Evolution and Issue Patterns for Major-Sport-Event Organizing Committees and Their Stakeholders
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".