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<br />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.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".