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
Introduction Sporting Capital: Multinational and Transnational Corporatism David L. Andrews, University of Maryland, Michael L. Silk, University of Maryland and C.L. Cole, University of Illinois Section One: Multinational Sporting Corporatism Professional Sport Teams, Global Logos, and the Global Media/Entertainment Industry: A Political Economy of Transnational Sport Jean Harvey and Alan Law, both at University of Ottawa Corporatizing Sport: Adidas, ISL and the Reshaping of Sports Political Economy Alan Tomlinson, University of Brighton Marketing Generosity: The Avon Worldwide Fund for Womens Health and the Reinvention of Global Corporate Citizenship Samantha King, Queens University SEGA Dreamcast: National Football Cultures and the New Europeanism Philip Rosson, Dalhousie University, Canada Fram Pac Bell to the Tokyo Dome: Baseball and Economic Nationalism Jeremy Howell, University of San Francisco Section Two: Transnational Sporting Corporatism Every Girls a Superhero: Corporate (Trans)Nationalism(s), Womens Soccer, and Global (W)USA Michael D. Giardina and Jennifer L. Metz, University of Illinois Imagining Benevolence and Nation: Tragedy, Sport and the Transnational Marketplace Mary G. McDonald, Miami University, Ohio Making it Local?: NBA Expansion and the English Basketball Subculture Mark Falcous, University of Otago and Joseph Maguire, Loughborough University Cultural Contradictions / Contradicting Cultures: The Corporate Transnationalization of China? Trevor Slack, University of Alberta, Michael L. Silk, University of Maryland and Fan Hong, DeMontfort University Sport, Tribes and Technology: The New Zealand All Blacks Haka and the Politics of Identity Steven J. Jackson and Brendan Hokowhitu, both at University of Otago, New Zealand Beyond Sport: Imaging and Re-imaging Guiness as a Global Brand John Amis, University of Memphis
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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