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Record W2936286901 · doi:10.1108/sbm-09-2017-0047

Sport event hosting capacity as event legacy: Canada and the hosting of FIFA events

2019· article· en· W2936286901 on OpenAlexaffabout
Becca Leopkey, Dana Ellis

Bibliographic record

VenueSport Business and Management An International Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsLaurentian University
Fundersnot available
KeywordsOriginalityEvent (particle physics)FootballValue (mathematics)TourismEvent managementPublic relationsPolitical scienceQualitative researchSociologyMarketingBusinessComputer scienceLawSocial scienceCritical success factor

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to explore how a legacy of event hosting competencies from one event can contribute to advancing the overall hosting capacity of a nation for future events. More specifically, the project focuses on determining the event hosting capacity legacies from the Men’s Under-20 2007 Fédération Internationale de Football Association (FIFA) event in Canada and how they contributed toward winning the rights for the Women’s FIFA World Cup 2015 event. Design/methodology/approach A qualitative case study design focusing on FIFA events held in Canada in 2007 and 2015 was used. Findings Four broad event hosting capacity legacies from the U-20 2007 event that potentially impacted Canada’s ability to secure the WWC 2015 were identified. These legacies included: exemplifying success, advancement of hosting concepts, staff and leadership experience and development and enhancement of sporting infrastructure. Research limitations/implications The findings formed the basis of a discussion on the increasing formalization of event organizing committees, the need to consider collective (i.e. multiple events) legacies in the development of hosting strategies as well as the importance of developing the trust of the local community to support future sport event bids and hosting. Originality/value The originality and value of this research paper lies in its use of empirical case study findings to illustrate the potential for hosting capacity legacies of sporting events as well as the level and type of event under investigation (i.e. large-scale, football/soccer).

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.879

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 communication0.0000.001
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 head0.014
GPT teacher head0.278
Teacher spread0.264 · 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

Citations9
Published2019
Admission routes2
Has abstractyes

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