From Carbon Democracy to Carbon Rebellion: Countering Petro-Hegemony on the Frontlines of Climate Justice
Bibliographic record
Abstract
This essay combines salient instances of climate justice activism in key battlegrounds against the fossil fuel industry in the United States and Canada with theoretical interventions in studies of corporate power, grassroots democracy, and counter hegemony. It explores Timothy Mitchell's Carbon Democracy and the term’s relevance to understanding the conditions in which climate justice activists must combat the entrenched interests of fossil fuel companies. It suggests that Carbon Democracy is a helpful concept for understanding how fossil fuel dependency both shapes and distorts democratic governance. Drawing upon insights in three case studies - activism against Chevron in Richmond California, the Water Protectors and the Dakota Access Pipeline at Standing Rock, and the First Nations-led fight against the Trans Mountain Pipeline in British Columbia - the essay supplements Carbon Democracy with two more terms: Petro-Hegemony and Carbon Rebellion. These reveal three power relations, namely consent, compliance, and coercion, upon which fossil fuel companies depend and in which climate justice activists must strategically intervene to move beyond conditions of Carbon Democracy. I show that dual power is a logic of strategic intervention that climate justice activists are successfully using to intervene in all three of these relations to reign in corporate power and assert their own sovereignty.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.077 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.009 |
| 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".