Overcoming Barriers to Scaling Up Sustainable Alternative Food Systems: A Comparative Case Study of Two Ontario-Based Wholesale Produce Auctions
Bibliographic record
Abstract
Conventional food systems are viewed by the literature as unsustainable in that they provide consumers with convenience while disconnecting them from producers thus leading to environmental and social problems. By contrast, sustainable or “alternative” food systems are viewed as correcting such problems. Wholesale produce auctions, which are well established in the Old Order Mennonite community, are physical sites where large quantities of produce are sold through a competitive bidding process to local buyers. These are seen as a way of better connecting producers and consumers and thus realizing a more sustainable food system. However, this potential has not been tested. Therefore, this paper explores two produce auctions in southwestern Ontario, Canada, using an interview based methodology (N = 48) and demonstrates that despite wholesale produce auctions offering many opportunities to promote the benefits of alternative food systems, produce auctions are limited in that they fail to provide a practical and functional way of distributing food to individual consumers. Overall, this research highlights what appears to be a tension in the alternative food systems literature: producers and consumers may be simultaneously looking for the sustainability benefits associated with “alternative food systems” without wanting to sacrifice any of the convenience found in conventional food systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.018 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".