Delivering Care to Women who are Homeless: A Narrative Inquiry into the Experience of Health Care Providers in an Obstetrical Unit
Bibliographic record
Abstract
The purpose of the study was to explore the experiences and perceptions of health care providers in an acute care setting delivering care to pregnant women who are experiencing homelessness. In recent years, the number of women experiencing homelessness has significantly increased. In North America, the emerging homeless profile is that of a younger person and more often women. Living in precarious housing situations increases one’s risk for serious health conditions. Women who are homeless often experience complex health issues but many intersecting barriers exist between homeless women and health care providers, which impacts the care provided. A better understanding of the health care providers who provide care is urgently needed. A narrative inquiry design was implement. We recruited 10 health care providers from antenatal, postpartum, and labour and delivery units in a large, urban tertiary care hospital. Using narrative inquiry methodology, and a conversation guide we explored care providers’ personal and professional experiences over time, place, and within social contexts. Conversations with participant were held 2 or 3 times. From participants’ narrative accounts, we identified four threads that were evident across their experiences: shaping and being shaped by institutional mandates, the importance of conversational spaces, the lack of interprofessional interactions and living with conflicted views about practice. Care practices are shaped by complex personal, interpersonal, and institutional factors. Contextualized learning experiences within health care settings may serve to encourage narrative reflective practices and support communities of practice with the ultimate goal to improve health care delivery for women in precarious housing situations.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".