Translating Ismaili Muslim Experience in Canada: Integrative Choral Pathways of Belonging
Bibliographic record
Abstract
This study explores possibilities for blending choral forms of singing with traditional Ismaili Muslim devotional recitations. In particular, the focus is on finding new musical translations as a means of interpreting tradition and negotiating belonging in Canada. In music education scholarship, Muslim musical traditions can often be portrayed in ways that delimit the communities represented. In doing so, Islam may be inadvertently positioned as a problem to be addressed. Furthermore, there is a paucity of scholarship in music education that illustrates the importance of sound and music in diverse Muslim cultures. This study aims to further the conversation. I propose an “enlightened encounters” theoretical framework that draws together post-colonial, indigenous, educational social justice, and Ismaili literature. Autoethnography and narrative research methods foreground the transformative impacts of integrative vocal practices on retranslating Muslim experience in new contexts. Key findings include: 1) Blended sound and music can play a significant role to feel faith and embody cultural knowledge; 2) Integrative vocal practices can provide the possibility of avenues for Ismaili youth to navigate delicate relationships of belonging within their own traditions, as well as in the larger cultural context; 3) Engaging in participatory communal activities can provide youth with safe spaces for receiving, translating and interpreting knowledge; 4) Music and sound can have a powerful impact on reconnecting spirituality with life.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.034 | 0.016 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 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".