What Hath Dobbs Wrought? Abortion activism in precarious and punitive times
Bibliographic record
Abstract
In June 2022, the U.S. Supreme Court in Dobbs v. Jackson Women’s Health Organization (2022) overturned Roe v. Wade (1973), abolishing the constitutional right to abortion. Significant in its radical criminalization of abortion, Dobbs reinvigorated feminist activism for reproductive justice. Digital and mobile technologies are used in innovative ways by activists to organize, educate, and dispel counter-narratives about abortion, including feminist global networks that provide medication abortion and abortion storytelling through social media and media interventions. There continue to be analogue interventions that are the legacy of the 1960’s-era Jane Collective. In this vexatious legal environment, the communication technologies that facilitate abortion activism are weaponized by restrictionist actors to not only misinform, but also, through abortion surveillance, to track and curtail access to reproductive care by tapping into and exploiting what we term the personal data economy of reproductive health. Activists are thus countering the surveillant assemblages engaged by restrictionist states whose objective is to criminalize abortion access and care across borders. This article considers the historical and current media ecology surrounding reproductive health, care and justice, the technologies that have and continue to shape it, and the array of analogue, digital, mobile and hybrid feminist activist interventions emerging post-Roe.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.025 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".