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Record W2318044972 · doi:10.1093/ehr/ces265

Theatrical Nation: Jews and Other Outlandish Englishmen in Georgian Britain, by Michael Ragussis

2012· article· en· W2318044972 on OpenAlexaff
Daniel O’Quinn

Bibliographic record

VenueThe English Historical Review · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsGeorgianEthnic groupNational identityHistoryPopulationGender studiesSociologyClassicsPolitical scienceLawPoliticsDemographyPhilosophy

Abstract

fetched live from OpenAlex

Michael Ragussis, the distinguished scholar of anti-Semitism in nineteenth-century Britain, died shortly after the publication of this monograph. He has left behind a provocative polemic that will incite productive debate for many years to come. As in the case of his important Figures of Conversion: ‘The Jewish Question’ and English National Identity (1995), this present book is a significant intervention in multiple fields of enquiry. It offers a history of ethnic conflict in the British Isles during the late eighteenth century that counteracts Linda Colley’s arguments about the consolidation of British national solidarity from the Seven Years War onward. By focusing on conflict, dissension and on the sheer longevity of ethnic stereotypes, Ragussis mobilises a diverse archive of material which testifies to the fractious splintering of the population in a period of ostensible assimilation and national identification. Much of the book’s first chapter is concerned with building an argument for the importance of looking at how ethnicity is mobilised in representation. But the transformative aspect of this book is a shift in the field of analysis. Theatrical Nation is yet another example of how recent work on the theatre is changing our understanding of Georgian culture in quite fundamental ways.

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)0.002
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.101
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0030.004
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.283
Teacher spread0.250 · 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
Published2012
Admission routes1
Has abstractyes

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