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Record W1485555484

Shakespeare and England's Empire, 1780-1800.

2010· dissertation· en· W1485555484 on OpenAlexaboutno aff
Sarah Sheena

Bibliographic record

VenueWhite Rose eTheses Online (University of Leeds, The University of Sheffield, University of York) · 2010
Typedissertation
Languageen
FieldArts and Humanities
TopicHistorical Art and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEmpireAffectionParliamentSubjectivitySculptureContext (archaeology)British EmpireArtPaintingHistoryLiteratureArt historyPoliticsAncient historyLawPolitical sciencePsychologyPhilosophyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

This thesis is a study of Shakespeare and imperialism in England between 1780 and 1800. Chapters investigate landscape art and empire in the Boydell gallery, death and imperial subjectivity, gender and form in appropriations of Shakespeare by women artists and writers, caricatures that reference Shakespeare during these years, the use made of Shakespeare by prominent individuals to formulate their identities in the context of empire and the debates on the Quebec Bill in London’s parliament in May 1791. The thesis is primarily concerned to explore how gothic forms and representations were integrated into the history of Britain’s relationship to its empire; to assess the use of Shakespeare in academy painting and in forms such as engraving, graphic satire, relief sculpture and in writing. The study also emphasises affect: fear of imperial identities, the danger of overseas life, terror, nostalgia, affection in connection to the nation and its spaces, the increasingly imperial reach of relations with revolutionary France during these years, and pleasurable diversion in reappropriations of the plays in varying arenas.

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)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.225
Threshold uncertainty score0.448

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.008
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.001
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 head0.019
GPT teacher head0.191
Teacher spread0.172 · 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
GenreOther

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
Published2010
Admission routes1
Has abstractyes

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