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Record W2118633702 · doi:10.1177/0002764210381728

Culture, Rap Music, “Bitch,” and the Development of the Censorship Frame

2010· article· en· W2118633702 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Behavioral Scientist · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsCensorshipPopular musicSociologyDeviance (statistics)Mass mediaFraming (construction)Popular culturePublic opinionDemonizationMedia studiesSocial psychologyPsychologyPolitical scienceLawPoliticsVisual artsHistoryArt

Abstract

fetched live from OpenAlex

Drawing theoretically both from cultural studies and cultural criminology, this exploratory project suggests that negative public perceptions associated with rap music are in large part informed through both formal and informal censorship agendas and campaigns, what the author terms the censorship frame. The censorship frame consists of mass media reports that proclaim the cultural association between music and collectively shared and culturally agreed-upon perceptions of deviance. The focus of this project concerns rap music and the term bitch, a relatively recent common feature of everyday language use. This article (a) investigates the increased use and acceptance of “bitch” in popular culture; (b) examines this process in relation to the demonization of rap music; and (c) demonstrates the role of both mass media and claims-makers in shaping public opinion of rap music as deviant, even while other similar messages continue to remain virtually unchallenged throughout the popular cultural milieu. Implications for future research are discussed.

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.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.999

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 studies0.0010.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.247
Teacher spread0.218 · 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