Exploring Food Guidance Approaches for Seniors in Antigonish, NS: Is There Still Gold at the End of the Rainbow?
Bibliographic record
Abstract
Purpose: As Canada rethinks approaches to food guidance, insights into the needs of seniors in rural communities are important to ensure their nutrition issues are addressed. This study aimed to explore the food guidance needs and wants of a group of seniors living in Antigonish, Nova Scotia. Methods: Three focus groups were held with a total of 12 participants over the age of 65 years, living independently in the community. Seniors were asked about their views on Canada’s Food Guide (CFG) and the Brazilian Dietary Guidelines (BDG). Results: Participants identified CFG as a trusted source of information and related well to the food groups and directive statements. Portion sizes were confusing and advice on food choices was not seen as being realistic in terms of cost and availability. The holistic nature of the BDG was appealing but guidance on processed food and social eating was not seen as relevant. Neither guidance tool addressed concerns about sustainability and environmental issues. Point of purchase nutrition information was preferable to receiving it from health professionals. Conclusion: CFG was seen as a trusted source of advice; however, locally accessible guidance on affordability and environmental issues related to food choice is needed for this group.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".