Bibliographic record
Abstract
In recent years, quinoa (traditionally grown in South America) has been imagined as a food crop that addresses the world’s most pressing problems: climate change, water scarcity, food insecurity, malnutrition, and economic inequality. Valued for being nutritionally exceptional and resistant to several agronomic stresses, quinoa has attracted the attention of consumers, researchers, and development agencies. This paper focuses on the World Quinoa Congress and other international gatherings of experts (plant scientists, quinoa farmers, social scientists, development practitioners, and entrepreneurs) who produce and share knowledge about quinoa’s cultivation, production, consumption, and diversification. I examine how various actors materialize quinoa through different ways of conceptualizing seeds, property, and knowledge. In some cases, quinoa is part of a larger socioecological system, while in others, seeds are disembedded from their geographical context and studied in terms of their efficiency and yields. I explore the convergence and divergence of knowledges that accompany quinoa’s globalization, shedding light on the frictions, conflicting priorities, opportunities, and questions that arise in spaces of knowledge creation and exchange.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".