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Record W4404466155 · doi:10.56579/rei.v6i4.1288

CORRENTES E ESTILOS DE AGRICULTURA DE BASE ECOLÓGICA NO BRASIL

2024· article· pt· W4404466155 on OpenAlexaff
Márcio Harrison dos Santos Ferreira, Adriana Ferreira Nascimento, Jackson Paulo Silva Souza, Cristiane Moraes Marinho, Hélder Ribeiro Freitas

Bibliographic record

VenueRevista de Estudos Interdisciplinares · 2024
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

O presente trabalho analisa as correntes e estilos de Agricultura de Base Ecológica no Brasil, investigando suas origens, contextos, sujeitos e organizações envolvidas. Objetiva compreender como essas práticas sustentáveis estão sendo implementadas no país e identificar os desafios enfrentados por movimentos sociais, instituições e sujeitos na promoção desses estilos de agricultura. A metodologia utilizada foi o Mapeamento Sistemático da Literatura nas bases de dados Google Scholar, Portal de Periódicos da CAPES, Scielo e Redalyc. Foram triadas publicações entre 1992 e 2023, utilizando-se a string de busca “agricultura alternativa” AND “agricultura de base ecológica” AND “Brasil”; e seus equivalentes em inglês e espanhol. A partir dessa triagem, efetivou-se uma busca ativa pelos descritores: “agricultura orgânica”, “agricultura ecológica”, “permacultura”, “agricultura biodinâmica” e “agricultura natural”, com a seleção de 30 publicações relevantes para análise. Os resultados apontam para a diversidade de correntes de Agricultura de Base Ecológica no Brasil, cada uma com suas particularidades e contribuições para a sustentabilidade da agricultura no país. Destaca-se o papel fundamental dos movimentos sociais, da educação popular e da agroecologia na promoção dessas práticas e a necessidade de construção de processos organizativos e tecnologias apropriadas para uma maior difusão desses estilos de agricultura em todo o país.

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), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.728
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.018
GPT teacher head0.272
Teacher spread0.255 · 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
Published2024
Admission routes1
Has abstractyes

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