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Record W4401701846 · doi:10.1057/s41296-024-00707-y

Feminist approaches to environmental politics

2024· article· en· W4401701846 on OpenAlexaff
Jennifer L. Lawrence, Isabel Altamirano‐Jiménez, Cara Daggett, Sherilyn MacGregor, Emily Ray, Sarah Wiebe, Hannah Battersby, Magdalena S. Rodekirchen, Heather Urquhart

Bibliographic record

VenueContemporary Political Theory · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of VictoriaUniversity of Alberta
Fundersnot available
KeywordsPolitical philosophyCritical theoryPoliticsFeminismSociologyFeminist philosophyEnvironmental ethicsPolitical scienceSocial scienceGender studiesEpistemologyPhilosophyLaw

Abstract

fetched live from OpenAlex

Ecofeminism as scholarship and practice continues to polarize, draw criticism, and inspire scholarly works and politics that account for the structures of domination that perpetuate sexism and ecological exploitation. Ecofeminist scholarship grew in volume and prominence in the 1970s and 1980s but began to falter under the weight of critiques that the approach upheld gender essentialism and a white western feminism that does not account for the needs, views, politics, and orientations to the planet outside of the global north. And yet, ecofeminism still holds relevance and offers significant perspectives and tools that can respond to these important criticisms and offer key insights in the ongoing efforts to address climate change and environmental and gender injustices. As a conversation among scholars working in ecofeminist political thought, this Critical Exchange asks about the contemporary relevance of this tradition to their approach as scholars, inside and outside of the academy.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0060.038
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0100.001

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 head0.149
GPT teacher head0.332
Teacher spread0.182 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations6
Published2024
Admission routes1
Has abstractyes

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