Abortion: US “global gag rule” is killing women and girls, says report
Bibliographic record
Abstract
A US government policy that blocks federal funding for non-governmental organisations that provide or support abortion is killing women, a new report says, because they are being excluded from a range of essential sexual and reproductive health services and information and turning to unsafe abortions. The “global gag rule” rule prohibits foreign non-governmental organisations that receive US global health funding from providing legal abortion services or referrals and also bars advocacy for abortion law reform. The rule, first implemented by the Reagan administration and rescinded by subsequent Democratic presidents, was reinstated and expanded by Donald Trump when he took office in 2017. It now affects an estimated $9bn (£7bn; €8bn) of US global health assistance. Two years on, an assessment of services in Kenya, Nepal, Nigeria, and South Africa has found “irrefutable evidence” that the gag rule was “depriving women and girls and other marginalised populations of essential information and services,” with devastating consequences.1 Vanesa Rios, who wrote the report for the US based International Women’s Health Coalition, told a press briefing at the Women …
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.017 | 0.006 |
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".