Femicide Legislation: Lessons from Latin America
by
Michelle Carrigan
A Thesis presented to The University of Guelph
In partial fulfillment of requirements for the degree of Master of Arts in Criminology and Criminal Justice Policy
Guelph, Ontario, Canada
© Michelle Carrigan, August, 2016
ABSTRACT
Femicide Legislation: Lessons from Latin America
Michelle Carrigan Advisor: University of Guelph, 2016 Dr. Myrna Dawson
Femicide is the killing of women because they are women. Previous research has examined femicide within specific countries in Latin America, but to date no regional assessment of the legislation and its effect on homicide rates has been conducted. This study analyzes femicide in Latin America at the regional level. A multi-stage mixed method analysis is conducted to examine how legislation has approached the problem of femicide and whether this has had an impact on the rates of femicide in the area.
Beginning with a qualitative analysis, thirteen legislation summaries were examined to assess how has femicide been constructed as a social problem within legislation.
Following this, a quantitative analysis was conducted on a variety of country-level variables including the focal variables female homicide rate and the introduction of legislation. Results of this analysis demonstrated that femicide legislation, in its current capacity, does not appear to be protecting women from femicide. ACKNOWLEDGEMENTS
I wish to extend a sincere thank you to all the people who made the pursuit of my Master’s of Arts Degree possible.
To begin, I would like to express my appreciation to my advisor, Dr. Myrna Dawson, who sparked the idea for this project and has been integral in the development of this research. Your feedback always encouraged me to think critically about each section of my thesis. Thank you for your guidance and insight throughout the last two years.
I would also like to thank my committee member, Dr. Lisa Kowalchuk. Thank you for your helpful feedback and excellent criticisms throughout each chapter of my thesis. Your expertise in Latin America has been very valuable throughout the development of this project.
To my friends, near and far, thank you for your reassurance, optimism, and support. The last two years have been amazing, overwhelming, and insightful. At times when insanity seemed probable, your distractions and friendship were crucial to my survival. In particular, I would like to express my sincere gratitude to those I have met during this program, who I am certain will be lifelong friends. You have truly shaped this experience, thank you for the wonderful memories over the last two years.
Lastly, to my parents, who have always said that I could do anything I put my mind to; thank you for your unwavering encouragement throughout my university career.
iii TABLE OF CONTENTS
CHAPTER 1: INTRODUCTION Global Context of Femicide……………………………………………………………….2 Overview of Latin America……………………………………………………………….3 Femicide Legislation………………………………………………………………………6 The Current Study…………………………………………………………………………9 Chapter Overview………………………………………………………………………..10
CHAPTER 2: LITERATURE REVIEW Introduction………………………………………………………………………………11 Defining Femicide……………………………………………………………………….12 Existence of Femicide in Latin America………………………………………………...17 Predictors of Femicide…………………………………………………………………...19 Gaps in Research…………………………………………………………………………32
CHAPTER 3: THEORETICAL FRAMEWORK Introduction………………………………………………………………………………34 The stages of social problems……………………………………………………………36 Contextual Constructionism……………………………………………………………...41 Development of femicide as a social problem…………………………………………...43
CHAPTER 4: METHODOLODY Introduction………………………………………………………………………………50 Qualitative Methods……………………………………………………………………...52 WPR Approach…………………………………………………………………………..54 Quantitative Methods…………………………………………………………………….59 Bivariate Analysis………………………………………………………………………..72 Before and After Legislation…………………………………………………………….72 With and Without Legislation……………………………………………………………74 Strengths and Limitations………………………………………………………………..75
CHAPTER 5: QUALITATIVE RESULTS Introduction………………………………………………………………………………78 Question 2 Findings……………………………………………………………………...81 Question 3 Findings……………………………………………………………………...93 Question 4 Findings……………………………………………………………………..97 Summary………………………………………………………………………………..100
iv
CHAPTER 6: QUANTITATIVE RESULTS Introduction……………………………………………………………………………..102 Before and After Legislation…………………………………………………………...103 With and Without Legislation………………………………………………………….108 Bivariate Analysis……………………………………………………………………...109
CHAPTER 7: DISCUSSION AND CONCLUSION Introduction……………………………………………………………………………..121 Success of Claims-Makers……………………………………………………………...125 Do Constructions make a Difference?………………………………………..………...129 Policy Implications……………………………………………………………………..136 Limitations and Future Research ………………………………………………………138
REFERENCES………………………………………………………………………...140
APPENDICES…………………………………………………………………………156
v
LIST OF TABLES
TABLE 1. WPR Approach
TABLE 2. Country Sentence Length
TABLE 3. Country Definitions of Violence
TABLE 4. Directions of Relationships: Macro-level Variables and Female Homicide Rates
TABLE 5. Directions of Relationships: Macro-level Variables and Femicide Legislation
vi
ACRONYMS
ECLAC Economic Division for Latin America and the Caribbean
GBV Gender-based violence
GDP Gross Domestic Product
NAFTA North American Free Trade Agreement
NGO Non-Governmental Organization
OAS Organization of American States
PAHO Pan American Health Organization
UN United Nations
UNODC United Nations Office on Drugs and Crime
VAW Violence Against Women
WB World Bank
WHO World Health Organization
WPR What’s the Problem Represented to be
vii CHAPTER ONE – INTRODUCTION
You can find them thrown onto the pavement like litter; fractured limbs scattered in the cotton fields of Juárez or found in dumps. The number of gender-directed murders has been soaking the depths of Latin America. Even more concerning is Latin American governments’ disregard for legislation put in place to ensure women’s safety (Domfeh 2014).
Violence against women (VAW) occurs in countries all over the world regardless of race, ethnicity, religion, or dominant political system. Millions of women live every day in fear of violence and approximately one in three women have been “beaten, raped, or experienced another form of abuse in her lifetime” (Fried 2003:91; Wilson 2014).
Recognized by the international community as a serious problem, femicide, a type of
VAW, is defined as the gendered killing of women by men because they are women
(Caputi and Russell 1990; Fried 2003; Wilson 2014). This phenomenon was coined in the
1970s and has become an increasing concern since then. Much of the violence that occurs against women is the result of unequal power relations. A continuum of violence illustrates ways in which women experience violence in everyday situations (True 2012).
The continuum ranges from subtle forms, such as sexist language, to overt forms with femicide being the final act of the continuum of violence against women (Caputi and
Russell 1990; Stout 1991). Other forms of VAW are important to understanding femicide because of the documented association between chronic non-lethal intimate partner violence and intimate partner femicide (Campbell et al. 2007; Goetting 1991; Smith et al.
1998; Taylor and Jasinski 2011). Femicide is complex because motives include the socioeconomic, political, and cultural contexts that support unequal power relations and
1 dynamics of control between individual men and women that underlie violence against women (Fregoso and Bejarano 2010:41).
The introduction of violence against women legislation began in Latin America in the 1990s. Within early VAW legislation, there were significant discrepancies between human rights’ recommendations and their translation into national policy (Friedman
2009). A closer look at the national policies uncovered that legislation was not fulfilling its intended objective and, in fact, was reinforcing gender inequality (Friedman 2009).
The current study aims to address how femicide has been defined as a social problem through legislation in Latin American countries and whether femicide legislation has been effective in reducing rates of femicide in the region.
Femicide in a Global Context
Globally, there are more male homicides than female homicides per year, which may cause some to wonder why femicide is considered a problem when more men are killed than women (Sanford 2008). Except in cases of transgender or homosexual murders, however, male homicides are not gender specific and men are killed for reasons other than being men (Prieto-Carrón et al. 2007). Additionally, men are most often killed by other men, while women are rarely killed by other women (Sanford 2008). Women are killed by men as a direct result of their gender and the vulnerability that accompanies the position of being a woman. Furthermore, available literature uncovers that femicides typically involve extreme and unnecessary levels of violence before, during, or after the act of killing, indicating additional cruelty and inhumanity inflicted against the body of a woman (Sagot 2005; Sarmiento et al. 2014).
2 Patterns of femicide
Femicide exists all over the world, however, the rate at which femicide occurs differs from region to region and country to country. Sub-Saharan Africa and Latin
America are regions with the highest femicide rates in the world (Nowak 2012). In contrast, North America, Western Europe, and Australia are among the regions with comparably low femicide rates (Alvazzi del Frate 2011). The most common perpetrator of femicide is another characteristic that differs depending on country and region. The most prominent type of femicide in western countries is intimate partner femicide. In most cases, this type of femicide accounts for more than half of all femicides perpetrated in western countries (Alvazzi del Frate 2011:129–30; Campbell et al. 2003; Stöckl et al.
2013). While intimate partner femicide is also a problem within Latin America, this region is also prone to femicides perpetrated by strangers, gang-members or other non- intimate persons. The reason for this discrepancy will be discussed below.
Overview of Latin America
Latin America is a multicultural, multiracial region, with strong Spanish and
Portuguese influences (De Ferranti et al. 2004). This area is comprised of Mexico,
Central and South America, and the Caribbean. Figure 1 displays all 47 countries in the region (Gwynne and Cristobal 2014:4). Latin America has a distinctive pattern of population and settlement (Gonzalez 2011). Rapid urbanization has characterized the region, particularly in South America.
Countries in Latin America have incurred drastic changes in the last three decades, particularly in political and economic spheres, but currently, most countries are in a time of peace (Moser and Clark 2010). However, crime and violence levels have
3 been on the rise in the region since the 1970s (Green 2013). With more than 140,000 homicides per year, Latin America’s homicide rate is twice the world’s average, making it the second most violent region in the world (Heinemann and Verner 2006). The Pan-
American Health Organization (PAHO) has characterized violence in Latin America as a regional pandemic (Heinemann and Verner 2006). Women in Latin America have been the victims of various forms of violence including torture and rape during civil war, domestic abuse, and femicide (Wilson 2014). Both the destabilization of family relations and a renewal of familial patriarchy during times of war are two of several explanations as to why violence often continues for women after conflict has ended (Cockburn 2004).
Inequality is widespread throughout Latin America with economic, racial, and gender inequality occurring in the region (De Ferranti et al. 2004). Gender inequality has a persistent history in Latin America, greatly affecting the likelihood of poverty and opportunity (De Ferranti et al. 2004). Frequently portrayed as feminine and submissive, women in many Latin American countries are still considered second-class citizens
(Green 2013). The inequality between the genders in this region can be attributed, in part, to the culture of machismo (Wilson 2014). The culture of machismo is the belief that women are expected to submit to the desires of men; their roles in society are in relation to the roles of men, generally as wives and mothers. These values demand the subservience of women and legitimize the use of violence against them if this subservience is challenged (Wilson 2014). Over the last three decades, women’s groups have been making progress on improving the lives of women in areas of education, politics, and fertility (Green 2013). However, in 2000, the World Bank found that all women do not enjoy this progress; women of African or Indigenous descent are making
4 much fewer gains than other women (Green 2013). Inequality of women in Latin
America is also a contributing factor to the impunity of crimes against women and is an important feature of femicide in the region.
Figure 1 Countries of Latin America
Femicide in Latin America
Latin America has unusually high rates of gender-based violence (GBV) and femicide (Prieto-Carrón et al. 2007). El Salvador had the highest femicide rate in the world in 2011 with 17.8 per 100,000 of the population (UN Women 2013). Following El
Salvador were Guatemala and Jamaica with the second and third highest femicide rates
5 respectively. The magnitude of femicide in Latin America in comparison to western countries is also of increasing concern. In countries such as Honduras, El Salvador,
Guatemala, and Colombia, femicide occurs at least five times more often than in Canada or the United States (Alvazzi del Frate 2011). Femicide in other Latin American countries has also reached pandemic proportions with Caribbean countries being no exception. The
Bahamas and the Dominican Republic are among the top 25 countries that have the highest femicide rates in the world, while no western countries make this list (Nowak
2012).
Justice for femicide in Latin America is largely unheard of with many of the crimes against women never moving past initial investigations (Prieto-Carrón et al. 2007;
Wilson 2014).
Governments in the region are allowing men to get away with murder. Murders continue because national governments and public order systems ignore them. Impunity facilitates further murders and, in a cultural climate where violence is commonplace, men kill women because they can (Prieto-Carrón et al. 2007:31).
The pervasive impunity that occurs in Latin America is, perhaps, the largest discrepancy that exists between this region and western countries. Impunity, like femicide, is a global problem, however, in most western nations, men who kill women face punishment for this crime. A notable exception to this, however, is the issue of murdered and missing
Aboriginal women in Canada, many of whose perpetrators are never brought to justice.
As a result, Aboriginal women in Canada are seven times more likely to be victims of homicide than non-Aboriginal women (Fry 2011).
6 Femicide legislation
Reducing femicide in Latin America has become the objective for international and local organizations. Latin American governments have an international commitment to respond to violence against women, including femicide. Two international mechanisms have been particularly important in the development of femicide legislation, the
Declaration on the Elimination of Violence against Women, adopted by the UN General
Assembly in 1993 and The Belém do Pará Convention (The Inter-American Convention on the Prevention, Punishment, and Eradication of Violence against Women), adopted in
1994 and signed by 27 countries across Latin America (Insulza 2012). The above define violence against women as a severe human rights issue and call for the development of national level instruments to protect and defend women’s rights. Although many countries supported these mechanisms, there was and still is concern that countries are unwilling to apply the recommendations (Wilson 2014).
Beginning in 2007, countries throughout Latin America began to introduce legislation to prevent and punish femicide and more than 15 legislations have now been enacted throughout the region (Sarmiento et al. 2014). The depth and strength of femicide legislations differ substantially from country to country. The development of femicide laws is a notable advancement, but these laws will only be effective if they are properly implemented and enforced. In the time that femicide legislation has been in place, many criticisms have been made that countries have failed to enforce the legislation or protect women from violence (Sarmiento et al. 2014). The Organization of American States
(OAS) has created an evaluation system to assess the progress of Member States. A
Committee of Experts for Follow-up Mechanism of the Belém do Pará Convention has
7 evaluated country progress on eliminating VAW in Latin America (Insulza 2012). In their Second Hemispheric Report, the committee reported that femicide is still not being considered a serious issue by most states (Insulza 2012). However, countries that have successfully implemented VAW legislation elsewhere, such as the United States, have found some support that legislation has been effective in protecting women from violence
(Stout 1992; Dugan 2002; Dugan et al. 2003).
There are a number of factors that increase the likelihood of high national femicide rates. For example, regions with the highest femicide levels correspond to regions with the highest general overall rates of lethal violence (Alvazzi del Frate 2011:119; Nowak 2012). However, few researchers have assessed femicide at the regional level, taking into account structural factors, such as cultural, economic, and political issues, which may also have an impact on this problem (Palma-Solis et al. 2008).
Femicide is a difficult topic to study for a number of reasons including: (1) the sensitivity of the subject; (2) availability of data; and (3) problems with reporting (Dugan
2002; Fontes 2004). As a result of these limitations, most prior research on femicide has centered on advanced democracies or a small number of countries (Dugan et al. 2003;
Htun and Weldon 2012; Fernandez 2012; MeneghelI and Hirakata 2011). Despite the widespread international support for violence against women legislation, there is an even smaller body of research that evaluates their effectiveness (Dugan 2002). Few combine cross-regional analysis with an examination of change over time, and even fewer use statistical analysis to do so (Htun and Weldon 2012:549). Some research has assessed individual countries’ attempts to combat femicide, however, to date, no comprehensive assessment of femicide legislation in Latin America and its impact on the rate of femicide
8 has been conducted (Fernandez 2012; Franceschet 2010). Calls have been made for further research on femicide (Carcedo and Sagot 2010; MeneghelI and Hirakata 2011).
As a result, this research aims to contribute to this body of literature by assessing femicide legislation and its effectiveness in Latin America. The following two research questions will be addressed:
Research Question #1: Has the way that femicide is defined as a social problem in Latin
American countries determined the legislative responses to this violence?
Research Question #2: Have the responses to femicide reduced female homicide rates in
Latin America?
The current study
This research takes part in two stages, using a sequential mixed-methods approach, which is a combination of quantitative and qualitative approaches that occur in a logical predetermined order (Palys and Atchison 2014). In the first stage, a qualitative analysis was used to extract information to respond to the first research question. As governments’ framing of the problem of femicide may impact the effectiveness of the legislation, the qualitative analysis precedes the quantitative portion to examine how femicide has been defined through legislation within Latin America before analyzing whether this legislation is effective in reducing female homicide rates. Using a quantitative analysis in response to the second research question, stage two of this research is designed to test the effect of femicide legislation on the rate of female homicide in Latin America. This stage also includes other country-level factors which may have an impact on femicide or the development of femicide legislation. The sample in the second stage of this analysis was comprised of 24 Latin American countries.
9 Chapter Overview
Chapter two provides a comprehensive literature review of previous femicide research. First, femicide and related terms are explained. Next, this chapter outlines femicide as it occurs in Latin America. Predictors of femicide are then discussed, including legislation. Finally, the gaps within existing research are illuminated.
Chapter three outlines the theoretical framework used to guide this research. The constructionist approach and contextual constructionism, a branch of the constructionist approach, will be reviewed. The contextual constructionist approach is then applied to the phenomenon of femicide. This chapter explains how femicide has been constructed as a social problem in Latin America by examining the various claims that have been made and the key claims-makers.
Chapter four provides an overview of the methodology of this mixed-method research. First, this chapter reports the data used for the qualitative analysis and explains the “What’s the Problem Approach,” the method of the qualitative analysis. Next, the methods employed in the quantitative analysis are outlined including descriptions of the sample, primary dependent and independent variables and additional macro-level variables. Chapter four also explains the limitations of this research design.
Chapter five highlights the qualitative results, while chapter six reports the quantitative findings of this research. Chapter seven discusses the general conclusions, locating study findings in the prior literature and theoretical framework introduced in chapters two and three. Policy implications that have developed from the findings of this research are also discussed. Finally, all limitations of this research are reviewed, noting directions for future studies.
10 CHAPTER TWO - LITERATURE REVIEW
This research examines how femicide has been constructed as a social problem and whether the responses to femicide have decreased femicide rates in Latin America.
Numerous studies exist on violence against women, its causes and consequences
(Ackerson and Subramanian 2008; Chon 2013; Vives-Cases et al. 2010). However, fewer studies have examined country-level factors related to femicide (Dugan 2002; Stout
1992). Additionally, research on this phenomenon in Latin America is particularly scarce
(Palma-Solis et al. 2008). Drawing on a variety of offenses including violence against women, domestic violence, homicide, and femicide, this chapter presents a review of previous research that has addressed where violence takes place and what underlying factors can perpetuate its existence. This literature will outline why femicide is considered a social problem, particularly in Latin America. Additionally, the literature will suggest what responses, or other variables, may influence rates of femicide in the region. In terms of this research, the information provided in this chapter will inform how femicide and its definitions may differ within Latin American legislation, what is the expected effect of femicide legislation in Latin America, and what other forces may be important in reducing femicide.
The first section will define femicide and related terms, which will be important as constructions of femicide outlined in legislations may differ from previous research.
The next section will examine femicide in the global context and within the region of
Latin America. This section is important to understand why femicide in Latin America is a problem distinct from other regions. Next, macro-level predictors of femicide, homicide, and violence against women in Latin America and more generally will be
11 discussed in order to suggest which forces may increase the likelihood of femicide. The final section will introduce gaps that currently exist within femicide research, which will illustrate what research has been previously conducted, and how the present study will contribute to this body of research.
Defining Femicide
Gender-based violence (GBV) refers to the violence women experience as a result of gender norms (True 2012). Gender norms dictate the types of appropriate or desirable behaviour for each gender as determined by society, often portraying women as inferior and submissive to men (Piper 2014). GBV is used interchangeably with violence against women (VAW); however, GBV does not describe the experiences of women uniquely because, although disproportionately less, men can also be subject to violence for stepping outside societal gender norms (True 2012). Thus, while both terms are used, the focus of this research remains on the experiences of women.
The term femicide, a type of GBV, was first used by Diana Russell in 1976, when she testified at the International Tribunal of Crimes Against Women, to bring attention to the violence and discrimination being experienced by women worldwide (Godoy-Paiz
2012). Femicide is defined as the intentional murder of women because they are women
(Godoy-Paiz 2012; WHO 2012). Russell (2001:3) further specifies femicide “as the intentional murder of females by males” which emphasizes that femicide is the product of a patriarchal society. A patriarchal society is one that engages in the systematic oppression of women by men both mentally and physically (Boesten 2012). Russell
(2001) argues that femicide is a method used by men to maintain control by making all
12 women feel unsafe.
Femicide can be categorized in a variety of ways. Understanding the distinctions across the different forms of femicide is useful as it identifies the various ways women may experience this type of violence. Additionally, the distinctions across the forms of femicide can facilitate the creation of policies that address the specific factors behind the killing of women. According to Russell (2001), there are four types of femicide, each explaining the relationship of the victim to the perpetrator including: partner femicides, familial femicides, other known perpetrators of femicides, and stranger femicides
(Russell 2001:21). Perpetrators are most often current or former partners, known as intimate femicide or intimate partner femicide (Fernandez 2012; Fried 2003). While the categories proposed by Russell (2001) are commonly referred to, other categories of femicide exist (Fernandez 2012; Sarmiento et al. 2014; WHO 2012). Categories that differ from those outlined by Russell (2001) include femicide in the name of “honour,” dowry-related femicide, and “linked femicide,” whereby a person is killed for attempting to save the aggressor’s primary target (Fernandez 2012; WHO 2012). Other types of femicide will be outlined below.
