Bibliographic record
Abstract
The third edition of Governance and Policy in Sport Organizations introduces readers to the power and politics of sport organizations. It explores the managerial activities essential to governance and policy development, and it looks at the structure and function of organizations like those with which readers will interact in the workplace. It also demonstrates where the power lies in an organization or industry segment and how individual sport organizations fit in to the greater industry. Current policy issues and the ethical questions they raise are also addressed. Real-world case studies demonstrate the types of dilemmas that sport managers face every day. In addition, professional administrators from a wide variety of sport organizations contribute their perspectives, giving readers a glimpse into the real concerns of sport professionals and the impact of governance and policy on their jobs. The book's practical foundations, readability, and logical organization all help readers to understand the big picture of the sport industry and their place in it as future sport managers.New to the third edition is a chapter on individual professional sport, which explores how this industry segment differs from professional sport leagues. In addition, contributions from Thierry Zintz, from the Universite catholique de Louvain, offer insights into European sport organizations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".