Nature of Co-management in Community-owned Renewable Energy Project: A Comparison between Canada and EU Countries
Bibliographic record
Abstract
Co-management is a governance system which is consisted with the sharing responsibilities, entitlements, decentralized institutional rules and agreements between the state and local community for maintaining certain resources. Community owned renewable energy (CRE) is such kinds of collaborative energy management where both state, regional and others nongovernmental organizations has been involved. However, very few numbers of study focus on the co-management aspects of CRE. This study explores the patterns of co-management including policy regulations, ownership structure, stakeholder’s participations and decision making process of CRE both in Canada and EU by the summative content analysis method. Study found that different EU countries have applied miscellaneous effective policy tools like Feed-in-Tariff, Feed-in-Premium, Community and Renewable energy scheme, Local energy activism. Consequently, manifolds energy cooperative and community based ownerships have been developed and local residence could be engaged in highest level of participation ladder. Where as most of the Canadian renewable energy policies are more technocratic and accelerating “energy developer” oriented commercial ownership. Therefore, public participation of these renewable energy project is like "Decide-announce-Defend”. Strong decentralized governance, awareness rising and policy reformation should be increased for prolific renewable energy co-management.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".