Since the term femicide has arisen, other related terms have evolved to further define gender-targeted deaths. Instead of merely translating the term femicide, Latin
American feminists have taken this term and adapted it to describe femicide within the local context. Feminicidio is used predominantly in Latin America to describe the experience of killing women that is unique to that region. Similar to femicide, feminicide is used to describe the killing of women because of their gender, but it adds to the traditional definition of femicide a political aspect (Sanford 2008; Fregoso and Bejarano
13 2010). Even if a complete stranger perpetrates the killing of a woman, it occurs within intricate systems of power characterized by certain attitudes and practises toward women, their bodies and their rights, making this concept undeniably political (Godoy-Paiz 2012).
Feminicide functions as a “tool of patriarchal oppression, but also serves as a tool of racism, economic oppression, and colonialism” (Smith 2006:417). Many argue that, in
Latin America, the lack of a state response which results in the inability of women to live free from violence, is in itself a human rights violation (Fried 2003; Fregoso and
Bejarano 2010). Feminicide suggests a dual culpability: “the perpetrator of the crime is the obvious responsible party, but the state also shares responsibility for failing to protect or counter the violence” (Sanford 2008:105).
The Special Rapporteur on Violence Against Women, its causes and consequences, an individual working on behalf of the UN who is responsible for investigating human rights problems, categorizes femicide in two ways: direct femicide and passive femicide. These categories are comprehensive, distinguishing femicides by methods, detailing specific ways women and girls may be killed. As its name suggests, direct femicide includes femicides that have been deliberately committed including:
Killings of women and girls as a result of domestic violence, inflicted by an intimate or domestic partner; misogynist killings of women; killings of women and girls in the name of “honour”; armed conflict-related killings of women and girls (as a strategy of war, oppression, or ethnic conflict); dowry-related killings of women and girls; gender identity and sexual orientation-related killings of women; female infanticide and gender-biased sex selection (feticide); and ethnic and indigenous identity-related killings (Sarmiento et al. 2014:14/15).
14 Passive femicides encompass the death of women from neglect, illegal, or unsafe activity including:
Deaths due to unsafe abortions; maternal mortality; deaths from harmful practices (for example, those resulting from female genital mutilation); deaths connected to human trafficking, drug dealing, small-arms proliferation, organized crime, and gang-related activities; the death of girls or women from neglect, starvation, or ill-treatment; and deliberate acts or omissions by public servants or agents of the state (Sarmiento et al. 2014:15).
Regardless of the categories used, femicides share common characteristics.
Namely, this type of violence is rooted in the conceptualization of women as inferior and an acceptance of male-domination. Using the term femicide as opposed to homicide exposes the inordinate amount of violence that results from marginalization, oppression, and danger that women experience. Understanding how femicide or feminicide has been defined and adopted in Latin America is important to the understanding of this social problem.
The use of the term femicide over feminicide depends on the author and country
(Fernandez 2012). For example, within Mexico, Nicaragua, and the Dominican Republic the term most commonly used is feminicide. However, in Honduras, Guatemala, Chile, and Argentina the term predominantly used is femicide (Fernandez 2012). The first documented use of feminicidio was in the Dominican Republic by feminist activists
(Fregoso and Bejarano 2010:5). The creation of the term feminicide was an attempt to
“reverse the hierarchies of knowledge” that traditionally flows from North to South
(Fregoso and Bejarano 2010:5). The term feminicide is important to our understanding of this issue in Latin America. However, as more countries in Latin America use femicide over feminicide, this study will use the more general term femicide to discuss all further femicides/feminicides.
15 Global Existence of Femicide
Femicide remains a devastating issue in many countries and an increasingly severe problem globally (Wilson 2014). The global extent of femicide for the years of
2004-2009 was estimated at approximately 66,000 victims per year, which represents about 17 percent or almost one-fifth of all killings for an average year (Geneva
Declaration Secretariat 2011:7). In 2011, the United Nations Office on Drugs and Crime
(UNODC), in their Global Study on Homicide, recognized that intimate partner and family-related violence is a significant share of the global female homicide rate (UNODC
2011:11). Furthermore, while the overall global homicide rate can fluctuate significantly from year to year, the share of partner and familial femicides remains relatively stable
(UNODC 2011:49). In western countries, the most common type of femicide is intimate partner femicide (Campbell et al. 2003; Stout 1992). In the United States, approximately
40-50 percent of female homicides are perpetrated by an intimate partner (Campbell et al.
2003). In a study conducted by Campbell et al. (2003), they found that in 70 percent of the 307 femicide cases reviewed, the woman had experienced domestic violence by the same partner who killed them. Similarly, in 2009 in the United Kingdom, 54 percent of female homicides were committed by an intimate partner (Stöckl et al. 2013). In France and Portugal, countries with low femicide rates, intimate partners perpetrate more than eighty percent of all femicides (Alvazzi del Frate 2011:129–30). Victims of intimate partner homicide are predominately women. In Canada, in 2009, females represented
71% of victims of homicide committed by a current spouse (Hotton Mahony 2011).
While femicide is a global problem, the rates at which these killings occur are typically much lower in western countries than in Latin America (UNODC 2013).
16 Existence of Femicide in Latin America
Femicide is not unique to Latin America, however, femicide rates are particularly high in this region. Latin America has the second highest female homicide rate in the world, second only to Africa (UNODC 2013). Furthermore, more than half of the 25 countries with high and very high femicide rates as defined by the UNODC (at least three femicides per 100,000 female population) are in Latin America; four in the Caribbean, four in Central America, and six in South America (Nowak 2012:1). For the purpose of this research, it is important to understand the types of femicides that take place in Latin
America and how this differs from other regions in the world as this may effect how legislation attempts to resolve this issue.
Figure 2 presents a visual representation of femicide in four Latin American countries over a three-year period. These countries were chosen because of their regional proximity to one another demonstrating that femicide is not only a regional problem, but occurs within the unique context of each country. Mexico, El Salvador, and Belize all border Guatemala, yet, as Figure 2 demonstrates, femicide rates vary significantly from country to country. In the three years shown above, femicide rates are highest in El
Salvador, significantly higher than the other three countries. The reason for these differences may be the result of country predictors of violence, described in more detail below.
To recap, for the purpose of this research Latin America includes Mexico along with countries from Central and South America, and the Caribbean (See Appendix A for a list of countries). Femicide in Latin America is a problem between both intimate partners and non-intimate partners or strangers. In 2013, a study by the UNODC
17 determined that, within Latin America, more than 38 percent of all reported homicides of women were committed by an intimate partner in comparison to five percent of all homicides of men (UNODC 2013). Similar to western countries, studies conducted in
Brazil, the Dominican Republic, Costa Rica, and Mexico reveal that between 60-78 percent of all femicides are intimate femicides or femicides committed by someone known to the victim (Lagarde y de los Rios 2006; Sagot 2005). In Argentina in 2010, more than 80% of femicides were perpetrated by male intimate partners (Fernandez
2012:43). In contrast to many western countries, however, a significant proportion of femicides in some Latin American countries are committed by strangers or other non- intimate persons (Sanford 2008; Alvazzi del Frate 2011). For example in El Salvador and
Colombia, countries known for high rates of femicide, only three percent of all femicides occurred at the hands of a current or former intimate partner (Alvazzi del Frate 2011).
In Ciudad Juarez, a city close to the US-Mexican border, over four hundred women have been killed and another thousand have disappeared in a ten-year period
(Fregoso 2006). In 2014, Amnesty International reported that VAW in Mexico, such as rape, kidnapping, and killing remains “an epidemic throughout the country” (Amnesty
International 2015:250). In contrast to homicides of men, femicides are often accompanied by sexual violence and mutilation (Godoy-Paiz 2012). In Mexico,
Guatemala, Argentina, and El Salvador, women’s bodies are found in public places, violated and dismembered (Fregoso 2006). The rate and type of femicide committed differs significantly in Latin America from country to country, yet the cause of these discrepancies has not been fully explained (see theoretical framework for further discussion on theories relating to differing rates of femicide).
18 Figure 2 Female Homicide Rates: Four Latin America Countries
Rate of Female Homicides Latin American Countries (per 100, 000 pop.)
2010 2011 2012
17.8 17.1
12.5
10.1 8.3 8.4 7.2 5.7 5.6 3.7 4.1 4
Mexico Guatemala El Salvador Belize
Predictors of Femicide
Previous research has been conducted on determinants of homicide, VAW, and femicide in the US, Latin America, and globally (Gauthier and Bankston 1997; Briceño-
Leon et al. 2008; Gartner et al. 1990; Palma-Solis et al. 2008). Until recently, studies on female homicide victimization were largely micro and descriptive (Bailey and Peterson
1995). The literature suggests that there is no single explanation for these acts of violence
(Stout 1992a). This research focuses on factors that exist at the macro or ecological level, including the overarching institutional patterns of the culture such as economic, social, educational, legal, and political systems (Stout 1992). “A broad, inclusive examination of factors which may be associated with intimate femicide is important to establish the context of violence against women” (Stout 1992a:32). Additionally, macro predictors of
19 femicide help conceptualize this violence as a societal issue rather than random individual acts. As such, these macro-level factors are discussed in more detail immediately below.
Previous research has shown that victim demographics can differ from country to country (Prieto-Carrón et al. 2007). However, there are certain groups that are at higher risk of becoming victims of femicide. Adolescents and young adults, particularly those who live in poor communities or are of lower economic status, are at the highest risk for becoming victims of femicide (Amnesty International 2005; Prieto-Carrón et al. 2007). In
Latin America, economic insecurity, organized crime, drug and human trafficking, and high homicide rates of men, all increase the likelihood of being a victim of femicide
(Prieto-Carrón et al. 2007). In several Latin America countries, victims of femicide are primarily poor women, living in unsafe cities ruled by drug traffickers and gang members where safety is almost nonexistent (Campbell 2007). As a result, predictors of femicide include, but are not limited to, state responses, armed conflict, economic stability, employment, education, gender equality, and political representation. Many of these predictors such as economic stability, employment, education, gender equality and political representation are not specific to Latin America, but have been shown to influence homicide rates globally (UNODC 2013). These country-level variables may also impact the enactment and implementation of femicide legislation. State responses, including legislation, and armed conflict, though not unique to Latin America have more of an impact in this region than other areas of the world. This subsection will begin with the factors that are specific to Latin America before moving to general predictors also relevant in the Latin American context.
20 State responses
An important predictor that sets Latin America apart from many western countries is the unwillingness of the state to respond. The inaction of the state to investigate and prosecute homicide, and particularly femicide, has been cited as a condition that fosters this violence (Briceño-Leon et al. 2008). Impunity is a problem for all crimes in Latin
America, but responses are particularly ineffective when the victims of these crimes are women (Hernandez 2003). To date, countries that have been criticized for impunity include Mexico, Guatemala, Argentina, El Salvador, Brazil and Nicaragua (Amnesty
International 2015; Carey and Torres 2010; Fernandez 2012; Prieto-Carrón et al. 2007).
As described by Carey and Torres (2010), in order to understand how femicide takes place we must look at the social structure that allowed this problem to become normalized. Femicide in Guatemala, for example, has been linked to the failure of the state to prevent all forms of violence against women (Carey and Torres 2010; Godoy-
Paiz 2012). Perpetrators in Guatemala frequently go unidentified and unpunished
(Godoy-Paiz 2012). Even if the victim’s family knows who the perpetrator is, they may not come forward due to fear of retaliation. The state’s lack of response to femicide perpetuates further violence. The fear faced by victims’ families and the lack of justice suggests that the number of reported femicides by the state is underestimated (Velasco
2008).
Mexico has also been described as having a “culture of impunity” (Fregoso 2006;
Prieto-Carrón et al. 2007). The police, who are at least partially responsible for protecting women, frequently look the other way or do not pursue cases with vigour
(Swanger 2007). Amnesty International (2015:250) reported, “many authorities
21 continued to fail to implement legal and administrative measures to improve prevention, protection from, and investigation of gender-based violence”. In Argentina, Fernandez
(2012) reports that many femicides are officially reported as suicides. Authorities tend to be uncooperative with organizations that work toward justice for victims of femicide. The attitudes and general inaction of authorities leads to the belief that femicide can go unpunished.
As previously discussed, femicide often occurs after recurring and chronic domestic violence. Insensitive, discriminatory, or insufficient responses by police also play a big role in normalizing domestic violence, or portraying it as trivial or not a real threat to women (Prieto-Carrón et al. 2007). A legal service provider from Nicaragua reported:
All in all, it’s a very painful experience. Many times women go to the police in tears, and the police tell them not to be irresponsible and waste their time with that kind of complaint . . . They tell them, ‘tonight your man is going to be between your legs again’ (Sagot 2005:1307; Prieto-Carrón et al. 2007).
The state and police enforcement can play a very crucial preventative role in reducing femicide through successfully responding to domestic violence. Impunity not only denies victims and their families justice, but a failure or inability to prosecute as a result of police investigations normalizes violence, making communities believe that there is no penalty for killing women.
Violence Against Women Legislation
Legislation is often the first step in combating femicide. However, there is a dearth of quality research upon which to base new legislation. Dugan et al. (2003) attribute the lack of research to “scarcity of data for assessing resource effectiveness
22 across a broad range of services, multiple sites, and differing victim characteristics” (p.
172). The research that exists on the effectiveness of VAW legislation has been conducted primarily in the United States (Stout 1992; Dugan 2002; Dugan et al. 2003).
Domestic violence legislation
Some research has examined the impact of domestic violence legislation on the rates of domestic violence and intimate partner femicide (Stout 1992; Dugan 2002;
Dugan 2003). This legislation is relevant to femicide rates as domestic violence legislation can serve as a preventative measure. Femicide that occurs by current or former partners often involves repeated domestic abuse before the final act of femicide (Stout
1992). Domestic violence legislation is multidimensional and can include increased penalties for domestic violence, restraining orders to protect women from their abusers, and commitments to provide services for victims of abuse (Oritz-Barreda et al. 2013).
The results of research on domestic violence legislation demonstrate that legislation can reduce femicide rates across the US. Both Stout (1992) and Dugan (2002) who analyzed the effectiveness of legislative variables on reducing femicide found that legislation that limits the contact of an abusive partner were most successful in lowering the rates of femicide. However, Dugan et al. (2003) found changes in legislation were able to reduce violence only between unmarried intimate partners. They discovered that the implementation of policies that encourage a more assertive police response resulted in fewer deaths of unmarried intimate partners. However, these policies were not effective in reducing homicides between married partners.
23 The creation of legislation, however, is not enough. While the development of legislation is important to protect women against violence, laws are only useful if they are effective at influencing the practices on the ground (Prieto-Carrón et al. 2007). Vives-
Cases et al. (2010), in their analysis of 80 countries worldwide, noted that 29 countries in the Americas have VAW legislation. However, the analysis of the 80 countries revealed that many countries were not following international recommendations (Vives-Cases et al. 2010). The authors found considerable limitations in the content of legislation with many of the violence against women legislations never specifically referencing women as the victim or complainant. Additionally, Vives-Cases et al. (2010:61) noted that many of the legislations were also limited in their application, and “the extent to which it provided women with integrated protection, support, and care.”
Franceschet (2010), in a comparative analysis of domestic violence legislation introduced by Chile and Argentina, determined that Chile had introduced more successful domestic violence legislation. This was partially explained by national institutional factors. Specifically, Franceschet (2010) argued that Chile has a stronger, more centralized government, which led to more effective policy implementation. In contrast,
Argentina is cited as having a weaker administrative capacity, which led to an ineffective policy outcome.
Femicide legislation
Fewer studies have examined the effects of femicide legislation. Palma-Solis et al.
(2008) found that government expenditure, including the total amount spent on individual and collective goods and services, was an important factor in reducing the risk of
24 femicide (Palma-Solis et al. 2008). While government expenditure and legislation
implementation are not synonymous, they are interrelated. Government expenditure
refers to the amount governments spend on social needs and services, including safety.
Palma-Solis et al. (2008) deduced that low government expenditure could result in a
greater risk of femicide because it is connected with a shortage of laws and policies
requiring interventions and government investment.
For example, Guatemala has taken several steps to reduce violence against
women, including femicide. These measures include the signing of international human
rights treaties, enacting new laws, and creating VAW agencies (Velasco 2008). However,
these measures have been described as ineffectively implemented, lacking sufficient
monitoring and review, thus, seldom protecting women from violence (Amnesty
International 2006). An obvious example of this can be in 2011 when more than 20 000
cases were filed under the law implemented in 2008 Ley contra el femicidio y otras
formas de violencia contra la mujer (Law against Femicide and Other Forms of Violence
against Women). The 20, 000 cases mentioned included femicide, as well as physical,
sexual, and emotional abuse against women (Musalo and Bookey 2014:106). In spite of
the substantial number of cases filed, less than three percent of these cases resulted in a
judgment (Musalo and Bookey 2014:106).
Armed conflict Research has shown that armed conflict is an important variable when measuring
femicide (Murray 2002), particularly in Latin America where there has been a history of
brutal dictators and civil wars through the end of the twentieth century (Sanford 2008;
Wilson 2014). “In contrast to virtually every other region, South and Central America
25 feature the fastest and most dramatic temporal escalation of armed violence since 1999”
(Jütersonke et al. 2009:375). Crime and violence rates are especially high in post-conflict countries (Heinemann and Verner 2006; Amnesty International 2004). In times of conflict, violence against women increases dramatically (True 2012). The effects of war can be divided into two categories: direct and indirect consequences. Direct consequences are primarily deaths or injuries related to battle while indirect consequences are all deaths or injuries caused by war that do not occur in battle, such as civilian causalities or deaths occurring as a result of disease and malnutrition (Spagat 2009). Indirect consequences disproportionally affect women and may last several years after the war has ended
(Murray et al. 2002; True 2012). Countries that have incurred problems of armed conflict since the 1980s include Guatemala, Colombia, El Salvador, Peru and Nicaragua (Centeno
2002).
Guatemala, for example, has seen a dramatic increase in homicides in a time of presumed peace, now having one of the highest homicide rates in the world (Carey and
Torres 2010; Godoy-Paiz 2012; Sanford 2008). The genocidal conflict during the war has been compared to the current issue of femicide (Carey and Torres 2010). Though women were not the only targets of authoritarian aggression, this violence filtered down to community and family relationships (Carey and Torres 2010). High levels of violence during the civil war are thought to have normalized violence in the country (Sanford
2008). As a result, high levels of femicide and inaction by the state to counter this violence are perceived as a cultural norm.
In Colombia, women have endured civil conflict for more than 40 years and have been raped, tortured, and killed with the paramilitaries noted as having committed most
26 of these heinous acts (Amnesty International 2004:18; Wilson 2014). In some Latin
American countries, the state struggles to maintain order and political control. For this reason, police forces legally or illegally depend upon external personnel to carry out assignments (Howard et al. 2007). Illegal help includes localized militias, vigilante, and paramilitary groups. These groups are sometimes linked to the protection of elite interests
(Howard et al. 2007:720).
An important contributor to armed conflict in Latin America is gang involvement.
According to the UNODC (2013:77), a significant share of homicides that occur in post- conflict countries is related to other criminal activities that prosper when law enforcement institutions are weak. Gang activity in Central America has direct ties to the United States
(Suarez and Jordan 2007). When the gang problem in the United States became too dangerous, the US conducted a mass deportation of all Central American gang members
(Suarez and Jordan 2007). While gang activity is not unique to Latin America, gangs in
Central American countries are described as having infiltrated many aspects of society, making this issue more severe than in other countries (Suarez and Jordan 2007).
Three Latin American countries, El Salvador, Honduras, and Guatemala have very serious gang problems (Rodgers 1999). “One of the most visible expressions of
Central American violence is undoubtedly the gang” (Jütersonke et al. 2009:376). The prevalence of gangs varies widely across the region. For example, the three countries listed above encounter significantly higher levels of gang activity than Costa Rica or
Nicaragua (Jütersonke et al. 2009). It is difficult to measure the exact effect gangs have on the number of crimes committed, including femicide. According to UNODC (2007:
64), the magnitude of all violence perpetrated by gangs in the region ranges from 10% to
27 60%. Criminal activities include homicide, rape, theft, kidnapping, extortion and drug trafficking (Jütersonke et al. 2009). However, there are speculations over how many instances of femicide can be attributed to gang activity. For example, Suarez and Jordan
(2007) argue that in Guatemala, gangs are cited as the main cause of femicide as activities involved in gang initiation often include the killing of an innocent person. Many femicides in Guatemala have been connected to these initiation activities (Suarez and
Jordan 2007). In contrast, however, other authors argue that gangs are being blamed for more than their share of femicides because governments find it easier to blame gangs than to address the structural causes of femicide (Prieto-Carrón et al. 2007; Godoy-Paiz
2012).
Economic indicators
For some time, criminologists have identified that socioeconomic inequality could be a relevant factor to higher rates of violent crime (Whaley and Messner 2002:188).
