Relations and Influences in the Process of Conventionalization of Organic Markets in the Southern Region of Brazil: A Multilevel Perspective Analysis
Bibliographic record
Abstract
The organic markets from all around the world are changing fast. An example is the proliferation of standards and the entrance of new actors in the organic market, as the processors. In this paper, organic farmers, agro industries, retailers, consumers, and rural extension agents were consulted through qualitative research methods to better understand these changes and to assess the conventionalization-bifurcation process of organic markets in the Southern Region of Brazil. The relations and influences that exist between these actors were identified and analyzed. The theoretical approach used in this study comes from the Multilevel Perspective. This approach sustains that a novelty, like organic farming, can produce radical or incremental changes in a socio-technical regime, as the dominant agro-food regime, while connections between both are built. We observed that these relations and influences are of three main types: outsourcing and elongation of supply chains; restrictions in the commercialization of the farmer’s production; and the consequences, adjustments and commercial conditions established through contracts with retail chains besides commercialization in alternative networks. Through these findings, we identified a bifurcation in the organic markets where some actors demonstrate practices similar to agrifood dominant regime. In this process, the regime is changing, but so are the alternative networks. It indicates that once again the alternative agriculture is capable of reaffirmation by some ways.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".