Linking Local Food Systems and the Social Economy? Future Roles for Farmers' Markets in Alberta and British Columbia*
Bibliographic record
Abstract
Abstract Often organized as grassroots, nonprofit organizations, many farmers' markets serve as strategic venues linking producers and consumers of local food while fulfilling multiple social, economic, and environmental objectives. This article examines the potential of farmers' markets to play a catalyst role in linking local food systems to the social economy in western Canada. We used the Delphi method of inquiry to solicit and synthesize perspectives on the future role of farmers' markets within local food systems and the social economy from farmers' market vendors, market managers, and policy and government representatives in each province. We found that negotiations over the definition of local food systems, the dynamics of supply and demand relationships, and perceptions of “authenticity” affect the positionality of farmers' markets in relation to other marketing channels within regional food systems. Stakeholders engaged in this Delphi inquiry strategized ways to scale up local food systems beyond current limits while also maintaining the “authentic experience” offered by farmers' markets that has helped to fuel increased consumer interest, demand, and growth. Results confirm the need for further investigation of the relationship between the social economy, infrastructure, and authenticity in the development of local food systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".