‘Nature’ is Not Guilty: Foodborne Illness and the Industrial Bagged Salad
Bibliographic record
Abstract
Abstract Increasing incidents of widespread foodborne illness continue to highlight problems with industrialised food production. These problems emerge as a result of complicated interactions between humans and non‐humans in food production networks. This article combines actor‐network theory and political economy to critically examine foodborne illness, focusing on outbreaks related to industrially produced bagged salads from California. The article explores the evolution of the bagged salad, the emergence ofEscherichia coliO157:H7, howE. coliO157:H7 enters the salad production network and the responses of industrial actors. While many continue to blame external nature for foodborne illness, doing so overlooks the fact that outbreaks are co‐produced by humans and non‐humans. Profit‐driven industrial production designs play an important role in the emergence and spread of pathogens. While efforts to address outbreaks focus on controlling non‐humans and adopting new technological fixes, effectively minimising foodborne illness may require a reevaluation of high‐volume and centralised production systems.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".