Bibliographic record
Abstract
POUND'S MEDIEVALISM Pound first read Dante in 1904 as an undergraduate at Hamilton College in upstate New York. His Dante instructor, Professor William Shepard, “Shep,” admired Pound's seriousness as a student of languages. Pound's study of Dante continued for another sixty-eight years, until his death in 1972. He continued to study Dante in 1904, following Shepard's lectures in medieval poetry, with a great deal of excitement. Pound's principal literary correspondent during that time was his mother, and whatever parental conflict he experienced as a teenager was with her. The United States had manifested considerable anti-Catholic sentiment from before its founding, and that prejudice was reinforced by the waves of Italian Catholic immigrants who were arriving on its shores, many of them living in tenements in South Philadelphia. Pound's parents, Homer and Isabel, who lived in a Philadelphia suburb, volunteered as missionaries in those slums, trying to convert the Italians to their Presbyterian version of Christianity. Of course there was an American Dante movement in New England centered on Boston. Longfellow was the first instructor of Dante at Harvard, starting in 1836, and there was a kind of Dante club or cult in Boston in the latter part of the nineteenth century. America needed an epic and perhaps Dante might do. He had denounced the corruption of the Catholic Church and clergy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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.
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".