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Record W4327590751 · doi:10.1177/01634437231159528

Disablement in figure skating: Media, celebrity, spectacle

2023· article· en· W4327590751 on OpenAlexaff
Adan Jerreat-Poole

Bibliographic record

VenueMedia Culture & Society · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAthletesSpectacleNarrativeNationalismSociology of sportVulnerability (computing)Gender studiesSociologyPsychologyMedia studiesPolitical scienceArtMedicineLiteratureLawPhysical therapy

Abstract

fetched live from OpenAlex

Blood on the ice. Cheers when the injured athlete stands and limps off the field. Comebacks, backflips, and back injuries. Celebrity athletes are punished and rewarded for their abilities, including their ability to perform while injured or work through pain. Injuries, illness, disablement, and even death are not uncommon in celebrity culture broadly and the field of competitive sports more specifically. While critical disability studies often attends to disabled celebrities, less research and critical attention has been paid to the disablement of celebrity and the expectation and performance of injury or illness understood through the lens of ablenationalism. Focusing on international figure skating and the 2022 Winter Olympics, this paper offers a supercripping of athletic celebrity by interrogating how gender, race, age, and nationality impact a global audience’s view of vulnerability, risk, and harm. Analyzing media coverage of the event alongside popular discourse uncovers the impact of nationalism, white supremacy, and patriarchy on sports narratives and celebrity cultures of debilitation and disablement.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.276
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.336
Teacher spread0.299 · 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 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

Citations2
Published2023
Admission routes1
Has abstractyes

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