The Oil and Natural Gas Exploitation in Petrol Field of Urucu and Their Impacts on the Traditional Peoples of Amazon
Bibliographic record
Abstract
This study deals with an approach to the design of Petrobras oil and gas in Amazonas, Brazil, establishing an analytical cut on environmental issues and social issue that affects traditional peoples impacted by Coari / Manaus, located in the heart of the Amazon Brazilian. In 1986 was discovered the first commercial oil field and natural gas in urucu River, a tributary of the Solimoes basin in the Amazon, considered a watershed event in the history of Petrobras and the local development process. Since then, Petrobras built two underground to conduct gas to regional capitals pipelines. This research shows that large impacts hit the Amazon forest to logging of native trees without replacement and management with assault on rivers, lakes, streams and flooded areas. The pipeline that connected the town of urucu where Petrobras is installed to the city of Coari, county seat of oil and gas in the Amazon, dried three streams supplying water to fish and riparian communities. Added to this, the impact of social order that reached the lives of people with traditional land dispossession of local people, sexual exploitation among other social problems. It should be recognized, finally, that the development model implemented in the Brazilian Amazon has no way to thread the ethnic issue. Economic growth under the auspices of big business does not have to induce and basic environmental conservation and human development of traditional indigenous and non-indigenous peoples, from an ethic of social and environmentally sound development.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".