Bibliographic record
Abstract
Today when people are asked what they know about T. S. Eliot, most mention three things: he was the librettist of the enormously popular Andrew Lloyd Webber musical Cats; he wrote one of the most celebrated and difficult poems of the twentieth century, The Waste Land; and he was an anti-Semite. This last tag, fastened to him after the end of the Second World War, has been the focus ever since of a sometimes acrimonious debate among critics, scholars, and, occasionally, in the popular press. Although Eliot's offending works were written before the Second World War, it wasn't until after the war that anyone thought the anti-Semitism was significant enough to make it the topic of public argument. It seems that before the war, the incidental anti-Semitism of many Europeans and Americans camouflaged attitudes that after the war took on a more sinister and menacing colouring. Two things contributed to the appearance and persistence of the charge against Eliot: firstly, the new position of Jewry in the public sphere after the Holocaust and, secondly, Eliot's own fame and celebrity as a poet and cultural spokesman. After his Nobel prize in 1948, he was a leading public intellectual in the English-speaking world. It did not help that he spoke for a conservatism that some people mistook for the virulent, right-wing authoritarianism of Fascist Germany, Italy and Spain. Although his visibility as a public figure brought greater attention to his work, it also made him a target.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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; both teacher heads agree on what is shown here.
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".