Changing Content in Flagship Music Theory Journals, 1979–2014
Bibliographic record
Abstract
Since the founding of the Society for Music Theory in 1977, the Anglophone music theory discipline has extensively diversified, now encompassing manifold subfields. A pertinent question arises: how does the music theory discipline balance this diversity with a sense of unity and cohesiveness? An investigation into journal articles—one of the main ways music theory presents itself to the world—can serve as a useful entry point for this question. We develop and analyze a corpus of article abstracts published between 1979 and 2014 from four general-scope flagship periodicals: Journal of Music Theory , Music Theory Spectrum , Music Analysis , and Music Theory Online . For each of 1063 abstracts analyzed, theoretical topics and repertoire (including composer) are tabulated. Observations are organized according to which topics and repertoires are addressed most frequently, as well as whether correlations between leading topics and repertoires might exist. Extending beyond our initial question regarding diversity and cohesiveness, the corpus data is then used to assess how music theory research relates to trends in concert programming, as well as the repertoire used in textbooks designed for undergraduate theory curricula. Based on the data generated in this study, we find that a balance of diversity and cohesiveness appears to exist in the form of a broad range of research topics engaging with a comparatively small canon of music by only a few composers. This relationship is, however, paradoxical; the small canon belies the diversity of repertoire that currently permeates the discipline.
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 | 0.008 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.056 | 0.062 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".