HEADLESS MUSICAL SEEDS AND GESTURES WITH ADJECTIVES: AN INTERVIEW WITH KEIKO DEVAUX
Bibliographic record
Abstract
Abstract Keiko Devaux (b. 1982) is a Canadian composer, originally from British Columbia, who now lives in Montréal. She began her musical career in piano-performance studies as well as composing, touring and recording several albums in independent rock bands. Her concert music is widely performed throughout Canada and Europe. From 2016–18, Keiko was the composer in residence of Le Nouvel Ensemble Moderne. She joined Salvatore Sciarrino's masterclasses at L'Accademia Musicale Chigiana in Siena, Italy, between the years 2017 and 2019. Keiko was commissioned by music@villaromana festival, Florence, to create Echoic Memories. She is the inaugural winner of the Azrieli Commission for Canadian Music (2020) and is also engaged in a two-year residency as a Carrefour composer with the National Arts Centre Orchestra (2020–22). This interview was conducted over Zoom in late spring 2020, in the midst of the Covid-19 pandemic.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.013 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".