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Record W4280563188 · doi:10.1177/10704965221090602

Making Sustainable Palm Oil? Developmentalist And Environmental Assemblages In The Brazilian Amazon

2022· article· en· W4280563188 on OpenAlexaff
Diana Córdoba, Renata Moreno, Daniel Araújo Sombra Soares

Bibliographic record

VenueThe Journal of Environment & Development · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsQueen's University
FundersSocial Science Research Council
KeywordsVisionAmazon rainforestSustainabilityEcological modernizationEnvironmental crisisZoningPalm oilSustainable developmentAssemblage (archaeology)State (computer science)Political scienceSociologyEnvironmental ethicsGeographyEcologyLaw

Abstract

fetched live from OpenAlex

The question of how to generate development while preserving the environment is central to the history of the Brazilian Amazon. Many decades of top-down state interventions conceived and executed under a developmentalist framework have resulted in a socioenvironmental crisis. In response, the Sustainable Oil Palm Production Program (SPOPP) was launched in 2010. It promised to break with developmentalist visions and articulate environmental and sustainability concerns. This paper uses assemblage thinking to examine how these contrasting, often impossible-to-balance, views manifest within SPOPP implementation. We describe how non-human actors (trees, diseases, previous policies and agroecological zoning technologies) interact with human actors. However, powerful actors, in the state and beyond, continue to garner support for their developmentalist interests and thwart or depoliticize environmental and social concerns, thus limiting change.

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)0.003
metaresearch head score (Gemma)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.011
Scholarly communication0.0050.003
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.197
Teacher spread0.184 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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