Equity, diversity and inclusion promises, exclusive practices? How to move towards effective and just energy transitions
Bibliographic record
Abstract
Equitable, diverse and inclusive action in a climate emergency is not optional – it is an imperative. Despite the growing rhetoric for inclusive energy systems transformations, many such promises are often empty signifiers and lack substantive action. For energy transitions to be effective and sustainable, they must include, prioritize, and benefit diverse groups, encompassing marginalized communities, underrepresented stakeholders and those disproportionately burdened by current energy systems – a wider range of groups than at present. In this perspective, we argue why and how it is necessary to embed concrete practices that center equity, diversity and inclusion for meaningful energy systems transformation. As researchers and practitioners, we can influence and support the larger energy community to move from pledges to practice by supporting locally led energy systems transitions, by building participatory energy governance, addressing intersectional inequalities in energy systems and centering equity diversity and inclusion as metrics for successful energy systems.
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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 | 0.038 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.091 |
| Scholarly communication | 0.020 | 0.051 |
| Open science | 0.003 | 0.031 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".