The Extraction Unconscious: Solar-Powered Utopias in Catching the Sun (2015) and In the Name of Lithium (2021)
Bibliographic record
Abstract
By comparing the depictions of future energy regimes in the two ecodocumentaries, Catching the Sun (2015) and In the Name of Lithium (2021), this article explores representations of post-carbon futures from the US and Argentina. Read closely alongside Frederic Jameson’s notions of utopias, the article delineates the extent to which a solar powered future challenges and reiterates current neocolonial extractivist structures. Basing myself on Patricia Yaeger’s concept of an “energy unconscious,” I argue that these solar utopias maintain an “extraction unconscious” that continues to produce sacrifice zones where primary commodities needed for the energy transition can be found. By analysing closely the representations of energy and the cinematic technique of montage, the article demonstrates how the energy used in the creation of these utopias can itself invite new postextractivist imaginations.
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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 | 0.006 | 0.023 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".