A powerful landscape: First Nations small-scale renewable energy development in British Columbia
Bibliographic record
Abstract
Action on climate change will require an increase in renewable energy projects to support electrification in the transition away from burning fossil fuels. Indigenous peoples throughout Canada are developing community-owned small-scale (producing less than one megawatt of power) renewable energy projects and are interested in developing more. Despite Indigenous peoples’ involvement and interest, there is a lack of research into the impact of these projects for communities. This thesis explores whether and how small-scale renewable energy projects developed by First Nations communities in British Columbia (BC) might contribute to supporting justice within the energy transition. The research included a province-wide survey (First Nations Clean Energy Survey), and a case study with a remote First Nation with multiple small-scale renewable energy projects in operation—the Village of Skidegate on Haida Gwaii. This research found that small-scale projects are a distinct experience within the renewable energy sector, one that is offering First Nations communities an accessible form of power production that provides myriad benefits. Some benefits were easy to measure, such as cost savings and greenhouse gas reductions, while the majority of benefits were not as easy to quantify, such as increasing connection and engagement with energy, increasing self-sufficiency, providing a vision of a future free of oil and gas reliance, community pride and education. As these benefits indicate, the thesis concludes that small-scale renewable energy developments offer a distinctive and important opportunity that First Nations are using to enforce self-determination and build community resilience.
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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 | 0.002 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".