“Governing discourses” in Canadian environmental assessment: A critical discourse analysis of climate change in the Northern Gateway Pipeline review process
Bibliographic record
Abstract
This qualitative inquiry focuses on Canada’s environmental assessment (EA) of the controversial—now defunct—Enbridge Northern Gateway Pipeline as a case study. Adapting Fairclough’s (1992) approach to critical discourse analysis (CDA) as a methodological framework, I investigated how Northern Gateway’s environmental effects were discursively framed and rationalized in relation to climate change, and how these discourses are connected to statutory interpretations and institutional norms. Using frame analysis and argumentation analysis as methods, I examined a corpus of publicly available Joint Review Panel (JRP) documents, federal statutes and official decision statements related to Northern Gateway’s EA. Findings suggest that the convergence of particular discourses, ideologies, institutional power relations, and entrenched discretionary practices tended to marginalize and depoliticize climate change considerations in Northern Gateway’s EA. These dynamics provided a foundation to rhetorically legitimate contentious project-related governance decisions, and arguably expose areas of potential concern in the contemporary EA and climate change context.
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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 | 0.039 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.044 | 0.041 |
| Scholarly communication | 0.019 | 0.006 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".