Risk Management in Major Sporting Events: A Participating National Olympic Team's Perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article explores the process of risk management in a major sporting event from the perspective of a participating team. More specifically, the article examines how Norway's national team before and during the 2010 Olympic Winter Games (OWG) in Vancouver (i) identified the risk management issues, and (ii) handled risk strategies. The qualitative case study reported here draws upon documents and interviews with key actors in the Norwegian Top Sports Program (Olympiatoppen) and other important stakeholders for the preparation and implementation of the Vancouver project based on the experiences from 2006 OWG in Turin, Italy. The article utilizes previous research on risk management and strategic management in order to analyze a participating team's preparation and implementation. A framework for dealing with risk management issues experienced by participating teams at sporting events is provided.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it