Territorial Changes and Effects on the Health of the Populations Surrounding Case Study: Itaqui Port, Northeast of Brazil
Bibliographic record
Abstract
This study addresses the territorial changes and health conditions of populations living in the area affected by the Porto do Itaqui Thermal Power Plant (TPP), specifically the Vila Maranhão, Cajueiro, Camboa dos Frades, Nova Camboa dos Frades and São Benedito communities located in the municipality of São Luís – MA, Brazil. The data consisted of 191 interviews that were conducted from January to October 2013. The results showed that the individuals from these communities had a low educational level, with most having attended school only up to the elementary level, which contributes to a high rate of unemployment or of individuals surviving on temporary jobs. The communities’ environmental awareness indicated that the main difficulties were associated with the lack of public policies, particularly regarding roads, garbage collection, low sanitation coverage, increased violence, unemployment, and informal employment. Regarding air quality, the results showed that the air pollutant concentrations still met the established limits, although the Camboa dos Frades community showed greater health problems due to a direct influence of pollutants. The reconfiguration of land use and land cover caused changes in the organization of the communities and the environment, reflected by the predominance of semi-urbanized areas and changes in the flows of small bodies of water caused by siltation from erosion. The identification of health conditions and the changes occurring in the communities affected by projects such as the TPP is important; therefore, public policies for urban mobility, spatial planning, health, education and urban safety should be proposed for such communities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".