The Search for Canadian Art Song: Developing the Framework for a Database of Art Song by Canadian Composers
Bibliographic record
Abstract
Art song is a diverse, inclusive genre of music, as well as an important pedagogical tool for singers. It can be performed in the smallest of spaces, but it is also able to hold its own in the largest concert halls. It requires only a few musicians, making it an ideal choice for a concert or recital setting, and its poetic content describes virtually every aspect of life, in many languages, making it accessible to a broad audience. Many of its works require less physical maturity on the part of singers and require less rigorous technical ability than larger concert repertoire or opera arias. Canadian singers are seldom exposed to their own version of this genre, and/or have difficulty accessing Canadian art song. This study aims to address this problem by demonstrating the need for a graded, online database of Canadian art song, termed the Database of Canadian Art Song (DoCAS). The DoCAS will be an open-access, graded online catalogue of Canadian art song. The design of the DoCAS will focus on the following primary directives: ease of use, opportunity for exploration and discovery of new music, augmentation of educational resources for singers and singing teachers, knowledge mobilization, and promotion of Canadian composers and their music. All art songs housed in the DoCAS will be evaluated according to a grading scheme devised by the author, assigned a difficulty level, and will be catalogued with relevant information. Users of the website will be able to browse a database of Canadian art song by level, or to search by composer (or composer’s gender or Indigenous Canadian identification), title, poet, language, duration, voice type, instrumentation, publication date, or keyword and create a profile to save art songs into collections for future reference. Additional features of this website include a profile page for anyone who creates a free membership account, the ability to save art song into public or private collections, networking with other members by viewing their profile pages or public collections, an events calendar populated by members (searchable by date, location, and event type), as well as many educational resources. This document will develop the necessary curriculum and templates for the website, as well as a sample database with 100 entries to demonstrate the potential functions of the DoCAS. An online collection of all Canadian art song does not currently exist, making this project unique in its conception. Having virtually all of our art song collected in one single location alone would be of tremendous value to Canadian musicians or anyone interested in Canadian music, and would increase access to Canadian art song for singers, singing teachers, and collaborative pianists, in addition to increased exposure for Canadian art song and Canadian composers. Also unique to this project is the application of a grading system on the art song housed in the database, which will efficiently indicate the appropriate song choice for a given student, the networking opportunities created for everyone who creates a personal profile, and the promotion of art music events throughout Canada as well as the international art music community.
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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 | 0.012 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.024 | 0.029 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.019 | 0.016 |
| Open science | 0.008 | 0.012 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".