Bibliographic record
Abstract
Why Baseball? attempts to answer the personal question of what led a kid from the Canadian prairies to a lifelong love of America’s pastime and explore the larger question of other Canadians’ connection to the game through a close reading of several recent books on the topic. The books under review are Andrew Forbes’ The Utility of Boredom and The Only Way Is The Steady Way, Stacey May Fowles’ Baseball Life Advice: Loving the Game that Saved Me, Mark Kingwell’s Fail Better: Why Baseball Matters, Andrew North (Editor)’s Our Game, Too: Influential Figures and Milestones in Canadian Baseball, Dale Jacobs and Heidi LM Jacobs’ 100 Miles of Baseball: Fifty Games, One Summer, and Heidi Jacobs’ 1934: The Chatham Coloured All-Stars’ Barrier-Breaking Year. This review essay blends anecdotes from the author’s life with quotes from the selected books to suggest that Canadian baseball fandom is not a unique experience but one experienced uniquely.
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 | 0.001 | 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) | 0.088 | 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".