Do outro lado da rua: riscos associados ao uso do território e bem-estar social de moradores em função da mineração em Paracatu-MG.
Bibliographic record
Abstract
This research was done in the city of Paracatu, northwest of Minas Gerais-Brazil. Paracatu has the biggest open-pit gold mine in the world, that is operated by a Canadian mining company. We approached the social and environmental risks coming from the large mining ventures associated to the used territory, and its effects on the welfare and life quality of its residents. Also, the implications of socio-environmental risks, specifically health risks and their changes in the health-disease process of the exposed population, especially those living in neighbourhoods close to the areas of operation of the mineral extraction activity. The study of the effects of the mining industry was motivated by the coexistence between spaces for housing and the presence of two large tailings dams and the proximity of the neighborhoods to the company's mining area.The research goal was to respond, systemically, on the social risks coming from the way that the appropriation of the territory has been done and the choice for large enterprises, as well as the consequent weakening of the residents' welfare, basing our reflections on the case of exploitation of gold in that city. The empirical field for the study, in the quantitative and qualitative method, was formed by the two neighbourhoods near the mining area, besides the focus on their residents, the key informants of civil entities, government agencies, and the company. The methodological instruments were the bibliographical research, as well as the collection, systematization, and analysis of secondary and primary data, through the methodological application of semi-structured interview scripts and pre-established questionnaires. As a result, among other aspects, it was concluded that events of the size of the mining company installed in the city and the level of exploitation of mineral goods, in this case, gold, will necessarily be marked by interest conflicts between the company's objective and living conditions of the residents. For the realization of major projects there is always the construction of a speech that transmits the safety condition in the ventures. However, what is noticed is that the installation of that type of work ends up exposing residents and workers to conditions of social vulnerability. The exploitation of goods will produce negative social and environmental impacts generated by the economic activity. In the present case, it was found that the health conditions and the health-disease process of some residents, may have a relationship with the mining practices. The territory used dynamics is altered by the processes imposed by the economic activity and the production of risks to the local population welfare and life quality, making it urgent to implement powerful public policies to deal with the impacts generated on the alive system.
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How this classification was reachedexpand
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) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".