Real Food, Real Facts: Processed Food and the Politics of Knowledge
Bibliographic record
Abstract
In recent decades, many members of the public have come to see processed food as a problem that needs to be solved by eating “real” food and reforming the food system. But for many food industry professionals, the problem is not processed food or the food system itself, but misperceptions and irrational fears caused by the public’s lack of scientific understanding. In her highly original book, Charlotte Biltekoff explores the role that science and scientific authority play in food industry responses to consumer concerns about what we eat and how it is made. As Biltekoff documents, industry efforts to correct public misperceptions through science-based education have consistently misunderstood the public’s concerns, which she argues are an expression of politics. This has entrenched “food scientism” in public discourse and seeded a form of antipolitics, with broad consequences. Real Food, Real Facts offers lessons that extend well beyond food choice and will appeal to readers interested in how everyday people come to accept or reject scientific authority in matters of personal health and well-being.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.023 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".