Recurring issues and concerns in wind energy project Environmental Assessments: analysis of western Canada
Bibliographic record
Abstract
Investment in renewable energy is essential to a low carbon future. Wind energy is Canada’s fastest growing renewable energy sector. Although not as disputed as fossil fuel-based energy projects, such as oil sands mines or pipelines, wind energy projects can be controversial. Understanding the typical issues and concerns that emerge when wind energy projects are proposed is important to manage the transaction costs for renewable energy projects. This research examined 16 environmental assessments (EAs) for wind energy projects in western Canada to determine the recurring issues and concerns raised by government reviewers, project interveners, and other affected interests when projects are tabled. A total of 50 different issues were identified. These were raised 848 times in EA comments and submissions. Although variability existed in the number and diversity of issues by jurisdiction and by project, depending on location and size, concerns about land use, impacts on human well-being, impacts on natural ecosystems, and economic opportunity and impact, represented 79% of all issues and concerns. The majority of issues reflect project-specific impacts and concerns, but many issues including impacts to other land tenure holders or licensees (such as other utilities and industries) are issues that are beyond the scope and scale of what can be resolved at the time wind energy projects are proposed. Understanding and addressing the recurrent issues and concerns raised when wind energy projects are proposed and identifying and off-ramping the bigger issues to the planning and strategic process, are important conditions for energy transition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.020 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".