Bibliographic record
Abstract
John B. Wiseman, ed. Joy in Mudville: Essays on Baseball and American Life. Jefferson, NC: McFarland, 2010. 252 pp. Paper, $39.95. Historian and enthusiast John B. Wiseman has brought together a fine collection of essays, personal reflections, and interviews that provide a history of the game of baseball, as well as a reminder of why it has remained popular despite its many setbacks. In fact, one of the great joys of this collection is the candid treatment of the social, financial, and other problems faced by the leagues, the various teams, and individual players. Far from a romantic paean to the national pastime, Joy in Mudville provides astute criticism as well as careful analysis, sure to be of interest to both the casual reader as well as academic historians, to say nothing of baseball's devoted fans. Organized so that the reader can follow baseball's development from its early years to the contemporary era, the single unifying theme of the collection is baseball as Americana, exploring how has served as a marker for the larger American society. Parts I and II, Baseball's Rise and a Cast of Characters and Beyond the Majors, provide a thoughtful balance between the history of the sport and focused attention on specific players. In both cases, the essays connect the game of to American culture at large. Even if at times these essays overlap in subject matter, such occurrences are a welcome reminder that players and events can be read in different contexts. More importantly, these essays include discussions of groundskeepers, radio broadcasters, and leagues (such as the West Virginia Coalfield and Negro National League), all of which help remind the reader just how enmeshed was in the daily lives of various communities, as well as how the development of the game depended on more than just the players and fans. Ultimately, as Peter Morris persuasively argues in his contribution, is America's game precisely because America as a whole shaped its development; in both its style of play and its history, is a truly democratic endeavor. Part III, Transcending Race, is, in the opinion of this reviewer, the gem of this collection. Bringing together three pieces about Jackie Robinson and one on Minnie Minoso, this section reminds its readers just how important racial integration was to the survival of in an America that witnessed rapidly changing racial demographics and significant social upheaval over questions of racial equality. …
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".