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Record W1987004565 · doi:10.1177/0038038511413426

How to ‘Use Your Olympian’: The Paradox of Athletic Authenticity and Commercialization in the Contemporary Olympic Games

2011· article· en· W1987004565 on OpenAlexaff
Momin Rahman, Sean Lockwood

Bibliographic record

VenueSociology · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsTrent University
Fundersnot available
KeywordsCommercializationCredibilityAppealAmateurSociologyEmbodied cognitionAestheticsDimension (graph theory)AdvertisingPublic relationsEpistemologyPolitical scienceLawBusinessArtPhilosophy

Abstract

fetched live from OpenAlex

A paradox between commercialization and the authenticity of the Olympic Games has been identified in the established literature. We add to this discussion but with a specific emphasis on how this paradox is embodied by the athletes involved. We argue that the commercialization of the Games is inevitable in the contemporary media and corporate contexts, whereby the finances available from both are necessary to stage and promote the event. Within these contexts, we suggest it is also inevitable that Olympians become commodities that promote the brand of the Olympics. Representations of their heroism and their modelling of achievement culture provide an authentic credibility for the Games. Moreover, the Olympics add a distinctive dimension to this contemporary authenticity in their appeal to an ancient amateur heritage. We demonstrate, however, that amateurism is a creation of the modern Olympic Movement and is deployed to add another dimension to the general sporting authenticity that is currently invoked to manage the paradox of commercialization.

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)0.005
metaresearch head score (Gemma)0.014
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.028
Scholarly communication0.0140.009
Open science0.0010.005
Research integrity0.0030.003
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 head0.179
GPT teacher head0.339
Teacher spread0.160 · 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

Citations14
Published2011
Admission routes1
Has abstractyes

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