Midwives as agents of change: a qualitative analysis of midwives’ experiences with abortion care provision in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Midwives possess the skills and competencies required to provide abortion care in Canada, yet their role is constrained in health systems. They are well suited to address barriers to abortion access related to geographical and social inequities, which deprive many Canadians of essential healthcare and impede reproductive justice. To address current gaps, this study explores midwives' experiences providing abortion care in Canada. Qualitative data were collected from 25 in-depth interviews and three focus group discussions with midwives between August and December 2023. Using reflexive thematic analysis, we explored how midwives work in communities to provide or work toward providing abortion care, including health system facilitators, barriers, and their values, needs, and preferences for implementation. Findings highlight the barriers midwives face, including regulatory restrictions and a lack of flexible funding arrangements. Despite these challenges, midwives are leveraging their skills to advance reproductive justice, offering culturally safe, client-centred abortion care to underserved populations, including uninsured individuals. The study also identifies facilitators, such as applying midwifery values and philosophies to provide the midwifery model of abortion care. This research contributes to the growing body of knowledge on midwifery and abortion care, advocating for the removal of regulatory and funding barriers that limit midwives' potential to provide comprehensive sexual and reproductive healthcare. The findings have significant implications for policymakers and health system leaders in Canada and beyond, calling for the optimisation of midwives' roles to improve access to abortion care and advance reproductive rights globally.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it