Economic indicators are not specific to Latin America, but are predictive of homicide more generally as more developed nations tend to have lower rates of homicide (Butchart and Engstrom 2002; Chon 2013). Two concepts that are important to understanding a nation’s economic development are GDP (Gross Domestic Product) per capita, used to measure economic development, and Gini coefficient used to measure income inequality
(Pridemore and Trent 2010; Ouimet 2012).
GDP per capita measures “the overall level of economic development or modernization in a country” (Chon 2013:606). Countries with a higher GDP per capita consistently have lower rates of homicide (Butchart and Engstrom 2002; Lin 2007). Blau and Blau (1982) argue that economic disparities increase interpersonal conflict, some of
28 which result in death. It follows that increasing economic wealth should result in fewer homicides. GDP per capita, however, is an interesting economic predictor for VAW. A cross-national study by Austin and Kim (2000) found no relationship between GDP and the rate of rape. Chon (2013), however, found that a higher GDP per capita is related to an increased amount of sexual violence, which is defined as rape and sexual assault. This contradicts the assumption that when nations become more developed, there is a decrease in violence (Chon 2013). More research is needed to explore the associations, if any, between GDP per capita and violence toward women (Palma-Solis et al. 2008). This is relevant to the backlash hypothesis, which will be addressed in greater detail below.
The Gini coefficient, an economic inequality indicator, describes the “numerical expression from 0 to 1 or from 0 to 100 that expresses the differences in the distribution of family incomes in a country” (Palma-Solis et al. 2008:324). In short, then, this variable measures the income gap between the rich and the poor. An analysis by Bailey and
Peterson (1995) found that the Gini index was a significant predictor of the rate of rape, but that poverty was not. These results support the Blau and Blau (1982) hypothesis that relative economic disadvantage is a significant determinant of violence. Relative economic disadvantage is economic inequality in comparison to those in the region, rather than absolute economic disadvantage, which is calculated based on a measure of poverty. Briceño-Leon et al. (2008), in their analysis of homicide rates in Latin America, found a statistically significant relationship between Gini coefficients and homicide rates.
Countries with very high Gini coefficients were associated with high homicide rates in
Latin America while countries with very low Gini coefficients have lower homicide rates
(Briceño-Leon et al. 2008). Additionally, Palma-Solis et al. (2008) found a statistically
29 significant relationship between femicide rates and the Gini coefficient, with a larger income gap corresponding to higher rates of femicide. Explanations for this correlation include frustration in younger generations who have high expectations but few opportunities, particularly when immense wealth and immense poverty exist in the same environment (Briceño-Leon et al. 2008).
Gender inequality Another significant predictor of femicide is gender inequality. “Scholars have suggested that the many forms of violence against women are related to a woman's status in a society” (Stout 1992a: 32; Russell 1984). Gender inequality is not specific to Latin
America, but the existence of inequality is well documented there (Carey and Torres
2010). The state of gender inequality within a country is measured by a variety of factors including: the percentage of women in primary and secondary education, the number of women in the workforce, socioeconomic status, the number of female headed households, the percentage of women in executive and managerial positions, and the number of seats women hold in parliament (Gartner et al. 1990; Gauthier and Bankston 1997; Chon 2013;
Whaley and Messner 2003). However, the relationship between measures of inequality and femicide is not always clear (Chon 2013; Palma-Solis et al. 2008).
Traditionally, advocates believed that more gender inequality in a society would result in high rates of violence, because within an unequal system, men dominate powerful positions and the status of women is of less value (Whaley and Messner 2003).
Feminists believed that increases in social and economic power for women would reduce the oppression of women, known as the ameliorative hypothesis (Chon 2013; Whaley and
Messner 2003). However, perpetrators may feel threatened by women in non-traditional roles and believe that “women are inappropriately competing with them for economic
30 status and resources” (Gartner and McCarthy 1991: 295). This is known as “patriarchal backlash” hypothesis as described by Russell (1975) in which femicide rates increase with higher levels of education and employment of women as a response by males to maintain control (Dutton 1994).
In support of the backlash hypothesis, Stout (1992), when analyzing the impact of gender inequality on intimate femicide across states, found that the percentage of women employed in managerial and administrative positions relative to the percentage of men in the same positions was positively correlated to intimate femicide in the United States.
DeWees and Parker (2003) found that gender disparity in higher education has a negative, statistically significant effect on female homicide victimization.
In support of the ameliorative hypothesis, Bailey and Peterson (1995) found that rates of intimate femicide are higher in cities where the college education gaps between men and women were greater and where female unemployment rates were greater for women than men. In an analysis of 61 countries including nine Latin American countries,
Palma-Solis et al. (2008), examined the effect of social, political, economic factors on femicide. Out of the ten independent variables tested, they discovered that lower female representation in politics appeared to be the greatest risk factor for femicide (Palma-Solis et al. 2008:327). Htun and Weldon (2012), in their comprehensive analysis VAW policy, found that a strong women’s movement and a strong participation of women in the legislature were statistically significant in the introduction of VAW policies.
The results of gender inequality research are challenging to compare due to differences in the sample population, varying measures of inequality, levels of accuracy in the recording of homicide rates and differing methods of analysis (Vieraitis et al.
31 2007). However, Vieraitis et al. (2007:61) argue that the evidence appears to be slightly in favour of the backlash hypothesis especially for variables measuring employment
(Brewer and Smith 1995; Gauthier and Bankston 1997; Vieraitis and Williams 2002;
Taylor and Jasinski 2011) and occupational status (DeWees and Parker 2003; Stout 1992;
Vieraitis and Williams 2002; Vieraitis et al. 2008; Whaley and Messner 2002).
Proponents of this theory suggest that after an undetermined amount of time, female homicide rates should decrease as men get comfortable with equality and realize the benefits that equality offers men (Whaley and Messner 2002). No matter the direction of this relationship, gender inequality is the root cause of violence against women, and thus is an important variable when examining levels of femicide (United Nations 2006).
Gaps in Research
Research is needed to analyze the effectiveness of pre-existing legislation designed to prevent femicide (Grana 2001). To date, no comprehensive assessment of femicide legislation and its impact on female homicide rates has been conducted in Latin
America or elsewhere. This could be partially due to the fact that homicide rates and other country level data are often inconsistently measured and difficult to obtain (Stöckl et al. 2013).
Macro-level country factors are important in analyzing how and why femicide exists. These factors are also important to understanding the development of femicide legislation. Social, economic, and political factors are among the characteristics that should be assessed when measuring the rate of femicide and the enactment of legislation.
Yet, few of these variables have been analyzed in the context of Latin America. This
32 literature reveals that with the exception of Palma-Solis el al. (2008), predictors of femicide and factors that influence femicide legislation developments have not been examined on a regional level in Latin America.
CONCLUSION
Femicide definitions are evolving and being shaped to describe a phenomenon that is specific to regional and cultural contexts. Responses to femicide have been implemented at national and international levels. Research on related legislation, though scarce, suggests that legislation has the ability to reduce femicide rates. However, the success of the implementation of femicide legislation in Latin America can be questioned as states have been criticized for their failure to respond to killings, particularly, the killings of women. In an effort to fill the gap of macro-level studies that examine femicide legislation and its impact on female homicide rates, this research examines the relationship between female homicide rates and a variety of country factors, including the introduction of femicide legislation. The following chapter discusses the relevant theoretical framework for examining femicide in Latin America.
33 CHAPTER 3 - THEORETICAL FRAMEWORK
The overall purpose of this research is to examine the phenomenon of femicide and its legislative developments in Latin America. Guided by a constructionist framework, this chapter will provide a theoretical foundation for the following two research questions:
Research Question #1: Has the way that femicide is defined as a social problem in Latin American countries determined the legislative responses to this violence?
Research Question #2: Have the responses to femicide reduced female homicide rates in Latin America?
In this chapter, the central tenets of social problems theory, more specifically the social constructionist orientation, will be discussed including the origin and stages of social problems. Next, a contextual constructionist approach, a branch of social constructionism, will be applied to the phenomenon of femicide. This chapter will examine the success of the claim of femicide as a social problem, looking at how the problem has been defined, by whom, and the responses that have been created as a result of these claims.
SOCIAL PROBLEMS THEORY
Constructionist Approach
John Kitsuse and Malcolm Spector (1973) have guided the work in the social constructionist perspective of social problems theory (Bacchi 1999; Best 2002). They wrote largely in response to the argument that societal problems are easily identifiable and in need of solutions (Bacchi 1999). This approach links all social problems together
34 through the way in which social problems emerge and solutions are developed. Spector and Kitsuse define a social problem “as the activities of individuals or groups making assertions of grievances and claims with respect to some putative condition” (1977:75).
In every identifiable problem, an individual or group is making a claim that some condition is having a negative impact on someone or something. A better understanding of all social problems can be developed by studying the process used by groups who are successful in bringing attention to a problem.
Definitions and concepts of social problems are not static or universal, but are the result of historical and cultural contexts (Muehlenhard and Kimes 1999). Social constructionism is useful in looking at how problems are constructed within a society.
Unlike “social issues” or “social conditions,” the term “social problems” implies the definitive presence of a concern, in addition to a possible solution (Best 1995). The social constructionist approach allows investigators to evaluate questions such as how a condition becomes labeled as a social problem and how solutions to social problems are developed.
Social constructionism provides a method for examining violence. Violence has cultural and social elements that determine what it means to be a victim and a perpetrator
(Comas-D’Argemir 2014). Identifying actions or behaviours that are violent may seem effortless, but what is considered “violence” is socially constructed; it differs over time, across cultures and countries, and is dependent on power (Muehlenhard and Kimes
1999). Not everyone is in an equal position to define a social problem. Those in power have the ability to define social problems more easily. Dominant groups have a tendency
35 to define problems in a way that exempts their behaviour. The constructionist approach is examined to explain why definitions of femicide and corresponding approaches differ.
The stages of social problems
Social problems do not spontaneously appear. Spector and Kitsuse (1977) identify four stages of the process of defining a social problem. Their approach is based on a
“grassroots view of social problems in which popular movements, as well as interest groups, agitate to bring about social conditions to official agencies for change or amelioration” (Spector and Kitsuse 1977:155). Feminist groups have largely influenced the recognition of femicide as key claims-makers of this phenomenon. The following section will examine the stages of social problems as described by Spector and Kitsuse
(1977) using examples from Latin America (Safa 1990).
The first stage is considered a process of identification during which a private issue is pushed into the public sphere. At this stage, an initial protest group brings attention to the issue and defines it as a social problem (Spector and Kitsuse 1977). In countries in Latin America, the initial protest group commonly includes the friends and families of victims of femicide (Prieto-Carrón et al. 2007).
The second phase in identifying a social problem is the legitimization stage.
During this time, the social problem is brought to light in a formalized way and is recognized by individuals outside the initial protest group (Spector and Kitsuse 1977).
During this stage, an institution must be created, or an existing institution must absorb the responsibility, to address the concerns of the condition identified (Spector and Kitsuse
1977). Without the existence of an institution, a social problem can easily lose momentum. Public policies are often introduced at this stage. The second stage is
36 concluded when the prevailing concerns of a condition have been recorded and an institution has committed to addressing them. Between 1995 and 2005, Cuidad Juarez and Chihuahua City, two northern Mexican cities, were well-known for their female-led protests against the killings and disappearances of women in the area (Wright 2006). In
1998, a special prosecutor was appointed to investigate the killings and an office was created to collaborate with victims’ families (Wright 2011). These improvements were considered major accomplishments for the movement.
The third stage occurs when the formalized response is unable to adequately address the problem. This stage is known as a ‘conflict stage’ (Spector and Kitsuse 1977).
An evaluation of the social programs or policies that have been introduced is common.
Advocates, victims, and other interest groups speak out against the problem and the ineffectiveness of current policies. An activity involved in stage three includes modifying the system that responds to this social problem. Despite the accomplishments mentioned above, femicides and kidnappings continued to occur in Mexico at alarming rates (Wright
2006). International organizations began to speak out against the killings and the apparent lack of justice. Amnesty International, in particular, published “a blistering critique of regional, political, and economic leaders” holding them accountable for their passivity in relation to the crimes (Wright 2006:683). Missing and murdered women in Mexico were now receiving international attention and the Mexican government was being pressured to modify the current system. This stage of social problems is of particular interest to the current study because it is concerned with evaluating the effectiveness of the responses to femicide in Latin American countries.
37 The last stage of social problems begins when the groups involved no longer feel that change within the current system is possible. When this consensus is reached claims- makers have two options: to attempt to radically change the system, or to work outside it
(Spector and Kitsuse 1977). Femicide was eventually acknowledged by the national government in Mexico as a serious crime, requiring amendments to the criminal code specifying femicide as a distinct form of violence. This classification is a radical change because criminal sanctions for killings in Mexico were previously gender-neutral.
The stages of social problems are important to understanding how the condition of femicide has emerged. The stages of social problems illustrate the process claims-makers must withstand in an attempt to get a social problem acknowledged as a legitimate claim.
Claims, claims-makers, claims-making
Key terms to the constructionist approach outlined by Spector and Kitsuse (1977) include claims, claims-makers, and claims-making. A claim is a declaration about the condition. Groups known as claims-makers make a declaration about the claim, deciding that the condition is problematic. Claims-makers are a fundamental aspect of the constructionist approach to social problems (Spector and Kitsuse 1977). These actors draw attention to the condition and help structure how the problem is defined. Claims- makers address different audiences, from those directly affected by the condition, to the general public, to those in charge of policy decisions (Spector and Kitsuse 1977). The study of how claims are made, known as the process of claims-making, and the responses to these claims are the areas of concentration for the study of social problems (Spector and Kitsuse 1977). The study of social problems involves examining the claims with respect to which groups make them, to whom the claims are made, and the activities
38 involved in making claims. The existence of social problems depends on the continued existence of groups or agencies that define conditions as a problem and attempt to do something about them (Spector and Kitsuse 1973:415).
Typification is the process by which claims-makers situate the social problem within a particular context. Claims-makers typify a social problem as an attempt to make others view the problem in a particular way (Spector and Kitsuse 1977). Usually, the characterization of a problem in a particular way offers both a cause and a solution.
Claims-makers emphasize particular aspects of the condition and its solution and may ignore others depending on the orientation. Typification is normally used by claims- makers and, thus, is important to the constructionist approach. As social problems evolve, different strategies are employed by claims-makers in an attempt to generate support. In
Mexico, for example, one strategy used by claims-makers was to frame femicide in a religious discourse. Linking victims` mothers to the “Madre Dolorosa” (the Suffering
Mother) and describing victims of feminicide as “virgin-daughters” helped rouse public support (Fregoso 2006:125).
The media plays a pivotal role in naming social problems as it has the power to make personal issues available to the public (Gillespie et al. 2013). Individuals who have little experience with violence gain their understandings or “social constructions” of crimes such as domestic violence through the media (Pantaleo 2010). The media is important to the construction of violence because it can distribute certain views and suppress others (Comas-D’Argemir 2014). Media attention is an important channel for claims-makers to generate support for their definition of a social problem. Different groups frame homicides, their possible causes and solutions in different ways (Pantaelo
39 2010). A study by Pantaleo (2010), who assessed the constructions of femicide by various groups, found that when providing reasons for this phenomenon, groups of claims-makers reported a different primary cause. The academics reviewed cited NAFTA
(The North American Free Trade Agreement) and the increase of women working in cheap labour manufacturing jobs as a cause of femicide (Pantaleo 2010:358). In contrast, human rights reports and newspaper agencies, presumably influenced by human rights groups, claimed corruption of the criminal justice system as the most common cause of femicides.
Criticisms of the constructionist approach
The most prominent criticism of the constructionist approach, particularly the work of Spector and Kitsuse (1977), comes from Woolgar and Pawluch (1985) who highlight the problem of ontological gerrymandering. Woolgar and Pawluch (1985) argue that the work of Spector and Kitsuse (1977) contains a contradictory theoretical stance. “The successful social problems explanation depends on making problematic the truth status of certain states of affairs selected for analysis and explanation, while backgrounding or minimizing the possibility that the same problems apply to assumptions upon which the analysis depends” (Woolgar and Pawluch 1985:216). In other words, ontological gerrymandering is the claim that objectivist assumptions remain because claims are being compared to a condition that is presumed to have remained constant over time (Bacchi 1999). For example, Spector and Kitsuse (1977) suggest that only the definition of the social problem has changed, but the condition has remained the same. However, claiming that the condition has remained the same involves, at least, some analysis of the condition.
40 This criticism initially encouraged constructionists to attempt to avoid any analysis of the condition. Responding to Woolgar and Pawluch (1985), Ibarra and Kitsuse
(1993) argued that the objective of the constructionist approach was to focus on the language used, believing that the study of social problems should be completely dissociated from the condition itself. As an example, if the condition is violence against women, constructionists should only focus on the claims made, refraining from assessing the seriousness or effects of this condition. However, some theorists acknowledge that the complete avoidance of the condition was impossible in practice (Best 1993; Bacchi
1999). The criticism of Woolgar and Pawluch (1985) led to the development of contextual constructionism (Best 1989).
Contextual Constructionism
Contextual constructionism is a more flexible form of the constructionist approach. The most important difference between strict constructionism, as labelled by
Best (1993), and contextual constructionism is that according to strict constructionism, social problems should be completely dissociated from the conditions themselves. For example, according to Spector and Kitsuse (1977), the factual existence of the condition is simply irrelevant to constructionists. “If the alleged condition were a complete hoax– a fabrication– we would maintain a noncommittal stance toward it, unless to those to whom the claim were addressed initiated their own analysis and uncovered it as a hoax”
(Spector and Kitsuse 1977:76). Thus, according to the strict constructionist approach, claims regarding alien abductions are just as valid as claims about violence against women so long as claims are being made about both conditions (Best 1993).
41 Contextual constructionists focus primarily on the claim and the claims-making process. However, unlike strict constructionists, contextual constructionists can assess the reality and seriousness of the claim (Best 1989). Contextual constructionists believe they are able to know, at least with some certainty, something about the claim. Best (2002) asserts that claims can be assessed against evidence, albeit evidence is socially constructed. Contextual constructionists have the ability to distinguish between real and false social problems by engaging with the conditions and supporting evidence (Holstein and Miller 1993).
Another distinction between the two approaches is that strict constructionists are instructed not to ask certain questions, fearful of participating in the claims-making process. For example, strict constructionists are supposed to refrain from questioning the motives or values of claims-makers (Best 2002). Contextual constructionists argue that the strict constructionist approach could undermine the study of social problems by making theorists hesitant to ask important questions about claims-making (Holstein and
Miller 1993). “Constructionists focus on claims rather than conditions, but few of them are interested in developing a purely abstract theory, which would be the only way to resolutely ignore the social context within which claims emerge” (Best 2002:704).
Contextual constructionists argue that the purpose of research into social problems should be to present some understanding of the problem. The social condition, the typification of the problem and the organization of social movements are an important focus in contextual constructionist research.
42 The contextual constructionist perspective can be applied to femicide to understand the varying constructions, which may result from different claims-makers, their perspectives, and power relations.
CONTEXTUAL CONSTRUCTIONIST APPROACH TO FEMICIDE
Development of Femicide as a Social Problem
Movements against VAW and femicide more specifically have been largely influenced by feminist research (Fried 2003; Prieto-Carrón et al. 2007; Wright 2006).
Feminist theory is not a single theory, but a variety of theories or perspectives that attempt to explain the oppression of women and various solutions. Feminist perspectives include: liberal, socialist, and radical feminism (Fiss 1994). Each feminist theory can be described as a separate construction as different camps of feminism offer different solutions to the oppression of women (Kaplan 1994; Vieraitis et al. 2008). At its foundation, however, feminist perspectives place the social construction of gender at the heart of their investigation (Lather 1988). Feminists in Latin America are not a single homogenous group, but have worked together on issues of VAW and femicide (Rojas
2005).
According to feminist scholars, Latin America is heavily ingrained in the culture of machismo, which has traditionally been reflected in legislation and criminal justice practices (Carey and Torres 2010; Speiler 2011). This culture reinforces patriarchy, which is a concept used to describe a system embedded in the structure of society that values masculine traits over feminine traits (Walby 1989). Patriarchy is not unique to
Latin America, but its existence is well documented there (Wilson 2014). For example,
43 as an initial response to the protests against the killings of women, a question asked by two governors and other political elites of Mexico was “why wasn't she at home in the first place?” (Wright 2005:285). From this particular orientation, the responsibility for the violence against women taking place in the public sphere was placed on the woman for being outside of the home. From this perspective, a solution to this problem is for women to stay at home in their traditional roles as wives and mothers (Wright 2005).
As previously mentioned, social constructions are largely dependent on power relationships. In most societies throughout history and largely still today, the powerful tend to be men. Men and women do not have equal social and economic rights or equal access to productive resources anywhere in the world (True 2012). When a less dominant group attempts to overthrow the existing structure and to promote social change, the initial battleground is frequently the words used to discuss the problem (Kelly and
Radford 1998).
Claims-making and Claims-makers
Through the feminist movement, women have influenced the recognition of VAW and femicide as a social problem. “Feminism gives shape and direction to the women’s movement and, of course, is shaped by it” (Fiss 1994:413). Feminist movements have led to an increase of women in the workforce and women now hold influential positions in government, academic, and economic institutions (Palma-Solis et al. 2008). Compatible with the constructionist perspective is the notion that increased power results in increased influence over the ability to define and highlight social issues (Muehlenhard and Kimes
1999).
