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Record W7084285807

Feminist Climate Policy in Industrialised States

2025· other· en· W7084285807 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsnot available
FundersInternational Council for the Exploration of the SeaNordForskSvenska Forskningsrådet FormasQueen's UniversitySwansea UniversityDurham UniversityEuropean CommissionEnergimyndighetenUdenrigsministerietUniversity of LeedsUniversity of OxfordVetenskapsrådetGovernment of Canada
KeywordsTransformative learningClimate justiceClimate changeGender mainstreamingPoliticsPraxisPolitical economy of climate changeUnderpinningClimate governance
DOInot available

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.597
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.019
GPT teacher head0.254
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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