Bibliographic record
Abstract
Eagle Minds —a selection from the correspondence between the Canadian composer and scholar Istvan Anhalt and his American counterpart George Rochberg—is a splendid chronicle and a penetrating analysis of the swerving socio-cultural movements of a volatile half-century as observed by two highly gifted individuals. Beginning in 1961 and spanning forty-four years, their conversation embraces not only music but other forms of contemporary art, as well as politics, philosophy, religion, and mysticism. The letters chronicle the deepening of their friendship over the years, and the openness, honesty, and genuine warmth between them provide the reader with an intimate look at their personalities. A fascinating intellectual tension emerges between the two men as they record their individual responses to musical modernism, to changing political and social realities, and to their Jewish heritage and sense of place, one as a son of Ukrainian immigrants to the United States, the other as a refugee from war-torn Hungary. Allowing us a privileged glimpse into the private lives and thoughts of these fascinating men, Eagle Minds is a valuable tool for scholars interested in North American composers in the late twentieth century and essential reading for anyone interested in the cultural and social history of that era.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.079 | 0.021 |
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".