Generating modernism and New Criticism from antisemitism: Laura Riding and Robert Graves read T. S. Eliot's early poetry
Bibliographic record
Abstract
The relationship between modernism and antisemitism – both in terms of the attitudes of individual writers and in terms of the ideology of the aesthetic itself – has long been a question in modernist studies, a question increasingly discussed with reference to T. S. Eliot's early works. Contemporary debate about Eliot foregrounds the poem ‘Burbank with a Baedeker: Bleistein with a Cigar’. In a poem about the decline of Venice, what does it mean that ‘The rats are underneath the piles. / The jew is underneath the lot’? Christopher Ricks, Anthony Julius, Rachel Blau DuPlessis, Vincent Sherry and Ronald Schuchard, among others, have all asked similar questions of ‘Burbank’. Is there antisemitism in the poem? If so, is the poem as a whole antisemitic? Whose antisemitism is it – Eliot's, Burbank's, an abstract narrator's? Is it being promoted, is it being undermined, is it simply being inspected? That critics should answer such questions in very different ways is not surprising. What is surprising, however, is that they should all have virtually ignored the first critical discussion of this question by Laura Riding and Robert Graves in A Survey of Modernist Poetry (1927). Riding and Graves not only ask the same questions but also provide answers that anticipate many of the positions maintained in the debate today. They do so, moreover, in one of literary history's first efforts to define modernist poetry in particular and modernism in general: their attention to the role in modernism of the First World War, Nietzsche's dead god, anti-romantic attitudes, technical experimentation and irony outlines definitions later sanctioned by academics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.029 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".