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A TEMÁTICA AMBIENTAL NO ENSINO SUPERIOR: UM ESTUDO SOBRE A UNIVERSIDADE FEDERAL DE RONDÔNIA, CÂMPUS DE PORTO VELHO

2018· article· pt· W2794077288 on OpenAlexaff
Clarides Henrich de Barba, Rosa Maria Feiteiro Cavalari

Bibliographic record

VenuePesquisa em Educação Ambiental · 2018
Typearticle
Languagept
FieldEnvironmental Science
TopicEnvironmental Sustainability and Education
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

<p>Este artigo analisa a inserção da temática ambiental na Universidade Federal de Rondônia (Unir),<em> campus</em> de Porto Velho. Caracteriza-se como estudo de caso, tendo como instrumentos de coleta de dados: a análise documental dos projetos pedagógicos e dos planos das disciplinas de 14 cursos de graduação que desenvolvem a temática ambiental, entrevistas semidiretivas com os coordenadores e professores. A “análise de conteúdo” proposta por Bardin e as características de <em>Ambientalização</em> curricular elaboradas pela Rede Aces foram utilizadas na análise dos dados. Os resultados demonstram que os cursos estão <em>ambientalizados</em> ou em processo de <em>Ambientalização </em>curricular, sobretudo<em> </em>os de Geografia e Ciências Biológicas. Identificaram-se seis características de um currículo <em>ambientalizado</em>: compromisso com a transformação das relações sociedade-natureza, complexidade, contextualização local-global-local global-local-global, levar em conta o sujeito na construção do conhecimento; considerar os aspectos cognitivos e afetivos, éticos e estéticos, espaços de reflexão e participação democrática, orientação prospectiva de cenários alternativos.</p><p><strong> </strong></p><p><strong>Palavras-chave</strong>: <em>Ambientalização</em> Curricular. Temática ambiental. Educação Ambiental.<em></em></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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.009

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 head0.008
GPT teacher head0.242
Teacher spread0.234 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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