Government Instruments and Community Energy: Advancing Energy Transition in Northern and Indigenous Communities
Bibliographic record
Abstract
Energy transition is considered to be one of the greatest solutions to climate change, given that the adoption of renewable energy reduces drastically the amount of greenhouse gas emissions. Renewable energy can also address energy security problems, especially when combined with local ownership. For example, community energy, that is, renewable energy projects with community ownership or participation, is one of the alternatives to the limited, unreliable and expensive power generation scenario of northern and Indigenous communities in Canada. The implementation of community energy, however, depends on supportive government instruments, such as energy policies and regulations. Nevertheless, there is limited research on the nature and implications of these instruments for enabling community energy, especially in the context of northern and Indigenous communities. Thus, this research explores role of government instruments in facilitating energy transition and renewable energy development in northern and Indigenous communities. To do so, this research explores the current emphasis of scholarly research on government instruments for community energy, and identifies the government instruments supporting or hindering community energy in northern and Indigenous communities in Canada. The results show that there are multiple instruments available to support community energy, and emphasizes the importance of coordination and complementarity between the levels of government and between government instruments. The findings also emphasize the importance of localized government instruments to offer equitable and meaningful opportunities for community-owned renewable energy projects in northern and Indigenous communities.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".