Public Acceptance And Engagement In Canadian Energy Infrastructure Projects: A Case-study Examination Of The Kinder Morgan Trans Mountain Expansion Project
Bibliographic record
Abstract
There has been a recent and unprecedented push to transport Canada’s land-locked oil sands to international markets via pipeline access to tidewaters. Kinder Morgan’s Trans Mountain Expansion Project (TMEP), proposing to transport crude oil from north of Edmonton, Alberta to Burnaby, British Columbia, has received significant media and public attention due to vocal opposition. Using TMEP as a case study, I examine whether current public engagement practices in large-scale energy development projects in Canada are meeting public expectations. Results of the study reveal that despite high levels of participation in the National Energy Board (NEB) regulatory review, significant gaps exist between public values and the review process in the areas of (1) Climate Change, (2) Environmental and Economic Risk; and, (3) Process Legitimacy. Such gaps have eroded public confidence in the ability of the NEB to make a decision in the interest of the public. I conclude this study with recommendations developed to address the deficiencies in the current public engagement approach used by the NEB.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.028 | 0.010 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| 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".