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Record W7100558452

The Lightness of Being ‘‘Gaie’’: Discursive Constructions of Gender and Sexuality

2006· article· en· W7100558452 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsnot available
Fundersnot available
KeywordsHuman sexualityPerformative utteranceLesbianSubjectivityNarrativeDiscourse analysisThematic analysisCritical discourse analysisCloset
DOInot available

Abstract

fetched live from OpenAlex

Abstract In this article, we explore the narratives of 14 young Francophone women from Montreal (Quebec, Canada) competing in team sports and identifying as ‘gay’, ‘lesbian’, ‘bisexual ’ or refusing labels altogether. We seek to gain a better understanding of these young women’s discursive con-structions of gender and sexuality as well as of their performative acts in sport and in other milieus. We submitted their narratives to a thematic analysis which was followed by a critical discourse analysis inspired by poststructuralism. Our findings suggest that the participants generally positioned themselves as ‘gaie ’ (as opposed to lesbian or queer), which seems specific to Quebec. By emphasiz-ing the lightness of being gaie in sport, the participants relied on an alternative discourse that tends to be positive towards gaie sexuality. Moreover, by constructing gaie sexuality as a more ‘feminine’, less visible and consequently less disturbing version of lesbian sexuality, these sportswomen also articu-lated dominant discourses that reproduce lesbo/butch-phobic ideas. We also show the participants’ unstable and changing subjectivity as we highlight the contradictions in their discursive constructions of gender and sexuality. Key words • discourse • gender • lesbian • poststructuralism • sexuality • women In the 1990s, studies focusing on issues of sexuality in female athletes were

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.605
Threshold uncertainty score0.794

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0140.030
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.288
Teacher spread0.273 · 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 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

Citations0
Published2006
Admission routes1
Has abstractyes

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