L'enjeu des communautés en sociomusicologie : Le cas du projet de recherche sur le développement des publics de la musique au Québec
Bibliographic record
Abstract
The basis of this article arises from the project “Developpement des publics de la musique au Quebec” (DPMQ), developed by the sociomusicology research team at the Observatoire interdisciplinaire de creation et de recherche en musique (OICRM) in partnership with nine musical organizations in Quebec. Our first research question involves interrogating the definition of “community” (or “communities”), and this article proposes an application of this concept in line with the objectives of the DPMQ: establishing a social map of audience attendance and numbers of musical amateurs in Quebec, and experimenting with new forms of musical mediation in collaboration with professional partners who will apply them within the context of their activities. The second question concerns the difficulty of reconciling different work “cultures” between researchers and professionals in the cultural realm. The question in simple terms, therefore, is how to overcome the absence of a tradition of research among community partners? The third question emerges from the previous question: how to resolve the issue of sharing information? We approach these three sociomusicological research questions with respect to our initial experiences with two community partners: la Societe de musique contemporaine du Quebec (SMCQ) and the Festival du monde arabe (FMA).
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.014 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".