BEANS BEFORE THE LAW: Knowledge Practices, Responsibility, and the Paraguayan Soy Boom
Bibliographic record
Abstract
This article provides an ethnographic response to the statement that soy kills (“la soja mata”), a refrain often repeated by campesino activists living on the edge of Paraguay's rapidly expanding soybean frontier. In the context of Paraguay's modernization projects since the 1960s, statements like these were easily disqualified as irrational or nonmodern. In the process, the political importance and analytic potential of the beans were dismissed, and so, too, were the lives and analyses of rural activists. And yet the activists with whom I worked managed, over the course of five years of court battles, to bring killer beans before the courts and to have them recognized as a force in Paraguayan politics. In so doing, they also opened up an analytic position for ethnography, allied with Isabelle Stengers's cosmopolitics, which emerges from a situation of mutually enacting responses, rather than as a mediator of relationships between beings included or excluded from the political territory by the criteria of modernity. [legal activism, response, responsibility, knowledge practices, modernity, human–plant relations, frontiers, agrarian transitions, rural politics]
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.027 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".