Understanding the Influence of Ghanaian Women’s Migration Patterns on Access to Health Care 
Bibliographic record
Abstract
Abstract Background: In recent years, there has been a noted increase in migration rates with trends marking a rise in women seeking relocation as means to access employment or academic opportunities; this growth is referred to as the feminization of migration. Migration stimulates female empowerment, increases access to financial opportunities, and promotes cultural diversity; all while simultaneously exposing women to detrimental conditions that impose risks to their physical and psychological well-being. Health is a fundamental human right that female migrants often get deprived of due to various social, cultural, political and economic factors in the destination region. These factors catalyze inhabitable environments in which migrant women are further exposed to harm, stimulating their status as vulnerable populations. Methods: We performed a secondary analysis to explore how the social determinants of health, specifically socioeconomic status, culture, and education impact health outcomes and health care access of Ghanaian women who migrated internally within Ghana or externally to Canada. Fourteen interview transcripts, seven from each primary study dataset, were analyzed using thematic analysis and an intersectionality approach. Ethical approval was received for the primary studies and our secondary analysis via the Ethics Review Board at the University of Alberta, Canada. Results: Ghanaian female migrants experienced varying obstacles in terms of accessing health care services. The barriers were identified as cultural, financial, social, and lack of health insurance. Ghanaian women’s health outcomes were influenced by the conditions surrounding their migration including working conditions, separation from family, altered social support systems, and financial constraints. Conclusion: Areas requiring further research and development were identified by assessing migrants’ social determinants of health in the destination country and the associated-barriers in accessing health services. We hope our findings will serve as a foundation for improving health outcomes for female migrant populations and support health care professionals' practice of cultural competence.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".