People, land, and pipelines: perspectives on resource decision-making in the Sahtu Region, Northwest Territories
Bibliographic record
Abstract
This dissertation examines the ways in which three Aboriginal communities in the Sahtu Region of the Northwest Territories are participating in decisions and activities related to non-renewable resource extraction on Sahtu lands. In particular, I examine local involvement in the assessment and regulation of a 1,220 km natural gas pipeline and related infrastructure, collectively termed the Mackenzie Gas Project, currently proposed for the Mackenzie Valley. Overall, this work addresses the conditions under which Sahtu Dene and Métis participation in resource decision-making takes place; it identifies and offers a critique of some of the assumptions inherent in regulatory, environmental assessment, and consultative processes currently in place in the Sahtu region, and argues that while there has been significant progress in establishing avenues for Sahtu Dene and Métis participation in resource decision-making, non-local epistemological underpinnings of governance, regulatory, and environmental assessment institutions and practices can hinder local participation in resource decision-making and may serve to reinforce existing power relationships between proponents, Aboriginal communities, and the Canadian state. The findings of this research suggest that there are several barriers to Sahtu Dene and Métis participation in resource decision-making, including: 1) how environmental impacts are assessed and the associated determination of their ‘significance’ in environmental assessment and management regimes; 2) the naturalization of techno-rational knowledge paradigms and legalistic discourse in environmental assessment and regulatory processes; 3) incongruent communicative practices and norms of appropriate human and human/other than-human relationships between local Dene and Métis participants and those of large development corporations and governments; 4) divergent perceptions of the landscape; and 5) changing governance structures resulting from the Sahtu Dene and Métis Comprehensive Land Claim. This research contributes to a growing assessment of current participatory and resource co-management processes in the Canadian north, and addresses the call for research reflecting local experiences of various participatory processes in resource management, including the often messy and contradictory positions taken by members of a diverse community.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.024 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".