Bibliographic record
Abstract
From his youth until his death, Ezra Pound found in Venice not only a hospitable environment for writing and living, but a paradigm for the design of The Cantos . Merely to cross its bridges, admire its legion of palazzi, or navigate its lagoons is to engage in Venice's brilliant light, eerie shadows, merger of water and architecture, intricate history, and unique blend of vibrancy and decay. As the center of a 1200-year long maritime power, with its unusual republican style of government and international commerce, La Serenissima , of course, has had its share of writers from Marco Polo (1256–1324) and Paolo Sarpi (1552–1623) to Carlo Goldoni (1707–93) and Gabriele D’Annunzio (1863–1938), figures who have distinguished it as among the world's most intriguing cities. And the number of visiting writers it has fascinated is great and ever-growing, from Petrarch (1304–74) to Joseph Brodsky (1940–96). Even with this rich legacy, to consider Venice as Pound did, especially in his poetry, is not only to rediscover it through the imagination of an exiled American modernist, but to appreciate how Pound's own art, despite its difficulties, is immediate and vital. Pound's first visit to Venice occurred at age twelve with his Aunt Frank in 1898. He intended “to return” ( PDD , 6). And return he did, at least six more times before he was thirty-five ( PDD , 6): in 1902, with Aunt Frank and his parents; in 1908, after his dismissal from Wabash College, when he published there A Lume Spento , his first volume of poems, and composed his “ Venetian sketch-book – ‘San Trovaso’ –” ( CEP , 55); in March 1910, meeting with Olivia and Dorothy Shakespear; in 1911; in spring 1913, when he met with H.D., her parents, and her husband Richard Aldington ( SL , 19–20); and in 1920, when he began writing “Indiscretions or, Une Revue De Deux Mondes ,” a rare foray for Pound into memoir.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.345 | 0.127 |
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".