Applied ethnomusicology : historical and contemporary approaches
Bibliographic record
Abstract
Applied ethnomusicology is an approach guided by principles of social responsibility, which extends the usual academic goal of broadening and deepening knowledge and understanding toward solving concrete problems and toward working both inside and beyond typical academic contexts (International Council for Traditional Music 2007). This edited volume is based on the first symposium of the ICTM's Study Group on Applied Ethnomusicology in Ljubljana, Slovenia in 2008 that brought together more than thirty specialists from sixteen countries worldwide. It contains a Preface, an extensive Introduction, and twelve selected peer-reviewed articles by authors from Australia, Austria, Canada, Germany, Slovenia, Serbia, South Africa, the United Kingdom, and the United States of America, divided into four thematic groups. These groups encompass: diverse perspectives on the growing field of applied ethnomusicology in various geographical and problem-solving contexts; research and teaching-related connotations; the potential in contributing to sustainable music cultures; and the use of music in conflict resolution situations. The edited volume Applied Ethnomusicology: Historical and Contemporary Approaches brings together previously dispersed knowledge and perspectives, and offers new insights to various disciplines within the humanities and social sciences. Rooted in diverse scholarly traditions, it addresses a variety of challenges in today's world and aims to benefit the quality of human existence.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.005 | 0.023 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".