Avanços e limites das políticas de desenvolvimento urbano no Brasil (1988-2013)
Bibliographic record
Abstract
The urbanization process in Brazil advanced in a disorderly way, which resulted in a severe urban crisis in the last quarter of the last century.The urban problem has deteriorated from the economic crisis that occurred in the 1980s and was not resolved during the economic recovery of the 2000s.Many problems related to the process of urbanization still occur, with some differences depending on the size of cities, but also linked to the pattern of public policies adopted in the area of urban development.Since 1988, many institutional and regulatory frameworks have been defined for urban development.Also, the urban policy had a significant increase of the funds invested.However, these policies had not provided a consistent improvement of living conditions in cities.The aim of this study is analyze the trajectory of institutional evolution, the approval of regulatory frameworks and the main programs for areas of housing, sanitation and urban mobility.To this end, in addition to examining the official documents of the federal government about the guidelines of these programs, the study also includes an evaluation of the results obtained from the main indicators available.It is evident that the process of institutionalization and regulation of urban development policies were an important step forward, but not enough to modify the brazilian urban context.The urban problems linking up with imbalances in the brazilian capitalist development, that is characterized by deep social inequality, which reflects in the cities.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".