44 Violence against women by male intimate partners has traditionally been culturally or legally labeled as a private issue (Comas-D’Argemir 2014). It was not until the 1970s that VAW and more specifically, femicide began to be recognized by the public as a serious social problem (Fried 2003). Local activists and organizations rooted in feminist perspectives began to work together to oppose violence against women at the regional level in Latin America in the 1980s (Friedman 2009).
According to Best (1995), private issues become public problems when the experiences of individual people are accepted as exemplifying a larger social problem. In the first stages of coordinating, women often lobbied governments to develop shelters and provide services for women experiencing violence (Fried 2003). The next step for women’s groups involved pushing the government from service provision to the implementation of laws and policies (Fried 2003). Women have struggled to get violence that was traditionally viewed as a private matter acknowledged in the public sphere as a social problem. Feminist organizations have been organizing around the claim that VAW is a public problem rooted in gender inequality that requires state intervention (Prieto-
Carrón et al. 2007).
An important objective of national and regional organizations was having VAW perceived as a violation of international human rights (Friedman 2009). Human rights which include civil and political rights, declare for example, the right to personal freedom and safety, the right to health services, and the right to social security, and are intended to increase state accountability, monitor development, and encourage consistency (Ropp and Sikkink 1999; United Nations 2006). An example of a traditional human rights violation is the use torture or slavery (United Nations 2006). Initially, a limited definition
45 of human rights was accepted by many nations, restricting human rights violations to violence in the public sphere hindered the consideration of women's rights (Bunch 1990).
Through defining femicide under the umbrella of human rights violations, claims-makers were able to gain provisions for human rights violations that occurred in the private sphere. In 1994, The Inter-American Commission on Human Rights (IACHR) included women’s rights as human rights with the creation of “The Special Rapporteurship on the
Rights of Women” which is a branch designed to make recommendations to states on how they can achieve equality and non-discrimination against women (Friedman
2009:356).
International and regional organizations such as the United Nations (UN Women) and Amnesty International often take the role of claims-makers. One tactic used by these groups includes ‘mobilizing shame’ and this has been an important tool in getting femicide recognized as a social problem (Fregoso 2006). Mobilizing shame is the process of “gathering the eyes of the world” and “shining the light of public scrutiny” (Fregoso
2006:118; Keenan 2004). It is the primary method for human rights organizations to make claims against the state. Exposing violence such as homicide, rape, and disappearances to an international audience, attention is turned to the state for their actions or inactions that allow this violence to continue (Keenan 2004). The media, and in particular image-based media, are largely influential in mobilizing shame. Their power lies in publicity and the ability to trigger a response.
Another tactic used by international and regional organizations is framing violence against women as a public health issue. Injury, disability, and death are dominant measurements used to rank the status of public health in a country (Winett
46 1998). The public health community can take up social problems that cause these consequences when the condition is argued to impact the population as a whole (Chrisler and Ferguson 2006). Violence, and femicide in particular, are a significant cause of premature death in many countries (Frye and Wilt 2001; Winett 1998). The diagnosis of violence against women as a public health issue is an important recognition of this problem as a societal problem. “With its use of an epidemiologic model, public health assumes that the majority of violence does not occur by chance, that violence has causal factors that can be identified and prevented, and that these factors can vary among different populations and places” (Orpinas 1999:232). For the same reason that public health organizations address AIDS, primarily its frequent cause of deaths and injuries, violence against women can be framed in the same way. The Pan American Health
Organization (PAHO) and the World Health Organization (WHO) are examples of organizations that make claims about VAW and femicide on the basis that this violence impedes women’s health and development (Heise et al. 1994).
Responses to Femicide
National governments are the most frequent recipients of claims. “Pressed from above and below, the states of the Americas [were] being held accountable for taking steps to combat the widespread problem of violence against women” (Meyer 1999:59). In response to international organizations and local interest groups, many states in Latin
America have included some version of the term femicide in legal protections for women.
National governments have a responsibility to prevent and protect women from violence, to investigate acts of violence when they occur, to prosecute and punish perpetrators, and to provide redress and relief to the victims and their families (United Nations 2006).
47 This obligation has been solidified through a ruling of the Inter-American Court of Human Rights. In 2002, in the case of Maria da Penha Maia Fernandes v. Brazil, the
Court ruled against Brazil, stating that the failure to prosecute and punish a perpetrator of domestic violence for more than 15 years since the investigation began was condoning the violence and contradicted the State’s international obligations (United Nations 2006).
Similarly, in 2014, the Inter-American Court of Human Rights ruled that Guatemala had acted in a prejudiced nature in the case of María Isabel Franco. María Isabel’s mother alerted the police to her daughter’s disappearance, yet authorities failed to act. Later,
María Isabel was discovered sexually assaulted, tortured, and killed. The Court ruled that the state should have acted immediately to the disappearance of María Isabel, particularly because of the prevalence of VAW in Guatemala, and that failing to do so was an act of discrimination towards her gender (Amnesty International 2014).
The acknowledgement of the term femicide and the implementation of legislation has been a notable victory for claims-makers. However, it is important to note the differences in the definitions employed by states. Examining how definitions and explanations of femicide have developed over time illustrates how these concepts are socially constructed. There is no universally recognized definition of “femicide” and
“feminicide” (Sarmiento et al. 2014). The breadth, composition and implications of these concepts continue to be the subject of debate in the social sciences in addition to political and national realms (Sarmiento et al. 2014). The definitions vary depending on the point of view from which they are examined and the discipline addressing it. Similarly, femicide legislation varies considerably between countries in Latin America (Sarmiento et al. 2014). Of interest to this research are the similarities and differences between Latin
48 American countries, the perceptions drawn on and the knowledge generated in the conceptualization of femicide as a social problem.
Definitions within legislation are important as they reflect the formal position of the state. People often rely on these definitions because they appear to be the “real or true” definitions, free from subjectivity. This idea is problematic as laws are never objective and are written almost exclusively by men of high social status (Muehlenhard and Kimes 1999). Definitions are created from a specific vantage point, with the interests of particular people in mind. “Who has the power to define and how these definitions shape the problem are important to our understanding of the problem. All attempts to create change involve questioning who decides 'what counts' as victimization and who defines its meaning and seriousness" (Kelly and Radford 1998:71). The criminalization of femicide by states defines who is a victim, who is a perpetrator, and how this condition should be managed.
CONCLUSION
This chapter outlines how contextual constructionism can be applied to the phenomenon of femicide. Femicide and its related terms have brought this social problem out of the private sphere. Defining femicide is important as it guides our perception of what is considered unacceptable behaviour. This influences what we believe merits research and legislative change (Muehlenhard and Kimes 1999). Claims-makers including women’s groups and the international community continue to highlight the incidence of femicide and fight for responses that may diminish its occurrence in Latin
America. The following chapter describes the methodology of the present study.
49 CHAPTER 4 - METHODOLOGY
This chapter identifies the approach and design of this research, including how the data were collected, organized, and interpreted. Using a two-stage sequential mixed method approach, the research addresses the following research questions:
Has the way that femicide is defined as a social problem in Latin American countries determined the legislative responses to this violence?
Have the responses to femicide reduced female homicide rates in Latin America?
This chapter will provide an overview of the mixed method research design including both qualitative and quantitative components. Using a qualitative approach to address the first research question, this study analyzed femicide legislation currently in place in Latin America. Next, using quantitative methods to address the second research question, this research examined whether the implementation of femicide legislation was associated with a decline in the rate of female homicide. Finally, this chapter will consider the strengths and weaknesses of this research design. The current study contributes to the body of femicide literature by assessing macro-level factors, including the existence of legislation, which may impact femicide rates. Additionally, this research is interested in which country-level factors may influence the development and implementation of femicide legislation. Lastly, this research contributes to the discussion surrounding policy implementation and potential recommendations that can improve the effectiveness of femicide legislation for women in Latin America.
50 RESEARCH DESIGN
As qualitative and quantitative methods are very different in their approaches, some researchers have suggested that they should not be combined (Green 2007; Palys and Atchison 2014). Researchers belonged to one of the two camps and never strayed from their orientation. This tradition has changed in recent years, however, with the notion that the two approaches can complement one another. In fact, the advantages of using a mixed method approach are numerous (Green 2007; Noaks and Wincup 2004;
Palys and Atchison 2014). Mixed method approaches can facilitate asking a wider range of questions than one method alone (Noaks and Wincup 2004). In this study, a mixed method approach was chosen because the research questions seek both detailed qualitative and generalized quantitative results (Creswell 2009). The use of both qualitative and quantitative methodological tools also reduces the limitations that result from using only one approach and can increase the validity of the findings (Noaks and
Wincup 2004; Palys and Atchison 2014). According to Maguire (2000), researchers should use as many different sources of evidence as possible in answering their research question. This mixed method approach relies on both methods equally, in contrast to triangulation, which uses one method to test or check another (Creswell 2009).
This research design is a two-stage sequential mixed method approach. That is, the research took place in two stages in a step-by-step fashion, collecting both qualitative and quantitative data in a logical pre-determined order (Green 2007; Palys and Atchison
2014). Qualitative methods were chosen as the first step of this research because the goal was to understand the content of femicide legislation that had been implemented in Latin
America. Following this, quantitative methods were used to assess the effectiveness of
51 the legislation in reducing female homicide rates. This stage also included several macro- level variables to examine whether other factors may be influencing a rise or fall in femicide either separately from or in combination with femicide legislation. The results of these types of questions provide an understanding of how femicide legislation and various other factors may be affecting rates of femicide across the region.
Research Question #1: Has the way that femicide is defined as a social problem in Latin
American countries determined the legislative responses to this violence?
The first stage of this research design sought to understand how femicide has been defined as a social problem by examining related legislation in Latin America. This research method is similar to the work of Ortiz-Barreda et al. (2013) who used a content analysis to map VAW legislation globally. Guided by the “What’s the Problem
Approach” (WPR), the content analysis used in the current study was concerned with the different definitions and interpretations used to describe the problem of femicide including the underlying beliefs about the problem and suggested solutions.
The sample
This stage included 13 legislative summaries from The Latin American Model
Protocol for the investigation of gender-related killings of women (femicide/feminicide), developed by the Regional Office for Central America of the United Nations High
Commissioner for Human Rights (OHCHR; see Appendix A for a full list of countries).
Published in 2014, this information is the product of a thorough review of legal procedures available to respond to crimes of femicide in Latin America, providing insight into the content of femicide legislation. More specifically, the UN documented the
52 provisions used in classifying and punishing femicide in each Latin American country that had passed femicide legislation. These legislative summaries include definitions of femicide, descriptions of the crime characteristics, and how this phenomenon may differ from homicide more generally. UN legislative summaries were chosen as the sample for analysis to overcome the language barrier that would have been faced if reviewing original legislative documents because government documents in Latin America are written almost exclusively in Spanish. A thorough Internet search was conducted for
English translations of femicide legislation in each country with no results. Confirmed by the UNODC, no translated full-text versions of legislations exist. Given the time and resource constraints of this research, this alternative to translating legislation was determined to be the most feasible choice. While there are limitations to using secondary documents, the UN has worked extensively on the issue of femicide in Latin America; therefore, this was the most accurate available sample for this research. Legislation implementation spanned from 2007-2013. Included in this analysis are Mexico and countries from Central and South America. No femicide legislations currently exist in the
Caribbean.
As the UN published femicide legislation summaries in 2014, legislation introduced more recently, from 2014-2016, was not included in the analysis. For example, the Brazilian legislation passed in 2015 and the Colombian supplementary femicide law, also enacted in 2015, were among the legislation not included in the current sample.
53
What’s the problem approach method
The content analysis conducted was guided by the “What’s the Problem
Represented to be? Approach” (WPR approach) (Bacchi 1999). A content analysis can be defined as “the systematic reduction (condensation) of content, analyzed with special attention on the context in which the data were created, to identify themes and extract meaningful interpretation” (Roller et al. 2015:230). The WPR approach is both a method of thinking and a method of analysis. As a way of thinking, this approach counters the idea that policy is solely a response to a problem. Instead, this approach suggests that policy implies a particular construction of the problem, which is only one interpretation
(Bacchi 1999). Within every policy, some condition has been defined as problematic and solutions have been put forth based on this definition. Bacchi (2009) contends that instead of evaluating policies solely in their capacity to solve the problem, we need to examine how policies construct the problems themselves. A qualitative content analysis focuses on the language and, in particular, its context and communicative intent (Hsieh and Shannon 2005). The WPR approach goes one step further than analyzing the content through an examination of the assumptions required to inform the content.
Bacchi’s (1999) work specifically makes connections to legislative development targeting gender-based violence, arguing that these developments can help or hinder women depending on how the problem is defined. For example, if a policy to reduce violence against women presumes that this problem is defined by the breakdown of social order rather than gender inequality, solutions could include allocating funds away from women’s shelters to increase police forces (Bacchi 1999). The WPR approach is
54 consistent with the contextual constructionist framework discussed in the previous chapter because the WPR approach explores the benefits and consequences of specific problem constructions.
The WPR approach has traditionally been applied to legislative documents, yet this method has an extensive field of application including any documents that explain the prescribed responses of policy institutions (Bacchi 2009). Thus, this approach is well suited for research on legislative summaries, which provide the necessary information to understand the ‘solutions’ to femicide that have been put forth. This approach has also been previously used to examine violence against women legislation (Murray and Powell
2009).
Data analysis approach
This analysis began with a thorough read through of the sample. As a method of analysis, the WPR approach, which is based on a set of predetermined questions, provides a clear method to examine policy. Four questions were asked from Bacchi’s
(1999:13) original WPR approach (see Table 1. for WPR questions)1. The inclusion of the WPR approach in the analysis of femicide legislation prevents this stage from being primarily descriptive as it challenges conventional policy approaches by asking how this construction of the problem affects the intended solutions. For example, if femicide is
1 Since then, Bacchi (2009) has included two additional questions to aid in the analysis of policy. The most recent questions ask how this problem has come about and how or where this representation has been produced, contended, or defended (Bacchi 2009). The latest two questions, introduced by Bacchi will not be introduced for two reasons. First, these questions have been approached, albeit generally, in previous chapters. Second, because of the means used to evaluate the legislation (UN recordings), fewer inferences can be drawn regarding how this representation has developed.
55 constructed as a problem that occurs between intimate partners, then the ‘solutions’ to this problem may differ from countries that have defined femicide in other ways.
Each of the four questions serves a particular purpose in uncovering ‘what’s the problem represented to be’. The first question is meant as a simple, introductory question into the problem with the aim of extracting what the policy aims to address. As all policies put forth a representation of a problem, it is important to clarify at the outset of this analysis the problem representation within each policy.
Table 1. WPR Approach
What’s the problem represented to be? An approach to policy analysis
1. What’s the problem represented to be within the specific policy?
2. What presuppositions or assumptions underlie this representation of the
problem?
3. How has this representation of the problem come about?
4. What is left unproblematic in this problem representation? What are the silences? Can the problem be thought about differently?
Question two of the WPR approach identifies and analyzes the “conceptual logics” that underpin problem representations. This refers to the meanings that must be in place for a particular problem representation to make sense (Bacchi 2009:5). The goal of this question is not to identify biases, but to analyze the assumptions that exist within problem representations. This distinction may appear obscure; however, the purpose of this analysis is to ask, “what meanings need to be in place for something to happen,” rather than asking “how is it possible for something to happen” (Bacchi 2009:5). In order to achieve this, Bacchi (2009) recommends a discourse analysis, which concentrates on
56 speech patterns and how words are used to express meaning (Harding 2013). Bacchi
(2009) suggests that for the purpose of the WPR approach, this analysis should include binaries, key concepts, and categories.
Binaries or dichotomies are words that streamline complicated relationships, examples of which include “legal/illegal, national/international, and economic/social”
(Bacchi 2009:7). These words are related to each other as they function on an A/not-A relationship (Bacchi 2009:7). In determining the assumptions that underlie femicide, it is necessary to examine how these relationships shape our understanding. Important to binaries are relationships of power as one half of the binary is usually prioritized over the other. Binaries were identified through coding central terms in the legislation. Next, central terms were analyzed with respect to any potential relationships among them. Any central term with an identified inverse was considered a binary.
Key concepts are relatively ambiguous labels such as “health” or “welfare” that have differing meanings based on the construction of the problem (Bacchi 2009:8).
These concepts are frequently challenged depending on the claim being made. As part of examining the underlying assumptions of this problem, researchers must identify key concepts and determine what meanings have been assigned to them. Key concepts were extracted from the text through searching for repetition. Unlike other concepts, which may appear in only one or two legislations, key concepts are used by more than half of the legislations analyzed.
People categories are also important to the construction of policies and legislation.
People categories place people into groups on the basis of one attribute or another
(Bacchi 2009). Similar to binaries and key concepts, people categories provide important
57 information on problem representations as they determine who is eligible to benefit from these constructions. This section examines how people are characterized in the legislation. The researcher identified people categories by coding all groups referred to in the sample.
Next, Bacchi (2009) asserts that there are two interconnected objectives to the third question. The first is to reflect on the specific developments and decisions that contribute to the identified problem. The second is to recognize that competing problem representations exist across time and space (Bacchi 2009:10). This question concentrates on the process of how this problem representation came to be. This exercise challenges the idea of this legislation in its present form as organic or inevitable and highlights the relationships in its historical progression (Bacchi 2015). Themes were extracted from the sample by coding important characteristics of the legislation. Codes were then sorted into themes based on these characteristics to highlight connections among countries and provide general explanations. Relevant literature will be drawn from in this question to provide explanations for why governments may have chosen particular constructions.
The final question of this analysis considers the limitations of underlying problem representations. The argument here is not only that there are other ways to think about the problem but that policies are limited by the way they represent the problem (Bacchi
2009:13). Similar to other discourse analyses, the WPR approach pays close attention to the gaps or silences in the text, looking for things unspoken (Tonkiss 2004). In this question, the binary analysis in the second question is helpful because it can shed light on some of the over-simplifications of certain problem representations.
58 In this approach, Bacchi (1999) maintains that there is some flexibility in how the questions can be asked. For example, questions can be asked all at once or question by question. In this study, questions were asked by the researcher sequentially for each country in the order suggested by Bacchi (1999). Specifically, the first question was asked with respect to each country’s legislation before moving on to the next question which helped to maintain consistency across countries. Qualitative content analysis often involves multiple readings and going back and forth between stages of analysis (Harding
2013). As such, each country’s legislative summary was examined several times, each time enriching the interpretation of the analysis.
The purpose of this analysis is to describe how femicide has been constructed as a social problem through legislation in Latin American countries. This stage also provides comparisons of problem constructions among countries. The examination of different conceptualizations of femicide and related responses will be important to making suggestions for future legislative developments. This qualitative analysis was chosen as the first step of the research design to gain an understanding of how constructions within femicide legislation may influence the effectiveness of legislation before assessing whether this legislation was reducing femicide. Conducting the qualitative portion prior to the quantitative analysis allows the researcher to assess whether particular representations of the problem were more successful than others in reducing femicide rates in Latin America. This analysis also proves beneficial for future recommendations if one country appears particularly successful in reducing female homicide rates.
RQ 2: Have the responses to femicide reduced female homicide rates in Latin America?
59 The second stage of this research aimed to assess whether the legislation enacted is reducing the rate of femicide. This stage comprised a macro-level analysis of the relationship between social, cultural and political factors, including existing femicide legislation, and the individual and combined impact of these factors on female homicide rates.
This research uses data collected from the United Nations Office on Drugs and
Crime (UNODC), The World Bank, and The United Nations Economic Commission for
Latin America and the Caribbean (ECLAC) Division, and the Pan-American Health
Organization (PAHO) to assess femicide rates before and after the introduction of legislation from 1997-2014 in 24 Latin American countries. This research draws on a variety of quantitative tools, including descriptive statistics, bivariate analyses, and non- parametric t-tests. This section will provide an overview of variables including definitions, the reasoning behind their inclusion, data sources used, and how variables were measured.
Measures and Variables
The sample
The final dataset included information from 1997-2014 for 24 countries including
Mexico, six Central American countries, ten South American countries and seven
Caribbean countries (see Appendix B for a full list of countries). The year 1997 was chosen as the first year because this is the earliest year for which data on the dependent variable, female homicide rates were available for most countries. Outlined below are key
60 dependent and independent variables in addition to the macro country-level factors considered.
Key dependent variable
In this research, the dependent variable used to measure femicide rates in Latin
America was female homicide rates. This variable was used as the key dependent variable instead of femicide rate for two reasons. First, not all countries record femicide rates and countries that do keep a record of this information have only recently begun to do so. Additionally, while some authors argue that in Latin America the killing of any woman is femicide (Fregoso and Bejarano 2010; Lagarde y de los Rios 2006), states have only permitted the classification of femicide under certain conditions. As countries in
Latin America define femicide in different ways, this research used female homicide rate as a way to capture the largest amount of female deaths and maintain consistency among countries. This information was collected by the PAHO and was measured by the rate per
100, 000 inhabitants.
