Bibliographic record
Abstract
Many teacher candidates (preservice teachers) in a Bachelor of Education degree cross the threshold into an elementary music methodology course with trepidation. Thus, teacher educators (music education professors) ought to explore the ways in which they can attend to students’ music experiences so as to increase teacher competence. This article explores three relevant areas of literature: fear of teaching music, relevance of informal music learning on influencing teacher identity, and influence of such experiences on teacher education programs. Building on this literature, the article concludes with highlighting a 2-year narrative inquiry exploring how the daily music experiences of teacher candidates’ inform their teaching practices. Through the use of visual narratives (body maps), oral and written narratives, and conversational interviews, 20 participants gave voice to their multilayered experiences that influenced their perceptions about music teaching. Findings deepen conceptualizations concerning the power of informal music learning in shaping teacher identity and practice.
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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.044 |
| Scholarly communication | 0.014 | 0.021 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".