Bibliographic record
Abstract
Abstract “Canadian” curricula and pedagogical approaches in music teacher education programs remain entrenched in a static and siloed system of colonial practices which hinder the liberatory potential of music education. The supporting epistemologies are steeped in a hegemonic settler colonial perspective that excludes and/or tokenizes the global majority of voices, pedagogies, and musics. To work toward countering these structures and epistemologies and shift to healing-centered music teacher education, I offer the relevance of intersectional Feminism and propose the applications of Femme pedagogy toward liberatory praxis. This affirmative vision is centered in relational, healing, loving, vulnerable, and collective work which at the outset involves intersectional inquiry to identify, name, and counter the root causes of harm. I then discuss ways in which pre-service music educators in our undergraduate methods class develop these skills through circles, mock-teaching, and reflective practices. It is necessary for teachers to explore not only the intersections of identities that have been institutionally marginalized, but to also understand and actively expose the power structures of colonialism and white supremacy which continue to sustain systemic oppression in order to heal, dream, and move outside of settler futurity.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.026 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".