Produção agroecológica: estudo da produção de hortaliças orgânicas no município de Silvânia – GO
Bibliographic record
Abstract
The general objective of this research is to study the production of organic vegetables in the municipality of Silvânia, State of Goiás. For this, we searched, through literature review, studies conducted at local and national level in order to understand about agroecology and organic production, as well as to research the theoretical bases on family farming, a deeply debated concept in literature, and public policies for regional development and support and strengthening of this new social category against conventional food production., Even though family farming remained outside governmental agricultural projects and on the sidelines of public investment, throughout the process of implementing the agricultural technology package, came to be remembered only in the 1990s with the creation of the National Program for the Strengthening of Agriculture Family Farming (PRONAF - Programa Nacional Para o Fortalecimento da Agricultura Familiar). Family Farming adapted very well to the cultivation of organic vegetables, as it is an activity that involves the whole family, uses areas depreciated by large capital, exhibits low entropy production, uses natural practices to produce food in a healthy way, benefiting both the producer as well as the consumer and the environment. Family farming was organized into associations as a way of strengthening and claiming individual and collective improvements; therefore, these associations came together in the creation of a cooperative to enable the commercialization of production. For the collection of information, bibliographic surveys of related works carried out in the research region were accomplished, as well as researches developed at the national level, at the Silvânia Rural Producers’ Mixed Agricultural Cooperative (COOPERSIL - Cooperativa Agropecuária Mista dos Produtores Rurais de Silvânia), as well as testimonials from the people involved in the project and that played a prominent role, both among the producers and among the COOPERSIL board members. These statements were made whenever possible in the rural property where the researcher corroborates the information, besides recording the location of the research by means of photography. Understanding public policies for the promotion of food security as well as family farm food acquisition programs are thermometers for the viability of agroecology and organic production in small municipalities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.025 |
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; both teacher heads agree on what is shown here.
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".