Research on gender-based violence in the developing world is finally beginning to get serious attention. But that research is, unfortunately, still overlooking violence to women in the burgeoning slums and informal settlements around the globe. The current study is one of the first to address the issue of gender-based violence in slum communities by presenting both qualitative and quantitative data from Kibera, Kenya—the largest slum in sub-Saharan Africa. Qualitative data were derived from the diaries of twenty women between the ages of 18-30 living in Kibera. Diary data were collected from 2007-2010. Quantitative data were derived from a survey administered to 200 Kiberan women in December, 2009. Results of the study‟s qualitative component show that women in Kibera use three main coping strategies to deal with gender-based violence. Although none of the strategies guarantees a cessation of violence, the endurance and faith strategy appears to be the most frequently chosen strategy and the one most effective in keeping women safe. The study also reveals a parallel between coping strategy and narrative style among the diarists, raising provocative questions about the relationship between journal writing and women‟s agency. Survey results show a higher rate of gender-based violence among women in Kibera (84.5%) than was measured among the general population (39%) in the KDHS (2008). The study also reveals that, although both diarists and survey participants appear to endure gender-based violence more often than they rebel against it, their attitudes toward gender-based violence are anything but accepting. Instead, both diarists and survey participants report that they do not believe gender-based violence is justified and that they are angry and upset over the amount of violence they experience.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-2974 |
| Date | 01 January 2011 |
| Creators | Swart, Elizabeth |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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