Best Practices for Renewable Energy Engagements and Consultations in Nunavut
Bibliographic record
Abstract
Energy and infrastructure projects in the Canadian North have historically been highly colonial, top-down exercises in sovereignty and control. This has largely been changing over the past several decades, with huge changes in the approach to infrastructure development since the publication of Canada's Truth and Reconciliation Commission's 94 Calls to Action, international efforts such as the United Nations Declaration on the Rights of Indigenous People (UNDRIP), and the concept of Free and Prior Informed Consent (FPIC) becoming more well understood and widespread. While these high-level policy tools and statements are helpful for grounding discussions and justifying engagement activities, this paper aims to give a more practical understanding of what following these directives and guidelines looks like in the context of the Canadian North. The information share is focused into five themes: The importance of community engagement; Communication in the North; Education and human capacity building; Project development; and Outcomes. The four key take-aways for best practices for community engagement in Nunavut: Listen!; Invest in people; Use hands-on activities; and Work on projects that are a priority for the 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 | 0.035 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.050 | 0.019 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.004 | 0.003 |
| 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".