Key independent variable
The primary independent variable used in this study was the existence of femicide legislation. As a method of protecting women from femicide, academics and
NGOs alike have been pushing countries to enact and enforce legislation (Amnesty
International 2006; Fried 2003; Prieto-Carrón et al. 2007; Sanford 2008). The literature discussed both the importance of legislation and the reluctance of countries in Latin
America to put legislation into practice. Many countries in Latin America have been
61 criticized for their failure to enforce legislation. Impunity, or a failure to respond to
VAW, has been acknowledged as a predictor of femicide (Carey and Torres 2010;
Hernandez 2003). Palma-Solis et al. (2008) that concluded a shortage of laws and policies requiring interventions and government investment could result in a greater risk of femicide. The literature suggests that there is an overall trend in Latin America showing ineffective implementation of femicide legislation. Drawing from previous literature, this study makes the following hypothesis:
Hypothesis 1: The enactment of legislation in Latin American countries will not result in a decrease in the number of female homicides.
Femicide legislation cannot reduce female homicide rates if legislation remains only words on a page (Fried 2003). Studies conducted in the US, among states with and without domestic violence legislation, have concluded that the implementation of legislation can reduce femicide (Stout 1992; Dugan 2003). While the United States and
Latin America have many regional differences, the success in the US demonstrates that legislation has the potential to reduce female homicide rates if properly implemented.
This variable was measured as a dichotomous 1=yes, 0=no for each year between 1997-
2014 (Appendix B provides a list of all variables and their measurements).
Country-level variables
Male homicide rate
In all countries, male homicides occur more frequently than female homicides, though usually under different circumstances (Sanford 2008; UNODC 2013). However, female homicide rates tend to be particularly high in countries that also have high male
62 homicide rates (Sanford 2008). Therefore, male homicide rates were included to assess whether there was any relationship between the rates of male homicide and female homicide in Latin America. There are common forces that make both male and female homicides more likely. For example, Marvell and Moody (1999) argue that as homicides tend to be committed by men, offenders are influenced by similar forces. Thus, even though the victims and the situations are different, the conditions that perpetuate homicide are the same. As femicide legislation only targets the killing of women, this legislation should have little impact on the rate of male homicides. The only impact femicide legislation may have on the rate of male homicide occurs when legislation implements more resources for women (Browne and Williams 1989). This option may provide women an alternative to killing their male partners in order to survive. If a correlation is found between male homicide rates and femicide legislation, it will suggest the need to assess other factors that are effecting homicide rates of both men and women.
This was a continuous measure variable collected by the PAHO and describes the number of male killings per 100,000 inhabitants. Male homicide rate was also used as a dependent variable during the Wilcoxon-signed rank test to compare homicide rates of males and females before and after the introduction of femicide legislation. The analysis will be discussed in further detail later in this chapter.
Intimate partner femicide rate
Some of the countries examined also collected rates of intimate partner femicide
(IPF). IPF is an important measure as a significant proportion of all femicides that occur within certain Latin American countries are intimate partner femicides (Lagarde y de los
Rios 2006; Sagot 2005). For example, in Brazil, Dominican Republic, and Costa Rica,
63 more than 60 percent of all femicides were intimate partner femicides (Sagot 2005). As such, several Latin American countries have specifically targeted or only targeted this type of femicide in their legislation. The impact of legislation that targets intimate partner femicide may get lost in the more inclusive measure of female homicide rate, particularly if the country’s legislation is only designed to reduce this type of femicide. This was a continuous variable collected for each country with available data from the UN ECLAC
Division measured by the rate per 100, 000 women. Intimate partner femicide rate was used as a dependent variable during the Wilcoxon-signed rank test to assess whether the enactment of femicide legislation had a greater impact on a particular measure of femicide.
Femicide rate
Some countries, such as the Dominican Republic, Costa Rica, and Nicaragua have also begun collecting data on the rate of femicide. This variable was included in addition to female homicide and IPF as it measures all femicides and only femicides within each country. The purpose of including this measure was to assess whether legislation may have an impact on this variable if no impact was found on female homicide rates.
Femicide rate was not used as the primary dependent variable as the recording of this variable has begun only recently. Additionally, as countries define femicide in different ways, this variable would not allow for comparisons among countries. This was a continuous variable measured by the rate of 100, 000 women collected by the UN
ECLAC Division. Similar to the previous variable, femicide rate was also used as a dependent variable during the Wilcoxon-signed rank test to observe whether using a measure other than female homicide rate would impact the results.
64 As femicide is a complex issue, legislation is not the only factor that may influence rates of femicide. As a result, variables capturing other social, economic, and political factors were examined in the bivariate analyses. The literature supports the examination of these factors because they are known to influence homicide rates and femicide rates more specifically. As there may be multiple causes for change in female homicide rates, it is important to analyze whether these factors may be contributing to any potential change. Bivariate analyses will examine whether there is any relationship between these factors, femicide legislation, and the rate of female homicide. Data were separated by country and by year to assess each country over the specified period of time.
VAW legislation enactment
Similar to the enactment of femicide legislation, the introduction of violence against women legislation was included as an independent variable in order to assess whether this legislation was reducing the rate of femicide. In many countries, femicide is often the result of chronic domestic violence (Carey and Torres 2010; Godoy-Paiz 2012).
Therefore, if the enactment of VAW legislation is effective in reducing the violence that often leads to femicide, this legislation could have a preventative effect on femicide itself. Similar, to femicide legislation, this variable was measured as a dichotomous
1=yes, 0=no variable for each year between 1997-2014.
GDP per capita
As discussed in the literature, GDP per capita may be associated with violent crime as greater economic tensions can increase interpersonal conflict which, in turn, may result in higher rates of homicide (Blau and Blau 1982). Countries with lower GDP per capita tend to have higher homicide rates (Butchart and Engstrom 2002; Lin 2007). It
65 follows, then, that countries in Latin America with a higher GDP per capita may have lower rates of femicide. This variable was continuous measure, representing GDP per capita in US dollars and was collected from the World Bank.
Gini coefficient
Gini coefficient is a variable that is typically used to demonstrate the level of socioeconomic inequality in a country. Economic inequality is defined as the highest income group having all the income or consumption while the majority of other income groups have little or none. This variable measures the deviation of the distribution of income among individuals or households within a country. As examined in the literature, a greater level of socioeconomic inequality may have an impact on the rate of violence against women, as greater inequality was associated with an increase in rape (Bailey and
Peterson 1992). This variable was included as it was expected that countries with more inequality would have higher rates of femicide. A zero reflects complete equality while
100 represents complete inequality. This variable was a continuous measure variable ranging from 0-100 and collected from the World Bank.
Armed conflict
Armed conflict can have a severe impact on both male and female homicide rates in a country. Women are particularly vulnerable during times of conflict, despite the fact that they rarely participate in the combat (True 2011). However, armed conflict is a difficult variable to measure, as homicide rates often remain elevated after conflict for years after the fighting ends. Regardless, elevated homicide rates due to armed conflict can be caused by scarce resources leading to disease and malnutrition, crippled infrastructures such as roads and buildings, and political instability, all of which can fuel
66 crime and insecurity (Human Security Report Project 2012; Murray et al. 2002).
Homicide rates are also affected in post-conflict countries by an increase in arms as well as men trained to use them. “In many cases, police and civilians are literally ‘outgunned’ by former combatants and criminals wielding military-style weapons” (Muggah
2005:241).
While increased homicide rates may last several years post-conflict, the time it takes to restore peace after a conflict varies from country to country usually taking several years (Harris and Lewis 2002; Ghobarah et al. 2004). The presence of armed conflict was coded as 0=no, 1=yes, or recently resolved (up to five years) to account for elevated homicide rates in a post-conflict state. The data used to measure armed conflict in Latin America, named UCDP/PRIO Armed Conflict Dataset v4-2015, 1946-2014, was the product of collaboration between the Peace Research Institute Oslo (PRIO), an independent multidisciplinary research institute, and The Department of Peace and
Conflict Research from Uppsala University in Sweden.
Employment to population ratio
Employment-to-population ratio expresses the percentage of the population over fifteen years of age that are employed, with data disaggregated by gender. The use of this variable was two-fold. First, high rates of sustained unemployment can perpetuate violent crime (Andresen 2012; Philips and Land 2012). Additionally, higher rates of female employment alongside decreases in male employment can cause frustration by males, supporting the backlash hypothesis (Dutton 1994; Russell 1975). This variable is a continuous measure variable and was collected from the World Bank.
Precarious employment
67 Precarious employment refers to employment that lacks regulations present in standard employment relationships such as worker’s rights, job security, and benefits
(Benach and Muntaner 2007). Precarious employment can also include unpaid family work or self-employed work (ILO 2010). The development of this type of employment has been attributed to economic insecurity in the formal sector as a result of the opening of the global economy (Tokman 2007). As employment is now more closely associated with the needs of the global market, opportunities for increased productivity and wages are limited (Tokman 2007). Employment of this type is more likely to have difficult or dangerous working conditions and insufficient social security (ILO 2010). For example, in Latin America, precarious employment may involve dangerous and low-paying factory work. Precarious employment often violates fundamental human rights and places workers at an increased risk of injury or death (ILO 2010). The relationship between precarious employment and homicide rates has not been explored in any of the research reviewed. However, as variables such as GDP per capita and rates of employment have demonstrated, economic insecurity has been correlated with increased homicide rates
(Blau and Blau 1982; Philips and Land 2012). Thus, it was expected that women working in this sector, or who have partners working in this sector, would be at an increased risk for femicide. Precarious employment was collected by the World Bank and is measured as the percentage of the population working in the vulnerable sector, disaggregated by gender.
Female judges
This variable measured the percentage of Supreme Court or high court judges who were female, which can be used to measure social and legal gender equality in a
68 country. An increase in female representation in a country’s highest court may reflect a commitment by the state to a more gender equal judicial system. No previous research has examined the effect of the percentage of female judges on VAW legislation, however countries have been encouraged to increase the percentage of women in the judiciary in order to enhance the gender responsiveness of courts (Chiongson et al. 2011). As judges make important rulings on crime and policy, including femicide, an increase in the percentage of female judges could result in more convictions for crimes against women
(Chiongson et al. 2011). Data were collected for each country with available data from the UN ECLAC Division.
Female members of parliament
This variable measured the percentage of female parliament members within a given country and is used as a political measure of gender equality. A significant representation of elected female officials could reflect a more gender equal society or a commitment by the state to achieve a gender equal society. Additionally, this variable was of particular interest to this study as it concerns legislation. Female parliament members have the potential to impact the rate of femicide in a country. In countries where femicide legislation exists, female members in parliament could positively effect the implementation of those laws. Htun and Weldon (2012), in their analysis of VAW policies, found a relationship between the introduction of VAW policies and female participation in the legislature. Female Member of Parliament is a continuous measure variable collected from the UN ECLAC Division.
Missing Data
69 As this research relied primarily on data collected by Non-Government
Organizations (NGOs) and other international organizations, missing, partial, or incomplete data was a concern. Data was collected by these organizations primarily from national sources within each country and there are many discrepancies among what countries choose to record and release, effecting the type and amount of information available for each country. This research initially intended to include data from all 47
Latin American countries; however, countries with limited or no available data were removed from the analysis. As this study examined the rate of femicide over time, countries with less than eight years of femicide rates between the years 1997-2014 were removed. Countries with femicide legislation that were not included in the quantitative analysis were Bolivia and Honduras as homicide rates disaggregated by gender were largely unavailable.
DATA ANALYSIS
Descriptive statistics, bivariate analyses, and two different types of non- parametric t-tests were used. First, descriptive statistics were conducted. Descriptive statistics are useful to demonstrate patterns and distributions of data across the countries examined (Vogt et al. 2014:207). Descriptive statistics are often the first stage in any quantitative analysis because they provide a synopsis of the data. Frequency tables were created for all categorical data and descriptive statistics were generated for all continuous measurements. Scatterplots were created to illustrate the rate of female homicide rates for all countries included. The year was measured across the Y-Axis and the rate of female homicide per 100,000 of the population was measured across the X-Axis.
70 In the second stage of analysis, inferential statistics were used to explore the relationship between variables. Inferential statistics determine whether there is an association between variables and the strength of that association (Palys and Atchison
2014). In this research, inferential statistics included non-parametric bivariate correlations and t-tests. Similar to parametric tests, non-parametric tests calculate how often random chance would produce the results of the data (Rugg 2007). Parametric tests assume that the data has particular characteristics such as a normal distribution with few outliers (Gorard 2004). One problem that researchers have long encountered is fitting data into conventional statistical theory (Conover and Iman 1981:124). Real world data does not always exist in the format required to run parametric tests (Conover and Iman
1981). Non-parametric tests have been identified as a useful way of circumventing these distributional assumptions (Allen et al. 2009; Field 2009). While some argue that non- parametric tests are less robust than their parametric counterparts, this is true only if no parametric assumptions have been violated (Field 2009). In this research, the data do not have a normal distribution and contain outliers. For this reason, non-parametric tests were deemed a more appropriate choice.
Rank transformation is a process used by several of the most common nonparametric tests (Conover and Iman 1981). Ranking involves giving the lowest data point a rank of 1, the next score a rank of 2 and continuing until all of the data points have been ranked. This results in the smallest scores being represented by lower numbers and the higher scores being represented by larger numbers. The analysis is then conducted on the ranks instead of the actual data, which is how non-parametric tests can
71 bypass some of the assumptions of parametric tests (Field 2009). However, statistical software, such as SPSS, completes the ranking process.
Bivariate correlations
Bivariate analyses discover whether any preliminary relationships exist between two variables. Of interest to this research is whether legislation, social, or political factors have any relationship with each other and with female homicide rates in Latin America.
For example, a correlation was conducted between female homicide rates and GDP per capita for every country to examine whether GDP per capita has any influence on the rate of female homicide in the region. Correlation analyses are used to test for a null hypothesis which implies that there is no relationship between the variables under examination (Babbie and Benaquisto 2009).
A non-parametric analysis, Spearman’s rho, was used. In a Spearman’s rho correlation, variables are put in order and numbered or ranked as described above.
Spearman’s rho applies the Pearson’s R correlation to the ranked data creating a more robust statistical test when parametric assumptions are violated (Field 2009). Spearman’s rho correlation does not require that data be normally distributed. Additionally, this correlation test is not sensitive to outliers (Vogt et al. 2014). In this case, this correlation measure was chosen because data are not normally distributed and contain several outliers. Additionally, Spearman’s rho provides a more robust analysis with small sample sizes (Field 2009). To gain an overview of the data in each country, variables were split by country. All continuous and ordinal level variables were entered into the correlation.
72 Not all countries recorded data on every variable. In cases where a country did not record data or did not include enough data to examine whether a correlation exists, this variable was removed only for this country. The removal of variables for countries with insufficient data on that variable was done to assess as many variables as possible within each country that may be having an effect on homicide rates.
Countries before and after legislation enactment
Within this research, the Wilcoxon-signed rank is used to test the effect of the implementation of legislation on the rate of killings in Latin American countries.
The Wilcoxon signed-rank was used to examine the impact of legislation on four different dependent variables. The dependent variables used were female homicide rate, intimate partner femicide rate, femicide rate, and male homicide rate. Each test was run for every country that has enacted legislation and has recorded data on the dependent variable rates for at least three years afterward (See Appendix C for a list of countries).
This analysis, which was primarily concerned with the overall homicide trends rather than homicide rates at one point in time, required multiple data points after the introduction of legislation to gain a sense of whether the legislation was having any impact. The results of this test will reveal whether the legislation appears to have any effect on the dependent variable within each country tested. A statistically significant change in the mean of female homicide rate, femicide rate or intimate partner femicide rate may suggest that legislation is having an impact.
The Wilcoxon-signed rank examines each of the dependent variables before and after the introduction of legislation. Two mean homicide rates are calculated for each test,
73 one for all the years prior to the introduction of the legislation and one for all the years after. A statistically significant difference between the two means would suggest that the dependent variable has increased or decreased over time. This test is the non-parametric equivalent of a paired t-test, also known as a simple time series design (Field 2009).
Similar to the previous test, a non-parametric test was used to control for non-normally distributed data that contained outliers.
This quantitative analysis involved descriptive statistics, correlations, and multiple non-parametric t-tests to examine the relationships between the implementation of femicide legislation, homicide rates, and other country factors that may be affecting homicide rates. The following section will discuss the benefits and limitations of this research design
Countries with and without legislation
The Mann-Whitney test (M-W) was chosen to compare female homicide rates between countries with and without legislation. This test is the non-parametric parallel to an independent t-test. T-tests require that the data are approximately normally distributed with no outliers (Cleophas and Zwinderman 2011). A non-nonparametric test was used for this analysis as this data violated the homogeneity of variance assumption as data was not normally distributed and contained outliers. The ranking of the data removes the problems of skew and outliers that would affect the reliability of this data if run with a parametric test (Lee 2014).
The purpose of conducting this test is to compare two unrelated groups on the same dependent variable. This study divided countries into two groups, countries that
74 have enacted legislation and countries without legislation. A Mann-Whitney (M-W) test was used to analyze homicide rates between countries with and without legislation. The mean homicide rate from 1997-2014 for each country was recorded. The M-W test ranks scores to test whether the scores of the two groups differ significantly from each other.
This test will signify whether a difference in female homicide rates between countries with and without legislation may be a meaningful one. If a statistically significant difference were present between the two groups, this would suggest that existence of legislation might reduce female homicide rates.
Strengths and Limitations of the Design
Benefits of the Study
This section focuses on the strengths and weaknesses of the methodology employed in this research. First, a benefit of this study is the use of a mixed method approach. Femicide in Latin America is a multifaceted issue. The use of a mixed method approach enriches the understanding of how femicide has been constructed and whether this has reduced female homicide rates in Latin America, eliminating some of the limitations that would be present if only one approach was used. Combining qualitative and quantitative methods maximizes the ability to bring different strengths of each approach together within the same project (Morgan 1998).
Second, in contrast to an assessment of only one country, this research provides a thorough investigation of femicide in Latin America. A comparison of multiple countries in the region provides an assessment of legislation across countries and time of
75 implementation. As a result, the inclusion of many Latin American countries makes the results of this research more generalizable to the region.
Finally, as stated in the literature, few researchers have studied the affects of macro-level variables on femicide or femicide legislation (Stout 1992; Dugan 2002;
Dugan et al. 2003) and even fewer have studied these effects in Latin America (Palma-
Solis et al. 2008). This research includes several macro-level factors related to development and equality. The relationships these variables have on the rate of femicide and the development of femicide legislation are important to understanding risk factors or protective factors of femicide in each country. The inclusion of macro-level factors contributes to this body of literature, filling a significant gap.
Limitations of the Study
Despite the benefits of a mixed method multi-country analysis, there were also limitations. First, while correlations between legislative developments and homicide rates are discussed, causation cannot be proven. The quantitative analysis can only suggest whether the enactment of legislation appears to be correlated with protecting women against femicide.
Next, the data used for this research were collected online from a number of Non-
Governmental Organizations. As international statistics are more difficult to retrieve the country itself reports much of the data collected by NGOs. As such, this research is restricted by the data available. Information not collected by these NGOs could not be examined. There also may have been information of varying quality, death underreporting, and inadequate completion of death certificates with homicides reported as suicides or injuries.
76 Lastly, a multiple regression analysis would have provided additional strength to this research. The purpose of a multiple regression is to assess the relationship among several independent variables on the dependent variable, while controlling for the effects of other independent variables. This analysis examines how strong the relationship is between the dependent variable with each independent variable, controlling for the influence of other variables (Weldon 2004). Multiple regression is a useful statistical tool to analyze the relationship of variables independently and collectively (Martin and
Bridgmon 2012). However, this dataset violated the necessary assumptions, as a multiple regression requires a robust sample size (Field 2009).
This chapter has outlined the methods used in conducting this research, describing the research design, data collection, and analysis. This study used a mixed method approach to examine femicide as a social problem in Latin America and test whether legislation implemented to reduce femicide rates was serving its intended purpose. The subsequent chapters examine the results of this research.
77 CHAPTER FIVE – QUALITATIVE RESULTS
Chapter five will present qualitative findings of the current study, which examined how femicide has been constructed as a social problem and whether these constructions have shaped the responses to femicide in Latin America. Recall, as discussed in the previous chapter, the qualitative analysis was organized around Bacchi’s
(1999) “what’s the problem represented to be” approach (WPR). The results of the quantitative analysis will be presented in chapter six.
RQ 1: Has the way that femicide is defined as a social problem in Latin American countries determined the legislative responses to this violence?
The findings will be presented separately for each of the four WPR questions to facilitate comparisons across the 13 countries for which legislative summaries were available.
1. What’s the problem represented to be within the specific policy?
The first WPR question is meant to interpret the problem as described within the legislation. For each legislation, it is important first to identify how the problem has been constructed. Although it is difficult to provide general problem representations for each of the thirteen legislations, some common threads emerge. Within each country, the term used to discuss the ‘problem’ is femicide or feminicide. However, the definitions of these two terms are not the same across all nations. Through these varying definitions, different problem representations can be identified. In all countries, the problem is defined as the killing of a woman. However, all thirteen countries have included at least one article or provision that describes under what circumstances the death of a woman can be classified as a femicide. The number and characteristics of provisions differ from country to
78 country ranging from one to 10 and varying from broad to precise. Legislations can be categorized from vague to inclusive based on the representations of femicide/feminicide.
