Two visions of climate colonialism in African gas producers: Europe’s demand for LNG and the danger of stranded assets
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".