“My coupons are like gold”: experiences and perceived outcomes of low-income adults participating in the British Columbia Farmers’ Market Nutrition Coupon Program
Bibliographic record
Abstract
OBJECTIVE: The British Columbia Farmers' Market Nutrition Coupon Program (FMNCP) provides low-income households with coupons valued at $21/week for 16 weeks to purchase healthy foods in farmers' markets. Our objective was to explore FMNCP participants' experiences of accessing nutritious foods, and perceived programme outcomes. DESIGN: The current study used qualitative description methodology. Semi-structured interviews were conducted with FMNCP participants during the 2019 farmers' market season. Directed content analysis was used to analyse the data, whereby the five domains of Freedman et al.'s framework of nutritious food access provided the basis for an initial coding scheme. Data that did not fit within the framework's domains were coded inductively. SETTING: One urban and two rural communities in British Columbia, Canada. PARTICIPANTS: Twenty-eight adults who were participating in the FMNCP. RESULTS: Three themes emerged: autonomy and dignity, social connections and community building, and environmental and programmatic constraints. Firstly, the programme promoted a sense of autonomy and dignity through financial support, increased access to high-quality produce, food-related education and skill development and mitigating stigma and shame. Secondly, shopping in farmers' markets increased social connections and fostered a sense of community. Finally, participants experienced limited food variety in rural farmers' markets, lack of transportation and challenges with redeeming coupons. CONCLUSIONS: Participation in the FMNCP facilitated access to nutritious foods and enhanced participants' diet quality, well-being and health. Strategies such as increasing the amount and duration of subsidies and expanding programmes may help improve participants' experiences and outcomes of farmers' market food subsidy programmes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".