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Record W4412423630 · doi:10.1080/09692290.2025.2532617

Two visions of climate colonialism in African gas producers: Europe’s demand for LNG and the danger of stranded assets

2025· article· en· W4412423630 on OpenAlexaff
Jesse Salah Ovadia

Bibliographic record

VenueReview of International Political Economy · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsVisionColonialismClimate changeNatural resource economicsBusinessEconomyEconomicsInternational tradePolitical scienceEcologySociologyBiologyLaw

Abstract

fetched live from OpenAlex

Wealthy countries and capital markets have moved to end support of new fossil fuel projects in the Global South, while simultaneously encouraging the export of African liquid natural gas (LNG) to meet Europe’s short-term need. While some have suggested denying African states the opportunity to exploit gas is a form of climate colonialism, I demonstrate that a more insidious expression of climate colonialism would be to replicate colonial and neo-colonial patterns of enclave extraction that direct new infrastructure spending toward facilitating the export of raw materials. Using a model of global LNG demand combined with a deeper dive into the case of Mozambique that was created for the African Climate Foundation (ACF), I explore the financial risks for African LNG projects and examine the financial outcomes at the project level for LNG assets across Africa. Connecting the risk of stranded assets to debates around resource-based development, structural transformation, and climate colonialism, I argue that while the conditions for gas investment seem favorable in the short- and medium-terms, new LNG projects promoted by Europe since 2022 involve considerable risk of stranded assets, lost opportunities, and underdevelopment for African nations in the long-term.

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 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: none
Teacher disagreement score0.830
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 spread0.273 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2025
Admission routes1
Has abstractyes

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