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Record W2126812744 · doi:10.1123/jsm.2013-0259

Understanding Urban Development Through a Sport Events Portfolio: A Case Study of London, Ontario

2014· article· en· W2126812744 on OpenAlexaffabout
Richelle Clark, Laura Misener

Bibliographic record

VenueJournal of Sport Management · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsWestern University
Fundersnot available
KeywordsPortfolioLocal DevelopmentPoliticsSustainable developmentEvent (particle physics)Process (computing)Community developmentPublic relationsBusinessMarketingPolitical scienceSociologyEconomic growthRegional scienceEconomicsFinanceComputer science

Abstract

fetched live from OpenAlex

This study investigates the underdeveloped area of event portfolios in an attempt to fill a gap in the existing literature. This research article examines strategic positioning of events and the critical role they play in local development. To understand this, a case study design was performed in a medium-sized city in Canada. The purpose of the study was to determine how the city has used sport events for broader local development and enhancement of the civic brand. Interviews with local city actors and document analyses were used to further understand the strategies within the community. The results show that although a city may possess the necessary portfolio components as per Ziakas & Costa (2011), it is essential that there is a strategy that bridges the pieces of the portfolio for sustainable development. Consequently, we found that sequencing, or the strategic timing of events and political grounds, played a crucial role in this process.

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)0.001
metaresearch head score (Gemma)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.313

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0120.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.099
GPT teacher head0.318
Teacher spread0.219 · 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

Citations66
Published2014
Admission routes2
Has abstractyes

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