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Experiência de educação ambiental: resgate histórico da ocupação e análise espacial da Nova Santa Marta - Santa Maria - RS

2010· article· pt· W1569284649 on OpenAlexaboutno aff
Ines Weber, Luís Eduardo de Souza Robaina

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2010
Typearticle
Languagept
FieldEnvironmental Science
TopicEnvironmental Sustainability and Education
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesNova scotiaPolitical scienceGeographyArtArchaeology

Abstract

fetched live from OpenAlex

O presente trabalho objetivou resgatar histórica e culturalmente a região de Nova Santa Marta, apresentando noções de localização e definindo o meio geográfico onde vive a comunidade. Além disso, pretende-se fazer uma análise crítica das contínuas transformações do ambiente no decorrer do processo histórico da ocupação da região. Para efetivação das atividades, construiu-se um referencial teórico-prático em ação coletiva com uma turma de trinta e três alunos da Escola Marista Nova Santa Marta. O conhecimento geográfico, da espacialidade e orientação, intimamente vinculados com a questão ambiental, passou a ser abordado com uma visão sócio-cultural, levando o aluno à compreensão do seu papel na transformação da realidade.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.347

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0060.005
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.171
GPT teacher head0.526
Teacher spread0.355 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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