Assessing local capacity for community appropriate sustainable energy transitions in northern and remote Indigenous communities
Bibliographic record
Abstract
Community renewable energy is increasing globally, but many northern and remote Indigenous communities remain energy insecure. Community appropriate sustainable energy solutions requires more than building renewable energy projects – it requires local socio-technical capacity to design, implement, and maintain renewable energy projects. Yet, notwithstanding advances in renewable energy technology there is limited understanding of the socio-technical capacity of northern and remote Indigenous communities to engage in energy transitions. Based on a review of energy transitions scholarship and northern contexts and informed by a workshop engaging northern and Indigenous community members from Canada and Alaska, this paper presents foundational pillars for assessing the socio-technical capacity needs of communities to pursue and sustain local energy transitions. These pillars are inter-dependent and emphasize the importance of local energy champions and inter-local energy networks to enable innovation and capacity building; community values that articulate immediate and longer-term goals for energy transition, including the social and economic opportunities to be realized by a more sustainable energy system; community knowledge of local energy resources, technologies, and opportunities, and embedded skills to support transitions; and the skills innovation to pursue and manage new energy systems, coupled with youth engagement as future community energy leaders. The proposed framework is intended to support the early stages of community energy transition planning.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| 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".