At one end of the spectrum is Colombia, whereby femicide is only defined as a homicide
“against a woman because she is a woman.” In contrast, Bolivian legislation, arguably one of the most inclusive legislations in the sample, defines feminicide as a crime that has occurred under one of nine distinct circumstances2. The definition of femicide and inclusion of provisions are relevant in terms of the first question as these features distinguish the representation of the problem within each country. Similar to previous findings (Sarmiento et al. 2014), this research takes note that legislations enacted more recently tend to be less vague in their definitions of femicide/feminicide. New legislations tend to explicitly identify the conditions that make a homicide a femicide. An example of this can be seen in the definitions in countries outlined above. While
Colombia’s legislation was one of the first introduced in 2008, Bolivia’s legislation was not enacted until 2013.
More recently enacted legislations also tend to be more progressive in their characterization of femicide. Femicide has been represented as a problem through
2 These nine conditions are as follows: The perpetrator is or has been the spouse or domestic partner of the victim, is or has been connected to her through an equivalent relation of affect or intimacy, even without cohabitation; Due to the victim declining to establish with the perpetrator a relation of partnership, love, affect, or intimacy; Due to the victim being pregnant; The victim is in a situation or relationship of subordination or of a friendship, work, or companionship relationship; The victim is in a situation of vulnerability; When prior to the killing, the woman had been the victim of physical, psychological, sexual, or economic violence committed by the same aggressor; When the act has been preceded by a crime against individual liberty or sexual liberty; When the killing is connected to the crime of human trafficking or smuggling; When the killing is the result of rites, group dares, or cultural practices.
79 legislations in Latin America in two different ways. First, some countries have characterized femicide as an aggravating circumstance of another crime such as homicide or parricide, which is the killing of a family member or other close relative (Heide and
Petee 2007). For example, in Chile, femicide is classified under Article 390 of the
Criminal Code, which is the crime of parricide. On femicide, this article states: “if the victim of the crime described above is or has been the spouse or domestic partner of the perpetrator, the crime will have the name of femicide,” which is considered an aggravating circumstance, accompanying an increased penalty. Most governments that classify femicide as an aggravating circumstance of another crime were among the first legislations introduced. An exception to this, however, is Argentina, whose government classified femicide as an aggravating circumstance of homicide in 2012. Second, and more commonly, countries have enacted femicide legislation that classifies femicide as an independent crime, one that is distinct from homicide or parricide. Guatemala’s legislation was the first of its kind to recognize femicide as a distinct crime. For example, femicide is codified as Article six of the Law against Femicide and Other Forms of
Violence Against Women. This crime is distinct from homicide and states “the crime of femicide is committed by a person that within the framework of unequal power relations, between men and women, kills a woman for being a woman, availing themselves of any of the following circumstances…” Since 2011, all countries that have implemented femicide/feminicide legislation have characterized femicide as a crime that is separate from homicide or parricide, with the exception of Argentina.
Regardless of whether femicide/feminicide was included as a separate offense or an amendment to a pre-existing offense, all legislations made amendments to the
80 Criminal or Penal code. This representation is significant as across all countries, criminal offenses are the most serious. How the legislation has been categorized is an important characterization of its construction. While the inclusion of femicide in the criminal code may seem like an obvious characterization, this development is significant when accounting for the fact that previously violence against women, particularly VAW involving intimate partners, was not considered a grave offense in some Latin American countries (Perez-Cotapos 2012). Adding femicide to the list of the most severe offenses signifies a written statement that legislators believe this to be a serious crime.
The classification of this crime within the criminal code also speaks to the type of problem femicide is considered to be by governments. For example, responses to femicide would look very different if added to a public health act in lieu of the criminal code. Femicide as a criminal code provision dictates punishments for those who commit this crime. This is meant to act as a deterrent for someone who would want to kill a woman and believes they could go unpunished. The provisions within each country that outline what constitutes a femicide/feminicide serve as a list of how legislators believe this problem occurs. Specific provisions of femicide legislation and how they effect the construction of femicide as a social problem will be reviewed in detail in question three.
2. What presuppositions or assumptions underlie this representation of the problem?
This question seeks to unpack the background knowledge that is taken for granted within a policy. To achieve this goal, Bacchi (2009) suggests a type of discourse analysis, examining and evaluating binaries, key concepts, and categories, each of which will be discussed below.
81 Binaries
Binaries or dichotomies are concepts that are related to each other and take on an
“A/not-A relationship” (Bacchi 2009:7). Binaries are important to our assumptions about problem representations because one half of the binary is often more important than the other. The researcher identified key terms as concepts that were common terms among legislations. Subsequently, the researcher, in search of any relationships between terms, studied codes to identify any connections. Important binaries were identified as (1) victim/perpetrator, (2) public/private, and (3) body/mind. Each binary is expanded upon below.
Victim/Perpetrator
In many countries, this binary is interchangeable with woman/man as women are exclusively the victims of femicide, while men are almost exclusively the perpetrators of femicide. As femicide is a crime that can only be perpetrated against a woman, women are considered the victims within all 13 legislations analyzed. While the definition of the victim remains stable across countries, there are some discrepancies when examining the descriptions of perpetrators. Three legislations specifically name men as the perpetrator of femicide. However, other countries, such as Chile and Costa Rica, further define perpetrators as men who have a current or previous relationship with the victim. These problem representations, which suggest that men are most frequently perpetrators of this crime, support Russell’s (2001) definition of femicide, which is the killing of a woman by a man. In contrast, perpetrators of femicide in five countries (i.e. El Salvador, Peru,
Bolivia, Panama, and Mexico) are not gender-specific; rather, legislations define the perpetrator as a “person” who kills a woman for gender-related reasons or in the
82 circumstances outlined in the legislation. Contrary to other definitions of perpetrators, this definition presupposes that women can also commit femicide. Three countries have included a provision that makes the perpetrator more specific. El Salvador has included an increased penalty of at least 10 additional years if the perpetrator of the crime is a public servant. “The crime of feminicide will be punished with a sentence of 30-50 years in prison if carried out by a public or municipal servant, public authority or agent.” The implications of this provision will be reviewed in the third question.
Generally speaking, more recently enacted legislations are more inclusive in their definition of the perpetrator than their predecessors. The oldest legislations, such as those found in Costa Rica and Venezuela, name perpetrators as intimate partners, while newer legislations, such as those found in Bolivia and Panama, name perpetrators as a person.
While more progressive legislations tend to include more relationships, the gender neutrality of legislation could be interpreted as a benefit or a limitation, depending on its intent and application. Unfortunately, the intent of legislations cannot be inferred from the sample. These possibilities will be discussed further in chapter seven.
Private/Public
The private/public binary has a dual meaning. First, this binary can be used to describe the physical location of this violence. For example, in Mexico, if the body of the victim is displayed in a public place, this is cause to classify the crime as femicide. No legislations make specific reference to femicide committed within the home, but five legislations state that femicide can be classified as femicide “with or without cohabitation.” For example in Honduras, homicide can be classified as femicide:
83 When the perpetrator of the crime maintains or has maintained a partner relationship with the victim, whether matrimonial, de facto, free union, or any other equivalent relationship that involves or had involved cohabitation or not, including those in which there is or had been a sentimental relationship.
The private/public binary is also used to describe spheres of interaction that explain how or under what conditions femicide occurs. The private sphere refers to close relationships such as family while the public sphere involves less intimate relationships (Bunch 1990).
Three legislations, Chile, Costa Rica, and Venezuela, limit femicide to the violence in the private sphere by defining femicide as the killing of women by men who are their current or former intimate partners. However, seven countries explicitly acknowledge both public and private relationships within their legislation. Nicaragua’s legislation clearly states that the circumstances that define femicide can occur in either the private or public sphere. “The crime of femicide is committed by a man that, within the framework of unequal power relations between men and women, kills a woman whether in the public or private sphere, in any of the following circumstances…” Nicaragua is the only country that mentions both the public and private sphere in this way. However, the other six countries include provisions within the legislation that pertain to both spheres.
As explained above, one side of the binary is often more important than the other.
In two countries, Nicaragua and El Salvador, a crime committed in the private sphere is perceived as more serious by legislators and is considered an aggravating circumstance of the crime, accompanied by an increased penalty. For example, El Salvador’s legislation includes an increased penalty for femicide that occurred in the private sphere stating that an aggravating circumstance of femicide is “If the perpetrator enjoyed superiority over the victims based on their trust, friendship, domestic, school, or work relationship.” An
84 increased sentence length for violence that occurs in the private sphere illustrates a greater commitment to deterring this type of violence.
Body/Mind
Femicide is constructed in all countries as an offense against the body. Therefore, solutions, as defined by legislators, in all countries are concerned with protecting the physical body. Legislations prioritize the physical body, making body the more important concept in this binary. As such, many countries include classifications of femicide that involve acts of violence toward the physical body while relatively few countries have specifically addressed psychological violence within the legislation.
With respect to protecting the body, six countries include provisions that pertain to physical acts of violence by the same aggressor. In Mexico, provisions that relate to physical acts of violence include if the victim “shows signs of violence of any kind…” or if “the victim was inflicted with humiliating or degrading injuries or mutilations, before or after her life was taken, or acts of necrophilia.” In Honduras, the legislation dictates that homicide will be classified as femicide under four conditions including “When the crime is committed with ruthlessness or when humiliating or degrading injuries or mutilations have been inflicted, before or after the loss of life.” Several countries also name crimes of sexual violence as conditions that allow a homicide to be classified as a femicide. For example, in El Salvador, if a crime is committed against the “sexual liberty” of the victim prior to her homicide, then this killing can be classified as femicide.
Peru’s legislation includes rape as an aggravating circumstance of feminicide, increasing
85 the minimum penalty from 15 years to 25 years. These provisions acknowledge that femicide is often the result of repeated expressions of physical violence against women.
Conditions of femicide that explicitly involve the mind or psychological forms of violence are limited in comparison. Bolivia is the only country analyzed that explicitly mentions previous psychological harm as a condition of femicide, stating that a homicide can be classified as femicide under a number of conditions including “when prior to the killing, the woman had been the victim of physical, psychological, sexual, or economic violence committed by the same aggressor.” However, Mexico and Honduras include situations where the victim has been previously harassed by the perpetrator as a condition of femicide. For example, Mexico’s legislation declares that homicide can be classified as femicide when “There were prior threats related to the crime, harassment, or injury by the perpetrator against the victim…” while Honduras’ legislation states that homicide can be classified as femicide “When the crime is preceded by a situation of sexual violence, harassment or persecution of any kind…” However, three countries use general terms such as intra-familial violence or family violence that could include emotional or psychological abuse. These types of violence will be outlined in further detail below.
Key Concepts
Key concepts are words that have different meanings depending on who uses them. Disagreements over key concepts often stem from differing political perspectives, therefore, the meaning assigned to these concepts by legislators are relevant to our understanding of the problem (Bacchi 2009). The researcher, through a qualitative discourse analysis, identified concepts used in all or most of the sample, identified key
86 concepts. The concepts outlined below, femicide/feminicide and violence, were present in nine legislations analyzed.
Femicide
Femicide or feminicide is the most obvious example of the ambiguous labels described by Bacchi (2009). As reviewed in the theoretical framework (see Chapter three), the definition of femicide or feminicide varies depending on who is constructing the problem. Within the legislations analyzed, femicide was the most popular term used to define the killing of women. In fact, only four of the 13 femicide legislations opted for the term feminicide. El Salvador was the first country to legislate against feminicide in
2010 followed by Mexico, Bolivia, and Peru.
As mentioned above, all countries identify circumstances that, when they occur, change the classification of homicide to femicide. The reasoning behind the decision to use femicide or feminicide within the legislation is unclear, as countries with similar provisions have chosen different terms. For example, Panama’s femicide legislation and
Bolivia’s feminicide legislation were enacted the same year. These legislations contain the same provisions with the exception that Panama’s definition includes killing a woman in the presence of her children. As stated in previous chapters, the terms used by countries are not universal, as the definitions employed differ by state, academic, or non- governmental organization. There are, however, two notable differences between femicide and feminicide definitions. First, in contrast to the term femicide, all feminicide legislations include other relationships than those involving intimate partners such as the killing of a woman by a person who is a family member, friend, co-worker, or stranger.
87 Additionally, all feminicide legislations classify this violence as a crime distinct from homicide, while some femicide legislations limit femicide to a crime committed by intimate partners or as an aggravating circumstance of homicide. As discussed in the theoretical framework, the academic definition of feminicide acknowledges a political component of this crime. However, only two of the four countries, Mexico and El
Salvador, use the term feminicide recognize this political component as these feminicide legislations contain provisions regarding the impunity of public servants.
A country’s decision to use the term femicide over feminicide does not appear to effect mandatory sentence length. Imposed sentence length differs from country to country with most countries providing a range of years. Table 3 depicts the country definition used and sentence length. When averaging the minimum and maximum sentence length for each country, the average sentence length across seven femicide definitions was approximately 32 years. There does not appear to be a connection between the use of term femicide of feminicide and sentence length as the average sentence length for feminicide is 30.5 years. However, feminicide legislation in Mexico has the most severe sentence, with a minimum sentence of 40 years.
Three countries do not provide specific details about sentence length. The legislation in Argentina dictates that the punishment for femicide is “Life,” however, what constitutes life imprisonment in Argentina is unclear from the summaries analyzed.
Peru provides a mandatory minimum of fifteen years, which is one of the most lenient sentences, but does not specify a maximum penalty. Chile’s legislation states that femicide will be punished by “rigorous imprisonment,” but does not define what this
88 entails. Unclear sentencing mandates leave sentencing open to judicial discretion, which is a problem that will be discussed further in chapter seven.
Table 3. Country Sentence Length
Country Year Definition Sentence Length
Argentina 2012 Femicide Life
Bolivia 2013 Feminicide 30 years
Chile 2010 Femicide Unspecified
Colombia 2008 Femicide 33.3-50 years
Costa Rica 2007 Femicide 20-35 years
El Salvador 2010 Feminicide 20-35 years
Guatemala 2008 Femicide 20-50 years
Honduras 2013 Femicide 30-40 years
Nicaragua 2012 Femicide 15-20 years
Mexico 2012 Feminicide 40-60 years
Panama 2013 Femicide 25-30 years
Peru 2013 Feminicide 15+ years
Venezuela 2007 Femicide 28-30 years
Violence
Violence is another key concept used widely throughout femicide legislation.
Femicide, a type of violence, is preceded by other acts of violence. As discussed in previous chapters, violence is socially constructed; those in power determine what
89 constitutes violent acts. Seven countries include past violence against the victim as a reason to classify the killing of a woman as femicide. However, the constructions of violence differ across legislation, suggesting how legislators may perceive femicide when they provide detail on the circumstances or conditions that are believed to be a precursor of femicide.
Some countries do not describe the types of violence that can precede homicide that will lead to its classification of femicide. In countries that do not explain what they constitute as violence or what types of violence they consider, it is unclear whether this definition is referring only to physical acts (see Table 3 for country definitions of violence). For example, in Argentina, homicide can be classified as femicide if “the killing was perpetrated by a man involving gender-based violence”. Peru’s definition is one of the most limited because it restricts violence to “family violence” (Sarmiento et al.
2014: 153). Family violence or similar terms such as intra-familial violence are more restrictive definitions because these terms tend to prioritize the stability of the family unit over the health and safety of the victim (Ortiz-Barreda and Vives-Cases 2013). Bolivia’s definition of violence is perhaps the most inclusive because it classifies an act of homicide as femicide under several conditions including “when prior to the killing, the woman had been the victim of physical, psychological, sexual, or economic violence committed by the same aggressor” (Sarmiento et al. 2014:152). When assessing how countries describe violence, it becomes evident that they do not characterize violent acts against women in the same way.
90 Table 3. Country Definitions of Violence
Country Definition
Argentina Gender-based violence
Bolivia Physical, psychological, sexual, or economic violence.
Chile Does not define violence
Colombia Does not define violence
Costa Rica Does not define violence
El Salvador Does not define violence
Guatemala Does not define violence
Honduras Domestic or Intra-familial violence
Nicaragua Does not define violence
Mexico Violence of any kind
Panama Does not define violence
Peru Family Violence
Venezuela Does not define violence
People Categories
Bacchi (2009) argues that people categories are relevant to the understanding of problem constructions as they signify who is targeted by the legislation. People categories were extracted from the sample by coding all groups referred to in the legislation. Within this type of legislation, the most important people categories are those that separate people by gender. Within all legislations examined, femicide is considered a
91 gendered issue by legislators as the legislation uses gender to describe the group that is supposed to benefit from this legislation. In most cases, it can be inferred that legislation is designed to protect most women.
Women are specifically named as the beneficiaries of the legislation in 10 countries. For example, Panama’s legislation states: “the person that kills a woman in any of the following circumstances, will be punished with a sentence of 25-30 years in prison…” However, an exception to the inclusion of all women is legislations that define femicide as an act committed by a former or intimate partner. None of the legislations examined require that a woman is married to her perpetrator in order to classify it as femicide. However, some legislations required the perpetrator to have had a previous relationship with the victim. Therefore, women or children who have never been in a relationship are excluded from those legislations. For example, Venezuela’s legislation reads:
In the cases of intentional homicide in all its qualifications, classified in the Criminal Code, when the perpetrator of the crime set out in this Law is the spouse, ex-spouse, domestic partner, ex-domestic partner, person with whom the victim maintained a married life, stable union, or affective relationship, with or without cohabitation, the sentence to be imposed is between 28 and 30 years of prison (Sarmiento et al. 2014:151).
People categories are further defined in aggravating circumstances. Two countries
– El Salvador and Peru – include more specific people categories as aggravating circumstances of femicide. These categories increase the penalty of femicide and are considered more vulnerable groups including minorities, elderly, or pregnant women.
Aggravating circumstances will be discussed further in the subsequent question.
92 3. How has this representation of the problem come about?
The first objective of this question is to reflect on specific developments that contribute to problem constructions and developments of femicide. Within each country, femicide legislation has been the product of both regional and national contributions. The creation of femicide legislation is not solely a national exercise as all legislations analyzed were introduced within seven years of each other as a product of regional development. Older legislations tend to be more restrictive than those enacted more recently. For example, Chile and Venezuela have some of the oldest legislations in Latin
America and they define femicide as the murder of a woman that occurs between a current or former partner. The exception to this trend is the 2008 Guatemalan legislation, which is quite inclusive being the first of its kind to acknowledge power relations between men and women and set out specific provisions that permit the classification of femicide. The inclusivity of more recent legislations is thought to be, in part, a lesson learned from countries that have already legislated against femicide (Sarmiento et al.
2014).
Previous research has demonstrated that femicide does not occur under the same circumstances in every country (Alvazzi del Frate 2011). Though all femicides are rooted in gender inequality (Russell 2001; Fernandez 2012), the most prevalent type of femicide differs by country, suggesting the possibility that country-specific conditions may perpetuate certain types of femicide. Country-specific provisions are important to understanding the construction of femicide for two reasons. First, some countries have included articles within the legislation that appear to be specific to the country context of femicide. At the very least, these provisions are what legislators have identified as
93 relevant to the context of the country. Second, country provisions demonstrate how femicide legislation can differ across space.
Focusing on country-specific provisions addresses the second objective of
Bacchi’s (2009) third question, which is to acknowledge competing causal factors of the problem. Themes identified by a qualitative content analysis of femicide legislation summaries, whereby patterns and regularities in the data were recorded, are detailed below, including: (1) unequal power relations, (2) gang activity, (3) kidnapping and human trafficking, (4) impunity, and (5) other aggravating factors.
Unequal power relations
Four countries – Guatemala, El Salvador, Nicaragua, and Panama – have acknowledged unequal power relations between men and women as a contributor to femicide. This statement acknowledges that femicides are not individual crimes, but are connected to the social structural differences in power granted to men and women solely on the basis of their gender. The recognition of unequal power relations was the only root cause of femicide suggested within all the legislations analyzed. For example, Panama’s legislation includes a provision that states that homicide can be classified as femicide if a person kills a woman “for any motive based on her condition as a woman or in the context of unequal power relations.”
Gangs
Five countries have included provisions that apply to group activity. This problem representation also suggests that femicide is not always perceived as a crime that is committed by an individual person. Nicaragua is the only country that mentions gangs explicitly, stating that homicide can be classified as femicide when a man kills a
94 woman… “As a result of group rituals, of gangs, whether or not using weapons of any kind.” However, Guatemala, Bolivia, and El Salvador have included a provision that classifies the killing of a woman by more than one person or that is committed on a group dare as femicide. These provisions could also apply to femicides committed by one or more family members in the name of “honour.” The provision outlined in the femicide legislation of El Salvador differs from the others as it describes the killing of a woman by two or more persons as an aggravating circumstance and increases the minimum sentence length by 10 years.
Kidnapping and human trafficking
Seven countries have included circumstances where the victim was held against her will or in which another crime was committed against her prior to death. Mexico and
Panama have included an article relating to kidnapping; if the victim was kept
“incommunicado” or held against her will before her death, the crime would be considered femicide. Additionally, these states have included displaying the body of a victim in a public place as a crime of femicide Bolivia includes a killing that is
“connected to the crime of human trafficking or smuggling” as a circumstance before death that permits homicide to be classified as femicide.
