Consumer quest for embeddedness: a case study of the Brantford Farmers' Market
Bibliographic record
Abstract
Abstract Farmers' markets (FMs) in the US, Canada and Britain are often held as one key response to the unsustainability of conventional food production systems, as they provide consumers with a potentially more comprehensive valuation venue for their food purchases. This paper categorizes and examines the range of consumer motivations at the Brantford FM in Ontario, Canada using the concept of embeddedness. Though not a simple concept, embeddedness proves useful for framing non‐economic values sought by consumers at FMs in a way that helps to build our understanding of the context‐specific quality of patron motivations at FMs. In the study, values of social embeddedness (social interaction, knowledge of vendors, etc.) and spatial embeddedness (food freshness, supporting the ‘local’, etc.) emerge as core sets of consumer motivations at this FM, while natural embeddedness values (organic production, ‘food‐miles’ concerns, etc.) are less strongly held. This case study helps advance that specific sets of embedded values are expressed at FMs – consumer motivations partly reflect their historic and situated contexts, while contributing to our understanding of the importance of the embeddedness concept to alternative food system arguments for change.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.022 | 0.008 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".