Socioeconomic Characteristics and the Impacts of Land Use Changes to Sugar Cane in Quirinópolis, Brazil
Bibliographic record
Abstract
The socioeconomic impacts arising from the change in the traditional productive systems for sugar cane have caused weightings. This article proposes to investigate the socioeconomic characteristics and impacts of the use of the land with cane field, by using municipal indicators and agricultural establishments of Quirinópolis. The field survey used margin of sampling error of 5% and a confidence level of 95%, sampling 58 establishments and aiming to analyze their characteristics and impacts in function of this change by means of socioeconomic indices proposed, statistical tests and correlations. We used the survey methodology applying inferential statistical techniques, cluster analysis, Spearman correlation tests of normality (Kolmogorov-Smirnov and Shapiro-Wilk) and hypothesis tests (Wilcoxon Test). The analysis of the socioeconomic indices approached two perspectives. In the Municipal Prospect, found that the indexes: IFDM-2005 [0.6713], IFDM-2016 [0.8387] and IFDM-V [0.1996]. The indices show the range of a high municipal development. In the analysis of agricultural establishments, the indices assessed the following values: rural exodus [-0.09], succession [1.44], association [3.75], rural heritage [-0.44 and -0.04] and overall remuneration [0.57]. About land use change, it was detected that occurred mostly in pastures converted to sugar cane; there is a correlation between the indices that the Wilcoxon tests confirmed the statistical significance at the level of 5% (p-value). It is concluded that the socioeconomic impacts promoted from change in land use of traditional productive systems for sugar cane were overwhelmingly positive and promoted the development in a view of municipal and agricultural establishments in the period studied.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".