Pluralizing energy justice: Incorporating feminist, anti-racist, Indigenous, and postcolonial perspectives
Bibliographic record
Abstract
Justice represents not only a moral obligation but can enhance the legitimacy and acceptance of a rapid push toward global decarbonization. Innovations in technology, even those geared toward sustainability, can both reinforce and introduce new inequalities and disparities across populations, while also perpetuating environmental degradation. The concept of energy justice has emerged as a conceptual, methodological, and empirical tool to both highlight and remediate many of these concerns, with an emphasis on what is morally just or right. But much of this body of scholarship fails to adequately account for gender, Indigeneity, race, and other intersecting inequalities. Feminist, Indigenous, anti-racist and postcolonial approaches to justice offer an important remedy to theories of justice with underlying colonial, liberalist, majoritarian, utilitarian, or masculinist assumptions. Our Perspective is grounded in these four core, but often misperceived or even radical, approaches to justice. We first provide an overview of each of these approaches and then synthesize them into a set of themes, principles, and questions, which can guide future energy justice research and practice.
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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 | 0.017 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.015 | 0.085 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.006 | 0.008 |
| 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".