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Owen, Wilfred (1893–1918)

2018· book-chapter· en· W4256146381 on OpenAlexaff
Nicholas Beauchesne

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicGerman Literature and Culture Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPoetrySubversionBattlefieldElegiacRhymeArtLiteratureOpposition (politics)Performance artPhilosophyArt historyClassicsHistoryLawAncient historyPolitics

Abstract

fetched live from OpenAlex

Wilfred Edward Salter Owen (1893–1918) is among the most renowned British poets of the First World War (1914–1918). His style can best be described as elegiac or tragic, standing defiantly against the idealized or propagandistic depictions of the battlefield prevalent during the ‘Great War’s early stages. In opposition to the sentiments of Rupert Brooke (1887–1915) and Rudyard Kipling (1865–1936), and more akin to those of Isaac Rosenberg (1890–1918) and Siegfried Sassoon (1886–1967), Owen considered such reductive glorifications of mass slaughter ignorant, if not outright dishonest — a radical viewpoint at the time. Owen’s influences range from Dante and Shakespeare to Thomas Gray, William Collins, Percy B. Shelley, Samuel Taylor Coleridge, Robert Burns, Alfred Lord Tennyson, Robert Browning and Elizabeth Barrett Browning, and especially John Keats. Owen’s poetic signature and chief innovation was his subversion of traditional rhyme schemes. He experimented with consonantal end-rhyme (or ‘pararhyme’), a technique that, along with Edmund Blunden (1896–1974), he helped popularize. Critic Sasi Bhusan Das interprets Owen’s use of this technique, in conjunction with broken rhythms, as an effort to capture ‘the disharmony of the [Great] War’ (13).

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.458
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1210.007

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 head0.027
GPT teacher head0.203
Teacher spread0.176 · 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; both teacher heads agree on what is shown here.

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
Published2018
Admission routes1
Has abstractyes

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