Are we all Pussy Riot? On narratives of feminist return and the limits of transnational solidarity
Bibliographic record
Abstract
On Friday 17 August 2012, members of the feminist collective Pussy Riot were sentenced to two years in jail after their staging of a musical protest in a Russian Orthodox church. This article analyses Western news media responses to the Pussy Riot affair. It first examines how the event has resonated across various news media, activist, and social media networks. Focusing on the phrase, ‘We are all Pussy Riot’, which became a Twitter hashtag following the incarceration of Pussy Riot members, I argue that narratives of feminist return (Hemmings, 2011) and of US exceptionalism have shaped the eventfulness of the Pussy Riot affair in the West. While not dismissing the activism of Pussy Riot, this article asserts that the discourses of transnational solidarity and feminist renewal that the arrests engendered rely on the perceived whiteness and non-Western identities of the members who were incarcerated.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.028 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".