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Record W2126621252 · doi:10.1080/17460263.2010.481208

From Mixed-Sex Sport to Sport for Girls: The Feminization of Figure Skating

2010· article· en· W2126621252 on OpenAlexaffabout
Mary Louise Adams

Bibliographic record

VenueSport in History · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsQueen's University
Fundersnot available
KeywordsFeminization (sociology)Sex segregationGender studiesAdvertisingPsychologySociologyBusiness

Abstract

fetched live from OpenAlex

The history of women's sport is often written as a history of gender segregation and women's subordination. This article, however, demonstrates the historical contingency of gendered sport categories and argues that gender segregation has not always been fundamental to the organization of competitive sports. Drawing on the history of figure skating, the article illustrates how a once ‘manly exercise’ went through a relatively gender-balanced period in the early 1900s before coming to be understood, by the end of the Second World War, as a ‘girls' sport’. Focusing on the 1920s, 1930s and 1940s as significant decades in this change, the paper discusses the factors that contributed to the shift in the meanings of skating: the popularity of Norwegian Olympic champion Sonja Henie, whose post-competition career as a Hollywood film star brought figure skating to a mass audience for the first time; women's increasing prominence as the technical innovators of the sport; and the intersection of these factors with the social and demographic changes that resulted from the Second World War.

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)0.002
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: none
Teacher disagreement score0.013
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.011
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.026
GPT teacher head0.283
Teacher spread0.257 · 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

Citations19
Published2010
Admission routes2
Has abstractyes

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