Bibliographic record
Abstract
Despite having the most expensive system of maternity care in the world, outcomes for birthing people in the USA are worse than other high-income nations. Critically, US outcomes also reflect deep and persistent racial and ethnic health disparities. The maternal mortality rate (deaths occurring within 42 days of pregnancy per 100 000 live births) in the USA was 23.8 in 2020, the highest of all comparable countries. Non-Hispanic black (NHB) and Native American individuals are two to three times more likely to die during or after childbirth compared with those who are non-Hispanic white (NHW). In contrast, maternal mortality outcomes for Hispanic and Asian/Pacific Islanders are generally comparable with those of NHW individuals, though some research findings suggest health disparities among specific subgroups. NHB and Native Americans also experience higher rates of severe maternal morbidity (SMM), resulting in significant short-term or long-term consequences to their health. While mortality rates among industrialised countries are highest in the USA, racial and ethnic disparities in outcomes have also been noted in Brazil, Canada, the Netherlands and the UK.
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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 | 0.027 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.046 | 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".