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Record W1817564718 · doi:10.3138/topia.26.85

Meanings of Bhangra and Bollywood Dancing in India and the Diaspora

2011· article· en· W1817564718 on OpenAlexvenueaboutno aff
Anjali Gera Roy

Bibliographic record

VenueTOPIA Canadian Journal of Cultural Studies · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Cinema and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsDiasporaDanceHomelandHindiMusicalMedia studiesElectronic dance musicPopular musicHistoryGender studiesPoliticsVisual artsSociologyArtPolitical science

Abstract

fetched live from OpenAlex

The mid-1980s witnessed the invention of a new musical genre in Britain consisting largely of remixes of Punjabi folk music and Bollywood music. Dubbed the “new Asian dance music,” it emerged as an important site for the production of South Asian diasporic identities. From the beginning, these hybridized bhangra and Hindi film remixes attracted considerable media and academic attention in Britain and, over the last two decades, they have become a global cultural phenomenon, with South Asian youth from Amsterdam to Singapore dancing to these beats in clubs, at parties, at college functions and at community gatherings. While Asian dance music returned to India through its popularization in clubs and at weddings and other events, its emblematic status in the diaspora has elided other significatory functions of dance and music in popular, social and political life in the homeland. This essay examines the meanings of bhangra and Bollywood dance in India and the diaspora by drawing on fieldwork conducted among male and female youth aged eighteen to thirty-five at bhangra and Bollywood nights, clubs, community festivals and gatherings in Bangalore, Chandigarh, Delhi, Kharagpur, Kolkata, Canberra, Melbourne, Sydney, Singapore, Stuttgart, Heidelberg, New York, Toronto and Vancouver between 2004 and 2011.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.044
GPT teacher head0.219
Teacher spread0.175 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2011
Admission routes2
Has abstractyes

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