Screening women’s history in the film <i>Suffragette</i> (2015): between intersectional feminist activism and historical memory
Bibliographic record
Abstract
Prior to its release, the film Suffragette (2015) generated significant media commentary when its marketing campaign emblazoned a controversial historical quotation on promotional t-shirts. The 1913 Emmeline Pankhurst quotation generated a variety of negative emotional responses across digital, print, and social media because it compared women’s disenfranchisement to slavery. This article builds on recent historical analyses of national and transnational women’s movements that are informed by the history of emotions. It considers the operation of discourses of slavery within the history, memory, and popular culture of the transatlantic women’s suffrage movement. Using Jemima Repo’s concept of feminist commodity activism to situate the t-shirts, this article examines the anger and frustration that dominated media commentary about the Suffragette marketing campaign across the United States, Britain, Australia, and Canada. Both the filmmakers and intersectional feminist activists embraced historical evidence—from primary and secondary sources—to mobilise different narratives about the Women’s Social and Political Union. Yet many journalists and commentators envisioned the film’s construction of historical memory as insufficiently attuned to racism within the history of feminism, and thus as a failure of intersectional feminism. Suffragette reveals significant anxieties about how the women’s suffrage movement should be remembered in the twenty-first century.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| 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".