The Emergence of Low Carbon Energy Autonomy in Isolated Communities
Bibliographic record
Abstract
This study examines the concept of switching from a centralised energy supply model towards a more autonomous model based on the use of low carbon technologies, from the viewpoint of isolated communities in the industrialised world. The study begins by establishing the importance of isolated communities within the field of energy research, and examining the concept of low carbon energy autonomy. It then analyses a number of exemplary case studies from across Europe, all of which have adopted (or are in the process of adopting) a highly autonomous energy supply model based on the use of low carbon technologies. The communities studied exhibit many of the theoretical challenges and opportunities associated with low carbon energy autonomy, including the potential for stimulating socio-economic development. They also highlight the need for a supportive and structured policy framework and more transparent routes to project funding, in order to lessen the reliance for the success of such projects upon motivated community groups. The role of academia and its relationship with industry was found to be important and the findings call for much greater transparency and knowledge sharing between key stakeholders to facilitate increased development and deployment of low carbon energy autonomy in the future.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| 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".