"Cities in the forest" and "cities of the forest": an environmental Kuznets curve (EKC) spatial approach to analyzing the urbanization-deforestation relationship in a Brazilian Amazon state
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Bibliographic record
Abstract
Contemporary urbanization has been reorganizing the territories and the socioeconomic relations in the Brazilian Amazon as a whole. We seek to identify a general typology of relationships between urbanization and deforestation in the Brazilian Amazon, in the light of the environmental Kuznets curve (EKC) theory. We have applied this approach to the 144 municipalities of Pará, in the Brazilian Amazon, in the inter-census interval from 2000 to 2010. The EKC approach included the spatial analysis method of geographically weighted regressions (GWR). Deforestation, measured by the PRODES program by Instituto Nacional de Pesquisas Espaciais (INPE), was used as a measure of environmental degradation and the urbanization has been restricted to a socioeconomic characterizing, based on a set of 22 variables from the national census database, aggregated at the municipalities level. The results showed two main typologies: (1) the decreasing monotonic and (2)
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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