Examination Of The Joint Review Panel’s Aboriginal Consultation Process In Enbridge’s Proposed Northern Gateway Project
Bibliographic record
Abstract
Oil and gas development is expanding at a rapid rate in Canada and companies are becoming increasingly desperate to ship their product to international markets. Expanding petroleum development in Canada, with dependence on the United States as the chief destination, has prompted energy companies to push for access to international, particularly Asian markets. The Northern Gateway Project (NGP) is a pipeline proposed by Enbridge that will ship diluted bitumen (DilBit) from Alberta’s oilsands to the central coast of British Columbia (B.C.) for shipping to Asia via supertankers. The proposed pipeline and tankers will cross the traditional territories of many First Nations and Métis communities throughout Alberta and B.C. and the federal government has a responsibility to consult and accommodate these Aboriginal groups. A Joint Review Panel (JRP), mandated by the National Energy Board (NEB) and Ministry of Environment to determine whether the NGP is in the public interest, is tasked with fulfilling the Crown’s duty to consult. This paper uses the NGP as a case study of examining the effectiveness of JRPs in fulfilling the Crown’s duty to consult Aboriginal people for large mid-stream energy infrastructure projects. More effective methods are recommended for Crown consultation with Aboriginal people for large energy projects that require a federal environmental assessment, such as an Ecosystem-based Management (EBM) approach. Research for this paper was completed prior to December 19, 2013 release of the Joint Review Panel their decision to recommend the approval of the NGP.
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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 | 0.562 | 0.610 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.019 | 0.007 |
| Open science | 0.012 | 0.010 |
| Research integrity | 0.024 | 0.014 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".