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In the landlocked country of Bolivia, the indigenous and post-colonial cultures have interacted and influenced one another for hundreds of years. As these cultures have merged, they have formed a unique set of social and cultural norms that govern the Bolivian peoples’ attitudes and behaviors towards all aspects of life. These social and cultural norms play both a constructive and deconstructive role in creating gender roles, identities, and expectations. They also shape what are considered appropriate and inappropriate behaviors between men and women. A behavior that is prevalent in Bolivia is violence against women. The 2008 Demographic and Health Survey (DHS) estimates that 47% of women, married or in common unions, have experienced psychological, physical, or sexual violence in the past 12 months.1 In 2010, 72 women in Bolivia were victims of murder. Records show that 42% of murder victims were between 18 and 30 years old and that their intimate partners were responsible for more than 50% of their deaths.2 In 2010, 4,515 women were admitted to hospitals due to serious violence related injuries.3 A cross-country study led by Victor Asal and Mitchell Brown established that, in comparison with 31 other countries, violence against women in Bolivia can be considered widespread.4 This project aims to unpack the prevalence of violence against women in Bolivia and identify key risk factors that are present. Due to Bolivia’s demographic diversity, it is important Coa, Ramiro and Luis H. Ochoa. “Encuesta Nacional de Demografia y Salud (DHS) 2008.” Instituto Nacional de Estadistica adn Ministerio de Salud y Deportes, October 2009, 240 2 “Se registraron 117 asesinatos de Mujeres.” El Diario La Paz- Bolivia. 25 November 2010. http://enfermeria.bvsp.org.bo/cgi/sys/s2a.xic?DB=B&S2=2&S11=21319&S22=b Date of Access: 15 January 2011. 3 “En 11 meses, 4,514 mujeres llegan a hospital por violencia.” Los Tiempos 26 November 2010. http://enfermeria.bvsp.org.bo/cgi/sys/s2a.xic?DB=B&S2=2&S11=21321&S22=b Date of Access: 15 January 2010. 4 Asal, Victor and Mitchell Brown. A Cross-National Exploration of the Conditions that Produce Interpersonal Violence. In Politics and Policy. (38, 2) 2010, 175. 1 to analyze these factors by state. By using GIS to plot key risk factors one is better able to present data and prescribe policy interventions. Methodology This project will use Lori Heise’ 1998 Violence against Women: An Integrated, Ecological Framework, which incorporates a multilevel and multi-factor approach to analyzing violence against women. The Ecological Framework is made up of four levels of analysis that include the interplay between individual characteristics, relationships, community, and society.5 Within each level, Heise outlines a series of risk factors that are considered true casual factors that affect the likelihood of an individual becoming a victim of intimate partner violence. A list of all the factors that lead to women being victims of violence are included in Appendix A. In this analysis, I have chosen to focus primarily on four key community-based indicators. They are: female and male illiteracy, female and male unemployment, and poverty. Since county or municipality data could not be found, the information is plotted at the state administrative level. In addition, I have opted to add an indicator: the number of individuals that identify themselves as indigenous. Since this specific data point could not be found, ‘selfidentified mother tongue’ is used as a proxy indicator. The use of this indicator is an attempt to determine whether there is a correlation between violence against women, where people live, and their perceived culture. Data on the prevalence of physical, sexual, and psychological violence against women, and the associated risk factors is derived from the Demographic Health Survey (DHS) and the National Statistic Institute of Bolivia. The DHS data is one of the most robust collections of Heise, Lori. “Violence against Women: An Integrated Ecological Framework.” In Violence against Women 1998 (4):262 ; Centre for Disease Control (CDC). “Sexual violence prevention: beginning the dialogue.” Centre for Disease Control and Prevention. 2004 http://www.cdc.gov/ncipc/dvp/SVPrevention.pdf. Date of Access: 17 January 2011; Bolt (2008). 5 health-related data (the latest survey was conducted in 2008). The National Statistic Institute of Bolivia conducted its latest population survey in 2001. The foundational maps that provide the background to input the data come from ArcGIS. Table 1 provides a detailed description of the data sources. Table 1: Data Sources utilized in this study Data Source Website Violence Rates DHS Literacy Rates DHS Unemployment Rates Income Quintiles DHS Indigenous Languages INE http://www.measuredhs.com/countries/country_main.cf m?ctry_id=2&c=Bolivia http://www.measuredhs.com/countries/country_main.cf m?ctry_id=2&c=Bolivia http://www.measuredhs.com/countries/country_main.cf m?ctry_id=2&c=Bolivia http://www.measuredhs.com/countries/country_main.cf m?ctry_id=2&c=Bolivia http://www.ine.gob.bo:8082/censo/make_table.jsp?query =poblacion_15 DHS Online Metad ata N.A Source Scale Year Presented 1 2008 N.A 1 2008 N.A 1 2008 N.A 1 2008 N.A 1 2001 The first step taken to prepare the data analysis was inputting the data from tabular format into GIS. Once that data was inputted, a layer was created for each of the risk