Gluten-Free Foods in Rural Maritime Provinces: Limited Availability, High Price, and Low Iron Content
Bibliographic record
Abstract
We investigated the price difference between gluten-free (GF) and gluten-containing (GC) foods available in rural Maritime stores. GF foods and comparable GC items were sampled through random visits to 21 grocery stores in nonurban areas of Nova Scotia, New Brunswick, and Prince Edward Island, Canada. Wilcoxon rank tests were conducted on price per 100 g of product, and on the price relative to iron content; 2226 GF foods (27.2% staple items, defined as breads, cereals, flours, and pastas) and 1625 GC foods were sampled, with an average ± SD of 66 ± 2.7 GF items per store in rural areas and 331 ± 12 in towns. The median price of GF items ($1.76/100 g) was more expensive than GC counterparts ($1.05/100 g) and iron density was approximately 50% less. GF staple foods were priced 5% higher in rural stores than in town stores. Although the variety of GF products available to consumers has improved, higher cost and lower nutrient density remain issues in nonurban Maritime regions. Dietitians working in nonurban areas should consider the relative high price, difficult access, and low iron density of key GF items, and work together with clients to find alternatives and enhance their food literacy.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".