Impunity
Three countries, Costa Rica, El Salvador, and Mexico have included a provision that is applicable, not to the perpetrator of the crime, but to those responsible for investigating or prosecuting femicide. These provisions threaten to punish any public
95 servant who impedes the investigation or prosecution of the crime of femicide. Costa
Rica’s legislation reads:
The person that, in the exercise of a public function, fosters, through an illicit means, the impunity or obstruction of the police, judicial, or administrative investigation of physical, sexual, psychological, or patrimonial violence, committed against a woman, will be punished with three months to three years in prison and disqualification from the exercise of any public service for one to four years…
In El Salvador, the legislation states…
The person that in the exercise of a public service fosters, promotes, or tolerates, impunity or obstruction of the investigation, prosecution, and punishment of the crimes established in this law, will be punished with 2-4 years in prison and disqualification from the public service that they provided for the same amount of time…
In Mexico, a public servant that:
Maliciously or negligently delays or impedes the pursuit or administration of justice will receive a sentence of 3-8 years in prison and 500-1500 days of fine, and in addition will be removed and disqualified for 3-10 years from holding any other public commission, position, or employment (Sarmiento et al. 2014:156).
Other aggravating factors
Lastly, four countries have included aggravating circumstances within the legislation that would increase sentence length. Aggravating factors are important as they suggest what legislators believe to be the most serious circumstances of femicide. Some of the aggravating factors have been discussed above, such as El Salvador’s gang involvement. El Salvador’s legislation also contains two additional aggravating circumstances, however, including “If the crime is committed in front of any family member of the victim…” and “When the victim is a minor, an elderly person, or has a physical or mental disability”. These provisions, which pertain to child witnesses and
96 other vulnerable groups, provide increased punishment, suggesting that these circumstances make the crime more severe. Similarly, Peru’s legislation contains seven aggravating factors, which include instances of increased vulnerability of the victim. For example, aggravating circumstances include: “The victim was a minor”… “The victim was pregnant”… “At the time the crime was committed, the victim had any type of disability.” In these circumstances, femicide is punished by no less than 25 years in prison with the possibility of life imprisonment when two or more aggravating factors are present. However, other states are more general when identifying aggravating factors.
For example, femicide legislation in Nicaragua does not outline specific instances that make femicide an aggravated crime, but states that if two or more of the circumstances outlined in the codification of femicide occur, then the sentence can be increased by one- third, up to 30 years. For example, if the perpetrator killed the victim after failing to re- establish a relationship and in the presence of the victim’s children, this would satisfy two conditions and would permit a longer sentence. In these instances, legislators are prescribing tougher sentences for acts of femicide that they believe may have been more callous.
Country-specific provisions of femicide shape the construction of the problem.
State provisions are shaped by conditions within the country or by legislator’s beliefs about conditions within the country and the construction of femicide as a social problem is shaped by these conditions.
97 4. What is left unproblematic in this problem representation? What are the silences? Can the problem be thought about differently?
The last question of the WPR approach is meant to explore how constructions could be reframed. Bacchi (2009) suggests that the analysis of binaries in the second question is particularly helpful in responding to this question because it illustrates the polarization of issues within legislations. In this case, one of the most obvious silences occurs in the private-versus-public sphere dichotomy within three countries’ legislations.
Countries with more limited definitions of femicide fail to problematize other circumstances under which women are killed. The most limited definitions are those that classify femicide as a crime specific to intimate partner relationships. This silence is interesting as governments are usually more hesitant to interfere in the private sphere, especially on spousal matters (Bacchi 2009). Traditionally, domestic violence, particularly in Latin America, was presumed to be an issue between a husband and wife.
However, Chile, Costa Rica, and Venezuela, only address the private sphere. This problem representation suggests that femicide is an issue that takes place in the private sphere and is one that requires state intervention.
Legislations that do not classify femicide as a separate crime, but rather as an aggravating condition of homicide are also more limited in their definition. Classifying femicide as an aggravated circumstance of homicide portrays femicide and homicide as being the same or similar social problems. This construction is problematic because femicide and homicide often occur under different circumstances. These definitions fail to acknowledge the specific conditions, primarily unequal power relations between men and women, which incites this violence.
98 Within all legislations analyzed, the crime of killing a woman is classified as a homicide unless the conditions set out in the legislation are met. Conditions that are particularly vague or may be difficult to prove may prevent femicides from being classified as such. For example, the classification of femicide in Colombia as “killing a woman because she is a woman…” could be difficult to prove when the legislation does not outline what is involved in the killing of a woman because she is a woman. In contrast, El Salvador’s provision clearly outlines five provisions that allow homicide to be classified as femicide including “the killing was preceded by an incident of violence committed by the perpetrator against the woman, regardless of whether the victim had reported the act…” This provision provides greater protection than those previously mentioned as it acknowledges the relevance of both reported and unreported violence.
Three legislations, Guatemala, Nicaragua, and Panama, contain controversial language related to the actions of perpetrators. Language was determined as controversial by the researcher during the content analysis, with the help of previous literature. These legislations use the exact same phrasing to describe a provision of femicide which states that homicide can be classified as femicide in several circumstances, including if the body of the victim was disrespected “to satisfy sexual instincts” (Sarmiento et al. 2014:
148). This provision is an interesting construction because, at the outset, it appears to be synonymous with the sexual classification of El Salvador, whereby if a crime is committed against the “sexual liberty” of the victim prior to her homicide, it is considered femicide. However, the word ‘instinct’ implies a mindset, one that is biologically or socially predisposed. This phrasing may suggest that men are predisposed to have urges that result in the sexual assault of a woman leading up to her death. This
99 type of language could mitigate responsibility. As violence against women legislation in
Latin America has in the past reduced the responsibility of males under certain conditions
(Perez-Cotapos 2012), the language of the legislation must clearly establish responsibility
(Ortiz-Barreda and Vives-Cases 2013).
Summary
The WPR method can seem to over-simplify viewpoints by suggesting that well- defined distinctions exist when, in fact, boundaries are more obscure, however, this approach condones oversimplification as a strategy (Bacchi 2009). This study of problematizations provides a method to unpack the constructions of femicide and to examine how countries in Latin America are governed based on these constructions.
In response to the research question of whether the recognition of femicide as a social problem shapes the response to this violence, some preliminary conclusions can be drawn. Overall, this analysis suggests that the recognition of femicide as a social problem has been shaped by country and regional contexts. Constructions of femicide within legislation differ across time and space. The process of defining this violence is related to the societal contexts under which this violence occurs because how this problem is defined depends on what policy-makers view as conditions of femicide. However, the responses to this violence do not differ significantly based on the definition of the problem because sentences are similar for both femicide and feminicide, regardless of their construction. Many of these themes will be discussed further in chapter seven.
Results of the qualitative analysis were used to inform the quantitative analysis in the following section. As the constructions outlined above may have an impact on how
100 successful governments are in reducing the rate of female homicide in Latin America, if one construction of femicide proves particularly successful, this may be cause for reform in other countries.
101 CHAPTER SIX – QUANTITATIVE RESULTS
This chapter will focus on the quantitative findings of this research. The following section examines non-parametric paired t-tests3, non-parametric independent t-tests, and descriptive statistics. This section will focus first on all results related to the primary research question: Have the responses to femicide reduced female homicide rates in Latin
America? Following this, the results of additional macro-level variables that may influence female homicide rates and femicide legislation will be reviewed.
Bivariate Analysis – Femicide legislation
A statistically significant relationship between the existence of femicide legislation and female homicide rate was not evident for many Latin American countries in the Spearman’s rho correlation. In fact, a relationship between these two variables was found only in Colombia where the bivariate analysis revealed a negative statistically significant association between femicide legislation enactment and female homicide rates. A negative relationship suggests that as femicide legislation is introduced, female homicide rates decreased. Findings from the bivariate analyses that include other macro- level factors will be discussed towards the end of the chapter. The next section will outline the results from the Wilcoxon-signed rank test, highlighting statistically significant findings before and after the implementation of legislation for (1) female
3 While non-parametric versions were the most appropriate choice given the characteristics of the data, with non-parametric tests, some information is lost. Non- parametric tests can increase the type-two error, meaning that it may illustrate that no relationship exists, when there is, in fact, a relationship (Field 2009). A Wilcoxon signed- rank test typically has approximately 90 percent of the power that a parametric t-test has with no assumptions violated (Cohen and Lea 2004).
102 homicide rate, (2) male homicide rate, (3) intimate partner femicide rate, and (4) femicide rate.
Before and After Legislation Enactment
The Wilcoxon signed-rank test analyzes homicide rates before and after the introduction of legislation to determine whether femicide legislation has an impact on reducing female homicide rates in Latin America. This analysis presents three critical pieces of information, the mean pre-test score, the mean post-test score and the p-value
(Knapp 2013). The p-value signifies whether the difference between the two means of homicide rates is due to more than chance. Within each test, two means were calculated for every country analyzed, one before the legislation was enacted and one afterward.
The null hypothesis for the Wilcoxon signed-rank test is that the difference between the dependent variable before and after the introduction of legislation is zero. In other words, the null hypothesis implies that there is no difference between the two groups. If the independent variable had a statistically significant impact on the dependent variable a difference in the two means would be present.
Female homicide rate:
A mean was calculated for female homicide rates before and after the introduction of legislation for all countries with sufficient data (N=5). As this analysis attempts to determine whether femicide legislation is reducing rates of female homicide, it is important that countries have data collected for multiple years before and after the introduction of legislation. Costa Rica, Colombia, Chile, Venezuela, and Guatemala were included. The results of each of the five countries will be discussed in detail. Figure 3
103 represents female homicide rates in Costa Rica, the only country with a statically significant result between the variables mentioned above, illustrating all available data on female homicide rates between the years 1997-2014.
The female homicide rate in Costa Rica is comparable to western countries, slightly higher than Canada’s, but slightly lower than the United States’ (PAHO 2014).
Female homicide rates in 1997 in Costa Rica are relatively low, with a rate of 1.1 per
100,00 of the population. However, after 1997 homicide rates begin to rise
In 2007, the year of Costa Rica’s legislation enactment, there is a dramatic decline in female homicide rates. The Wilcoxon-signed rank, which calculated mean homicide rates for all years prior to and following the introduction of legislation, found a statistically significant relationship for Costa Rica, with a p-value of .028. This finding signifies that a difference was found between mean female homicide rates before and after the introduction of legislation.
Figure 3 Costa Rica Female Homicide Rates
104 In 1997, Chile had the lowest female homicide rate of the countries analyzed with a rate of 0.6. This rate is even lower than Canada’s, which was 0.8 that year. One of the highest female homicides rates occurred in 2010, 1.3 per 100, 000 inhabitants, the year of femicide legislation enactment. Since then, there has been a decline in the rates of female homicide, however, there were not enough data on the rate of female homicide after the enactment of legislation to determine whether or not this is simply a fluctuation that will be superseded by another rise in rates. No statistically significant relationship was found between the mean homicide rates before and after the introduction of legislation, supporting the null hypothesis.
Of all countries with data available for the year 1997, Colombia had the highest rate of female homicide with a rate of 10.9 per 100,000 inhabitants. Female homicides in
Colombia peaked in 2002 with a rate of 13.9. After 2002, homicide rates declined, though remaining much higher than Chile or Costa Rica. In 2009, the year after the introduction of legislation, female homicides rose again to a rate of 9.0 per 100, 000 inhabitants. In
Colombia a statistically significant in difference mean homicide rates before and after the introduction of legislation was not found, supporting the null hypothesis.
Female homicide rates were not disaggregated by sex until 2005 in Guatemala.
Homicide rates in Guatemala increase steadily from 2005 to 2009. The highest female homicide rate was recorded in 2009 with a measure of 11.3 per 100, 000 inhabitants, occurring two years after the implementation of femicide legislation. Since 2009, there appears to be a downward trend in female homicide rates. However, no statistically significant relationship was found between the mean homicide rates before and after the introduction of legislation, retaining the null hypothesis.
105 Venezuela’s lowest female homicide rate occurred in 1997 with a rate of 2.3 per
100,000 inhabitants. Homicide rates increased steadily until 2002, with a peak homicide rate of 5.5 per 100, 000 inhabitants. After this time female homicide rates began to decline, however, rates in 2009 remain much higher than rates in 1997. In Venezuela, a statistically significant difference in mean homicide rates before and after the introduction of legislation was not found, retaining the null hypothesis.
The results of this analysis signify that there is no statistically significant relationship between the enactment of legislation and female homicide rates in four of the five countries analyzed. In all countries, except for Costa Rica, the null hypothesis was retained.
Male homicide rate:
This analysis examined male homicide rates before and after the introduction of femicide legislation to test whether potential differences in female homicide rates are the product of a national trend rather than the result of femicide legislation. Means were calculated for male homicide rates before and after the implementation of legislation for countries with a sufficient amount of data (N=5), Costa Rica Colombia, Chile,
Venezuela, and Guatemala. In contrast to female homicide rates, which recorded one significant result, two of five countries, Colombia and Costa Rica, showed a positive statistically significant relationship between the rate of male homicide and the inception of femicide legislation. A positive correlation signifies that there were statistically significant changes in male homicide rates after the introduction of femicide legislation.
This finding is significant as the legislation is tailored specifically to protect women. For
106 Colombia, this analysis recorded a value of .043, while a value of .018 was recorded for
Costa Rica, safely rejecting the null hypothesis.
Intimate partner femicide rate:
This analysis examined intimate partner femicide rate before and after the inception of legislation to explore whether femicide legislation appeared to reduce the rate of intimate partner femicide. Four countries (N=4) Costa Rica, Colombia, Chile, and
Nicaragua, contained enough data for this analysis. Of these four countries, two of them,
Chile and Costa Rica, have introduced femicide legislation that pertains only to intimate partner femicide. However, the results of this analysis revealed that there was no relationship between intimate partner femicide rate and the introduction of femicide legislation. Out of the four countries analyzed, none exhibited a statistically significant association and the null hypothesis was retained.
Femicide rate:
Unlike female homicide rate, which measures the murder of all women by the percentage of 100, 000 habitants, femicide rate measures the rate of femicide as defined by that country, by the percentage of 100, 000 women. Only one country (N=1),
Nicaragua, was included in this analysis as no other country had collected enough data on the dependent variable, femicide rate, before and after the inception of legislation to allow for analysis. The mean femicide rate before and after the introduction of legislation was calculated. This analysis revealed no statistically significant relationship between femicide rate and the introduction of legislation. Thus, the null hypothesis was retained.
In all Wilcoxon signed rank tests, across three dependent variables, female homicide rate, intimate partner femicide rate, and femicide rate, only one statistically
107 significant relationship was found. Costa Rica was the only country for which the analysis revealed a statistically significant difference of homicide rates before and after legislation. This finding will be discussed in more detail in the following chapter.
Countries With and Without Legislation
The Mann-Whitney test, a non-parametric test, is used to test two independent groups on one dependent variable (Lee 2014). This test was chosen to assess whether there was a statistically significant relationship in female homicide rates between two groups, countries with legislation and countries without legislation (see Appendix E for a list of countries in each group). If femicide legislation was contributing to a reduction in female homicide rates, it was hypothesized that there would be a statistically significant difference in the mean female homicide rate for the two groups. The null hypothesis was that the mean female homicide rate was the same across countries with and without legislation. This null hypothesis was retained as the results of Mann-Whitney test revealed that there was no statistically significant difference between countries with or without femicide legislation. This finding suggests that having femicide legislation does not appear to impact female homicide rates across the region.
As the most prevalent type of femicide differs by country, country-specific conditions may perpetuate certain types of femicide. While it appears that femicide legislation has not had a significant effect on female homicide rates across the region, there are a number of economic and social factors that may impact female homicide rates.
Additionally, there are various factors that could impact the introduction of legislation.
108 Several other macro-level variables were included to examine other possible contributors to femicide and femicide legislation.
Bivariate Analyses
These analyses highlight correlations between female homicide rates and various social, economic, and political variables, including the key focal variable of femicide legislation. Using the Spearman’s rho correlation measure4, the analyses examined whether there were any preliminary correlations between female homicide rates, legislation, and other country variables as previously discussed.
Within the bivariate analysis, many of the independent variables tested revealed a significant relationship with the dependent variable, female homicide rate. These variables include: male homicide rate, GDP per capita, Gini coefficient, employment to population ratio, precarious employment, female judges, and female members of parliament. Several variables also revealed significant relationships with femicide legislation including GDP, employment and precarious employment of male and females, supreme court judges, and the percentage of females in national parliament. Each of the independent variables that highlight a significant relationship in at least one country will
4 Similar to Person’s R, Spearman’s rho tests for the probability of a null hypothesis (Gorard 2004). If the probability is very low, a null hypothesis can be safely rejected. The most common measure used is 5% or 0.05, which means that there is a 95% chance that the null hypothesis can be safely rejected (Field 2009). Spearman’s rho provides an indication of the direction and strength of the relationship through the value of R. R is measured on a scale between -1 and +1. A value of zero suggests that there is no relationship at all while a +1 suggests a positive relationship whereby when one variable increases the other also increases. On the otherhand, a -1, however, suggests a negative relationship, which whereby when one variable increases, the other decreases (Gorard 2004).
109 be reviewed below with respect to their relationship with female homicide rate and femicide legislation. Table 4 depicts relationships between macro-level factors on female homicide rates while Table 5 outlines all relationships between macro-level factors and legislation.
VAW legislation
Spearman’s rho was not able to measure the relationship between VAW legislation and female homicide rates in many countries as a result of the characteristics of the data. In order to conduct bivariate correlations on dichotomous variables, a variation in the data is required. For example, if all of the data points are 0, whether a relationship between the two variables exists cannot be determined. In this case, many of the countries that had VAW legislation implemented this legislation in the 1990s, meaning that these countries had VAW legislation for the entire length of time examined.
Similarly, some countries do not have VAW legislation and have never had this legislation. These two scenarios result in no variation because the data for these countries would be all 0=no or all 1=yes5. Thus, this correlation could only assess countries that had implemented VAW more recently. Of the countries examined, one country,
Paraguay, had a relationship between the VAW legislation and female homicide rates.
This relationship was a negative relationship, which suggests that a decrease in female homicide rates was influenced by the introduction of VAW legislation.
5 A similar situation occurred with the variable Armed Conflict. As many countries that have had armed conflict have had conflict that spans several years (Such as El Salvador and Colombia). Similarly, many countries that are not in conflict have had times of peace for several years. Armed conflict is not included in this discussion as no statistically significant relationships were found in the countries that could be measured.
110
Intimate partner femicide (IPF) rate
A positive statistically significant relationship was found between intimate partner femicide and female homicide rate only for Costa Rica. This correlation implies that when intimate partner femicides increase, female homicide rates also increase.
No relationship was found for Chile, Colombia, Nicaragua, Dominican Republic, Peru, and Paraguay. More statistically significant relationships were expected, as the rate female homicide should include intimate partner femicide rates.
Positive and negative correlations were also found between intimate partner femicide rate as a dependent variable, and femicide legislation enactment, the key independent variable. Spearman’s rho highlighted a positive statistically significant relationship between intimate partner femicide and femicide legislation for Nicaragua.
This suggests that intimate partner femicides have increased with the introduction of femicide legislation. A negative statistically correlation between intimate partner femicide and femicide legislation was found for Chile and Peru. These relationships suggest that intimate partner femicides may have decreased with the introduction of femicide legislation.
Femicide rate
A positive statistically significant relationship was found between female homicide rate and femicide rate for Costa Rica and the Dominican Republic. This correlation suggests that when femicide rates increase, female homicide rates also increase. No relationship was found for Colombia, Nicaragua, and Peru. Similar to the
111 variable intimate partner femicide, positive statistically significant relationships were expected as female homicide rates are supposed to include femicide rates.
112 Table 4. Directions of Relationships: Macro-level Variables and Female Homicide Rates
Costa Dominican El Argentina Belize Brazil Chile Colombia Rica Cuba Republic Ecuador Salvador Guatemala Mexico Nicaragua Panama Paraguay Peru Venezuela - Femicide Legislation
VAW - Legislation
IPF rate +
Femicide rate + +
Male + + + + + + + + + + + + + + Homicide GDP per - + - + + + + + capita -
Gini + - - - -
Employ Males . - + + -
Employ + + + + + + - + Females Male + - Precarious Employment
Female + + Precarious Employment Female + + + - + + - National Parliament
113 Female Judges + + - + + + - -
114 As a dependent variable, Spearman’s rho highlights several statistically significant correlations between the rate of femicide and the enactment of femicide legislation. A highly statistically significant positive relationship was found between the rate of femicide and the enactment of femicide legislation in Nicaragua. This correlation suggests that femicide rates have increased with the introduction of femicide legislation.
An explanation for an increase of femicide rates after the introduction of legislation will be provided in the subsequent chapter. A negative statistically significant correlation was found between femicide rate and the introduction of femicide legislation for Peru. A negative relationship suggests that femicide rates have decreased with the introduction of femicide legislation.
Male homicide rate
The most common statistically significant relationship with female homicide rate across all countries was male homicide rate, with 16 of the 24 countries included having a significant positive relationship between male homicide rate and female homicide rate.
A positive association suggests that when male homicide rates increase, female homicide rates also increase. The countries that indicated that there was no association between these two variables were Belize, Paraguay, Suriname, Uruguay, Jamaica, Dominica,
Bahamas, Barbados, and Saint Lucia.