factors. Then two foundational layers were created to highlight (1) the percentage of women that had experienced sexual and physical violence, and (2) the percentage of women that had experienced physiological violence. Depending on the risk factors, pie or bar graphs were created to illustrate whether a particular state that had high percentage of violence also had a high risk factor. Results There is a general prevalence of violence against women across all provinces. Across the country, between 20% and 28% of women had experienced sexual or physical abuse in the past 12 months (Map 1). The overall variance between 20% and 28% is not significant. Map 1: Percentage of Women who have experienced Sexual or physical assaults in the past 12 months. Likewise, psychological violence is also prominent throughout the country with 30% to 37% of women experiencing abuse in the past 12 months (Map 2). While the lack of a significant variance in either one of these statistics shows that the country needs to work hard to address violence, it does not indicate how it should go about doing so nor does it indicate how it should prioritize strategies. Map 2: Percentage of Women who have experienced Psychological assaults in the past 12 months. When correlating geography, prevalence of violence, and literacy rates one gains a greater depth of understanding into the policy options that the government of Bolivia may have. Throughout Bolivia, women are, on average, less educated than men. Provinces with the highest prevalence of violence against women also have the greatest percentage of women that have not completed primary school. Increasing women’s literacy rates and education standards is a policy option that may reduce both poverty and the prevalence of violence against women. (Map 3 and 4) Map 3: Percentage of level of women’s education by state (2008) Map 4: Percentage of level of men’s education by state (2008) Having an indigenous language as a mother tongue may be the most adequate proxy to represent culture. Bolivia is a very diverse country in which multiple cultures have interacted for centuries. There appears to be little correlation between the percentage of people who speak a certain language and whether there is a high prevalence of violence in that state. For instance, in the state of Potosi, more than fifty percent of the population speaks an indigenous language as their mother tongue. However, neighboring province Oruro, which also has a high prevalence of sexual or physical violence, the majority of people speak Spanish. More detailed studies at the micro-administrative level need to take place to truly determine if there is a relationship or not. What is certain is that any policy initiative will have to be communicated in a multi-lingual format in order to reach the greatest number of households. Map 5: Percentage of women’s mother tongue by size of total state population Map 6: Percentage of men’s mother tongue by size of total state population Poverty is another risk factor that Lori Heise identifies in her study as leading to violence against women. In the Bolivian case, it becomes apparent that provinces with a high prevalence of sexual and physical violence also have more than 50% of the population living in the lowest three income quintiles. When one compares Potosi and Santa Cruz, it becomes evident that not only does Santa Cruz have lower rates of violence against women, but wealthier people also reside in this province. Unemployment rates for men are generally steady between 22% and 11%. However, unemployment rates for women vary extensively across provinces from 45% to 21%. Hence, another policy option for the government of Bolivia is to tackle both unemployment and poverty. Map 7: Income Quintiles by State and by Total State Population Map 8: Unemployment Rates by State Challenges: While there are a lot of statistics in tabular format, finding GIS related information about Bolivia was a difficult process. Information is not always disaggregated at the municipal or county level. This makes it difficult to prescribe policy recommendations and to conduct a more complex analysis. For instance, by not knowing the number of police stations or their locations, one is unable to determine whether interventions that are run from those offices are able to reach victims of violence or not. One is also unable to use ArcGIS to answer questions related to access to healthcare clinics or schools. Conclusion This project enables the visualization of very important data and allows for policy makers to better understand the gravity of violence against women within each state. Unfortunately, this project provides little additional insight into why there is such a concerning prevalence of violence against women. Since the data provided within the DHS survey is at the provincial level, there is little variance in percentage of women that experience sexual, physical or psychological violence. More so, when analyzing the risk factors, it is unclear which one is of more importance. To date, no researcher has aggregated risk factors or prioritized them, hence, providing any sort of ranking is difficult. To move forward with this project one would have to plot some of the other risk factors that Lori Heise argues are of importance. Some of these include: whether communities sanction violent acts, marital dissatisfaction, and use of alcohol. However, finding robust data on these is difficult, particularly