A Survey of Music Teacher Educators' Professional Backgrounds, Responsibilities and Demographics
Bibliographic record
Abstract
Little is known about the professional lives of those who teach current and/or future music teachers,thus the primary purpose of the current study is to present the demographics of a sample of the members of the music teacher education (MTE) profession, an overview of their faculty responsibilities, along with their professional and educational backgrounds. Surveys (N = 959)were sent to those whose instructional area included music education as indicated in the Directory of Music Faculties in Colleges and Universities, U.S. and Canada, 2003-2004 (College Music Society, 2003). Respondents? demographic information generally mirrored that of the general teacher education profession. Music teacher educators are overwhelmingly White (94.0%), predominantly male (56.1%), approximately 51.65 years of age and married (78%). Additionally,MTEs spend more time teaching and preparing to teach than in any other professional activity,including scholarship. Many MTEs teach outside of the music education area. Discussion of these results and directions for future research were explored.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".