Baseball without borders: the international pastime
Bibliographic record
Abstract
Introduction: Around the Horn - George GmelchPart 1. Asia1. Japan: Changing of the Guard in High School Baseball - Dan Gordon 2. Japan: The Hanshin Tigers and Japanese Professional Baseball - William W. Kelly 3. China: Silk Gowns and Gold Gloves - Joseph A. Reaves 4. Taiwan: Baseball, Colonialism, and Nationalism - Andrew Morris 5. Korea: Straw Sandals and Strong Arms - Joseph A. ReavesPart 2. The Americas6. Dominican Republic: Forging an International Industry - Alan Klein 7. Cuba: Behind the Curtain - Tim Wendel 8. Cuba: Community, Fans, and Ballplayers - Thomas Carter 9. Puerto Rico: A Major League Steppingstone - Thomas E. Van Hyning and Franklin Otto 10. Nicaragua: In Search of Diamonds - Dan Gordon 11. Brazil: Baseball Is Popular, and the Players Are Japanese! - Carlos Azzoni, Tales Azzoni, and Wayne Patterson 12. Canada: Internationalizing America's National Pastime - Colin HowellPart 3. Europe13. Italy: No Hotdogs in the Bleachers - Peter Carino 14. Holland: An American - Coaching Honkbal - Harvey Shapiro 15. Great Britain: Baseball's Battle for Respect in the Land of Cricket, Rugby, and Soccer - Josh ChetwyndPart 4. The Pacific16. Australia: Baseball Down Under - Joseph ClarkAfterword: Is Baseball Really Global? - George Gmelch
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 | 0.000 | 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 | 0.000 | 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) | 0.016 | 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".