Of pipe dreams and fossil fools: Advancing Canadian fossil fuel hegemony through the Trans Mountain pipeline
Bibliographic record
Abstract
This article uses the Trans Mountain pipeline expansion project as a Canadian case study to critically examine and showcase one instance of the hegemony of fossil fuels in the era of global heating. The present Canadian federal government, under the leadership of Liberal Prime Minister Justin Trudeau, is seeking to simultaneously position itself as a global climate leader while supporting the exploitation of Canada’s extensive bitumen oil reserves. We apply a critical discourse analysis to seven speeches given between 2016 and 2019 by two members of the Canadian federal government on the Trans Mountain pipeline expansion project to interrogate how the government discursively reconciles these two contradicting stances. Our analysis yields three main results: 1) the government naturalizes bitumen as a substance, culturally and politically hindering the capacity for Canada to move beyond it, 2) the extraction of bitumen is portrayed as an imperative, implicating the overall economic and social health of Canada and justifying the government’s use of coercion and 3) appeals to climate change and action are paradoxically subsumed into the argument for bitumen extraction. Overall, we argue, this discourse depoliticizes the social and environmental struggles surrounding bitumen extraction. It functions to maintain the hegemony of fossil fuels in the era of global heating, thus foreclosing on possibilities of leaving the fuels in the ground while reinforcing Canadian bitumen’s multi-dimensional carbon lock-in.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.044 | 0.028 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".