Bibliographic record
Abstract
Ten years ago, the death of a Pakistani singer, no matter how talented, would have gone unnoticed by most of the world. But when Nusrat Fateh Ali Khan (see Fig. 1) died in August 1997, at the age of forty-eight, even America's notoriously parochial television news programs carried the story. Khan was not just one of the world's greatest singers, he was emblematic of a startling rise of interest in non-Western music, especially within the last quarter of the twentieth century. The late Pakistani singer, along with such world-wide sensations as Youssou N'Dour of Senegal and the globe-trotting choirs of Tibet and Bulgaria, came to represent a musical genre known by the informal and somewhat loosely defined term ‘world music’. This chapter provides an armchair traveller's guide to the world's increasingly miscegenated music. Nusrat Fateh Ali Khan, for example, was a master of the infectious, rhythmically charged Sufi devotional music known as qawwali. Lionised by such rock musicians as Peter Gabriel, The Who's Pete Townsend, and Pearl Jam singer Eddie Vedder, he also proved himself a thoroughly modern fellow, eagerly embracing his unexpected musical allies and moulding their Western pop styles to suit his own needs.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".