Reassessing “Local”: The Commodity Chains of Fruits and Vegetables Sold at the Jean Talon and Atwater Markets in Montréal, Québec
Bibliographic record
Abstract
Given the perceived failures of the modern food system, there has been renewed interest in the role of local food system initiatives (LFSI); farmers’ markets represent one of many examples of such initiatives. Central to these initiatives are short supply chains which seek to bridge the gap between producers and consumers while re-embedding trust and transparency. Despite the proliferation of farmers’ markets in recent decades in North America, conceptual expectations and the material product flows of local food sometimes clash. In this thesis, I investigate what constitutes ‘local’ for the commodity chains of fruits and vegetables supplied to the Jean Talon and Atwater Markets in Montréal, Québec, Canada. Using a multi-methods approach, including a survey of vendors at both Markets drawing from open-ended and fixed-response questions, informal conversational interviews, and observations, I identify and weave together the actors, food provenance, supply chains, and conceptualizations of ‘local’ that construct the commodity chains of fruits and vegetables. Upon doing so, I examine the relationships amongst the Markets, rural and peri-urban agriculture, and urban consumption that connect the LFSIs on the Island of Montréal to farmers across southern Québec. While vendors delimited ‘local’ to the provincial boundaries of Québec, sourcing of fruits and vegetables sold at the Markets did not always align with this definition.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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".