Local gastronomy, transnational labour: Farm-to-table tourism and migrant agricultural workers in Niagara-on-the-Lake, Canada
Bibliographic record
Abstract
Each year, migrant workers from Mexico and the Caribbean travel to Canada via a bilateral agreements to provide labour essential to the agricultural sector. One destination for these workers is Niagara-on-the-Lake (NOTL), a microclimate in which labour intensive crops such as tender fruits and grapes are grown. These local crops form the basis of a significant gastrotourism industry. This industry turns on the narrative of an historical idyll in which producer and consumer share a close relationship, one manifested in the farm-to-table discourse that permeates NOTL. Yet agricultural production in the area is entirely dependent upon a globalized labour force, a dependence that is inconsistent with the narrative of locality. The structure of this transnational labour program and the requisite aesthetics of tourism in NOTL render migrant workers and their labour invisibility and this invisibility, in turn, exacerbates the precarity of transnational workers within global capitalism.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".