Box-scheme as alternative food network—the economic integration between consumers and producers
Bibliographic record
Abstract
Abstract As a growing option for small farmers, alternative food networks (AFN) have attracted the attention of researchers around the world. Nevertheless, not much focus is given to box-schemes as a format itself. The nomenclature is often associated with community-supported agriculture (CSA) and solidarity purchase groups (SPG), but many companies have reduced geographic and informational distances without demanding such a narrow relationship between collaborators. The aim of this article is to analyze the relationship between companies and their customers. A theoretical framework was built based on thoughts about economic integration and the relationship in the retail environment to examine the possibility of reciprocity and redistribution. The fieldwork was conducted in São Paulo, Brazil. Technology is found to be fundamental to the rise of such companies, but the Internet is not the only key, the telephone is also important for a warmer and closer relationship. The interviews revealed different signals of reciprocity supporting a trusting relationship while the occasional buyers demonstrate more opportunistic behaviors. Of the cases studied, one successful company demonstrated signs of reciprocity between companies and customers, as well as customer integration based on redistribution characteristics. This confirmed the possibility of the box-scheme contributing to rural sustainability, related to customers who have built a broader perspective, going beyond price and quality. The article concludes defending that this format of commerce should be further studied to confirm its capacity to support rural development and continue to deepen the understanding of the conditions that can make it successful.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".