Decentralised energy, decentralised accountability? Lessons on how to govern decentralised electricity transitions from multi-level natural resource governance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Emerging decentralised electricity systems require new approaches to energy governance. As energy sources shift and technology evolves, electricity governance is shifting from largely centralized models to include multiple decentralised and multi-level sites not bounded in their operations by established democratic processes. New forms of accountability are required to ensure that multi-level electricity systems meet societal needs and expectations. While multi-level governance dynamics are new for many electricity systems, they are common across other resources (e.g. water). This article uses an OECD framework that synthesizes decades of research on multi-level natural resource governance to describe 12 principles for “good” resource governance. These principles are developed and applied to decentralising electricity governance contexts in order to develop mechanisms, and identify potential governance gaps, that are relevant for ensuring accountability in decentralised electricity governance systems. The nature of decentralised electricity systems particularly highlights the need to rescale many governance functions, while paying attention to issues of inclusion, capacity building, coherence, adaptiveness, and transparency.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it