28 times feminist joke lists were real AF: feminist humour and the politics of joke lists
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
Despite the pervasive visibility of joke lists in online popular culture, the latter remains a surprisingly neglected site of scholarly inquiry. Feminist joke lists represent the concerted efforts of online content producers to curate a wide range of feminist humour—content that is expressly feminist in political orientation and/or sympathetic to highlighting feminist issues and sensibilities. These lists offer a compelling point of departure for interrogating the uses, limitations, and possibilities of joke lists for feminist communities of practice and how this cultural form enacts or inscribes feminist politics online. In this essay, I theorize the political significance of feminist joke lists through an examination of 20 distinct lists featuring over 350 jokes spanning a six-year period (2013–2019). Through an examination of general curated feminist joke lists, as well as humour lists produced in the wake of the 2017 and 2018 Women’s Marches, I argue that these broader activities contribute to the visibility and validation of feminist humour, the sharpening of feminist critique, and the solidarity of feminist communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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