(Re)producing feminine bodies: emergent spaces through contestation in the Women’s March on Washington
Bibliographic record
Abstract
The Women’s March on Washington was an event organized to protest the erosion of women’s rights, and created a space where women in the United States (and beyond) could publicly voice their concerns. Yet the organization and effects of events surrounding the March seemed to be invoking conventional understandings of what counts as femininity. We conceptualized this tension as a practice associated with Foucault’s ideas about the politics of purification. We look at the construction of pure bodies to the detriment of unpure ones in three contested sites of the March: the erasure of Indigenous women and women of colour within the Women’s March on Washington-Vancouver organizing group, the use of the PussyHat to symbolize unity of all women, and the reclamation of the nasty woman meme. From our critical reflection on these productive processes, we suggest that new spaces have emerged as an effect of these acts that possess the potential to produce alternative notions of femininity that can challenge conventional, hegemonic ones.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.042 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| 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".