The Language of Dreams: A story of reconnecting with my heritage and learning about the traditional Ojibwe flute
Bibliographic record
Abstract
The Language of Dreams examines Indigenous music in Canada, with a particular focus on the Bibigwan. This research project asks how we can decolonize music education and how the effects of colonization have affected music. To answer these questions, I used a literature review and lived experiences. Through the writings and teachings of Indigenous researchers and articles by ethnomusicologists, it is clear that musical institutions need to be decolonized and Indigenized. Not only will Indigenizing colonial music institutions aid in decolonizing Canadian culture, but also help with students' mental health and overall well-being. This study discovered that Westernized music conservatories and post-secondary programs are often tied to mental health issues and performance anxiety. The findings of this study imply that adding Indigenous teaching pedagogies, such as land-based pedagogies, could bring Indigenous students closer to their culture and create a more accessible learning environment, which causes less harm to its students.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.034 | 0.036 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".