Exploring Barriers Refugees and Refugee Claimants Experienced Accessing Reproductive Health Care Services in Toronto
Bibliographic record
Abstract
A qualitative feminist study was conducted to explore the access barriers to three reproductive health care services: prenatal care, postnatal care, and screening for cervical cancer, experienced by women refugee claimants in Toronto, Ontario, Canada. The study was informed by social constructionist epistemology and antiracist and intersectional perspectives, and focused on the social, political, economic, and historical contexts of the participants lives and their experiences with migration and the Canadian health care system. \nSixteen women refugee claimants and 6 service providers were interviewed individually. The study explored how the systems, structures, and policies of Canadian society shaped refugee claimants womens use of these services, or lack thereof, and shaped their everyday life experiences. The research findings indicated that the study participants immigration status, lack of health coverage, living arrangements, absence of service provider support, degree of health care knowledge, discrimination, and having suffered pain, discomfort, or trauma in the past impacted their use or lack of use of prenatal care, postnatal care, and cancer screening services. An intersectional analysis revealed that the gendered and racialized immigration and integration policies, and neoliberal ideologies and practices intersected to locate the participants in racialized and disadvantaged situations as the other wherein access to these services became challenging. \nWomen refugee claimants access to these and other reproductive healthcare services needs to be understood beyond the attempts to know their cultural health beliefs and practices, and beyond the neoliberal ideas of self-care, individual responsibility, and culturally sensitive care. Equitable access to healthcare cannot be ensured without resisting these womens racialized position as the other while addressing the social, political, historical, and structural inequities in Canadian society. To ensure barrier-free, full health care coverage to women refugee claimants, as well as other refugee claimants and immigrants, social inequities need to be addressed coupled with instituting broader structural changes federally and provincially in policies, funding, procedures, and practices.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.022 | 0.012 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".