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Record W1614839136 · doi:10.1017/cbo9780511777486

Ezra Pound in Context

2010· book· en· W1614839136 on OpenAlexaff
Ira Nadel, Vincent Sherry, Ellen Stauder, Steven G. Yao, David Ten Eyck, Demetres P. Tryphonopoulos, John Gough Nichols, Matthew Hofer, Eric Bulson, Alec Marsh, Leon Surette, Benjamin Friedländer, Robert Spoo, Mark Byron, Caterina Ricciardi, Peter Liebregts, William D. Paden, Tim Redman, Emily Mitchell Wallace, John Gery, Peter Brooker

Bibliographic record

VenueCambridge University Press eBooks · 2010
Typebook
Languageen
FieldArts and Humanities
TopicModernist Literature and Criticism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPound (networking)PoliticsPoeticsModernism (music)LiteratureChinaPoetryPublishingPortraitHistorySociologyAestheticsArtArt historyLawPolitical scienceArchaeology

Abstract

fetched live from OpenAlex

Long at the centre of the modernist project, from editing Eliot's The Waste Land to publishing Joyce, Pound has also been a provocateur and instigator of new movements, while initiating a new poetics. This is the first volume to summarize and analyze the multiple contexts of Pound's work, underlining the magnitude of his contribution and drawing on new archival, textual and theoretical studies. Pound's political and economic ideas also receive attention. With its concentration on the contexts of history, sociology, aesthetics and politics, the volume will provide a portrait of Pound's unusually international reach: an American-born, modern poet absorbing the cultures of England, France, Italy and China. These essays situate Pound in the social and material realities of his time and will be invaluable for students and scholars of Pound and modernism.

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)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.012
Scholarly communication0.0090.007
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0130.002

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 head0.023
GPT teacher head0.190
Teacher spread0.166 · 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

Citations66
Published2010
Admission routes1
Has abstractyes

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