The Playing’s the Thing: A Ludic Approach to Diversifying Digital Shakespeare
Bibliographic record
Abstract
An examination of the potential for diversifying digital Shakespeare scholarship through a ludic approach. After arguing for game-making as a scholarly activity, a survey of the history of Shakespeare and digital games is followed by a discussion of how two interactive digital works—Golden Glitch's Elsinore and Lapin Lunarie Games's Elsinore: After Hamlet—offer models for thinking through creative/critical ways of diversifying digital Shakespeare.Il s'agit d'une étude du potentiel de diversification de la recherche numérique sur Shakespeare par une approche ludique. Après avoir défendu la création de jeux en tant qu'activité scientifique, une étude de l'histoire de Shakespeare et des jeux numériques est suivie d'une discussion sur la manière dont deux œuvres numériques interactives - "Elsinore" par Golden Glitch Studios et "Elsinore : After Hamlet" de Lapin Lunarie Games - offrent des modèles de réflexion sur les moyens créatifs et/ou critiques de diversifier le Shakespeare digital.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.031 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".