Bibliographic record
Abstract
Does hockey provide a better understanding of the differences between Canadian and Québécois nationalisms? Is there a fundamental relationship between the hockey arena and the political arena? What have we lost as a society in abolishing the tie game? Are salaries in the NHL really that outrageous? Is hockey more art than sport? Should hockey players be banned from using performance-enhancing drugs at all costs? Do goalies suffer from angst? Does our national sport have its own mythology and metaphysics? Do hockey brawls reflect our true human nature more than we would care to admit? And what would it be like if the great philosophers were to face off on the ice? A team of philosophy and hockey buffs go deep with these fascinating questions and many others in this examination of a worshipped sport elevated to something akin to a cult. Accessibly written and peppered with humour, the essays in this book will charm specialists, sports fans, and everyone in between. Whether you’re a fan of Richard, Gretzky, Crosby, Plato, Kant, or Kierkegaard, you’re invited to be a spectator at this very special meeting of minds!
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 | 0.001 | 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 | 0.008 | 0.014 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".