Bibliographic record
Abstract
People have been working on “what to do with Shakespeare” – a more accurate, if more awkward term than “adapting” – for over four hundred years. Even in England in his own lifetime fellow playwrights were citing, rewriting and contesting the work of this “upstart crow.” His younger colleague and collaborator, John Fletcher, went so far in 1611 as to write The Woman’s Prize; or The Tamer Tamed, a fanciful sequel and arguably protofeminist response to The Taming of the Shrew. Since then, reproductions, homages, appropriations, exploitations, citations, translations, adaptations and tradaptations of various kinds, dramatic and otherwise, have surfaced in an astonishing range of historical periods and cultural contexts, ranging from respectful updatings and popularizings in classic cartoons and mainstream modern dress productions to resistant rewritings such as, archetypically, Aimé Césaire’s postcolonial La Tempête. “Shakespeare” has been appropriated in the service of everything from “Ye Olde” faux Tudor “Shakespeare Arms” pubs everywhere, through conservative cultural critiques such as Robertson Davies’ Tempest Tost, to armaments advertising that links Shakespeare’s Globe, early modern imperialism and Britain’s contemporary global arms trade; from journalistic accounts of the O.J. Simpson trial (Othello) through, in Canada, pop-music, de- or re-contextualized settings of Hamlet’s “Never Doubt I Love” by singer/songwriter Melanie Doane, to irreverent, almost gratuitous gestures directed at the Shakespearean high-cultural sheen, as in the album title, Shakespeare My Butt, by the rock group, Lowest of the Low (which includes no other references to Shakespeare). The gesture positions Shakespeare on the wrong side of the Pink Floyd rock culture anthem, “We don’t need no education/We don’t need no mind control,” an agent of what Louis Althusser has taught us to call the Ideological State Apparatus.
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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.573 | 0.411 |
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".