Sustainability in Soybean Production from the Perspective of the Producers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study aims to analyze the sustainability in the context of soybean cultivation by the cultivators’ perspective. The research is descriptive, with quantitative evidences operationalized through the application of questionnaires to a sample of soybean producers in the state of Rio Grande do Sul/Brazil. It was executed descriptive analysis of the profiles of the soybean farmers and the properties and technical-agronomic aspects profiles, then subsequently, a correlation analysis between variables from the producers and properties profiles with the environmental, social and economic of sustainability dimension. By the result of the research, it was observed that the majority of soybean producers have been doing this work for 30 years, with low schooling. In addition, regarding the structure of the properties, the area intended for soybeans varies in the sample from 5 to 2,300 hectares, with 25.1% of producers allocating more than 296 hectares for this cultivation. In the production process, it was noticed that most producers use different inputs, such as herbicides, insecticides, fungicides and fertilizers, besides the care with the soil through the use of no-tillage system and search from crop diversification. In producers’ perspective of the sustainability, it is identified some significant associations between certain producers’ profiles and property variables with environmental, economic and social topics. However, the evidences, it is suggested a wariness from these analyses, since there is a disagreement in the literature on sustainability in agricultural activities, such as soybeans, because of the complexity of assessing the performance of farmer perception and sustainability indicators.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it