The Challenges of Providing Postpartum Education in Dar es Salaam, Tanzania: Narratives of Nurse-Midwives and Obstetricians
Bibliographic record
Abstract
Postpartum education can save lives of mothers and babies in developing countries, and the World Health Organization recommends all mothers receive three postpartum consultations. More information is needed to better understand how postpartum education is delivered and ultimately improves postpartum health outcomes. The purpose of this qualitative study was to examine how postpartum care was delivered in three postnatal hospital clinics in Dar es Salaam, Tanzania. Semistructured interviews with 10 nurse-midwives and three obstetricians were conducted. Feminist poststructuralism guided the research process. Postpartum education was seen to be an urgent matter; there was a lack of supportive resources and infrastructure in the hospital clinics, and nurse-midwives and obstetricians had to negotiate conflicting health and traditional discourses using various strategies. Nurse-midwives and obstetricians are well positioned to deliver life-saving postpartum education; however, improvements are required including increased number of nurse-midwives and obstetricians.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".