Can Food Banks Sustain Nutrient Requirements? A Case Study in Southwestern Ontario
Bibliographic record
Abstract
BACKGROUND: Concerns about adequate food supply is a mounting problem in Canada, making food bank visits a necessity for over 820,000 Canadians. Given this reliance, the purpose of this study was to compare contents of food hampers with Canadian guidelines, at a large urban food bank in Southwestern Ontario that intends to provide 3 days worth of food per person.\nMETHOD: Thirty hampers of each available size (for 1-6 people) were sampled (N = 180). Food items were recorded and analyzed for caloric value, food group, and macro- and micro-nutrient values. Results were compared to Dietary Reference Intakes (DRI) and Canada's Food Guide to Healthy Eating.\nRESULTS: 99% of hampers did not provide 3 days worth of nutrients. Grains and cereals met the lower range of Canada's Food Guide recommendations, and fruits and vegetables, meats and alternatives, and dairy products were below recommended levels, as were numerous vitamins and minerals, including vitamins A, D, B12, C, riboflavin, niacin, calcium, magnesium and zinc. Carbohydrates were slightly above recommended DRI, and energy from fat and protein scarcely met the minimums recommended. Hampers contained 1.6 days worth of energy per person.\nDISCUSSION: The energy available per person was below recommendations for most Canadians. Nutrients missing from the hampers can come from fresh fruits, vegetables, dairy products, and meats and alternatives. However, many low-income families have limited finances to purchase these foods which are relatively more expensive than processed foods. Encouraging more perishable food donations and storage facilities to maximize the nutritional intake for clients is imperative.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".