Bibliographic record
Abstract
Selected from thousands of pages of the daily journals of George Fetherling - the inexhaustible novelist, poet, and cultural commentator - The Writing Life reveals an astute and candid observer of his contemporaries as well as himself. Hundreds of figures in the arts and public life crisscross the pages of Fetherling's journals, from Margaret Atwood and Marshall McLuhan, to Gwendolyn MacEwen and Conrad Black. The book begins in mid-1970s Toronto, a time of cultural ferment, and carries on to Vancouver and a new century. A captivating and intimate narrative, The Writing Life provides a compelling portrait of the last three decades of Canadian cultural life. From the book: Tuesday 4 February 1992 / Toronto Early this morning the latest in a series of strange phone calls from Edmund Carpenter in New York to discuss successive versions of his Canadian Notes & Queries piece on Marshall McLuhan. He falls to reminiscing and at one point says: "Marshall always reminded me of that passage in Boswell in which Boswell says that if you chanced to take shelter from a rain storm for a few minutes in Dr Johnson's company, you would come away convinced that you had just met the smartest man in the world. Marshall was like that too. Of course, if you spent an hour with Marshall, well, that was something quite different."
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.017 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.092 | 0.064 |
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".