Bibliographic record
Abstract
The saga of New York's push to build two minor-league baseball stadiums, colored by dollars, politics, and dreams. Bush League, Big City tells the interwoven stories of two low-level minor league baseball teams brought to New York City in the late 1990s. It also illuminates the history of the New York-Penn League, America’s oldest and longest-running minor league, from its inception in 1939 until its abrupt contraction by Major League Baseball in 2020. With an eye for details and firsthand accounts by many of the baseball people involved, Michael Sokolow tells the story of two franchises that went in very different directions, as the Cyclones achieved astronomical success while Staten Island’s ‘Baby Bombers’ sank under the weight of debt and recriminations. Along the way, the book visits small communities in upstate New York, New England, and Canada, introduces the multimillionaires who came to dominate small-time baseball ownership, and tells the tale of two of the most expensive minor-league baseball stadiums ever built. It also sheds light on the complex, behind-the-scenes influence of New York City politics, as the indomitable will of Mayor Rudy Giuliani reshaped the geography of both the city and professional baseball. Bush League, Big City is a compelling examination of both the power and limits of nostalgia in a sport that is increasingly focused on the bottom line.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.298 | 0.092 |
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".