Feminist Climate Policy in Industrialised States
Bibliographic record
Abstract
Feminist Climate Policy in Industrialised States explores ways in which policymakers can overcome institutional barriers and conventions in pursuit of the radical changes necessary for a gender-just climate emergency response. In 2021, the Intergovernmental Panel on Climate Change acknowledged that addressing the climate emergency must involve social justice and equality. Feminist approaches to decision-making, policy-making, community organising and their underpinning methodologies can enable this. The authors draw critically on case studies, research and interviews with feminist practitioners, legislators and leaders who have implemented significant changes, to signal how change might be achieved and ask what lessons can be drawn. The book posits that we need to ultimately move beyond the gender mainstreaming and gender equality issues which have been integrated into existing – and failing – structures, to more transformative feminist approaches. It concludes by identifying key strands of feminist-oriented praxis that offer the potential to expedite responses to climate change across multiple levels of governance. With industrialised states shifting rightwards to a politics which diminishes the importance and urgency of gender equality, diversity, human rights and the need for climate action, this volume will inspire, guide, and provide tools for policymakers, politicians, community activists, academics, and students to take transformative action to address the climate emergency. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons [Attribution-Non Commercial-No Derivatives (CC BY-NC-ND)] 4.0 license.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".