#MeToo and #ShoutYourAbortion: Claiming Standing and Exploding the Private Sphere
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
Abstract This paper analyses the recent viral #MeToo and #ShoutYourAbortion campaigns and argues that examining them illuminates our thinking about privacy and standing.The paper argues that one of the aims of these campaigns was to debunk the view that women did not have standing with respect to matters concerning sexual harassment and reproductive care. The myths the campaigns sought to discredit – myths about sexual harassment and assault and abortion – involve victim-blaming, and one thing we do when we victim-blame is deny that the victim had standing. This paper also argues that women proved they had standing through these campaigns by revealing what was private. This is, I argue, a way of ‘exploding’ the private sphere as MacKinnon famously put it. By looking to these campaigns, we can see that their strategy relied on the value of privacy.
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 | 0.001 | 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 | 0.001 | 0.000 |
| 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 it