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Record W4402613449 · doi:10.18778/2083-8530.29.09

Shakespeare and Covid Drama in This England (Winterbottom, 2022)

2024· article· en· W4402613449 on OpenAlexfundno aff
Agnieszka Rasmus

Bibliographic record

VenueMulticultural Shakespeare Translation Appropriation and Performance · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
FundersUniversity of TorontoUniversity of OxfordUniversity of Cambridge
KeywordsCoronavirus disease 2019 (COVID-19)Drama2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)HistoryLiteratureArtMedicineVirologyInternal medicineOutbreak

Abstract

fetched live from OpenAlex

This article considers the significance of different Shakespearean allusions in a political docudrama miniseries This England (2022), directed for Sky by Michael Winterbottom and scripted by Winterbottom and Kieron Quirke. The action focuses on the first crucial months in England after the outbreak of the Covid-19 pandemic, offering a panoramic view of the nation under duress as a newly formed government, with Boris Johnson at its helm, mishandles the crisis. The article seeks to explain the presence of multiple Shakespearean references, from the title alone, through numerous direct quotations to the casting of Kenneth Branagh as Johnson. Shakespearean traces play a pivotal, though confusing, role as they both critique the actions of the government and its leader by offering an ironic framing device while increasing the viewer’s sympathy for its central protagonist via the presence of a Shakespearean celebrity.

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 score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.015
Scholarly communication0.0070.003
Open science0.0000.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.034
GPT teacher head0.245
Teacher spread0.211 · 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
Published2024
Admission routes1
Has abstractyes

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