Affective Mobilizations: Pinkwashing and Racialized Homophobia in <i>Out There</i>
Bibliographic record
Abstract
This paper focuses on the affective economies which materialize around race, sexuality and queerness in the British context to enable the production and mobilization of an exceptionalist discourse of gay-friendly and post-homophobic Britain (i.e., pinkwashing). The author investigates the discursive workings of pinkwashing coupled with the racialization of homophobia, through a critical reading of the BBC Two documentary Out There (2013a), written and narrated by British gay-identified writer, activist and artist, Stephen Fry. The documentary captures and is in fact captured within a global moment of human rights speculation in which some European nation-states have invested in affective discourses of queer futurities as a marker of their capacity for tolerance, in contrast to predominantly racialized subjects/communities within and outside of Europe, increasingly naturalized as always already homophobic (i.e., racializing homophobia). My reading of the documentary demonstrates the interconnection between pinkwashing and racialized homophobia as discursive inventions which depend on the mobilization of affects such as love, pride, terror, hate and (un)happiness, as currencies of governance. Far from being universal or abstract, I contend that British LGBTQ human rights speculative discourse draws on a highly racialized affective economy—which constructs racialized communities within Britain and racialized populations and states outside the West, as excessively homophobic, rendering pre-dominantly gay male British subjects (and homopatriarchy) as exceptional patriots.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.021 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".