Bibliographic record
Abstract
About the author William Shakespeare (1564–1616) is one of the most influential writers of all time. Born and raised in Stratford-upon-Avon, he worked as a poet and as a dramatist and actor in the London theatres. He was a shareholder in the Lord Chamberlain's Men acting company (later the King's Men). Shakespeare retired from writing for the stage in 1613–14. In 1623, John Heminges and Henry Condell published the ‘First Folio’, a collection of thirty-six of Shakespeare's plays. Shakespeare's writings on memory have attracted more critical attention than any other poet of the period, with Hamlet's plaintive question ‘Must I remember?’ (1.2.143) alerting readers to the crucial intellectual and religio-political concerns surrounding issues of memory and remembrance in Reformation England. Shakespeare never refers explicitly to the memory arts (unlike Webster, Jonson and others), but his works show a fascination with how memory functions, individually and socially. For example, in Love's Labour's Lost , Shakespeare repeatedly turns to the mechanics of memory: ‘Begot in the ventricle of memory, / nourished in the womb of pia mater’ (1.1.99–100), ‘Why that contempt will kill the speaker's heart, / And quite divorce his memory from his part’ (5.2.150–1) and ‘A fever she / reigns in my blood and will remember'd be’ (4.3.96–7). Similarly, in The Two Gentlemen of Verona , Shakespeare employs a familiar mnemonic image: ‘Lest, growing ruinous, the building fall, / And leave no memory of what it was’ (5.4.10–11). Such mention of ruins may evoke a wider cultural concern about the English Reformation's break from the Catholic Church, with abandoned monasteries in ruins a familiar sight in the English countryside. A curious episode in Titus Andronicus , where a Goth soldier ‘stray[s]’ from his troop to ‘gaze upon a ruinous monastery’ (5.1.21) once more alerts us to such topical concerns. A formal, deliberate approach to memorisation and remembrance is also often present in his works. Examples include: ‘Blotting your names from books of memory’ (1.1.96) in 2 Henry 6 ; ‘I would forget it fain; / But, O, it presses to my memory, / Like damned guilty deeds to sinners' minds’ (3.2.110–12) in Romeo and Juliet ; ‘Except they meant to bathe in reeking wounds / Or memorise another Golgotha’ (1.2.39–40) in Macbeth ; and ‘Yea, beg a hair of him for memory’ (3.2.131) in Julius Caesar .
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.053 | 0.028 |
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".