Bibliographic record
Abstract
Introduction: Borders, Boundaries and Crossings: Sport, Migration and Identities Section 1: Patterns of Migration and Sport 1. From the South to Europe: A Comparative Analysis of African and Latin American Football Migration 2. Why Tax Athletes' International Migration? The Coubertobin Tax in a Context of Financial Crisis 3. Moving with the Bat and the Ball: the Migration of Japanese Baseball Labour 1912-2009 4. From the Soviet Bloc to the European Community: Migrating Professional Footballers in and out of Hungary Section 2: Bridgeheads in Migration and Sport 5. Preliminary Observations on Globalisation and the Migration of Sport Labour 6. Sports Labour Migration as a Global Value Chain: The Dominican Case 7. Net-Gains': Informal Recruiting, Canadian Players and British Professional Ice Hockey 8. Have Board will Travel: Global Physical Youth Cultures and Transnational Mobility Section 3: Experiences of Migration and Sport 9. Migrants, Mercenaries, and Overstayers: Talent Migration in Pacific Island Rugby 10. Blade Runners: Canadian Migrants and European Ice Hockey 11. Female Football Migration: Motivational Factors for Early Migratory Processes Section 4: Identities in Migration and Sport 12. Globetrotters in Local Contexts: Basketball Migrants, Fans and Local Identities 13. Diaspora and Global Sports Migration: A Case Study in the English and New Zealand Context 14. Tries for the Nation?: International Rugby Players' Perspectives on National Identity Section 5: Impacts of Migration on Sports and Societies 15. The New International Division of Cultural Labour and Sport 16. Transnational Athletes: Celebrities and Migrant Players in Futbol and Hockey 17. Out of Africa: The Exodus of Elite African Football Talent to Europe 18. Touring, Travelling and Accelerated Mobilities: Team and Player Mobilities in New Zealand Rugby Union. Future Directions: Sporting Mobilities, Immobilities and Moorings
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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 | 0.000 | 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 | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".