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Record W2083696004 · doi:10.1504/ijsmm.2013.060640

"Tell me who's your host and I'll tell you who you are": Olympic Games image before and after the 2008 and 2010 Olympic Games

2013· article· en· W2083696004 on OpenAlexaffabout
Anahit Armenakyan, Louise A. Heslop, John Nadeau, Irene R. R. Lu, Norm O', N.A. Reilly

Bibliographic record

VenueInternational Journal of Sport Management and Marketing · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of OttawaCarleton UniversityNipissing University
Fundersnot available
KeywordsBeijingTourismAdvertisingDestination imageAsian gamesHost (biology)GeographyPolitical scienceDestinationsChinaBusiness

Abstract

fetched live from OpenAlex

The purpose of this paper is to explore the images of the Olympic Games and their host countries, as a country and as a tourism destination, before and after the 2008 Beijing Olympic Games (BOG) and 2010 Vancouver Olympic Games (VOG). The attitude changes towards the three image objects and relationships among them are examined in a combined ‘country − destination − mega-event’ model. The paper reports on a questionnaire-based study completed by 1,292 American respondents who were approached two months before and two months after both the 2008 and 2010 Games. Results indicate a significant decrease in the attitudes towards the OG in the case of the 2008 BOG and some improvement in the case of the 2010 VOG. This contrast between the OG hosted in a developed country and one held in a developing country is an important contribution to the sport events literature. Further, regression analysis shows that evaluations of the OG as a destination are influenced (mediated) mainly by the evaluations of the host country as a destination.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.009
GPT teacher head0.255
Teacher spread0.246 · 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

Citations2
Published2013
Admission routes2
Has abstractyes

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