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Record W2425778508 · doi:10.3138/md.2957r

Compromised Epistemologies: The Ethics of Historiographic Metatheatre in Tom Stoppard’s <i>Travesties</i> and <i>Arcadia</i>

2016· article· en· W2425778508 on OpenAlexvenueno aff
Phillip Zapkin

Bibliographic record

VenueModern Drama · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArcadiaNarrativeLiteratureArtValue (mathematics)HistoriographyAestheticsFace (sociological concept)MistakePhilosophyHistoryLawLinguisticsComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Tom Stoppard uses historiographic metatheatre to question the efficacy of historical narratives: plays such as Travesties directly address the constructed texture of history. However, partially because the 1809 scenes in Arcadia are naturalistic, critics generally accept Arcadia as presenting a “real” history. But taking anything in Stoppard’s plays at face value is a crucial mistake. Instead, we should read Arcadia as participating in a self-consciously destabilizing cultural project building a historiography of error – like Travesties, but through a less obviously constructed historiographic metatheatre – a reading that prompts us to reconsider standard narratives of Stoppard’s development as a playwright of epistemological uncertainty. Part of Stoppard’s joyous humour in Arcadia goes beyond satirizing Bernard and extends to the critical misreadings through which we, as critics, reproduce Bernard’s unreliable thesis and, like him, risk convincing ourselves that we are right. Taking Arcadia at face value undermines the ethical imperative to uncertainty and multiplicity inherent in historiographic metatheatre, an ethic that runs through both Travesties and Arcadia.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.873
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.042
GPT teacher head0.242
Teacher spread0.199 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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