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Record W3091888527 · doi:10.5210/spir.v2020i0.11187

LIFE WITH DICK AND DICK: RACE AND MALE PORNOGRAPHICSELF-REPRESENTATION ON REDDIT

2020· article· en· W3091888527 on OpenAlexaff
Rhiannon Bury, Lee Easton

Bibliographic record

VenueAoIR Selected Papers of Internet Research · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsAthabasca University
Fundersnot available
KeywordsAppropriationWhite (mutation)Race (biology)Representation (politics)Identity (music)SociologyGender studiesAestheticsArtPoliticsPolitical scienceLaw

Abstract

fetched live from OpenAlex

This paper broadly focuses on the sharing of male pornographic self-representation (PSR) on the Reddit forum, Massive Cock. Our previous study examined how gay-straight relations are recoded on the forum. Drawing on new data currently being collected, we focus on the operation and intersection of racialized masculinities as afforded by hybrid networked technologies, platforms, and screens. Based on preliminary data collection and analysis, we argue that Massive is a space of unmarked whiteness, with a paucity of racialized dick pics. We discuss the ways in which the less than 10 percent of posters of colour mark out their racialized identities, including through the mobilization of the problematic trope of the BBC (“big black cock”), with its roots in interracial pornography. We also examine the ways in which a much smaller number of racialized men, who are not black, mark out their racial/ethnic identity. Finally we look at the few white men who draw attention to their race through appropriation of the BBC discourse as BWC ("big white cock"). Taken together it is clear that Massive is a “fraternity of the [white] cock” (Waugh, 2004) but it is one that is disrupted and unsettled by the presence of racialized PSR.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.373

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.059
GPT teacher head0.355
Teacher spread0.296 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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