Making Space for Midwifery in a Hospital: Exploring the Built Birth Environment of Canada’s First Alongside Midwifery Unit
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Canada's first alongside midwifery unit (AMU) was intentionally informed by evidence-based birth environment design principals, building on the growing evidence that the built environment can shape experiences, satisfaction, and birth outcomes. OBJECTIVES: To assess the impact of the built environment of the AMU for both service users and midwives. This study aimed to explore the meanings that individuals attribute to the built environment and how the built environment impacted people's experiences. METHODS: We conducted a mixed-methods study using a grounded theory methodology for data collection and analysis. Our research question and data collection tools were underpinned by a sociospatial conceptual approach. All midwives and all those who received midwifery care at the unit were eligible to participate. Data were collected through a structured online survey, interviews, and focus group. RESULTS: Fifty-nine participants completed the survey, and interviews or focus group were completed with 28 service users and 14 midwives. Our findings demonstrate high levels of satisfaction with the birth environment. We developed a theoretical model, where "making space" for midwifery in the hospital contributed to positive birth experiences and overall satisfaction with the built environment. The core elements of this model include creating domestic space in an institutional setting, shifting the technological approach, and shared ownership of the unit. CONCLUSIONS: Our model for creating, shifting, and sharing as a way to make space for midwifery can serve as a template for how intentional design can be used to promote favorable outcomes and user satisfaction.
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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 | 0.010 | 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 | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it