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Record W3013838454 · doi:10.5539/ijel.v10n3p177

Intertextual Relationships in Literary Genres

2020· article· en· W3013838454 on OpenAlexvenueno aff
Ayman Farid Khafaga

Bibliographic record

VenueInternational Journal of English Linguistics · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
FundersDeanship of Scientific Research, Prince Sattam bin Abdulaziz UniversityPrince Sattam bin Abdulaziz University
KeywordsOriginalityIntertextualityValue (mathematics)AsideLiteratureArtSociologySocial scienceMathematics

Abstract

fetched live from OpenAlex

Most contemporary playwrights acknowledge that Shakespeare’s dramas are for use as raw material to be assimilated into contemporary mould, not to be revered strictly as untouchable museum pieces. Being the model of all dramatists, Shakespeare had a great influence on English theatre, his plays are still performed throughout the world, and all kinds of new, experimental work find inspiration in them. This paper investigates the intertextual relationships between William Shakespeare’s King Lear (1606) and Edward Bond’s Lear (1978). The main objective of the paper is to explore the extent to which Bond manages to use Shakespeare’s King Lear as an intertext to convey his contemporary version of Shakespearean classic. Two research questions are tackled here: first, how does Shakespeare’s King Lear function as a point of departure for Bond’s contemporary version? Second, to what extent does Bond deviate from Shakespeare to prove his originality in Lear? The paper reveals that Bond’s manipulation of intertextuality does not mean that he puts his originality aside. He proves his originality by relating the events of the old story to contemporary issues which in turn makes the story keep pace with modern time.

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)0.004
metaresearch head score (Gemma)0.022
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 score0.018
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0100.010
Science and technology studies0.0060.019
Scholarly communication0.0180.011
Open science0.0020.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.062
GPT teacher head0.269
Teacher spread0.207 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of English LinguisticsSame topicShakespeare, Adaptation, and Literary CriticismFrench-language works237,207