Cluster Analysis Referring to Rural Enterprises of Sugarcane Local Productive Arrangement (LPA) in Quirinópolis, Brazil
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
In Brazil in recent decades, the the dynamics of land use widened the agricultural frontier for sugarcane cultivation by modifying and replacing intensively traditional and pasture crops. It is proposed to examine the aggregating characteristics of rural enterprises that are part of the sugarcane agribusiness productive arrangement, evaluating their profiles, providing a more effective understanding of their socioeconomic sustainability. The quantitative approach was adopted applying statistical tests for variable selection and multivariate statistical techniques (cluster analysis) to evaluate rural enterprises. The results indicated two clusters with peculiar profiles, and the average distance between farm and agribusiness (± 22 km) and succession capacity (± 2.5 points) of both are similar. The other variables were discrepant (P <0.05), in cluster 1 the very negative rural exodus (-48%) and in cluster 2 positive (23%). Operating costs in relation to compensation for Cluster 1 was 61%, much higher than cluster 2 with 6% on average. It was concluded that through cluster analysis that the contract variables and the size of the establishment are the most significant factors directly influencing the rural exodus and production costs. These observations contribute to the creation of sectorial policies for the use of land and regional economic development, as such imply in a theoretical consolidation of precepts on the sugarcane expansion, as such also imply, under the perspective of the rural practice, in elements for the improvement in planning the agricultural enterprise.
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 | 0.000 | 0.000 |
| 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) | 0.001 | 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