Exploring Musical Knowledge Within One Canadian School Of Music: Ideology, Pedagogy, And Identity
Bibliographic record
Abstract
The purpose of this study was to understand how the distribution and transmission of musical knowledges impacted the identities and consciousness of agents within one Canadian school of music which was given the pseudonym Eastern Urban School of Music (EUSM). The project was framed using Basil Bernstein’s (2000) theory of the Pedagogic Device, offering a language of description to examine how forms of regulation differentially distributed various identities and forms of consciousness. Specifically, this study explored how varying modalities of classification and framing revealed competing values about what counts as legitimate and ‘excellent’ music education and who is seen as legitimate or excellent within this social arena.\nThis research implemented a qualitative, single case study design (Yin, 2014) focused upon the experiences and perspectives of agents within the EUSM. These were framed and contextualized using classroom observations, field notes, and documents (Merriam & Tisdell, 2016), which further shaped and added context to interviews with agents. Using a codes-to-theory model (Saldaña, 2013), data were organized into codes from which categories and themes emerged related to the nature of musical knowledges and the impacts these have upon identity and consciousness.\nFindings indicated that tensions surrounding what counts as ‘excellent’ musical knowledge and pedagogies differently shape the ideologies and practices of agents. Discourses surrounding what and who could be considered excellent within the social arena of the EUSM were framed within the emergent themes of competition and performance, international reputation, interdisciplinarity, and the development of citizens. This study suggests that agents within the school of music might benefit from an educative space where tensions and boundaries between categories of musical knowledge are negotiated and where competing ideologies collide and interact to foster creativity, communication, and collaboration. Findings suggest that agents of the school of music might benefit from rethinking how supports can be embedded—and not just included—within curriculum to ensure their effectiveness for meeting health, wellness, and EDI needs. This study offers a space for rethinking who is served by dominant pedagogic and curricular models in higher music education and how agents might negotiate their own pedagogic spaces to better meet the needs of students.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.044 | 0.014 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".