The Lived Experiences of Immigrant Canadian Women with the Healthcare System
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
Immigrants to Canada report better health status than the Canadian-born population when they first arrive in Canada, a phenomenon called the Healthy Immigrant Effect. However, by the fourth year after immigration, immigrants report a health status that is worse than that of the Canadian-born population. Visible minority immigrant women report the largest deterioration in health. The purpose of this qualitative study was to explore the lived experiences of visible minority immigrant women with encounters with the Canadian healthcare system to examine the multiplicative impact of gender, ethnicity, and immigration on their health. This phenomenological study, guided by Crenshaw's feminist intersectionality framework, explored the perspectives of a purposive sample of 8 immigrant women in Ottawa, Canada, about their encounters with the healthcare system. Data were collected through individual interviews. These data were inductively coded and subjected to thematic analysis following the process outlined by Smith et al. for interpretative phenomenological analysis. Key findings of the study revealed that immigrant women define health more holistically and have expectations of the encounters with healthcare that are not met due to barriers that impact them accessing healthcare services, experiencing healthcare services, and following the recommended options. The positive social change implications of this study include recommendations for public health to consider immigration and racism as determinants of health; and for Health Canada to undertake system-level lines of inquiry to shed light on the ways structural discrimination and racism have had an impact on immigrant women's social and health trajectory.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it