Territorial Changes and Effects on the Health of the Populations Surrounding Case Study: Itaqui Port, Northeast of Brazil
Bibliographic record
Abstract
<p class="Nornaltexto">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.</p>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".