Key leadership qualities for major sporting events: the case of the World Aquatics Championships
Bibliographic record
Abstract
The purpose of this study was to examine specific leadership qualities identified as important by stakeholders of large-scale sporting events. The 2005 'Federation Internationale de Natation' (FINA) World Aquatics Championships was used to build a case for determining what leadership qualities were necessary throughout the evolution of the event. The data, collected through means of archival material and interviews of the organising committee and its stakeholders, emphasised the importance of networking and human resource management as key leadership skills. Leadership qualities depended on the organising committee's mode (planning, implementation, wrap-up) and included, for example, financial skills, ability to access resources, credibility, and communication and public relations. Each of the qualities could then be classified as either an antecedent or a consequence of networking, thus supporting networking and its political, business and sport components as being a critical leadership quality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".