The Search for Canadian Art Song: Developing the Framework for a Database of Art Song by Canadian Composers
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,012 | 0,049 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,024 | 0,029 |
| Études des sciences et des technologies | 0,008 | 0,005 |
| Communication savante | 0,019 | 0,016 |
| Science ouverte | 0,008 | 0,012 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,008 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».