Book Review: Leon Craig. <em>Of Philosophers and Kings: Political Philosophy in Shakespeare's Macbeth and King Lear</em>. Toronto: University of Toronto Press, 2001.
Bibliographic record
Abstract
remain firmly committed to these notions.Dawson even-handedly assesses strengths and shortcomings of both these conflicting views.There is much pleasure in this book.Alexander Leggatt wonderfully compares legendary Canadian indecisiveness (evident perhaps in the question mark in this collection's title) with the characteristic Shakespearean 'refusal to take sides' that Keats called 'negative capability'.In addition to enjoying the droll doings of Canadian anti-Stratfordians as chronicled by Paul Yachnin and Brent E. Whitted in the essay 'Canadian Bacon', I was delighted to learn that on 2 July 1951, a mulberry tree, 'purportedly a scion of the true Shakespeareean root', was ceremoniously planted in the Trinity College quadrangle at the University of Toronto (Makaryk 21).And I rejoiced to be informed that 'in 1990, a Canadian living in Oxford set the speech record for reciting Hamlet's "To be or not to be" soliloquy' (24 seconds) (38).Both as a thought-provoking cultural critique and as a treasury of delectable information, this book is outstanding.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.082 | 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".