Agricultura urbana e periurbana: análise de suas particularidades em Regente Feijó/SP e em Centre Wellington/ON – Canadá
Bibliographic record
Abstract
Urban and peri-urban agriculture (UPA) is a type of agricultural production that takes place within cities and in their surroundings. Its recognized benefits, which encompass the social, environmental and economic spheres, have made this practice increasingly popular in several countries. The objective of this article is to understand the particularities of the UPA practiced in Regente Feijó, a municipality located in the interior of the Brazilian State of São Paulo, and Centre Wellington, located in the province of Ontario, in Canada; analyzing how this type of agriculture can contribute to the improvement of food security and the local food supply of both landscapes, and contributing to the dissemination of knowledge about UPA and the elaboration and implementation of public policies that stimulate and support its development. The primary data presented in this paper were collected mainly through interviews with urban and peri-urban farmers and other key people of UPA in both municipalities. The results revealed that, despite the UPA practices of researched municipalities being different in some aspects, such as the purpose of the productions - predominantly aimed at self-consumption in Regente Feijó and at commercialization in Centre Wellington - they contribute significantly to the improvement of food security and for local food supply in both locations. In addition, it was found that, both in the area studied in Brazil and in the area examined in Canada, UPA does not receive adequate government support, which is one of the main challenges to its development.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".