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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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