Illicit food: Canadian food safety regulation and informal food economy
Bibliographic record
Abstract
Food economies that take place informally or ‘under the table’ can offer interesting insights into relationships that people have with their food, and with social and institutional frameworks that shape their food systems. Relying on data from 14 in-depth interviews conducted in Nova Scotia in 2013, this paper interrogates the tensions between everyday eating practices and food safety regulations. Specifically, I examine how informal economic activities related to food expose some of the (perceived) shortcomings of those regulations. The stories that the participants shared offer a glimpse into the world of meaning attached to a range of practices that exist on the margins of contemporary food and public health systems. These stories and the associated practices challenge current regulatory policies as scale-inappropriate, and criticize the industrial food system as inadequate for meeting the needs of contemporary eaters. My analysis offers a cultural studies perspective on food safety regulation and on ideological resistance embedded in informal food economies. I illustrate this with a specific example of raw milk to further probe how people engage with their food and how they navigate through the world of food safety – and more generally public health – regulations.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| 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".