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Record W1594041073 · doi:10.1108/ijefm-03-2012-0010

Semiotic representations of Olympic mascots revisited

2014· article· en· W1594041073 on OpenAlexaff
Peter Knight, Ina Freeman, Stephen A. Stuart, Gerald Griggs, Norm O’Reilly

Bibliographic record

VenueInternational Journal of Event and Festival Management · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsOriginalitySemioticsValue (mathematics)AdvertisingSociologyPublic relationsMedia studiesPolitical scienceBusinessComputer scienceQualitative researchSocial scienceLinguistics

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to review Olympic mascots in the electronic and traditional communications environments. Design/methodology/approach – Olympic mascots from 2006 to 2012 are analyzed using a descriptive semiotic analysis technique. Findings – Results found that none of the 2006-2012 mascots clearly represented the two most recognizable icons of the Olympic movement, the Olympic Rings and the Olympic Flame. The association of the London 2012 mascots with the Olympic Games are found to be limited. Research limitations/implications – This research sets the stage for a number of future studies to further assess the management issues, social benefits, and potential missteps regarding mascots at the Olympic Games and other mega-events. Practical implications – The practitioner of today working for a mega-event like the Olympic Games needs to be aware of the potential benefits and inherent risks of developing and implementing a mascot. Originality/value – This research is the first to look specifically at Olympic mascots in the electronic age and contrast their use to traditional communications.

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 score0.618
Threshold uncertainty score0.210

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 studies0.0000.000
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 head0.022
GPT teacher head0.340
Teacher spread0.318 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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