A dispute for land and gold: The State between a Canadian mining company and a small scale mining cooperative in Amazon – Brazil
Bibliographic record
Abstract
"The history of mining in Latin America is marked by conflicts between large companies and the local population of the areas where mineral resources are found. The aim of this study is to analyse the conflict between a small-scale mining cooperative and the Canadian company Belo Sun Mining Inc. The framework of this research is the Latin America political ecology and the ethnography of social and environmental conflicts as a theoretic and methodological guide. The conflict will be analysed using a theoretical framework of political ecology in Latin America The cooperative and the company are involved in a dispute over gold mining in the area of the “Big Bend” of Xingu River, or Volta Grande do Xingu, in the Amazon, Brazil. The region is known as “Stretch of Reduced Instream Flow”, since the dam for the Belo Monte Hydroelectric Plant was built, around 13 Km upstream from where the small scale mining families have been living since 1940’s. The synergetic impacts of the Belo Monte Dam and the Belo Sun Mining on the livelihood of the local communities are very large. The research question is how did the government of Pará shut down the activities of the small-scale mining cooperative, but gave Preliminary License for gold exploitation to a Canadian mining company. The results showed how companies and some sectors of the government used tricks to approve licenses, despite them going against the Brazilian Law. Some clashes surrounding the process of environmental licensing of Belo Sun Mining Inc. have brought into discussion the high risks for the environment and the disregard" for the small-scale mining rights. Moreover, accusations of land grabbing weigh heavily on the company.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".