Doing feminism in the network: Networked laughter and the ‘Binders Full of Women’ meme
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We analyse how memes construct networks of feminist critique and response, mobilising the derisive laughter that energises current feminisms. Using the 2012 case of the ‘Binders Full of Women’ meme, we argue that feminist memes create online spaces of consciousness raising and community building. The timeliness, humorous affect and media techné of meme propagators become significant infrastructures for feminist critique, what we term ‘doing feminism in the network’. If the Internet is particularly good at facilitating the diffusion of feminist jokes, as others argue, we illustrate how the networking and distribution capacities of social media platforms such as Tumblr, Facebook and the online shopping site Amazon.com also cultivate new modes of feminist cultural critique and models of political agency for practising feminism through meme production and propagation.
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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 | 0.017 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it