Bibliographic record
Abstract
Potentiality, Transformation, Struggle: Seeds During the summer of 1918 in the United States, Rudhyar found himself at a crossroads: he could either continue to improve his piano technique and become a professional accompanist, or do something more drastic. Many years later he recalled in his autobiography that he “simply could not follow such a professional course with all it implied.” Then something happened the same year: he met Leopold Stokowski in Ottawa when the French-Canadian pianist and composer, Alfred Laliberté, who was living in Montreal, invited Rudhyar to give lectures: “It was while in Toronto that Mr. [Siegfried] Herz—a piano dealer— took Rudhyar to Ottawa to meet Stokowski, then conductor of the Philadelphia Orchestra.” After meeting Rudhyar, Stokowski not only took him to an official reception at the governor's palace in Ottawa but also suggested that he come to Philadelphia to attend some of the rehearsals and concerts of the orchestra led by Stokowski. But when Rudhyar gave him the orchestral score of one of his early works, the conductor decided that it would be better to perform a more mature composition later. According to Rudhyar, this never happened because Stokowski “was never eager to give [him] a chance later on,” telling him that “he was many years ahead of his time.” In retrospect, Rudhyar would often regard this period as a pivotal point in his life: “A door was opened, and I stepped through. It turned out to be a cathartic step—the psychic ploughing under of what remained of old values and a tragic awareness of the darkness of roots and what was left of the Romantic pride: ‘a dark night with the soul.’” These early years were indeed marked by uncertainty, instability, and transformation for Rudhyar. His poem, “Anguish” (originally written in French during the winter of 1919, later translated by him into English, “though not quite as evocative as in French”), reflects the dark sense of tribulation of this Romantic feeling to which he was referring: … One would love to shout: but what for? No one would hear or, hearing, would only smile and shrug shoulders with the miserable scorn of happy people. And this will last, year after year, perhaps forever. If it should end, for what new anguish, new agony? And after so often dying, every minute dying, how will one ever know what is the real death?
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.066 | 0.014 |
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".