Agribiopolitics: The health of plants and humans in the age of monocrops
Bibliographic record
Abstract
The well-known story of biopolitics tells us that as Europe urbanized, security was increasingly linked to human well-being. What the story tends to leave out is the way that biopolitics also depended on the expansion of monocrop agriculture: the thriving of human populations was enabled by the thriving of non-human food crops, especially grains. As a result, new human diseases were also shadowed by new plant diseases, and a whole other, parallel governmental apparatus built to manage the crop health in rural Europe. During the great postwar development initiative known as the Green Revolution, plant health techniques would be expanded to the Global South in a massive realignment of biopolitical relations. Though the core tradition of biopolitical thought rarely made it explicit, biopolitics was always, in other words, agribiopolitics, a political technique that made certain populations of humans thrive alongside companion crops. Using Paraguay as a site of genealogical engagement, this paper explores agribiopolitical relations through three phases of the Green Revolution, culminating in the current age of monocrops.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.018 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".