Brooms and Ballots: #WitchTheVote, the Nostalgic Internet, and Intersectional Feminist Politics on Instagram
Bibliographic record
Abstract
Over the past decade, there has been significant scholarly and mainstream attention to the use of digital media technologies to engage in feminist politics and activism. This article explores an example of small-scale, feminist digital activism: the #WitchTheVote hashtag on Instagram. Using a visual and discursive analysis of 75 Instagram posts and interviews with four self-identified witches active on Instagram during the summer of 2020, we argue that #WitchTheVote is an example of reflective nostalgic activism that challenges the mediated popular feminism most visible across social media attention economies. This case study demonstrates the potential for doing intersectional feminist politics online that contradicts both popular feminism and its attendant platform conventions, imagining a different kind of feminist politics that troubles visibility, attention, celebrity, large audiences, and consumption as part of contemporary digital feminism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".