Bibliographic record
Abstract
Pyrrhic Progress analyses over half a century of antibiotic use, regulation, and resistance in US and British food production. Mass-introduced after 1945, antibiotics helped revolutionize post-war agriculture. Food producers used antibiotics to prevent and treat disease, protect plants, preserve food, and promote animals’ growth. Many soon became dependent on routine antibiotic use to sustain and increase production. The resulting growth of antibiotic infrastructures came at a price. Critics blamed antibiotics for leaving dangerous residues in food, enabling bad animal welfare, and selecting for antimicrobial resistance (AMR) in bacteria, which could no longer be treated with antibiotics. Pyrrhic Progress reconstructs the complicated negotiations that accompanied this process of risk prioritization between consumers, farmers, and regulators on both sides of the Atlantic. Unsurprisingly, solutions differed: while Europeans implemented precautionary antibiotic restrictions to curb AMR, consumer concerns and cost-benefit assessments made US regulators focus on curbing drug residues in food. The result was a growing divergence of antibiotic stewardship and a rise of AMR. Kirchhelle’s comprehensive analysis of evolving non-human antibiotic use and the historical complexities of antibiotic stewardship provides important insights for current debates on the global burden of AMR.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.182 | 0.119 |
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".