Bibliographic record
Abstract
Vía Campesina (“Peasant Road”) is a transnational social movement, founded in 1993, that links over 100 organizations of “peasants, small– and medium‐sized agricultural producers, landless, rural women, indigenous people, rural youth and agricultural workers” ( www.viacampesina.org ), in almost 60 countries in the Americas, Europe, Asia, and Africa. The membership is diverse and includes landless peasants in Brazil, small dairy farmers in Europe, well‐off farmers in South India, wheat producers in Canada, and land‐poor peasants in Mexico. The main issues of concern to Vía Campesina (always referred to by its Spanish name) include global trade rules, intellectual property and genetically modified organisms, the survival of family farms, sustainable alternatives to corporate‐controlled industrial agriculture, agrarian reform, the human rights of peasant activists, and “food sovereignty,” which it defines as the right to protect national production and to shield domestic markets from the dumping of low‐priced agricultural imports. Vía Campesina and its component subnational, national, and regional organizations have participated in numerous militant and theatrical protest actions against the World Trade Organization (WTO), the World Bank, and International Monetary Fund (IMF), G8 summit meetings, and large agribusiness corporations such as Monsanto, Cargill, and Syngenta. The movement has also been a prominent participant in global civil society gatherings, such as the World Social Forums.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.033 | 0.002 |
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".