Aboriginal Participation, Consultation, and Canada's Mackenzie Gas Project
Bibliographic record
Abstract
For the oil and gas industry, Arctic and Subarctic regions are considered to be some of the world's last energy frontiers, increasingly important for meeting global energy demands. As exploration intensifies and oil and gas development occurs in more of the Arctic, indigenous peoples are increasingly concerned about the interest of industry, national governments, and the far-reaching impact of the world market in their homelands. Pressure to sign on to development projects, to communicate and negotiate with industry and governments, and to adapt to a changing environment resulting from the activities of extractive industries is increasing. As a result, some indigenous peoples feel that they are losing control over their homelands and over their livelihoods. This article examines northern Canada's Mackenzie Gas Project and its possible implications for Aboriginal peoples in the Northwest Territories and northern Alberta. The Mackenzie Gas Project would see the development on Aboriginal lands of natural gas from three fields in the Mackenzie Delta area for delivery to markets in Canada and the United States by a pipeline up the Mackenzie Valley. The article looks at some of the key issues of this controversial project, examines local concerns over participation and consultation, and shows how it provides insight into some of the contested perspectives on the future of northern Canada, its peoples and the environment.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.072 | 0.017 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 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".