Evidence-informed framework for gender transformative continuing education interventions for midwives and midwifery associations
Bibliographic record
Abstract
INTRODUCTION: Continuing education for midwives is an important investment area to improve the quality of sexual and reproductive health services. Interventions must take into account and provide solutions for the systemic barriers and gender inequities faced by midwives. Our objective was to generate concepts and a theoretical framework of the range of factors and gender transformative considerations for the development of continuing education interventions for midwives. METHODS: A critical interpretive synthesis complemented by key informant interviews, focus groups, observations and document review was applied. Three electronic bibliographic databases (CINAHL, EMBASE and MEDLINE) were searched from July 2019 to September 2020 and were again updated in June 2021. A coding structure was created to guide the synthesis across the five sources of evidence. RESULTS: A total of 4519 records were retrieved through electronic searches and 103 documents were included in the critical interpretive synthesis. Additional evidence totalled 31 key informant interviews, 5 focus groups (Democratic Republic of Congo and Tanzania), 24 programme documents and field observations in the form of notes. The resulting theoretical framework outlines the key considerations including gender, the role of the midwifery association, political and health systems and external forces along with key enabling elements for the design, implementation and evaluation of gender transformative continuing education interventions. CONCLUSION: Investments in gender transformative continuing education for midwives, led by midwifery associations, can lead to the improvement of midwifery across all United Nations' target areas including governance, health workforce, health system arrangements and education.
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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 | 0.233 | 0.201 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.032 | 0.019 |
| Science and technology studies | 0.010 | 0.019 |
| Scholarly communication | 0.024 | 0.015 |
| Open science | 0.015 | 0.017 |
| Research integrity | 0.015 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".