RE-APPROXIMATING FOOD PRODUCERS AND CONSUMERS IN METRO VANCOUVER // REAPROXIMANDO PRODUCTORES Y CONSUMIDORES DE ALIMENTOS EN LA REGIÓN METROPOLITANA DE VANCOUVER // REAPROXIMANDO PRODUTORES E CONSUMIDORES DE ALIMENTOS NA REGIÃO METROPOLITANA DE VANCOUVER
Bibliographic record
Abstract
This paper interprets the Metro Vancouver food localization movement, thorough the lens of the second generation of food sovereignty, with the objective of exploring its economic dimensions. First we promote a theoretical discussion of food sovereignty explaining that it started in a rural setting of the global south as a means to contest the international neoliberal trade system, and how it has adapted in the global north to incorporate consumers. We then discuss the contradictions between British Columbia’s and Metro Vancouver’s food systems. In sequence, we present the results from interviews of the movement’s stakeholders, offering a qualitative analysis. Our findings demonstrate that there are several economic consequences, identifying: i) farmer markets as currently the most significant channel for the commerce of local foods and how they have been responsible for (re)approximating food producers and consumers; also, ii) institutional markets as a next step that can represent a true democratization of good food.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.004 | 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".