Encyclopedia of sports management and marketing
Bibliographic record
Abstract
Encyclopedia of Sports Management and Marketing. Edited by Linda E. Swayne and Mark Dodds. Los Angeles: Sage Reference, 2011. 4 vols. $695 (ISBN: 978-1-4129-7382-3). E-book available (ISBN: 978-1-412-99415-6), $895. According to the publisher, the goal of this four-volume reference work is to provide comprehensive and authoritative overview of the state of sports management and marketing today (publisher's publicity flyer). The coeditors, both highly qualified academics with established credentials, also feel that this fairly new academic field needs a work that covers its very wide spectrum and helps legitimize this area as an academic discipline. The 328 authors of the entries are all from colleges and universities; they are listed with their affiliation in volume 1. Full color illustrations are scattered throughout the text. The 825+ entries are arranged alphabetically and are the meat of the encyclopedia. They range from around one to eight pages. Each United States and Canadian professional team has an entry that goes beyond history and key figures to include brand management, marketing challenges, and ownership. One of the more interesting entries is Integration of Sport, Globalization, and Commercialization. The author begins with a general discussion of the terms and then narrows it down to sport. After that, sport, place, and commerce is discussed, then two case studies. One is about the branding of the New Zealand Blacks men's rugby team and the second about Michael Jordan as representative of the evolving nature of commercialization, globalization, and sport. A further case focuses on challenges facing female athletes. The author concludes the entry with his name and affiliation, five see also references, and seven further reading suggestions which include books, journal articles, and online references. Sports marketing is addressed in two ways: marketing of sports and sport-related products and the marketing of non-sports products and brands through sports figures or events. The terms and examples in this encyclopedia range from the very broad (Benchmarking) to the less broad (Tort Issues in Sports), to the very specific (Pricing of Parking). Front contents include a reader's guide, which groups the entries into 21 broad topics ranging from advertising (29 entries) to team management and marketing (138 entries). Other topics include sponsorship, social marketing, news media, legal, and financing of sports. A sixteen-page alphabetical list of entries appears at the front of each volume. …
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.270 | 0.150 |
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".