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Record W2620985469

Desire Change : Contemporary Feminist Art in Canada

2017· book· en· W2620985469 on OpenAlexaboutno aff
Heather Davis, Janice Capel Anderson, Gina Badger, Amber Christensen, Karen Cope, Lauren Fournier, Amy Fung, Kristina Huneault, Alice Ming Wai Jim, Tanya Lukin Linklater, Daniella Sanader, Thérèse St-Gelais, Jane Wark

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicHistorical Gender and Feminism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOppressionGender studiesContext (archaeology)FeminismHuman sexualityBeautyPatriarchyResistance (ecology)Contemporary artSociologyFeminist philosophyFeminist theoryAestheticsArtPoliticsHistoryPolitical scienceArt historyPerformance art
DOInot available

Abstract

fetched live from OpenAlex

In the resistance to the violence of gender-based oppression, vibrant - but often ignored - worlds have emerged, full of nuance, humour, and beauty. Correcting an absense of writing about contemporary feminist work by Canadian artists, Desire Change considers the resurgence of feminist art, thought, and practice in the past decade by examining artworks that respond to themes of diversity and desire. Essays by historians, artists, and curators present an overview of a range of artistic practices including performance, installation, video, textiles, and photography. Contributors address the desire for change through three central frames: how feminist art has significantly contributed to the complex understanding of gender as it intersects with sexuality and race; the necessary critique of patriarchy and institutions as they relate to colonization within the Canadian national-state; and the ways in which contemporary critiques are formed and expressed. The resulting collection addresses art through an activist lens to examine intersectional feminism, decolonization, and feminist institution building in a Canadian context. -- Publisher's website.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.221
Threshold uncertainty score0.904

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0410.024
Scholarly communication0.0110.002
Open science0.0020.004
Research integrity0.0020.004
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 head0.187
GPT teacher head0.314
Teacher spread0.127 · 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 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

Citations6
Published2017
Admission routes1
Has abstractyes

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