Ecolabeling as a Sustainability Strategy for Smallholder Farming? The Emergence of Participatory Certification Systems in Brazil
Bibliographic record
Abstract
This article explores the emergence of ecolabeling of organic products in the context of the contemporary debate on global risks related to food production and consumption, focusing in particular on the implications for smallholder farming in Brazil. Independent certification is sustained by technical and bureaucratic mechanisms, sanctioned by international organizations and multilateral agencies whose power structures encourage the production of rules and systems of enforcement. By contrast, local food movements and civil society initiatives point to the emergence of alternative, participatory forms of ecolabeling. These local organizations have come up with new ways of constructing collective quality seals and assurances for products. They have spurred debates on the technologies, power structures and risks associated with corporate agriculture, large-scale pesticide use and chemically grown produce. As an alternative, ecolabeling requires a multi-level articulation of smallholder farming, food cooperatives and farmer markets, in order to create a local certification system for eco-sustainable produce and maintain the sustainability of traditional modes of existence of small farmers. Grounded in a long-term ethnographic study among ecological family farming in the western region of Santa Catarina, Brazil, this paper examines ecolabeling legal frameworks both globally and locally. It highlights the complexity of the eco-labeling process in Brazil, a context where diverse farmers’ movements, non-governmental organizations and technical and State political actors grapple with questions relating to the social and economic values of sustainable organic agriculture. The data presented here is based on bibliographical, documental research and analysis of laws, decrees and norms. The study examines the recent historical process involving certification rules and regulations, especially those affecting agriculture. It also surveys the literature on the topic, bringing to light interpretive variations and other cases offering a contrast to Brazil’s experience.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".