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Record W2946608189 · doi:10.1080/19419899.2019.1615538

Femme resistance: the fem(me)inine art of failure

2019· article· en· W2946608189 on OpenAlexafffund
Rhea Ashley Hoskin, Allison Taylor

Bibliographic record

VenuePsychology and Sexuality · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsYork UniversityWomen's and Gender Studies et Recherches FéministesQueen's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsFemininityQueerOppressionResistance (ecology)AdornmentAestheticsSociologyPower (physics)Gender studiesArtPoliticsLawPolitical science

Abstract

fetched live from OpenAlex

Using femme theory, Foucault, and queer failure as analytical frameworks, the current paper demonstrates the role of feminine failure in resisting and subverting systems of oppression, subsequently providing the minute shifts in power necessary to expand the terms of patriarchal femininity. More specifically, the current paper draws on contemporary modes of art and aesthetics to examine the productive potential of failing to embody patriarchal femininity, positing this failure as a form of femme resistance. By hijacking cultural signifiers of adornment, femme and feminine failure celebrate that which is culturally shamed (queer, fat, disabled, variant, poor, and racially minoritised bodies), expose systems of erasure, challenge binary systems of meaning, and promote feminine growth. Examining each of these themes in turn, the current paper argues that feminine failure challenges the pillars of patriarchal femininity and discursive systems of normativity. To this end, femme as a theoretical framework demonstrates the freedom of failure by exposing the heterogeneous multiplicities of femininity, and offering possibilities that normativity never could. This critical discursive essay contributes to the emergent application of femme as a theoretical framework.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.326

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 studies0.0000.000
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 head0.042
GPT teacher head0.373
Teacher spread0.331 · 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 designObservational
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

Citations67
Published2019
Admission routes2
Has abstractyes

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