Using Indigenous legal processes to strengthen Indigenous jurisdiction : Squamish Nation land use planning and the Squamish Nation assessment of the Woodfibre liquefied natural gas projects
Bibliographic record
Abstract
This dissertation examines how Squamish Nation has created its own legal processes in land use planning and environmental assessment to strengthen its jurisdiction over land, water, and resources in Squamish Nation Territory. It provides a case study of Squamish Nation’s development of the Xay Temíxw Land Use Plan for Forests and Wilderness of Squamish Nation Traditional Territory, its negotiation of an agreement on land use planning with the Province of British Columbia, and its creation of an environmental assessment process (the Squamish Process) to assess liquefied natural gas (LNG) projects being proposed in Howe Sound. The case study reveals Squamish Nation’s motivations for developing the processes; the type of community engagement it used; the perspectives, values, and laws Squamish members brought to their deliberations in the processes; and how Squamish Nation made its final decisions. It illuminates how these processes articulate Squamish legal principles to wider Canadian audiences through the plans, reports and agreements that have emerged from the processes. It also shows how these processes placed pressure on the state, as well as third parties, and how these pressures led to shifts in state/proponent practices and behaviours that have strengthened Squamish Nation jurisdiction. The research suggests that successful implementation of the doctrine of free, prior, and informed consent (FPIC) will be better achieved if Canadian governments shift their focus away from narrow judicial interpretations of the duty to consult, and toward Indigenous-led processes for establishing consent, articulated through Indigenous legal orders.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.016 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".