MétaCan
Menu
Back to cohort
Record W2761653488 · doi:10.1386/qsmpc.2.3.293_1

A queer aesthetic: Representations of gender and sexuality in Sadie Lee’s Tomboys and Crossdressers

2017· article· en· W2761653488 on OpenAlexaff
Alisa Grigorovich

Bibliographic record

VenueQueer Studies in Media & Popular Culture · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsQueerLesbianSubjectivityMainstreamHuman sexualityGender studiesAestheticsPaintingRepresentation (politics)SociologySubject (documents)ScholarshipSalience (neuroscience)ArtVisual artsPsychologyPoliticsEpistemologyPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Abstract This article examines a series of paintings created by the artist Sadie Lee. Although these paintings are over twenty years old, their subject matter has salience to continuing debates about the nature of the relationship (if any) between gender and sexuality, and the role of clothing and physical appearance in self-representation, recognition and subjectivity. In focusing on queer women who do not easily fit within the homonormative cultural logics of mainstream lesbian culture, Lee directly challenges and enlarges contemporary understandings of current and historical queer subjectivities and sexualities. Drawing on recent scholarship regarding queer utopian looking practices and emotion, this article seeks to contribute towards ongoing debates about lesbian representation within popular culture by exploring the queer aesthetic of Lee’s paintings. What is ultimately argued is that Lee’s paintings generate an affective experience that offers us with a critical opportunity to disrupt the ‘straight time’ of the mainstream visual canon.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.014
Scholarly communication0.0050.002
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.130
GPT teacher head0.370
Teacher spread0.240 · 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
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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueQueer Studies in Media & Popular CultureSame topicFashion and Cultural TextilesFrench-language works237,207