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Record W1976668319 · doi:10.1080/02732170590883924

THE GLOBALIZATION OF A MINOR SPORT: THE DIFFUSION AND COMMODIFICATION OF MASTERS SWIMMING

2005· article· en· W1976668319 on OpenAlexaboutno aff
Donald W. Hastings, Sherry Cable, Sammy Zahran

Bibliographic record

VenueSociological Spectrum · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsCommodificationMinor (academic)GlobalizationDiffusionAdvertisingPsychologySociologyBusinessPolitical scienceEconomicsMarket economyLaw

Abstract

fetched live from OpenAlex

ABSTRACT We examine the global spread of Masters Swimming (MS) focusing on the economic, social, and demographic conditions associated with its initiation in the United States and its international growth. We characterize MS as a modern sport and look at its subcultural form, organizational structure, practices, and early pattern of organizational growth from bottom to top. Then we describe the top down role of La Federation Internationale de Natation Amateur (FINA) in supplying legitimacy, resources, organizational coherence, and corporate sponsors to spread the sport among FINA members. By establishing mutually beneficial relations with corporate sponsors, MS rapidly commodified and diffused to countries and territories with middle to high socio-economic development. Notes We appreciate assistance in the preparation of this manuscript from: June F. Krauser, Executive Secretary of United States Masters Swimming; Beth Whittall, Executive Secretary of Masters Swimming Canada; Masters swimmers Ted Lee Haartz and Tom Lyndon; coaches Judy Meyer (Bonner), Charlie Butt, and Dan Dakus; and our colleagues, Robert A. Stebbins, Jon Shefner, and Terese Stratta. As usual, any sins of omission or commission are ours. For Europe no info is available for 2 countries, for Americas no info is available for 1 country, and for Oceania no info is available for 1 country.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

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

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 head0.025
GPT teacher head0.301
Teacher spread0.275 · 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 designObservational
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

Citations21
Published2005
Admission routes1
Has abstractyes

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