Bibliographic record
Abstract
We propose a return to the forgotten agenda of comparative musicology, one that is updated with the paradigms of modern evolutionary theory and scientific methodology. Ever since the field of comparative musicology was redefined as ethnomusicology in the mid-twentieth century, musicologists have all but abandoned many features of its original research agenda, not least the overarching goal of cross-cultural musical comparison. We outline here five major themes that underlie the re-establishment of comparative musicology: (1) classification, (2) cultural evolution, (3) human history, (4) universals, and (5) biological evolution. Throughout the article, we clarify key ideological, methodological and terminological objections that have been levied against musical comparison. Ultimately, we argue for an inclusive, constructive, and multidisciplinary field that analyzes the world's musical diversity, from the broadest of generalities to the most culture-specific particulars, with the aim of synthesizing the full range of theoretical perspectives and research methodologies available.
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 | 0.020 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.013 | 0.006 |
| Science and technology studies | 0.008 | 0.057 |
| Scholarly communication | 0.018 | 0.024 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".