Listening with ‘Big Ears’: Accountability in cross-cultural music education research with Indigenous partners
Bibliographic record
Abstract
In this theoretical article, I examine various conceptions of focused listening-including those held by specific First Nations communities-to determine how each conception might offer insights for listening while conducting cross-cultural music education research. First, I discuss the notion of "Big Ears," as it is understood by the jazz community. Then, I turn to scholars from various First Nations in British Columbia to learn about their conceptions of listening. I outline decolonial listening strategies as proposed by Indigenous Arts scholar Dylan Robinson, before learning about the role of listening from a settler-Canadian who formally Witnessed the testimonies of Indigenous residential school survivors over a period of years while working for the Truth and Reconciliation Commission of Canada. I examine the writings of music education researchers who have proposed listening as an important strategy in cross-cultural/intercultural pedagogy and research, albeit in different circumstances and for different reasons. Finally, I describe/reflect on my process of learning to listen cross-culturally as a settler-Canadian music education researcher engaged in community-based participatory research (CBPR) over the course of three studies, and list some of the ongoing questions I have. I conclude by proposing a revised understanding of Listening with "Big Ears" as one possible way for non-Indigenous researchers using a CBPR approach to enhance their application of Indigenist research methodology, especially in demonstrating their accountability to Indigenous co-researchers, participants, and communities, as they engage collaboratively in music education research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".