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Record W4313682850 · doi:10.19088/1968-2023.107

Environmental Policy Reform and Water Grabbing in an Agricultural Frontier in the Brazilian Cerrado

2023· article· en· W4313682850 on OpenAlexaff
Andréa Leme da Silva, Ludivine Eloy, Karla Rosane Aguiar Oliveira, Osmar Coelho Filho, Marcos Rogério Beltrão dos Santos

Bibliographic record

VenueIDS Bulletin · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLand grabbingAgricultureAppropriationDeforestation (computer science)Natural resource economicsWater resourcesGrassrootsGeographyWater resource managementEnvironmental protectionEnvironmental sciencePolitical scienceEconomicsEcologyPolitics

Abstract

fetched live from OpenAlex

The spread of soy monoculture in the Brazilian Cerrado relies on land and water grabbing, although water appropriation is a least studied issue in the current literature. A mixed-methods approach was used to study changes in water use in western Bahia and the evolution of water and environmental standards over the last 20 years. The results show that the deregulation of environmental laws by the Bahia state Institute for the Environment and Water Resources (Instituto do Meio Ambiente e Recursos Hidricos, INEMA) has facilitated deforestation and water grabbing for large-scale irrigation by industrial agriculture. The social dynamics of struggles and resistance to this process was also analysed. The results show that water appropriation in the neoliberal agricultural frontiers of the Cerrado has changed not only water use and flows but also water governance systems, flows of power, and the representations that underpin them.

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 score0.108
Threshold uncertainty score0.214

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 studies0.0020.003
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.199
Teacher spread0.189 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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