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Record W4401596107 · doi:10.1080/14650045.2024.2385411

The ‘Green War’: Geopolitical Metabolism and Green Extractivisms

2024· article· en· W4401596107 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

VenueGeopolitics · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGeopoliticsFraming (construction)PoliticsDominance (genetics)Political sciencePolitical economySociologyLawGeographyBiologyArchaeology

Abstract

fetched live from OpenAlex

Through ‘green transitions’ and ‘climate action’, geopolitical actors seem to be vying for dominance based on justifications that articulate geopolitical, economic, and ecological concerns. This ‘Green War’ geopolitical framing advances and consolidates imperial power through policies seeking to promote and secure ‘low carbon technology’ and ‘critical minerals’ supply chains, intensifying what we see as a novel ‘geopolitical metabolism’. Whereas geopolitical metabolisms used to notably focus on controlling the flow of fossil fuels, there is a growing emphasis on the ‘green extractivisms’ that underpin ‘green transition’ initiatives. This Green War framing and accompanying geopolitical metabolism enable states and corporations to advance and consolidate imperial power by capturing and perverting a much-needed geo-politics, or ‘politics of the Earth’. As such, we challenge the Green War geopolitical framing as part of the crucial effort to articulate an alternative geo-politics that promotes peace while reducing and redistributing energetic and material flows.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.291
Teacher spread0.275 · 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