a four-week nutrition education program focused on food literacy, with demonstrated success amongst Western Australians. In the last two years, 25% of programs have been in regional and remote areas and therefore the aim of this research is to explore the impact of the program in regional areas. Methods: Participants answered validated pre- and post-questionnaires to assess change in food literacy behaviours (2016–2018). Results: Regional participants (n = 451) were more likely to live in low income areas, have lower education levels, and identify as Aboriginal, than metropolitan participants (n = 1398). Regional participants had statistically significantly higher food literacy behaviours in the plan and manage and preparation domains, and lower selection behaviours at baseline than metropolitan participants. Post program, regional participants showed matched improvements with metropolitan participants in the plan and manage, and preparation domains. Food selection behaviour results increased in both groups but were significantly higher in regional participants. Conclusions: The program demonstrates effective behaviour change in all participants; however, the increased disadvantage experienced by people residing outside of major cities highlights the need for additional government support in addressing regional specific barriers, such as higher food costs, to ensure participants gain maximum benefit from future food literacy programs.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".