Legitimating Media: Shakespeare’s Awkward Travels Through Video Games and Twitter
Bibliographic record
Abstract
Abstract Since the 19th century, Shakespeare references have recurred with surprising consistency in experimental forms of media. This article considers the role of references to and adaptations of Shakespeare texts when a media form takes on a new valence for a set of users in a particular time and place. We consider two different moments at length: a commercial interactive game from 1984 that made novel use of cassettes and sound, and the production and reception of early Twitter adaptations of Shakespeare in 2010. By standing in for the aesthetic possibilities and limits of a changing media space, Shakespearean references and deviations from them serve a key role for artists and critics in debates over the legitimacy and significance of creative work in emergent media. Thus, cultural producers, critics and audiences thus use these sometimes-awkward appearances of Shakespeare as a means of describing their aesthetic potentials and limits.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.019 | 0.041 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".