Book reviews
Bibliographic record
Abstract
No Logo: Taking Aim at the Brand Bullies. Klein, N. (1999). New York: Picador. 490 pages. France and the 1998 World Cup, the National Impact of a World Sporting Event. Dauncey, H. and Hare, G. (eds.). (1999). Frank Cass, London, UK and Portland, Oregon, USA. 232 pages. A Narrative Approach to Organization Studies. Czarniawska, B. (1998). Thousand Oaks: Sage. 78 pages. Globalization and Sport: Playing the World. Miller, T., Lawrence, G., McKay, J, and Rowe, D. (2001). London: Sage. 160 pages. Sport Marketing (2nd Edition). Mullin, B.J., Hardy, S., & Sutton, W.A. (2000). Champaign, IL: Human Kinetics Publishers. 456 pages. Negotiating on Behalf of Others. Mnookin, R. H., & Susskind, L E., Foster, P. C. (Eds.). (1999). Sage Publications Ltd., London, UK. 288 pages. Sport In The City: The Role of Sport In Economic and Social Regeneration. Gratton, C. and Henry, I. P., (Eds.). (2001) London: Routledge, 322 pages. Sport Ethics: Concepts and Cases in Sport and Recreation. Malloy, D., Ross, S., and Zakus, D. H. (2000). Toronto: Thompson Educational Publishing. 192 pages.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.515 | 0.463 |
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".