Bibliographic record
Abstract
The following autoethnographic duet by faculty advisor and professor creates a dramatic and evocative account of the personal and cultural experience about a disabled student teacher. They blend storytelling and music which fuses a theoretical analysis about storytelling and life. Although sociocultural issues draw deep reflection about the emotional turmoil, cultural influences of language and social interaction provide details that critique social structures. As musician becoming teacher is a passionate yet complex endeavor, the faculty advisor shares first-hand a poetic but painful story about a disabled teacher being inducted into the teaching profession. By making explicit the personal-cultural connection, they use the life-changing epiphany to critique cultural issues about teaching and disability. As the faculty advisor approaches the professor for advice, his musicianship shifts her forward, backward, and sideways through feelings that evoke, invoke, and provoke a curriculum that does not transfer knowledge from educational method classes. Instead, it embeds musical language as a metaphorical conduit to interrogate the pros, cons and both sides of the complicated issue of disability that influences the completion of his teaching practicum for his undergraduate bachelor of education degree. An epiphany from music and story reveals the irony of living in a culture of both uniformity and diversity. They explore the constructs of ideology, abnormality, marginalization, and secrecy. Thus, by blending story and music, the authors resolve a transformative autoethnographic aspect about the personal and cultural influences that provoke new deeper ways of thinking about curriculum.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.283 | 0.080 |
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".