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Record W3112138242 · doi:10.1080/14680777.2020.1861050

Low Femme, low theory: memes and the new bedroom culture

2020· article· en· W3112138242 on OpenAlexaff
Andi Schwartz

Bibliographic record

VenueFeminist Media Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsYork University
Fundersnot available
KeywordsSociologyQueerScholarshipQueer theoryHabitusCulture theoryPopular culturePoliticsInvisibilityCultural studiesAestheticsMedia studiesGender studiesEthnographyAnthropologyArt

Abstract

fetched live from OpenAlex

Are memes theory? Memes and femmes are both marked by failure; femmes fail to be sufficiently feminine, or sufficiently queer, memes fail as cultural productions, plagued by low-culture. Together, I argue, femmes and memes produce low theory. In my study of femme memes, I argue that they can be understood as making significant political and cultural contributions if framed by existing scholarship on memes that emphasize political and communicative functions (Chen 2012 Chen, C. 2012. “The Creation and Meaning of Internet Memes in 4chan: Popular Internet Culture in the Age of Online Digital Reproduction.” Habitus 3: 6–19. [Google Scholar]). Drawing from existing scholarship on internet memes, as well as feminist and queer theory, I argue that femmes are low theory practitioners, and memes are a mode of theorizing—a form of marginalized knowledge production that comes from a long lineage of the feminized, DIY cultures that occur in marginal spaces, like girlhood bedrooms. In this paper, I examine three key themes of femme memes—casual misandry, femme invisibility, and emotional vulnerability—to argue that femmes use memes to queer femininity and position femme as a political thinker and feeler. Through the creation and circulation of femme memes, femmes create a femme public that is both political and affective.

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)0.001
metaresearch head score (Gemma)0.005
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: none
Teacher disagreement score0.886
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.315
Teacher spread0.269 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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