Rural Health for Pregnant and Birthing People: Access and Advocacy
Bibliographic record
Abstract
Midwifery care is a safe and cost-effective care model; producing excellent outcomes especially for vulnerable and isolated people due to its one-on-one continuity of care and family-centered model. Recent research studies have shown out of hospital birth to have numerous benefits; shorter labors and lower rates of interventions, without an increase in adverse outcomes. These outcomes are more reliable when midwifery care is fully supported and integrated into existing maternity care systems. There are significant barriers to the provision of equitable reproductive health care to pregnant and birthing people in rural and remote areas. This, in the context of the United States being the only country where maternal mortality rates are on the rise. Midwifery care has been proposed as a potential solution but the need for working models of such care exists. The article showcases a working and replicable midwifery care practice model; showing how it can function to address inequity by building collaborative partnerships with other providers to advocate on clients’ behalf and reduce vulnerability to health disparities. This has practice implications for maternity providers and policy makers, introducing how advocacy can help remove the systemic barriers affecting reproductive justice and care.
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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 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".