Exploring Grassroots Renewable Energy Transitions: Developing a Community-Scale Energy Model
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
Decarbonizing energy systems through the integration of decentralized renewable energy generators creates opportunities for community-scale actors to participate in energy system decision-making. However, typical modelling approaches exclude community stakeholders, causing a loss of local knowledge. This exclusion is problematic for Indigenous peoples in so-called Canada where the natural resource industry harms their land and communities. The Exploring Grassroots Renewable Energy Transitions (EGRET) platform introduced in this work presents an alternative to typical energy system modelling because it facilitates community participation throughout the model development and application process. This platform was developed in partnership with a local First Nation's energy specialist to assess whether solar panels could increase community energy sovereignty. The platform's user interface, visualization suite, and high-speed machine learning models make energy system modelling accessible to community members through interactive workshops. In the future, the EGRET approach could be generalized for stakeholder-led renewable energy exploration in other community settings.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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