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Record W2067830381 · doi:10.1017/s0261143013000056

Afro-Samurai: techno-Orientalism and contemporary hip hop

2013· article· en· W2067830381 on OpenAlexaff
Ken McLeod

Bibliographic record

VenuePopular Music · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHybridityOrientalismAppropriationPopular cultureGender studiesNexus (standard)Identity (music)SociologyAestheticsCultural appropriationLiteratureMedia studiesArtAnthropologyEpistemologyPhilosophyEngineering

Abstract

fetched live from OpenAlex

Abstract This article examines the practice and recent rise in the use of various aspects of Japanese popular culture in hip hop, particularly as manifest in the work of RZA, Kanye West and Nicki Minaj. Often these references highlight the high-tech, futuristic aesthetic of much Japanese popular culture and thus resonate with concepts and practices surrounding Afro-futurism. Drawing on various theories of hybridity, this article analyses how Japanese popular culture has informed constructions of African American identity. In contrast to the often sensational media coverage of racial tensions between African American and Asian communities, the nexus of Japanese popular culture and African American hip hop evinces a sympathetic connection based on shared notions of Afro-Asian liberation and empowerment achieved, in part, through a common aesthetic of technological mastery and appropriation. The synthesis of Asian popular culture and African American hip hop represents a globally hybridised experience of identity and racial formation in the 21st century.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.021
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0010.002
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 head0.041
GPT teacher head0.274
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), 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

Citations20
Published2013
Admission routes1
Has abstractyes

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