Case Study Qualitative Inquiry of Healthy Food Retailing in Rural Newfoundland and Labrador
Bibliographic record
Abstract
Multilevel, multicomponent interventions are recognized approaches to promote public health and prevent disease. Our study focused on diet and its determinants to understand factors impacting healthy food retailing in rural Newfoundland and Labrador (NL), Canada, using a case study approach with community-engaged system-based processes. In three case study communities, we conducted two qualitative data generating processes (storeowner interviews and community focus groups), to inform the design and implementation of a healthy retailing intervention. We identified five key themes from describing the micro, meso, exo, and macro system of factors that impact healthy food retailing in rural NL communities: (1) consumers drive retailer behavior; (2) independence increases the stores’ capacity to serve the community; (3) “everything comes down to price, for us and the customers”; (4) the store is less about food, and more about the community; (5) frustrating conventional food systems are juxtaposed against aspirations of obtaining food locally. We reveal the important relationships between consumers and retailers, the value of independence in store ownership, the dominating challenge of food prices, and imperfect local and conventional food systems impacting healthy food retailing in small stores in rural NL. Our system of themes highlights the economic and social landscape in which the stores operate. Food retailers strategically balance this complex system of layered, interconnected factors, continuously seeking ways to support the wellbeing of their communities. Future research will explore the feasibility and impact of healthy food retailing interventions, informed by this research, within rural NL food stores and communities.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.021 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".