One Pipeline and Two Impact Assessments: Coproduction, Legal Pluralism, and the Trans Mountain Expansion Project
Bibliographic record
Abstract
Canada’s Trans Mountain Expansion Pipeline project is one of the country’s most controversial in recent history. At the heart of the controversy lie questions about how to conduct impact assessments (IAs) of oil spills in marine and coastal ecosystems. This paper offers an analysis of two such IAs: one carried out by Canada through its National Energy Board and the other by Tsleil-Waututh Nation, whose unceded ancestral territory encompasses the last twenty-eight kilometers of the project’s terminus in the Burrard Inlet, British Columbia. The comparison is informed by a science and technology studies approach to coproduction, displaying the close relationship between IA law and applied scientific practice on both sides of the dispute. By attending to differing perspectives on concepts central to IA such as significance and mitigation, this case study illustrates how coproduction supports legal pluralism’s attention to diverse forms of world making inherent in IA. We close by reflecting on how such attention is relevant to Canada’s ongoing commitments, including those under the UN Declaration on the Rights of Indigenous Peoples.
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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 | 0.029 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.037 | 0.055 |
| Scholarly communication | 0.021 | 0.008 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.008 | 0.013 |
| 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".