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Record W2888167289 · doi:10.1386/jpme.2.1-2.29_1

Conscious hip hop: Lupe Fiasco’s critical teachings on raced and gendered representations

2018· article· en· W2888167289 on OpenAlexaff
Alyssa Woods, Lori Burns

Bibliographic record

VenueJournal of Popular Music Education · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsUniversity of OttawaCarleton University
Fundersnot available
KeywordsIdeologySociologyCritical theoryAestheticsGender studiesPerforming artsCultural studiesContext (archaeology)Media studiesPoliticsEpistemologyArtVisual artsLawPhilosophyPolitical scienceHistoryAnthropology

Abstract

fetched live from OpenAlex

Abstract This article examines the critical pedagogy of Lupe Fiasco’s music video ‘Bitch Bad’ (2012). Situating Fiasco’s work as an instance of hip hop teaching, we propose an analytic model to facilitate the interpretation of genre conventions evident in the multimodal music video text. We place genre theory into dialogue with critical discourse analysis in order to bring forward the ideologies, social values and cultural norms invoked in Fiasco’s portrayal of hip hop video actors and spectators. The analysis reveals Lupe Fiasco’s and videographer Gil Green’s critique of racist and misogynist stereotypes perpetuated in the music industry. Fiasco and Green present the hip hop performer as a labourer who is asked to portray specific conventions of gender, race and class. They explore the impact of the genre conventions upon children who grow up in the context of these cultural norms; they situate Fiasco as a cultural critic and teacher; and they demonstrate the potential of the music video to function as a pedagogical text.

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)0.001
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 score0.134
Threshold uncertainty score0.951

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.328
Teacher spread0.277 · 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
Published2018
Admission routes1
Has abstractyes

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