The <i>Journal of Music Teacher Education</i>
Bibliographic record
Abstract
We analyzed each article published in 20 years (1991–2011) of the Journal of Music Teacher Education ( N = 282 articles) for possible changes across 5-year increments. All articles were examined by type of article, research methodologies used, and topics discussed. Nonrefereed articles included Society for Music Teacher Education chair and Journal of Music Teacher Education editor commentaries ( n = 77), and occasional statements by Music Educators National Conference (MENC)/National Association for Music Education (NAfME) officers ( n = 3). Peer-reviewed articles were classified as research articles ( n = 85), interest articles ( n = 99), and book reviews ( n = 18). Results showed a distinct increase in numbers of both quantitative ( n = 51) and qualitative ( n = 34 including historical) research articles over time with most appearing in the fourth quarter. Overall, more interest articles appeared ( n = 99), but the number decreased across each 5-year increment. Numbers of book reviews declined steadily. Analysis of specific topics revealed that curriculum, teaching techniques, and professional development were most frequently discussed but varied by type of article and methodology.
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 | 0.004 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.028 | 0.031 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".