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Record W2064942333 · doi:10.17271/23188472132013458

IMPACTOS SOCIOAMBIENTAIS DECORRENTES DAS ATIVIDADES TURÍSTICAS NO MUNICÍPIO DE RIO QUENTE (GO)

2013· article· pt· W2064942333 on OpenAlexaff
Roberta Vieira de Oliveira Ramos, Idelvone Mendes Ferreira

Bibliographic record

VenueRevista Nacional de Gerenciamento de Cidades · 2013
Typearticle
Languagept
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesPolitical scienceGeographyArt

Abstract

fetched live from OpenAlex

Resumo: Na atualidade, no processo de desenvolvimento das atividades socioeconômicas, o setor do turismo é um dos que mais tem crescido nos últimos anos e está ligado diretamente às questões ambientais e sociais, sendo capaz de expor nosso patrimônio natural e cultural, onde a natureza é vista como sendo um produto a ser vendido. O presente estudo visa analisar os impactos socioambientais e econômicos decorrentes das atividades do turismo nas estâncias termais e suas percussões no desenvolvimento local e regional, enfocando os elementos que caracterizam um turismo planejado. As ações decorrentes dessas atividades turísticas têm causados impactos ambientais e sociais, tanto negativos quanto positivos, para o município de Rio Quente (GO) e para a região, sendo o foco desta pesquisa a análise dos impactos socioambientais negativos, uma vez que são mais impactantes e perniciosos para a sociedade. Palavras- chave: Turismo. Impactos socioambientais. Rio Quente (GO).

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)0.001
metaresearch head score (Gemma)0.002
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 score0.144
Threshold uncertainty score0.287

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.036
GPT teacher head0.360
Teacher spread0.325 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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