Bibliographic record
Abstract
Active for over forty years with the Communist Party of Canada, Bert Whyte was a journalist, an underground party organizer and soldier during World War II, and a press correspondent in Beijing and Moscow. But any notion of him as a Communist party hack would be mistaken. Whyte never let leftist ideology get in the way of a great yarn. In Champagne and Meatballs — a memoir written not long before his death in Moscow in 1984 — we meet a cigar-smoking rogue who was at least as happy at a pool hall as at a political meeting. His stories of bumming across Canada in the 1930s, of combat and camaraderie at the front lines in World War II, and of surviving as a dissident in troubled times make for compelling reading. The manuscript of Champagne and Meatballs was brought to light and edited by historian Larry Hannant, who has written a fascinating and thought-provoking introduction to the text. Brash, irreverent, informative, and entertaining, Whyte's tale is history and biography accompanied by a wink of his eye — the left one, of course
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 | 0.002 | 0.004 |
| Science and technology studies | 0.043 | 0.013 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".