Lithium dreams, local struggles: Navigating the geopolitics and socio-ecological costs of a low-carbon future
Bibliographic record
Abstract
The global push towards renewable energy has surged the demand for lithium, which is vital for manufacturing batteries that power electric vehicles and stabilize energy grids. This literature review examines global lithium extraction's environmental and socio-political costs to highlight the tensions between sustainable development and extractive practices in the lithium industry. A comprehensive subset of scholarship reports the degradation of ecosystems, the commodification of Indigenous lands, and the erosion of biodiversity. Scholars have attributed lithium's socio-ecological cost to green extractivism, where the green agenda promotes extractive practices reminiscent of the fossil fuel era. A second strain of literature delves into how lithium is discursively framed and legitimized through ‘sociotechnical imaginaries’ (STI). Those imaginaries embody how societies collectively envision lithium's role in shaping future socio-political and economic structures, particularly regarding national identity, sovereignty, and sustainable progress. Additionally, these imaginaries highlight the tensions between local communities, national governments, and global stakeholders over extraction's socio-environmental costs. Finally, studies also discuss the geopolitical dimensions of lithium supply chains, particularly the tensions between China and Western economies over control of critical minerals—the fight for geopolitical dominance perpetuates colonial dynamics by both stakeholders. The findings underscore the need for more sustainable extraction policies and equitable governance mechanisms that account for the socio-environmental challenges posed by lithium mining in the context of global climate goals.
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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 | 0.007 | 0.014 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".