Mirages or miracles? Lithium extraction and the just energy transition
Bibliographic record
Abstract
Achieving a 1.5 °C global temperature limit by 2050 has heightened the need for lithium extraction for energy storage. This is touted by governments and industry as essential to a clean, just energy transition. However, critiques reveal tensions between this ideal and the realities of lithium extraction, questioning whether it represents a continuation of extractive capitalism or a pathway to sustainable development grounded in social and environmental justice. Our critical review of the literature synthesizes lithium supply chain dynamics and interdisciplinary critiques of lithium extractivism. It exposes the contradictions and challenges in relying on lithium for climate solutions. Key issues include high water usage, toxic waste, CO₂ emissions, and deepening global inequalities along racial and class lines. We argue that meaningful reform requires both local engagement with affected communities, especially Indigenous groups, and robust state policies to democratize the extraction process.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.034 |
| Scholarly communication | 0.005 | 0.013 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".