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Record W2732170352 · doi:10.3968/9352

Atwood’s Recreation of Shakespeare’s Miranda in The Tempest

2017· article· en· W2732170352 on OpenAlexvenueno aff
Awfa Hussein Al-Doory

Bibliographic record

VenueStudies in literature and language · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsTempestAppropriationLiteratureInnocenceWitchArtDramaSociologyPhilosophyPsychoanalysisEpistemology

Abstract

fetched live from OpenAlex

In The Tempest , Shakespeare portrays Miranda as a character which follows the path designed for her by Prospero, her father. Margret Atwood, through appropriating and intertextualizing Shakespeare’s The Tempest , reconstructs Miranda to be a motivator of action rather than a receiver of a patriarchal power. It is through recreating Shakespeare’s Miranda, Atwood gives her more spaces of critical analysis rather than being critically confined to the frame of femininity. This paper argues that Atwood’s Hag-Seed , by means of intertextuality and appropriation, recreates a new Miranda who is almost ignored by critical studies that focus mainly on reading The Tempest from post-colonial perspectives. As a feminist, though she claims not to be, Atwood consciously employs Shakespeare’s conceptual and thematic concerns like a play within a play, revenge, usurpation, and the father-daughter relationship. These concerns, which are mainly tackled in The Tempest , are employed by Atwood for the sake of creating a new Miranda who would determine and motivate the whole action of Hag-Seed . Atwood’s appropriation, this paper argues, is a feminist revision of a canonical text that limits woman’s role, and presents her either with the quality of passive innocence, or with that one of the devilish witch.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.305

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 studies0.0000.000
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 head0.044
GPT teacher head0.343
Teacher spread0.298 · 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 designQualitative
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

Citations1
Published2017
Admission routes1
Has abstractyes

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