Bibliographic record
Abstract
Safe abortion access is an essential aspect of reproductive justice and key to reducing global rates of maternal mortality, yet within the global heath enterprise, the rhetoric of sexual and reproductive health and rights has not yet been realised in practice. Access to safe legal abortion remains inequitable globally and within nations and deaths due to unsafe abortion take their highest toll in the Global South in jurisdictions with restrictive laws. Clandestine abortion access activist networks have been filling this gap offering life, dignity and futures to the people who seek their services. What should we make of clandestine activist networks around the world that help people access medication abortion? Such groups have been important players in women’s reproductive health in many jurisdictions for decades – but have typically, by necessity and design, flown under the radar. If visibility, accountability and humanitarian appeal are essential characteristic of global health work, how do we acknowledge and understand the work of clandestine abortion access activist networks? Does it count as global health? In this essay I offer the notion of ‘critique in action’ to further our understanding of such networks and also consider the idea of abortion access activist networks as an anti-regime of global health.
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.
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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.056 |
| Scholarly communication | 0.025 | 0.031 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".