Can a just transition achieve decarbonization? Explaining fossil fuel community opposition in the Canadian Oil Sands
Bibliographic record
Abstract
Just transition policies are widely viewed as one of the most effective mechanisms for compensating and building support for decarbonization in fossil fuel communities. However, early empirical work suggests that many coal-producing regions remain opposed to decarbonization even when just transition policies are proposed or implemented. In this study, I add to and nuance existing accounts by analyzing data from 18 interviews with oil and gas workers and community members in the Canadian Oil Sands, the world’s third-largest fossil fuel reserve. I show how those living and working in the Oil Sands remain skeptical of renewable energy, optimistic about the long-term viability of fossil fuels, and strongly oppose the proposal for a just transition. These responses are patterned by feelings of fear, exclusion, and resentment towards the motives and actors driving decarbonization, which I argue demonstrates a threatened sense of ontological security. Reframing decarbonization and just transition policies as an issue of ontological security encourages scholars and policy makers to prioritize the social and emotional impacts of decarbonization and reconsider the conditions necessary for a just transition.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.022 | 0.025 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".