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Record W3158550351 · doi:10.24908/iqurcp.7221

Playing With Time: An Analysis of Time and Space in Tom Stoppard’s Rosencrantz and Guildenstern Are Dead

2017· article· en· W3158550351 on OpenAlexvenueno aff
Johanna Lawrie

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsHAMLET (protein complex)Presentation (obstetrics)ArtLiteratureMultitudeSpace (punctuation)AestheticsHistoryPhilosophyEpistemologyLinguistics

Abstract

fetched live from OpenAlex

In this paper I will examine the multiple layers of time within Tom Stoppard’s play, Rosencrantz and Guildenstern Are Dead. Typically, a script plays with two definitions of the term: stage time being that of the audience and the “real world,” and dramatic time, the passing of time within the world of the play and the characters’ lives. Rosencrantz and Guildenstern Are Dead is unique in its multitude of times, each occupying its own space within the story. Hamlet resides in a time that extends beyond that of Rosencrantz and Guildenstern Are Dead, while presenting the same story through different characters. When are these stories presented harmoniously, and when can gaps be found between the two plays in terms of time? In contrast, the play‐within‐a‐play presented in Rosencrantz and Guildenstern Are Dead, titled “The Murder of Gonzago,” represents the story even prior to the opening scene of Hamlet and has an omniscient quality, presenting elements of both Hamlet and Rosencrantz and Guildenstern Are Dead. Though this play‐within‐a‐play represents the longest view of the overlapping stories, it is presented in the shortest amount of time. “The Murder of Gonzago” plays with the limitations of time and space and the acknowledgment of their presentation in theatrical terms. Throughout the paper I will determine the overlapping nature of times within the plays, how they are structured around one another, and what this symbolises for both the spaces of each play and the characters within.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.012
Scholarly communication0.0070.005
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.107
GPT teacher head0.341
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2017
Admission routes1
Has abstractyes

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