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Record W4391475046 · doi:10.1080/12259276.2024.2307720

Intersectionality and humanity: A keynote for “remapping the feminist global”

2024· article· en· W4391475046 on OpenAlexaff
Lisa Yoneyama

Bibliographic record

VenueAsian Journal of Women s Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIntersectionalityHumanitySociologyGender studiesPolitical scienceLaw

Abstract

fetched live from OpenAlex

That Modern Feminist Thought shares its lineage with the liberal Enlightenment and Humanism has continued to render certain feminist practices assimilable to the colonial-racial regime of knowledge that has long underpinned what we normatively uphold as political modernity and its foundational assumptions. This article, originally presented as a conference keynote address, revisits the familiar feminist aporia through exploring the multiple genealogies of feminisms to highlight their theorizations of difference, the human, and other ways of being and caring. It also reconsiders how “intersectionality” – a concept originally forwarded as an alternative legal doctrine yet extensively deployed for various political ends such that the term appears to have lost its original relevance for some – can be repurposed as a critical methodology with which to challenge the universalism of liberal humanism/feminism and the attendant compartmentalization of academic knowledge, but ultimately, to strengthen coalitional possibilities. The article addresses how some of the largely North America-based conversations can resonate transnationally and effectively with some of the most urgent feminist engagements that have unfolded across and beyond plural “Asias,” however imagined.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.083
GPT teacher head0.412
Teacher spread0.329 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2024
Admission routes1
Has abstractyes

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