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Record W4404742549 · doi:10.18274/zarb5225

Staging Shakespeare in Social Games: Towards a Theory of Theatrical Game Design Authors

2023· article· en· W4404742549 on OpenAlex
Jennifer Roberts-Smith, Shawn DeSouza-Coelho, Toby Malone

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBorrowers and Lenders The Journal of Shakespeare Appropriations · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsGame designVideo game designGame theoryGame mechanicsSociologyPsychologyComputer scienceAestheticsArtMultimediaMathematical economicsMathematics

Abstract

fetched live from OpenAlex

This essay discusses the theoretical implications of a recent experiment with game-based social media to increase Shakespeare literacy in eleven to fifteen-year-olds. In collaboration with the Stratford Festival, we aimed to make the gameplay of our pilot, Staging Shakespeare, and the social space it generated, experientially theatrical in some way. While the pilot itself was not, in our view, successful, the design process helped us articulate a theory of theatricality grounded in the ontological complexity of theatrical things and the ontogenetic conditions of theatrical environments. Our conclusion is that literal simulations of Shakespeare's plays or of Shakespearean theater production may not be the richest way to teach Shakespeare through social games. Instead, we may need a design theory grounded in the adaptation of theatrical principles to electronic media, and perhaps a new aesthetic and even a rhetoric of gameplay only associatively related to Shakespeare.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.071
GPT teacher head0.323
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it