Political power and renewable energy futures: A critical review
Bibliographic record
Abstract
Inspired by the energy democracy movement, this conceptual review critically explores relationships between concentrated or distributed renewable energy and political power. Advocates assert that because the renewable energy transition is fundamentally a political struggle, efforts to shift from fossil fuels and decarbonize societies will not prove effective without confronting and destabilizing dominant systems of energy power. The objectives of this paper include: 1) theorizing and exploring the relationships between renewable energy and political power, 2) critically assessing tensions associated with an energy democracy agenda, and 3) drawing out the implications for democratizing renewable energy development in practice. Distributed energy-politics posits that distributed energy sources and technologies enable and organize distributed political power and vice versa. Efforts are underway to find ways to re-organize distributed energy flows into aggregated and concentrated stocks of energy and other forms of political power. More democratic renewable energy futures may benefit from strengthening democratic practices and outcomes, extending democratization of energy systems across all components, stages and end uses, and sharpening positions relative to dominant pressures of capitalism and market ideology, the ideology of unlimited growth, and the modernist/industrialist agenda. Renewable energy systems offer a possibility but not a certainty for more democratic energy futures.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".