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Record W3036943403 · doi:10.33137/rr.v41i2.29834

Sion and Elizium: National Identity, Religion, and Allegiance in Anthony Copley’s <i>A Fig for Fortune</i>

2018· article· en· W3036943403 on OpenAlexaffvenue
Lucy Underwood

Bibliographic record

VenueRenaissance and Reformation · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicScottish History and National Identity
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProtestantismHumanitiesArtArt historyPhilosophyReligious studies

Abstract

fetched live from OpenAlex

This article uses Anthony Copley’s poem A Fig for Fortune (1596) to examine Elizabethan constructions of national identity. Acknowledging that religious and national identities were symbiotic in the Reformation era, it argues that the interdependency of Protestant and Catholic narratives of “nationhood” must be appreciated. Analysis of Copley’s text engages with previous critiques, including those of Clare Reid, Alison Shell, and Susannah Monta, in order to propose a more coherent interpretation of Copley’s engagement with Spenser’s The Faerie Queene. Copley did not merely defend Catholics as loyal subjects; he moved beyond debates about loyalty to reconsider ideas of nation, England, and Englishness more broadly, challenging the premises as well as the conclusions of Protestant statesmen and writers. Cet article examine les constructions de l’identité nationale de l’Angleterre élisabéthaine à travers le poème d’Anthony Copley A Fig for Fortune (1596). En considérant que les identités religieuse et nationale étaient liées de façon symbiotique pendant la période de la Réforme, on avance que l’interdépendance des versions catholique et protestante des récits de nationalité devrait être mieux prise en compte. L’analyse du texte de Copley met à profit différents commentaires critiques, en autres ceux de Clare Reid, Alison Shell et Susannah Monta, afin de proposer une interprétation plus cohérente du travail de Copley sur The Faerie Queene de Spenser. Copley ne s’est pas contenté simplement de défendre les catholiques en tant que sujets loyaux, il en a également profité pour dépasser les débats au sujet de la loyauté, pour remettre en question les idées de nation, d’Angleterre, et plus généralement de ce que c’est que d’être anglais, et par conséquent aussi, les prémisses et conclusions des écrivains et hommes d’État protestants.

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)0.003
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 score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.014
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.261
Teacher spread0.235 · 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

Citations16
Published2018
Admission routes2
Has abstractyes

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