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Record W2408773462 · doi:10.1057/9781137461964_1

Introduction: Into the Eurozone: European Dimensions of British Romanticism, Then and Now

2015· book-chapter· en· W2408773462 on OpenAlexaff
Steve Clark, Tristanne Connolly

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2015
Typebook-chapter
Languageen
FieldArts and Humanities
TopicTravel Writing and Literature
Canadian institutionsSt. Jerome's University
Fundersnot available
KeywordsRomanticismEnlightenmentHistoryRomanceScottish EnlightenmentOrientalismLiteratureColonialismArt historyArtPhilosophyArchaeology

Abstract

fetched live from OpenAlex

Studies of Enlightenment tend to take as their starting point the issue of whether the movement should be regarded as a unified phenomenon, based not only on circulation of texts but on networks of personal connection, such as Hume in Paris and Gibbon in Geneva, and Voltaire and Rousseau in Britain. European Romanticism tends to be perceived apart from these interactions, instead divided up into indigenous traditions, each embedded in its own distinctive language, ethnicity and popular culture. In contrast to the exhaustive attention paid to colonial contexts, comparatively little has been given to the interrelation of British Romanticism to other European national variants. James Chandler’s Cambridge History of English Romantic Literature (2009) does not even have an index entry for Europe. It includes essays by David Simpson on ‘France, Germany, America’, Esther Schor on ‘The “Warm South”’, and Mary Favret on ‘Writing, Reading and the Scenes of War’; overall coverage, however, remains minimal. Nicholas Roe’s Romanticism: An Oxford Guide allots ten pages of over 700 to one essay on ‘Europe’ by Christoph Bode, while Michael Ferber’s Companion to European Romanticism omits Scandinavia, Holland and Belgium, Portugal and almost the whole of Eastern Europe (only containing entries on Poland and Russia). This collection seeks to consider what British Romanticism looks like when its own international connections and circulations are taken into account. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.000
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.031
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.002
Scholarly communication0.0050.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0310.006

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 head0.020
GPT teacher head0.204
Teacher spread0.184 · 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
Published2015
Admission routes1
Has abstractyes

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