Bibliographic record
Abstract
Early influences T. S. Eliot, as we have seen, was born on the banks of the Mississippi River in St. Louis and it is wise when considering his life and work to remember his American origins. He certainly never forgot them. He may have felt an abstract or ideal relationship to Britain and Europe, but St. Louis was, on the other hand, all too real. This was Eliot's first and most enduring context. In 1888 the city was still the gateway to the western frontier and a river city in close touch with the American South. The Civil War had not yet faded from living memory and the consequences of the South's defeat and the formal end of slavery were still very much in evidence. Although slavery had disappeared from the southern states, the systemic racism of American society as a whole, which persisted well into the twentieth century, colored every aspect of social life in St. Louis. The surrender of the South in the Civil War signified more than a political defeat; it also heralded the end of a closely knit, rural, and deeply communal society. It had been brought to its knees by the emerging industrial might of its northern adversary. Eliot's later social and cultural conservatism had its origins in the nostalgia for a South brought down by the disintegrative power of the industrial North.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.008 |
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".