A review of large-scale renewable energy partnerships with Indigenous communities and organizations in Canada
Bibliographic record
Abstract
In this paper, a review of Indigenous engagement in renewable energy projects is conducted and the main elements of energy partnerships between stakeholders and Indigenous partners are discussed. In recent years, Canada has witnessed more significant Indigenous involvement in economic and energy development projects than ever before. For large-scale energy partnerships, the focus is on engagement, financial capital, community buy-in (readiness, and entrepreneurial and business skills), and benefits-sharing with community partners. Equity-ownership, reconciliation, and self-determination intersect with and impact the benefits and sustainability of energy projects, as they are interrelated in the framework of most energy partnerships. This paper illustrates policy disconnects in connection with partnership-making, social outcomes, and decision-making among Indigenous communities. Furthermore, findings from relevant literature explore the nuanced discourse on social implications and capacity challenges that interlink with climate adaptation and reconciliation when promoting large-scale renewable energy partnerships with Indigenous communities. Through a systematic review and a meta-analysis of the literature, we found 80 relevant studies during the screening process, of which 33 were selected for the synthesis. Findings demonstrate that the Crown, energy companies, and community partners need to coordinate and collaborate closely to achieve energy security and sustainable renewable energy. The review suggests that Indigenous engagement in energy partnerships supports positive outcomes for social development and environmental protection among Indigenous communities. The literature suggests that when government and industry mentor in the project implementation process, important positive impacts on energy transitions, and self-sufficiency can be realized.
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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 | 0.013 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.018 | 0.039 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".