Black, White and Brown on the Dance Floor: The New Meanings of Panjabiyat in the Twenty-first Century
Bibliographic record
Abstract
The relationship between music, ethnicity and identity is nowhere as apparent as in popular and academic discussions of Bhangra including those in anthropology, sociology and studies of culture, religion, music and dance, in addition to the print and electronic media. Bhangra scholarship examines it largely in relation to the identity politics of South Asian diasporic formations in Britain, Canada and North America in which Bhangra becomes the site for the production and contestation of hybrid, in-between diasporic identities by second-and third-generation youth of Indian/South Asian origin. even though the euphoric declarations of ‘the Asian youth finding their voice’ of the late 1980s and early 1990s1 gradually gave way to wry cynicism in the unpacking of the new politics of ethnicity and identity in subsequent examinations of South Asian youth subcultures,2 Bhangra continues to be theorized through an ethnic lens even in more recent studies.3 With its heavy investment in the politics of race, ethnicity, language, gender, caste, region and religion, it is not surprising that aesthetic or musical analysis of Bhangra texts has been marginalized to ideological considerations or the focus on uses and gratifications that is found in media and cultural studies. In this chapter I wish to investigate the production of Bhangra with the objective of examining the consolidation of ethnic identity in multicultural nations and societies in the wake of globalization and to focus on the benefits and dangers of the return of ethnicity in the identity discourses in the global village. The rhetoric of cultural difference in multiculturalism is seen as emerging from, and replicating, the older politics of race, colour, caste and religion in addition to building a new politics of ethnicity in which a mobilization of ethnicities fills us with multicultural hope but also makes us uncomfortable as participants in a neo-orientalizing 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.021 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".