Understanding the Influence of Ghanaian Women’s Migration Patterns on Access to Health Care
Bibliographic record
Abstract
Increased migration rates demonstrate a rise in women seeking relocation as a means to access employment or academic opportunities; this 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 are deprived of due to various social, cultural, political, and economic factors. A secondary analysis design was implemented to explore the impact of social determinants of health, specifically socioeconomic status, culture, and education, on health outcomes and health care access of Ghanaian internal and external female migrants. Interviews collected from two primary studies were analyzed using thematic analysis and an intersectionality approach. Ghanaian female migrants experienced cultural, financial, social, and health accessibility related barriers in accessing health care services. 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".