Toward transformative climate justice: An emerging research agenda
Bibliographic record
Abstract
Abstract Calls for climate justice abound as evidence accumulates of the growing social and environmental injustices aggravated or driven by climate change. There is now a considerable and diverse literature on procedural, distributional and intergenerational dimensions, including questions of recognition in climate justice. Yet its meaning, scope and practical implications are still contested. Importantly, the broader landscape within which climate justice is situated is rapidly changing, bringing new challenges to the understanding and practice of climate justice. This review takes stock of climate justice literature in view of this new context. We find several disconnects and tensions between more philosophical and academic treatments of the subject on the one hand, and “activist”‐oriented approaches to climate justice on the other. Scholarship often falls into silos around scales from global and local, between mitigation and adaptation or draws distinctions between climate justice and other forms of (in)justice. This inhibits an understanding of climate justice that can address more directly its underlying root causes in an historically constituted global economic system and intersecting set of social inequalities. We propose a research agenda centered on a transformative approach to climate justice, placing analysis of power in its various guises at the center of its enquiry, and subverting and moving beyond existing distinctions by focusing on the social and institutional relations and inequalities that both produce climate change and profoundly shape responses to it. We elaborate on three key strands of such an approach: inclusive climate justice, deepening climate justice and governance for climate justice. This article is categorized under: Climate, Nature, and Ethics > Ethics and Climate Change Climate, Nature, and Ethics > Climate Change and Global Justice
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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 | 0.024 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.039 |
| Scholarly communication | 0.018 | 0.027 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.012 | 0.014 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".