Resistance to Fossil Fuel Extraction Projects in Africa as Climate Action
Bibliographic record
Abstract
Abstract Since the early 2000s, new oil and gas reserves have been found in numerous African countries, prompting calls to use these resources for economic development and structural transformation. Citizens and their governments have been sold visions of fantastic new wealth springing from fossil fuel extraction. In enthusiastically pursuing these projects, governments have ignored the cursed legacy of environmental destruction and underdevelopment associated with oil and gas in the continent’s two major producers, Angola and Nigeria. They have also ignored the risks associated with new oil and gas developments in the context of green energy transitions. New fossil fuel projects, even those far offshore, have brought significant conflict and opposition from civil society and especially from host communities. In most cases, resistance to fossil fuel extraction has been noninstitutional and rooted in concern over who benefits rather than concern over climate action. However, the environmental and social impacts from these projects have already impacted citizens in their everyday lives. Therefore, African organizations and activists have begun to sound alarm bells about climate change as well as the transition risks (stranded assets and fossil fuel lock-in) associated with global climate action.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".