Bibliographic record
Abstract
Welcome to Compositional Crossroads.As Dean of the Schulich School of Music of McGill University, it gives me great pleasure to introduce this volume of essays that are both reflections on, and a celebration of, "new music" at McGill: reflective because new music continues to require careful introspection to meet its challenging and challenged status in contemporary society; celebratory because Compositional Crossroads marks both an intersection and a turning point in the history of music at McGill.The idea for this volume evolved during the planning of our one-hundredth anniversary season in 2004-05.That same season witnessed an exceptional range of events, including -to cite but a few of the more than 650 concerts and special projects that took place -honorary degrees for Joni Mitchell and Jane Eaglen; the successful revival of Canada's national opera Louis Riel, by Harry Somers and Mavor Moore; the second edition of the international new music Montréal, Nouvelles musiques festival international; the official opening of our state-of-the-art New Music Building expansion; and the naming of the Faculty as the Schulich School of Music in recognition of an unprecedented philanthropic gift to arts and higher education in Canada from McGill alumnus and businessman Seymour Schulich.New music at McGill has been a driving force in the development of our unique profile, which today balances the finest professional training in musical creation and performance with demanding humanities-based study of music and groundbreaking scientific-technological and interdisciplinary research on music and sound.Without losing its championship of traditional compositional craft, new music at McGill has
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.437 | 0.330 |
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".