Bibliographic record
Abstract
The Expos' move from Montreal to Washington, DC, and subsequent rebirth as the Nationals, was one of the sports success stories of 2005. As a result of the move, the team has enjoyed significant increases in home attendance and cash flow, broadcast revenues, and market valuation. This is but one example of the impact of sports league reorganization, a phenomenon as old as the leagues themselves. Frank Jozsa takes us on a tour, from the 1870s to the present, of the expansions and mergers, relocations and transfers that are constantly shifting the professional sports landscape. Incorporating concepts from economics, demographics, management, and marketing, he explains the successes and failures of such efforts in baseball, football, basketball, hockey, and soccer, including their effects on team competitiveness, market share, and prosperity—and their impact on the communities in which they operate. Arguing that professional sports teams are profit-maximizing businesses, Jozsa's analysis sheds light on the economics, culture, and politics of sports as big business, as decisions are made and implemented, and offers an insightful perspective on both the history and future of sports franchises. The Expos' move from Montreal to Washington, DC, and subsequent rebirth as the Nationals, was one of the sports success stories of 2005. As a result of the move, the team has enjoyed significant increases in home attendance and cash flow, revenues from local radio and television rights, and the estimated market value of the franchise—from $50 million to over $300 million in one year. This is but one example of the impact of sports league reorganization, a phenomenon as old as the leagues themselves. Frank Jozsa takes us on a tour, from the 1870s to the present, of the expansions and mergers, relocations and transfers that are constantly shifting the professional sports landscape. Incorporating concepts from economics, demographics, management, and marketing, he explains the successes and failures of such efforts in baseball, football, basketball, hockey, and soccer, including their effects on team competitiveness, market share, and prosperity—and their impact on the communities in which they operate. Arguing that professional sports teams are profit-maximizing businesses, Jozsa's sharp analysis sheds light on the economics, culture, and politics of sports as big business, as decisions are made and implemented. In addition to providing a unique perspective on the history and culture of sports management, he offers insightful commentary on the future prospects of sports franchises.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.021 | 0.016 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.100 | 0.042 |
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".