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Record W7162022016 · doi:10.82308/42578

Sexuality, Sport, and the City: Sporting Mega-Events and the Spatial Politics of Canadian Sexual Citizenship

2023· dissertation· en· W7162022016 on OpenAlexaboutno aff
Abbey-Leigh Heilig

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsnot available
Fundersnot available
KeywordsQueerPoliticsNationalismCitizenshipBody politicPower (physics)Relation (database)Inclusion (mineral)

Abstract

fetched live from OpenAlex

In an increasingly globalized world, the changing faces of sexual and national politics deserve interrogation. My thesis research uses the 1976 Summer Olympics in Montréal, and the 2010 Winter Olympics in Vancouver as case studies to illuminate moments of nationalist spectacle. Studying mega-sporting-events can be a way to understand issues of sexual citizenship, spectacle, and identity. These must be considered together to understand how the global locus of settler homonationalism is only liberatory for a privileged few. My goal is to interrogate why the national body politic incorporates some identities and marginalizes others, as well as how neoliberal queer politics operate to fortify Canadian nationalism and sexual exceptionalism. I achieve this goal by examining how discourses around these events generate particular sexualized, raced, and classed power structures. I explore how Canadian nationalism has changed over time, especially in relation to the inclusion of LGBTQ people, as well as in relation to the construction of “queered” Others. A critical discourse analysis method is used to make visible new formations of nationalisms compelled by neoliberal queer politics. My research corroborates and extends a crucial body of literature which challenges homonationalist Canadian queer politics

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.552

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0230.017
Scholarly communication0.0090.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.049
GPT teacher head0.325
Teacher spread0.276 · 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
Published2023
Admission routes1
Has abstractyes

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