Re-righting renewable energy research with Indigenous communities in Canada
Bibliographic record
Abstract
The global call to address climate change and advance sustainable development has created rapid growth in research, investment, and policymaking regarding the renewable energy transition of Indigenous communities. From a rightsholder perspective, Indigenous Peoples' vision of sustainability, autonomy, and sovereignty should guide research on their energy needs. In this paper, we present a multi-method, inductive examination to identify gaps between Indigenous communities' expressed needs and rights, and the questions researchers and policymakers investigate in energy transition research conducted in the context of Indigenous communities located in Canada. We combine a systematic review of the extant literature, a scoping review of the grey literature on off-grid communities by Indigenous and non-Indigenous governments and non-governmental policy bodies, qualitative primary data collected via fieldwork, and an in-depth study of an Indigenous-led renewable energy transition study conducted by Haíɫzaqv Nation's Climate Action Team. We holistically examine these different perspectives and identify emergent themes to recommend ways to bridge the gaps between off-grid renewable energy research and stated Indigenous community priorities. Specifically, we recommend designing equitable research practices, understanding community worldviews, developing holistic research goals, respecting Indigenous data sovereignty, and sharing or co-developing knowledge with communities to align with community priorities closely.
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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 | 0.029 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.037 | 0.018 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".