Bibliographic record
Abstract
Harry Freedman has been an important and respected figure in Canadian music for over half a century, and his productivity as a composer has been both prodigious and eclectic. Born in Poland in 1922 and raised in Winnipeg, Freedman studied at the Royal Conservatory of Music and played English Horn with the Toronto Symphony Orchestra. He resigned in 1970 to become the orchestra's first composer-in-residence, and has created some 175 works in a wide variety of genres including symphonies, concertos, string quartets, operas, ballets, film scores, popular songs, and jazz pieces. In The Music of Harry Freedman, Gail Dixon investigates Freedman's music with a view to illuminating its underlying principles, stylistic development, and means of coherence. Representative works from Freedman's oeuvre have been selected for detailed analysis. The chronological presentation of these works facilitates a clear understanding of Freedman's compositional style in its dramatic evolution from the tentative serial explorations of his early works to the eclectic stylistic spectrum of his later years. The analytic discussion is supplemented by a large number of musical examples, as well as compositional sketches and working notes, some in the composer's own hand. Numerous interviews with Freedman yield additional insights into his approach and perspective. Dixon does a great service to Canadian culture with this analytic study of the music of a celebrated twentieth-century figure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".