Barriers influencing the care of survivors of gender-based violence in the context of forced displacement in Kaya, Burkina Faso: a qualitative study
Bibliographic record
Abstract
ABSTRACT Gender-based violence (GBV) is a serious international health problem that challenges fundamental human rights. In addition to violating fundamental rights, it is an attack on the principles of gender equality. GBV is exacerbated in situations of conflict and forced displacement because of the vulnerability it engenders, particularly among women and children. Therefore, caring for victims of GBV in the context of a humanitarian crisis is special because of the specific nature of the context itself. This study aimed to explore the factors that negatively influence the care of survivors of GBV in the context of forced displacement. This was a descriptive and analytical-qualitative study. A total of 26 participants participated in the individual interviews. Most participants were healthcare workers (53,8%). The findings show that barriers to care are sociocultural (fear of stigmatization, ignorance of the benefits of seeking appropriate care and support, self-censorship among GBV survivors, fear or risk of reprisal, honor denied, fear of the aggressor punishment, shame and fear of being repudiated), institutional (lack of qualified human resources to care for GBV survivors, insufficient information on the availability of care services, geographical inaccessibility of care services, lack of confidentiality from service providers, inadequate health care and support systems, low availability of care services, poor quality of care) and financial. Bringing all care services together in one place, such as a one-stop center, is imperative to overcome these obstacles. In this way, it will be possible to improve accessibility to services and enhance the quality of care through effective coordination.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".