Bibliographic record
Abstract
Until 2019, Guatemala upheld a de-facto moratorium on GMOs. The ban has been attributed to broad-based social resistance and the unlikely alliances galvanized by the issue. Recent legislation, however, has been met with little resistance. In this paper, I show how the tensions between anti-GM actors and their interactions on the ground help to explain this turn of events in Guatemala, and—more broadly— contributes to our understanding of how biotechnology advances despite significant resistance. Drawing on interviews and ethnographic observation, I demonstrate how urban, professional class Ladinos who oppose GMOs draw on scientific and technical arguments divorced from broader political-economic critiques. Meanwhile, campesino and indigenous activists center their resistance within broader structures of oppression such as colonialism, racism, and capitalism. Specifically, I show how ‘biotechnologizing’ is employed in problematic ways, not only by pro-GMO coalitions—as other scholarship suggests—but also by anti-GM allies. This case contributes to our understanding of how anti-GMO movement frames get constructed in local contexts, and the tensions that arise between anti-GM groups, revealing significant impediments to creating a more just food future in Guatemala.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.030 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".