‘Nature’ is Not Guilty: Foodborne Illness and the Industrial Bagged Salad
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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 of Escherichia coli O157:H7, how E. coli O157: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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it