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Record W2100997225 · doi:10.7202/009258ar

“Was it for this [. . .]?”: The Poetic Histories of Southey and Wordsworth

2004· article· en· W2100997225 on OpenAlexvenueno aff
Simon Bainbridge

Bibliographic record

VenueRomanticism on the Net · 2004
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature: history, themes, analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryRomanticismLiteratureRomanceManifestoFeminization (sociology)HistoryArtPhilosophySociologyLawPolitical scienceGender studies

Abstract

fetched live from OpenAlex

This essay opens with a comparison of Robert Southey’s “History” and William Wordsworth’s The Prelude as poems of poetic dedication at a time of historical crisis. It argues that Southey’s text offers a manifesto for a different poetic mode to the one normally defined as Romantic. Through readings of Southey’s Joan of Arc and Wordsworth’s “The Discharged Soldier”, it examines the contrasting ways in which the two poets responded to the war with France and shows how the conflict played a major role in the shaping of their poetic identities. The writers’ different trajectories as poets are traced through an examination of their poetic dialogue from 1798 to 1802 as Southey countered what is often seen as one of the fundamental manoeuvres that characterizes the development of Wordsworthian Romanticism, the shift from a polemical humanitarian concern with suffering individuals to a psychological interest in their states of mind. Southey’s “The Sailor’s Mother” offered a reassertion of the importance of history so powerful that Wordsworth himself replied to it in a poem of the same name. Yet despite their differences, Southey’s “History” and Wordsworth’s The Prelude illustrate another crucial element of the two writers’ response to historical and vocational crisis during the war, the redefinition of poetry as a manly pursuit after its increasing feminization in the closing decades of the eighteenth century.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.932
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.210
Teacher spread0.186 · 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 teacher head, 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

Citations1
Published2004
Admission routes1
Has abstractyes

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