LIFE WITH DICK AND DICK: RACE AND MALE PORNOGRAPHICSELF-REPRESENTATION ON REDDIT
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".