Music and Digital Media: A planetary anthropology
Bibliographic record
Abstract
Anthropology has neglected the study of music. Music and Digital Media shows how and why this should be redressed. It does so by enabling music to expand the horizons of digital anthropology, demonstrating how the field can build interdisciplinary links to music and sound studies, digital/media studies, and science and technology studies. \n \nMusic and Digital Media is the first comparative ethnographic study of the impact of digital media on music worldwide. It offers a radical and lucid new theoretical framework for understanding digital media through music, showing that music is today where the promises and problems of the digital assume clamouring audibility. The book contains ten chapters, eight of which present comprehensive original ethnographies; they are bookended by an authoritative introduction and a comparative postlude. Five chapters address popular, folk, art and crossover musics in the global South and North, including Kenya, Argentina, India, Canada and the UK. Three chapters bring the digital experimentally to the fore, presenting pioneering ethnographies of an extra-legal peer-to-peer site and the streaming platform Spotify, a series of prominent internet-mediated music genres, and the first ethnography of a global software package, the interactive music platform Max. \n \nThe book is unique in bringing ethnographic research on popular, folk, art and crossover musics from the global North and South into a comparative framework on a large scale, and creates an innovative new paradigm for comparative anthropology. It shows how music enlarges anthropology while demanding to be understood with reference to classic themes of anthropological theory.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".