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. While it was probably an unintended result of the twentieth-century revolution in communications technology, with hindsight it seems unavoidable that people in the West would find themselves, for the first time since the Crusades, becoming keenly aware of non-Western systems of music and singing. ModernWestern listeners have had the unique experience of hearing their own popular music styles refracted through the prism of a hundred different cultures and returning as a brood of musical changelings – for example, in the form of African or Asian cross-cultural pop. And, of course, listeners in contemporary America or Europe have had the opportunity to hear live performances and recordings by some of the greatest singers in the classical, folk and popular styles of the world.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".