at the municipality level. Better descriptive data and GIS data, will provide even more adequate analysis and policy prescriptions. There remains much more work to be completed in the area of identifying risk factors and analyzing trends in violence against women. Appendix: A Risk factors for Victims and Perpetrators of Intimate Partner Violence and Sexual Violence PERPETRATION BY MEN VICTIMIZATION OF WOMEN INDIVIDUAL LEVEL Demographics Demographics Young age Young age Low education Low education Low socio-economic status/income Low socio-economic status/income Unemployment Pregnancy Separated/divorce marital status Exposure to Child Maltreatment Exposure to Child Maltreatment Exposure to child maltreatment Intra-parental violence Exposure to intra-paternal violence Sexual abuse Sexual and/or physical abuse Mental Disorder Mental Disorder Antisocial personality Depression Substance use Substance use Harmful use of alcohol Harmful use of alcohol Illicit drug use Illicit drug use RELATIONSHIP LEVEL Friction over women’s empowerment/ education disparity Friction over women’s empowerment/ education disparity Multiple partners/infidelity Large number of children Low resistance to peer pressure Male dominance in the family Relationship quality Marital dissatisfaction/discord Gender role disputes Marital duration Relationship quality Marital Dissatisfaction/discord COMMUNITY LEVEL Acceptance of traditional gender roles Acceptance of traditional gender roles Weak community sanctions Weak community sanctions Poverty Poverty Neighbourhood characteristics Neighbourhood characteristics High proportion of poverty High proportion of poverty High proportion of unemployment High proportion of unemployment High proportion of male illiteracy High proportion of female illiteracy Acceptance of violence Acceptance of violence High proportion of households that use corporal punishment High proportion of households that use corporal punishment Low proportion of women with high level of autonomy Low proportion of women with higher education SOCIETAL LEVEL Traditional gender norms and societal norms supportive of violence Traditional gender norms and societal norms supportive of violence Supportive of violence Supportive of violence Divorce regulations by government Lack of legislation on intimate partner violence within marriage Protective marriage law Adapted from the following sources: WHO (2010), Heise (1998) and CDC (2004). Apppendix B: Annotated Bibliography A. Coa, Ramiro and luis Ochoa. “Encuesta Nacional de Demografia y Salud ENSA 2008” October 2009 This is the 485 page report that summarizes the data collected as part of the Demographic Health Survey (DHS) 2008. It is the most comprehensive data on gender-based violence in Bolivia. The data in this report can be considered representative and is dissected by province, age, education, and income level. It becomes very useful to analyze information and construct map layers. B. Morales, Rolando and Ana Maria Aguilar, Alvaro Calzadilla. “Undernutrition in Bolivia: Geography and culture matter” Inter-American Development Bank. April 2008 This paper showcases the interlink between nutrition, health, and geography in Bolivia. My research study will try to test out the similar dynamic but including gender-based violence instead of nutrition. This paper also provides some background information on Bolivia’s culture, language, and religion. C. Morrow, Betty Hearn. “Identifying and Mapping Community Vulnerabilities.” In Disasters 1999 (23,1), 1-18 This paper does not address the subject matter related to Bolivia specifically. However, it provides a good framework to thinking about vulnerabilities (which Bolivian women have) and which factors to consider when conducting my research on Bolivia. D. Albers, Nathaniel. “The Geography of Domestic Violence: Assessing Reported Domestic Violence in Missouri.” Master Thesis. University of Missouri. April 2005. This Master Thesis is very interesting because by focusing on the state of Missouri, the researcher is able to do some of the work that I would like to do, but the data is so hard to find for the context of Bolivia. Nathaniel Albers uses GIS to plot incidents of violence by county within the state of Missouri. He also analyses the known risk factors that make some women more susceptible to becoming victims of violence. By identifying the different factors, it is easier to make policy recommendations, while still utilizing visual tools. E. Elizabeth Groff, David Weisburd, and Nancy Morris. “Where the Action is at Place: Examining Spatio-Temporal Patterns of Juvenile Crime at Places using Trajectory Analysis and GIS.” In Putting Crime in its Place 2009. The chapter in this book is useful because it spends some time analyzing the method by which the researchers went about to tackle the linkages between youth crime and location. They argue that a different technique of utilizing GIS leads to different outcomes. F. Steinberg, Michael K. and Carry Height, Rosemary Mosher, and Mathew Bampton. “Mapping massacres: GIS and state terror in Guatemala.” In Geoforum, 2006 (37) 22 April 2003 This paper is very useful because it shows how even at the provincial level one can aggregate information and place it on a map, utilizing GIS to further the analysis. It showed me that while my research question may not be as ambitious as it could be, there will be value in presenting the correlation between the different risk factors visually.