Bibliographic record
Abstract
Abstract Christopher Butterfield is a composer and composition teacher. His music has been performed across Canada and in Europe, with recordings on the CBC, Artifact, and Collection QB labels. He is currently the Director of the School of Music in the Faculty of Fine Arts at the University of Victoria. Christopher was born in 1952 in Vancouver, BC. He studied composition at the University of Victoria with Rudolf Komorous and at the State University of New York at Stony Brook with Bülent Arel. He was a performance artist, rock guitar player and composer while living in Toronto between 1977 and 1992, after which he returned to the University of Victoria as Assistant Professor of Composition. I studied composition with Christopher between 2000 and 2005. Earlier this year, I had the opportunity to sit down with him in Victoria. During our interview, I asked him about his life and work, and for his thoughts on how Czech-Canadian composer Rudolf Komorous has influenced composition in Canada over the last few decades.
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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.050 | 0.024 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.007 | 0.020 |
| Insufficient payload (model declined to judge) | 0.006 | 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".