Spinning wind into power : industry and energy in Gitxaała Nation, British Columbia
Bibliographic record
Abstract
Wind power currently represents the fastest growing renewable energy resource in the world. Disputes over siting, disparities in economic and community benefits, and perceptions of landscape change all surface with renewable energy projects. Recently, renewable energy projects in partnership with First Nations have spread throughout Canada, yet limited studies exist regarding First Nations and renewable energy projects. This research examines proposed wind farms in Gitxaała Nation, a First Nation located near Prince Rupert, on British Columbia’s North Coast. Gitxaała Nation has four wind projects proposed in their claimed traditional territory, including the Naikun Wind Farm, potentially Canada’s first offshore wind project. Based on three months of qualitative fieldwork in Prince Rupert, BC (May 2012-August 2012), this thesis examines wind turbine projects in the context of Gitxaała Nation’s experiences and explores the shifting terrain of renewable energy development in British Columbia. Twelve semi-structured interviews were conducted, paired with participant observation and numerous informal conversations. This thesis analyzes how wind turbine development in this context is intricately tied to (and viewed as) large-scale industrial development. For Gitxaała Nation, it is linked to the development of the Enbridge Northern Gateway Pipeline. In exploring views surrounding wind power’s introduction, the research examines how wind turbine projects are understood and the factors influencing how they are viewed and either accepted or rejected. It raises questions regarding renewable energies in BC and their place with First Nations, and it begins to address whether renewable energy is viewed differently from conventional resource extraction projects. Additionally, this research evaluates the impacts of renewable energy projects on local communities while exploring whether such projects are desired by and/or beneficial to Gitxaała Nation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.016 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".