Bibliographic record
Abstract
English literature as a national literature is in many ways a non-starter. Form and context, language and translation all exert centrifugal forces on English language and literature and, more specifically, poetry. English poetry becomes poetry in English, but even from the start in Old English, there are external cultural and linguistic forces. Here, I do not deny that we speak of English poetry or poetry in English, but I wish to explore the countervailing pressures away from the literature of a nation or an unbroken poetic tradition in English because literature in English was written before England was unified and is written in English in English-speaking places and other territories that have changed over time. T.S. Eliot’s tradition and the individual talent, which he first discussed in The Egoist in 1919, is a perceptive idea, but I would suggest that some of the individuals, even early on, were bilingual or multilingual and that the tradition is not unified culturally, socially, and politically. So here I offer a brief selection of literary history – that is, a historical account of poetry in English, in the context of Latin and other languages, with examples from Anglo-Saxon texts through those of Shakespeare and Ezra Pound to those works in the present – that shows aspects of comparative and world poetry from the beginning and not simply English poetry or poetry in English.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.028 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".