MétaCan
Menu
Back to cohort

Questions on gender and technology in the construction of agroecology

2017· article· pt· W2625550849 on OpenAlexaff
Márcia María Tait Lima, Vanessa Brito de Jesus

Bibliographic record

VenueScientiae Studia · 2017
Typearticle
Languagept
FieldEnvironmental Science
TopicRural Development and Agriculture
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHumanitiesPhilosophySociology

Abstract

fetched live from OpenAlex

O objetivo deste artigo é discutir o papel da mulher no desenvolvimento do pensamento agroecológico no Brasil, o qual se apresenta como uma proposta que alia ciência, tecnologia e movimento social, orientada por premissas éticas e epistemológicas, nas quais são centrais as características ambientais, a pluralidade cultural, o respeito aos diferentes povos, assim como a não exploração nas relações de trabalho e comercialização. Embora ele seja um pensamento progressista, ainda comporta reprodu- ção da desigualdade de gênero, o que tem aparecido em diversos debates dentro do próprio campesinato, nos ambientes de militância e acadêmicos brasileiros. A agroecologia e, de forma mais ampla, a agricultura familiar sempre tiveram a participação signifi cativa das mulheres. Porém, apenas há pouco mais de duas décadas o trabalho feminino na agricultura familiar e também na agroecologia tem sido desconsiderado proporcionalmente a sua real contribuição. Nesse sentido, discutiremos que não existe agroecologia sem feminismo, pois são mulheres que ocupam posições centrais e sustentam vários tipos de resistência ao modelo convencional de produção agrícola, com a organização de movimentos sociais agroecológicos e práticas associativas de produção. A relação aparentemente paradoxal entre as relevantes contribuições das mulheres e a negação das questões de gênero na agroecologia será discutida buscando estabelecer diálogos entre o pensamento agroecológico das mulheres e a perspectiva feminista

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.041
Scholarly communication0.0090.009
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.012
GPT teacher head0.246
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; 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 designQualitative
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

Citations6
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueScientiae StudiaSame topicRural Development and AgricultureFrench-language works237,207