Post-Olympism? Questioning Sport in the Twenty-First Century
Bibliographic record
Abstract
The Future of Multi-Sport Mega Events Richard Cashman, University of New South Wales Troping Along: A Historian's View of Olympic Scholarship Douglas Booth, University of Otago Citius, Altius, Fortius: A Critique and a Reinterpetation Sigmund Loland, Norwegian Sports University, Oslo What's the Difference between Propaganda for Tourism or for a Political Regime? The 1936 Olympics in World Perspective Arnd Krger, University of Gttingen Accelerating Olympism: The Poetics and Problematics of Nano, Virtual, and Cyborg Sport Technologies Synthia Sydnor, University of Illinois The Aesthetic Dimensions of Sport Soren Damkjaer, University of Copenhagen Drugs and the Olympics in the Context of Aesthetics Verner Moller, University of South Denmark, Odense Olympic Legacies: Sport, Space and the Practices of Everyday Life Douglas Brown, University of Alberta Olympism, Post-Humanism and the Spectacle of Race Ben Carrington, University of Brighton China and Olympism Susan Brownell, University of Missouri, St Louis The Global, the Popular and the Inter-Popular: Olympic Sport between Market, State and Civil Society Henning Eichberg, IFO, Denmark Laying Olympism to Rest Kevin Wamsley, University of Western Ontario Sportive Nationalism in an Age of Globalization John Hoberman, University of Texas Making the World Safe for Global Capital? The Sydney 2000 Olympics Helen Lenskyj, University of Toronto The Disneyfication of the Olympics: Selling the Spectacle Alan Tomlinson, University of Brighton
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 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".