A água e a gestão metropolitana em Vancouver: eficácia e eqüidade
Bibliographic record
Abstract
O artigo apresenta uma caracterização do sistema de gestão metropolitana de Vancouver, província de British Columbia, na costa oeste do Canadá, enfocando, entre outros aspectos, como têm sido tratados os conflitos entre a dinâmica urbana e a proteção das áreas de mananciais de água para abastecimento. São apresentadas informações coletadas em pesquisa realizada na região, em julho de 2002, quando foram entrevista¬dos diversos dirigentes, técnicos e pesquisadores e promovidas visitas de campo. Destacam-se aspectos — tanto operacionais quanto de natureza da organização política e administrativa e das estratégias adotadas — para comparação com a situação de gestão de mananciais em âreas metropolita¬nas no Brasil, particularmente na recém-criada Região Metropolitana de Campinas, no Estado de São Paulo.Abstract: This article presents a characterization of management and governance metropolitan system of the Greater Vancouver, in British Columbia, Western coast of Canada. We focus, among other issues, on how conflicts between urban growth and protection of strategic watersheds for drinking water have been focused. The upon information presented was collected during a research undertaken in July, 2002, when several managers, technicians and researchers were interviewed. Some aspects related to technical operation, political strategies and management are underlined, by comparison with the Brazilian watershed management in metropolitan areas, such as the recently institutionalized Metropolitan region of Campinas, in São Paulo State.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".