Bibliographic record
Abstract
Men of the future will not give a fahrt for the so-called poets unless they (the poets) combat the blackout of significant historical facts and the falsification of current news. Ezra Pound Ezra Pound was a poet first, a journalist second. Throughout his long life, he wrote thousands of literary essays, letters, editorials, and manifestoes for British, Japanese, American, French, and Italian newspapers so that his ideas could be transmitted in a timely fashion. To this day, however, Pound is not really remembered for his journalism, in part, because there is no comprehensive, annotated edition of his articles complete with translations. Anyone trying to read through Pound's journalism is forced to track down a copy of the oversized, twelve-volume collection Ezra Pound's Poetry and Prose Contributions to Periodicals (without notes or context), which is hard to come by, or turn to the Literary Essays and the Selected Prose, 1909–65 , both of them organized as a “greatest hits” series that emphasizes Pound's more “literary” side. Pound's journalism, though occasional, is absolutely critical for anyone with an interest in his life and work. In fact, it was in the columns of the newspapers that he engaged most directly with the public, doing everything he could to get his ideas in circulation. He published “How to Read,” for instance, in the book section of the New York Herald (1929) and had it reprinted in a Genovese newspaper, L’Indice (March 20, 1930) and the Tokyo-based Japan Times Weekly (February 20, and March 20, 1930). This mode of communicating with an international public through newspapers was Pound's way of keeping in touch with the world. In the 1910s and 1920s, he was mostly concerned with literary matters, and by the 1930s and 1940s, he shifted his attention to politics, economics, and history. And even if his subjects changed over the decades, his determination to educate the masses remained fixed.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.065 | 0.020 |
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".