MétaCan
Menu
Back to cohort
Record W1874872224 · doi:10.1123/jsm.22.2.135

Evolution and Issue Patterns for Major-Sport-Event Organizing Committees and Their Stakeholders

2008· article· en· W1874872224 on OpenAlexaffabout
Milena M. Parent

Bibliographic record

VenueJournal of Sport Management · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsStakeholderHierarchyPoliticsPublic relationsStakeholder analysisSociologyBusinessPolitical scienceLaw

Abstract

fetched live from OpenAlex

The purpose of this article is to develop a framework of how organizing committees operationally evolve and the types of issues with which they and their stakeholders must deal. Based on a combination of stakeholder theory and issues management, a case study of the 1999 Pan American Games held in Winnipeg, Canada, was built using archival material and interviews. Three major organizing-committee operational modes emerged: planning, implementation, and wrap-up. Issue categories faced by the organizing committee and its stakeholders included politics, visibility, financial, organizing, relationships, operations, sport, infrastructure, human resources, media, interdependence, participation, and legacy. Issue-category prominence depended on the operational mode and organizing-committee member hierarchical level, such that issues became less strategic and broad as one moved through operational modes or down the hierarchy. Issue categories also differed within stakeholder groups, whereas stakeholder interests (material, political, affiliative, informational, and symbolic) differed between stakeholder groups.

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)0.015
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.047
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.005
Science and technology studies0.0040.003
Scholarly communication0.0060.005
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.054
GPT teacher head0.284
Teacher spread0.230 · 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 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

Citations196
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Sport ManagementSame topicSport and Mega-Event ImpactsFrench-language works237,207