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Record W1990058853 · doi:10.4148/2334-4415.1737

“Knaller-Sex für alle”: Popfeminist Body Politics in Lady Bitch Ray, Charlotte Roche, and Sarah Kuttner

2011· article· en· W1990058853 on OpenAlexaff
Carrie Smith-Prei

Bibliographic record

VenueStudies in 20th & 21st century literature · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicGerman Literature and Culture Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFeminismGender studiesPopular cultureSubculture (biology)PoliticsDepictionSociologyHuman sexualityFemininityArtArt historyLiteratureMedia studiesPolitical science

Abstract

fetched live from OpenAlex

Germany has seen a recent upsurge in publications proclaiming that feminism is again an urgent matter for a new generation of women. Faced with the reactionary demography debate and the hegemony of second-wave feminism, young writers, musicians, journalists, and critics call for new models of feminism relevant to women today. As one of these viable models, popfeminism draws on dominant trends in mass culture, on pop’s forty-year history as a cultural prefix in Germany, and on traditional feminism in order to create a new, ostensibly apolitical, feminist subculture based in self-stylization and individual autonomy. Shared by many popfeminist sources is the depiction of negatively coded female corporeality. This article begins with a theoretical analysis of writings on sexuality and the body in recent (pop)feminist nonfiction. It then examines the negative corporeal self-stylizations in Turkish-German rapper Lady Bitch Ray’s performances since 2006, in former music video host Charlotte Roche’s novel Feuchtgebiete (2008), and in media personality Sarah Kuttner’s novel Mängelexemplar (2009). Ultimately, these negatively coded bodies are shown to uncover popfeminism’s political intent.

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)0.001
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 score0.014
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.015
Scholarly communication0.0050.003
Open science0.0000.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.036
GPT teacher head0.278
Teacher spread0.242 · 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

Citations8
Published2011
Admission routes1
Has abstractyes

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