Farmers' Markets and their Practices Concerning Income, Privilege and Race: A Case Study of the Wychwood Artscape Barns in Toronto
Bibliographic record
Abstract
The popularity of Farmers’ markets is on the rise; in Canada there are 425 farmers’ markets, with over 130 in Ontario alone (Feagan, Morris, & Krug, 2004). Farmers’ markets provide high quality, local produce and are often considered an environmentally sustainable food practice (Taxel, 2003; King 2008). United States studies have scrutinized farmers’ markets as exclusionary white spaces that are not equitably accessible, but similar Canadian studies are rare. A case study at the Wychwood Artscape Barns, located in an economically and culturally diverse neighbourhood, in Toronto Ontario has been conducted. Demographics surveys of patrons were compared with existing demographic data; interviews were conducted to discover who shops at the market and for what reasons; results were analyzed using whiteness theory. Results were consistent with U.S. studies – Wychwood Farmers’ Market patrons were white, high income,individuals with university educations; these individuals shop at the market disproportionally to the demographic data.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".