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Record W2598184979 · doi:10.5539/jsd.v10n2p249

Social and Environmental Impacts on Rural Communities Residing Near the Industrial Complex of Sao Luis Island, State of Maranhão, Brazil

2017· article· en· W2598184979 on OpenAlexvenueno aff
Tatiana Cristina Santos de Castro, Antônio Carlos Leal de Castro, Leonardo Silva Soares, Marcelo Henrique Lopes Silva, Helen Roberta Silva Ferreira, James Werllen de Jesus Azevedo, Victor Lamarão de França

Bibliographic record

VenueJournal of Sustainable Development · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicGeography and Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyHarmMangrovePopulationEnvironmental protectionNatural (archaeology)Natural resourceSocioeconomicsForestryEcologyArchaeologyDemographyPolitical science

Abstract

fetched live from OpenAlex

The aim of the present study was to analyze the major social and environmental implications of the presence of the industrial district of the city of São Luís (Brazil) over a span of 30 years. The district was established in the 1980s to receive industrial enterprises of the Grande Carajás Program, which led to the installation of a massive support infrastructure. Industrial activities have contributed substantially to rapid, definitive, irreversible changes to the way of life of the population residing near the district and have gradually altered the spatial organization of the area, with consequent harm to the natural landscape. Both the perceptions of the local population and data obtained using geotechnological tools offer evidence of the main changes having occurred and factors associated with such changes. Mangrove degradation and the loss of both natural and secondary vegetal cover were the most significant changes in the time interval studied. The main factors associated with environmental harm are industrial activities, the mineral extraction of sand and disorganized land occupation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.028
GPT teacher head0.243
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2017
Admission routes1
Has abstractyes

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