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Record W862623421 · doi:10.31542/j.muse.157

Beats from the East: Transcultural Adaptation of Hip-Hop from North America to Eastern Asia

2014· article· en· W862623421 on OpenAlexvenueno aff
Andrew Donald Melnyk

Bibliographic record

VenueMacEwan University Student eJournal · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsPopularityScholarshipEast AsiaGlobeChinaBeijingHistoryGender studiesGeographyPolitical scienceSociologyMedicine

Abstract

fetched live from OpenAlex

Hip-hop culture has spread from its origins in the South Bronx in the late 1970’s to many countries across the globe, leading to the creation of a Global Hip-hop Nation in which artist from every nation have the ability to share, collaborate, and critique the works of others. With the expansion of a culture that was created – predominately – by marginalized African-Americans, an issue that has arisen is the authenticity of what constitutes ‘real’ Hip-hop for those outside of North America. In this paper the author will explore the relationship between Hip-hop cultures in North America and Eastern Asia in an attempt to show how both cultures have influenced each other rather than the commonly held view that Eastern Asian countries (Japan, China, and South Korea) have copied and imitated the styles of North America. Through secondary research and exploring the scholarship surrounding the creation and expansion of Hip-hop culture the author will examine the circumstances that have lead to the popularity Hip-hop has gained in North America and Eastern Asia, and examine the aspects of Eastern Asian culture that have influenced Hip-hop artists in North America to show that the imitation and adaptation of cultures works both ways.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.728
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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.188
Teacher spread0.163 · 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.

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

Citations0
Published2014
Admission routes1
Has abstractyes

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