GDP per capita
GDP per capita had a statistically significant relationship with female homicide rates in several Latin America countries. A positive correlation was found for Costa Rica,
Dominican Republic, Ecuador, El Salvador, and Panama. This relationship suggests that when GDP per capita increases, female homicide rates increase. A negative relationship
115 was found for Argentina, Colombia, and Cuba. This relationship suggests that when GDP per capita increases, female homicide rates decrease.
Gini coefficient
A positive statistically significant association was found only for Argentina. This relationship suggests that when Gini increases or more inequality is present, female homicide rates also increase. A negative statistically relationship was found for Panama,
El Salvador, and the Dominican Republic. This relationship indicates that lower levels of inequality may be related to higher female homicide rates.
Employment
Both male and female employment rates were significantly correlated with the dependent variable, female homicide rates. As it relates to male employment and female homicide rates, a positive statistically significant relationship was found for Argentina, El
Salvador, and Panama. A positive association suggests that when male employment increases, female homicide rates also increase. A negative statistically significant relationship was found for Colombia and Paraguay. A negative association suggests that when male employment rates increase, female homicide rates decrease.
A positive statistically significant relationship between female employment and female homicide rates was found for Costa Rica, Dominican Republic, El Salvador,
Ecuador, Venezuela, and Panama. A positive relationship suggests that when female employment increases so too does female homicide rates. Paraguay was the only country that yielded a negative statistically significant correlation between female employment and female homicide rates. This relationship suggests that as female employment increases, female homicide rates decrease. Interestingly, only two countries showed
116 statistically significant results for the employment of both genders. Negative correlations were found in Paraguay between female homicide for both male and female employment.
In Panama, this analysis revealed positive relationships for both male and female employment. These relationships suggest that in Paraguay and Panama, female homicide rates are influenced by both male and female employment.
Several statistically significant correlations were found between the employment of both males and females with femicide legislation. Positive correlations were found between female employment and femicide legislation for Chile, El Salvador, Mexico,
Panama, and Venezuela. This finding suggests that the introduction of femicide legislation increases with the rate of female employment. Only Guatemala displayed a significant negative correlation between female employment and femicide legislation.
This correlation suggests that femicide legislation is introduced when female employment decreases. Concerning male employment and femicide legislation, positive correlations were found for Chile and Colombia, suggesting the introduction of femicide legislation is associated with an increase in male employment. Negative correlations were found for
Guatemala and Mexico, which suggests that femicide legislation is introduced when male employment decreases.
Precarious employment
Statistically significant associations were found for both male and female precarious employment, though no country had a statistically significant variable for both measures. Spearman’s rho highlighted that in Argentina there was a positive statistically significant relationship between female homicide rate and male precarious employment.
This correlation suggests that when male precarious employment increases, female
117 homicide rates also increase. In Costa Rica, however, a negative statistically significant relationship was shown between the same two variables. The direction of this relationship suggests that as male precarious employment increases, female homicide rates decrease.
As it relates to precarious female employment, Spearman’s rho highlighted a statistically significant positive relationship for Ecuador and Panama. This relationship suggests that when the percentage of women working in precarious employment increase, female homicide rates also increase.
Female judges
A positive statistically significant relationship was found for several Latin
American countries between female judges and female homicide rate. Spearman’s rho highlighted positive correlations between these two variables for Brazil, Costa Rica, and
El Salvador. The direction of this relationship suggests a higher number of female judges may increase female homicide rates. For Argentina, Colombia, Panama, and Paraguay negative relationships were found between the percentage of female judges and female homicide rates. A negative correlation suggests that when the percentage of female judges increases, the rate of female homicides decreases. Interestingly, a relationship was also found between female judges and femicide legislation. For Costa Rica, Chile,
Colombia, El Salvador, and Venezuela, significant positive relationships were found between the percentage of female supreme court judges and femicide legislation. A positive relationship suggests that the enactment of femicide legislation is influenced by an increase in female judges.
118 Table 5. Directions of Relationships: Macro-level Variables and Femicide Legislation
Argentina Chile Colombia Costa El Salvador Guatemala Mexico Nicaragua Panama Peru Venezuela Rica Female Homicide Rate -
IPF rate - + -
Femicide rate + -
Male Homicide Rate - + +
GDP per capita + + + + + + + + + + Gini - - - - Employment Males + + + - -
Employment Females + + + - + + +
Male + - - Precarious Employment
Female - + - - Precarious Employment Female National Parliament + + + + +
Female Judges + + + + - + +
119 Female seats in national parliament
Both positive and negative correlations were found between female seats in national parliament and female homicide rates. Positive statistically significant correlations between the two variables were found for Chile, Costa Rica, and El Salvador.
A positive relationship suggests that when females gain more seats in national parliament, female homicide rates increase. Meanwhile, a negative statistically significant relationship was found for Belize, Paraguay, and Cuba. The direction of this correlation suggests that when females gain more seats in national parliament, female homicide rates decrease. Similar to the other measure of gender inequality, female judges, relationships were found between the percentage of women in national parliament and femicide legislation. For Costa Rica, El Salvador, Mexico, Nicaragua, and Venezuela, significant positive correlations were found between the percentage of women in national parliament and the introduction of femicide legislation. A positive association suggests that the introduction of femicide legislation is influenced by an increase in the number of women in parliament.
Summary
These findings present an overview of female homicides, femicide legislation, and related variables in Latin America. The findings of the quantitative research suggest that femicide legislation in its current state does significantly impact the rate of femicide across the region. No significant difference in female homicide rates was found between countries with or without legislation. In the bivariate analysis, only Colombia displayed a statistically significant relationship between the two primary variables. Furthermore, with
120 the exception of only one country, Costa Rica, the enactment of femicide legislation appeared to have no impact on the rate of female homicide or related variables. However, this research found multiple factors within each country that may have an influence on female homicide rates and femicide legislation. These factors differ from country to country but include male homicide rates, both employment and precarious employment, female seats in national parliament and female judges.
CONCLUSION
This chapter featured the quantitative findings of this research, reporting the statistically significant results that impact female homicide rates and femicide legislation in Latin American countries. The significance of these results and the qualitative findings in accordance with the literature and theoretical framework will be discussed in the following chapter.
121 CHAPTER SEVEN - DISCUSSION AND CONCLUSION
The primary objective of this research was to examine how femicide has been constructed as a social problem in Latin America through legislation enactment and assess the impact of these constructions on the incidence of femicide. Additionally, this research aimed to contribute to the discussion of whether or not other factors may lessen or intensify the rate at which women are killed in Latin America or effect the development of legislation.
Based on the results of the qualitative and quantitative analysis, this research makes the following conclusions. First, the constructions of femicide differ from country to country and are shaped by country-specific circumstances. Second, femicide laws in
Latin America, in their current capacity, do not appear to significantly reduce female homicide rates in Latin America. Lastly, there are a variety of other forces that have the potential to impact female homicide rates and femicide legislation, but these forces may not have the same impact in each country. In this final chapter, the relevance of these findings with respect to theoretical considerations and prior literature are discussed.
This section will first outline constructions of femicide legislation in Latin
America, focusing on the strengths or weaknesses of particular legislation. Next, aspects of the legislation that appear, based on the literature, to have been influenced by claims- makers will be summarized. This chapter will then provide explanations for differing constructions of femicide before discussing the effectiveness, or lack thereof, of legislation in Latin America. A discussion on other factors that may be influencing female homicide rates and femicide legislation in the region will follow. Lastly, this
122 chapter will review policy implications and conclude with the limitations of the study and directions for future research.
Femicide Constructions in Latin America
Definitions of femicide and feminicide differ across nations and among claims- makers. The more general term femicide is more commonly used, though feminicide has gained popularity more recently. Governments that use the term feminicide, do not use it to imply impunity or take responsibility for failing to punish or prosecute a woman as described by Sanford (2008) and Fregoso and Bejarno (2010). The definitions of femicide and feminicide used by governments are not consistent with definitions used by academics.
Russell’s (2001) definition of femicide describes femicide as the killing of a woman by a man; within all of the legislation analyzed, women are named as the victims of this crime. However, perpetrators of the offense have been defined in different ways, with some governments straying from Russell’s (2001) definition of perpetrators as a man. As found in previous literature, there appears to be a trend in femicide legislation as newer laws are more inclusive in their definition of femicide than their predecessors
(Sarmiento et al. 2014). For example, Venezuela’s (2007) legislation pertains only to intimate or former partners, while Bolivia’s (2013) legislation includes multiple relationships including intimate partners, friendships, work acquaintances or relationships of subordination. This pattern also applied to the definition of the offender as some of the oldest legislation defined perpetrators as intimate partners, while the newest legislation simply defined perpetrators as a “person”. This could be an important development in
123 femicide legislation, acknowledging that women can be perpetrators of femicide. While men most often kill women, research suggests that women sometimes kill women and reinforce pre-existing gender norms linked to the patriarchy (Shalhoub-Kevorkian 2002).
An example of this would be a woman killing her daughter for disrespecting the family’s honour (Mayblin 2011; Shalhoub-Kevorkian 2002). However, legislations could also name the aggressor within the legislation as a ‘person’ to deemphasize the gendered component of this crime and the role of men as perpetrators. As newer legislations tend to be more advanced in their characterization of femicide, it is believed that this development is meant to include diverse relationships. However, as stated in chapter five, the true intent of legislations is unknown.
Femicide legislation as an aggravating circumstance of homicide or parricide is less progressive than legislation that has characterized femicide as a distinct crime because it does not attempt to challenge, or challenges to a lesser degree, existing gender norms. According to Htun and Weldon (2012), VAW policies, such as femicide legislation, are a progressive form of social policy as they attempt to shift values and improve the status of women. Fregoso and Bejarano (2010) argue that characterizing femicide as an aggravating circumstance of homicide, as four countries in Latin America have done, is problematic because treating femicide as a gendered homicide is evasive and neglects to acknowledge the power differences between men and women that make women more vulnerable to violence.
Two countries do not specify precise sentence lengths within their legislation.
Unclear sentence lengths and judicial discretion are problematic in crimes against women as gender inequality is a deeply rooted societal norm. As discussed in the theoretical
124 framework (see chapter three for the theoretical framework) Latin America is entrenched in the culture of machismo, which has traditionally been reflected in legislation and criminal justice practices (Speiler 2011). Femicide legislation is a policy that attempts to shift societal norms, however, no minimum sentence length leaves the legislation with less substance to affect change.
Each country includes different provisions under which a homicide can be classified as a femicide. However, many nations have added classifications of femicide or feminicide that are unique to the crime as it occurs in that country. For example, three states have included gang activity as a precursor of femicide. Additionally, many laws focus primarily on the physical consequences of violence and only Bolivia’s legislation provides a comprehensive description of psychological violence as a condition of femicide. This classification of psychological harm as a precursor to femicide is significant as it acknowledges that physical abuse is not the only type of violence that can precede femicide. It has been well documented that there are many different types of violence on the continuum of violence against women, including, but not limited to, physical acts of violence (Cockburn 2004; Stout 1992). Violence against women serves as an attempt by men to control women through many different forms of violence including leering, catcalls, verbal and physical abuse such as coercive control (Anderson
2009; Osborne 1995). By acknowledging emotional and psychological violence against women, governments recognize that there are multiple acts on the continuum of violence that women may experience before their deaths.
125 Success of claims-makers
Women’s groups in Latin America appear to have been successful in having femicide recognized as a social problem throughout the region. The level of this achievement varies from country to country, but can be displayed through various provisions of legislation including criminal sanctions, increased penalties for domestic crimes, and acknowledging the underlying causes of femicide. First, the characterization of femicide within criminal law, instead of family law or civil law, as VAW legislation has been characterized in the past in Latin America, implies great seriousness. If this crime were added to civil or family codes, the amendment would not carry the same weight. For example, in Chile, from 1994-2005, VAW legislation was considered a civil law provision, not a criminal offense and as a result, many rulings on VAW during this time were accompanied by a reduced penalty (Perez-Cotapos 2012). The classification of femicide as a criminal code provision can be considered a victory for women’s groups in
Latin America as they have fought to have violence against women viewed, not as a family matter, but as a criminal offense.
The deterrence of private sphere violence can also be considered a victory for claims-makers. Many countries now purposefully recognize violence that occurs in both public and private domains. Bacchi (2009) argues that within each binary one half is more important than the other. Several legislations such as those in Venezuela, Chile, and
Costa Rica, are only concerned with violence in the private sphere, in contrast to its treatment historically. Nicaragua’s femicide law, which recognizes violence in both public and private spheres, has placed an increased penalty on violence that occurs in the private sphere. This characterization is significant because it demonstrates a commitment
126 by the state to deter this type of violence. In the past, governments have been hesitant to legislate against violence that occurs in the home or between intimate partners (Comas-
D’Argemir 2014; Fried 2003). As women’s groups have fought to have violence that happens in the private sphere considered a public issue, Nicaragua’s commitment to deterring violence in the private sphere demonstrates another success of this movement.
Countries such as Guatemala, El Salvador, Nicaragua, and Panama, define the underlying cause of femicide as the unequal power relations between men and women.
Based on the literature, other constructions this study expected to find include references to patriarchy and machismo values. As these concepts reinforce gender inequality, and men’s superiority over women, this often leads to the acceptance of violence against women when they stray from what is considered acceptable behaviour for a woman
(Russell 2001; Wilson 2014; Wright 2011). Economic inequality and the North American
Free-Trade Agreement (NAFTA) were additional explanations of femicide expected, as traditionally men have been providers of economic resources (Pantaleo 2010). Through the process of globalization, more women have entered the workforce, which may threaten men causing them to lash out (Pantaleo 2010; Russell 2001). However, the recognition of unequal power relations was the only identified cause of femicide within the legislations analyzed which is consistent with feminist constructions that advocate that there is a root cause, primarily the oppression of women by men, that links all femicides. The acknowledgement of femicide as a crime grounded on the inequality between men and women addresses the root of this problem. Thus, under the definition of progressive social policies, as described by Htun and Weldon (2012), these social policies could be considered the most progressive as they attempt to shift normative values
127 through acknowledging the underlying cause of femicide. The acknowledgment, found in
Guatemala, El Salvador, Nicaragua, and Panama, demonstrates the success of particular claims-makers within these countries.
Countries that characterize femicide as an aggravating circumstance of homicide or parricide do not acknowledge unequal power relations and remain limited in their characterizations of femicide. In these countries, feminist groups may have been successful in getting femicide recognized as a social problem, but the root of this social problem, as defined by feminists, remains untouched. Until the unequal power relations faced by women are addressed, women will continue to face oppression and violence.
Criminal justice measures are an important tool in protecting women, but the elimination of femicide requires a shift in normative values. The difficulties of altering these values will be discussed in more detail when examining the policy implications of this research.
A condition that is particularly relevant to the results of this research is the responsibility three countries have placed on their public servants to prevent and punish femicide. Recall in previous chapters, some countries in Latin America have been criticized for having a culture of impunity (Fregoso 2006; Sanford 2008). Impunity or failure to respond pertains to crime more generally, but responses are particularly ineffective when the victims are women (Briceño-Leon et al. 2008; Hernandez 2002).
Costa Rica, El Salvador, and Mexico have included provisions that allow for the prosecution of civil servants who fail to investigate femicides. Additionally, El
Salvador’s legislation includes an increased penalty for public servants or other persons in authoritative positions who are perpetrators of femicide. Ending impunity is a necessary step in reducing femicide; provisions that legislate against impunity are
128 important as they acknowledge and attempt to diminish the problem. This commitment may be an attempt by countries to quell the criticisms of impunity and, thus, the inclusion of this provision could be considered a notable achievement for claims-makers.
Explanations for Differing Constructions
The failure to problematize certain conditions of femicide could occur for a variety of reasons. First, as examined in the literature, different types of femicide are more common in particular countries (Alvazzi del Frate 2011). Therefore, the problem as defined in the legislation could be an effort to prioritize the most common types of femicide. Additionally, constructions of femicide could be the result of the effectiveness or ineffectiveness of claims-makers within each country. The potential successes of women’s groups in claims-making processes have been outlined above; however, this does not mean that claims-makers are always successful. Spector and Kitsuse (1977) acknowledge that many social problems do not make it past initial stages. While femicide is a social problem that has received much support on national and international levels, the limitations of legislation, primarily the resistance to acknowledge the root causes of femicide, demonstrate a lack of success of claims-makers in some areas.
Lastly, differing constructions of femicide legislation in Latin America could be the result of countries learning from the shortcomings of previous legislations. Femicide legislation in Latin America was the product of national and regional development
(Prieto-Carrón et al. 2007). The first legislation implemented had no guidance from other countries on how to best address the problem. As legislation against this phenomenon,
129 particularly in Latin America, has only begun recently, states implementing legislation later benefited from the lessons learned from legislations implemented beforehand.
Do Constructions of Femicide make a Difference?
Findings highlighted both negative and positive relationships between femicide legislation and female homicide rate and other country-level factors. However, this research found little empirical support to suggest that femicide legislation in Latin
America is serving its intended purpose of reducing female homicide rates. Between the primary dependent and independent variable, female homicide rate, and femicide legislation, only three significant relationships were found - for Colombia, Peru, and
Costa Rica, which are discussed in more detail below.
A negative correlation was found between femicide legislation and female homicide rates for Colombia. A negative correlation suggests that with the implementation of femicide legislation, female homicides decrease, which provides support that legislation in Colombia, could be reducing femicide. However, this analysis also revealed a statistically significant negative association in male homicide and legislation. In fact, the correlation between male homicide rate and femicide legislation was stronger than the correlation between female homicide rate and legislation.
In Peru and Chile, a negative correlation was found between intimate partner femicide rate and the introduction of femicide legislation, which also suggests that legislation may be reducing at least one type of femicide in these countries. Nicaragua, however, showed an increase in intimate partner femicide rates after the implementation of femicide legislation. This finding suggests that the legislation produced the opposite intended result and increased the rate of intimate partner femicide. An increase in rates
130 of intimate partner femicide after the introduction of legislation, however, could occur for a number of reasons including a greater commitment to reporting female deaths, backlash from men as a result of the introduction of legislation, or some other factor unrelated to the enactment of legislation (Russell 2001; Fregoso and Bejarno 2010).
Results of the test before and after legislation enactment highlighted a significant relationship in female homicide rates after the introduction of legislation in Costa Rica.
However, Costa Rica’s construction of femicide is one of the most limited of the legislations analyzed as this country includes only the killing of a woman by her current or former partner in their definition of femicide. Interestingly, Costa Rica’s legislation is specific to intimate partner relationships, though no significant association was found when assessing intimate partner femicide rates in Costa Rica. However, Costa Rica highlighted a statistically significant association in male homicide rates and after the implementation of femicide legislation.
Browne and Williams (1989) argue that legislation can be seen as a resource to protect women from violence. In some circumstances, legislation that provides protection to women against their male partners may keep females from killing their partners in self- defence (Browne and Williams 1989). However, the statistically significant results reviewed above between male homicide rates after the enactment of legislation could also suggest an alternative cause of homicide rates more generally. The existence of some other factor occurring in these countries may have caused the variation in homicide rates.
Constructions of femicide did not appear to have a considerable impact on the effectiveness of femicide legislation. No definition of femicide or feminicide appeared more effective than the other given that neither definition significantly reduced female
131 homicide rates. Furthermore, country-specific definitions did not appear to aid in reducing female homicide rates. However, this research does not imply that constructions are irrelevant to the phenomenon of femicide. Rooted in the contextual constructionist approach, this research argues that constructions of femicide are paramount to our understanding of the problem. As it cannot be presently determined how well legislations are implemented, the effectiveness of particular constructions will have to be reassessed at a later time.
Other Factors Influencing Femicide in Latin America
This analysis illustrated that homicide rates and femicide legislation were correlated with a number of country-level social, political, and economic forces. These influences vary from country to country with respect to their potential effect on the dependent variable; however, significant predictors of female homicide rates included male homicide, gender inequality, GDP per capita, and employment. Gender inequality was also significantly correlated with the introduction of femicide legislation.
This research also provides tentative support for the belief that there is some relationship between homicide rates of males and females. Male homicide rates and female homicide rates had a positive correlation in more than half of the countries assessed, supporting previous literature that femicides are high in countries that also have high rates of male homicides (Steffensmeier and Allan 1988; Steffensmeier and Haynie
2000). A correlation between male and female homicide rates suggests that homicides of both sexes may be influenced by some of the same social and legal factors.
132 This research used two prominent measures of gender equality: female employment in national parliaments and female employment in national Supreme Courts
(Palma-Solis et al. 2008; Htun and Weldon 2012). Both variables were correlated with female homicide rates; the direction of this relationship varied by country, with equal numbers of positive and negative relationships found. These findings suggest that a greater participation of females in national parliament may reduce rates of female homicide in some Latin American countries. This result provides tentative support for the work of Palma-Solis et al. (2008), who found that greater political representation of females could result in lower rates of femicide. However, in countries with positive relationships, this research also provides support for the Chon’s (2013) findings who concluded that greater representation of females in national parliament was associated with an increase in sexual violence.
An increase in gender equality also appeared to impact the introduction of femicide legislation in Latin America. The percentage of women as members of national parliamentary positions appeared to have a positive impact on legislative change in Latin
America as the proportion of women employed in national parliaments had a positive correlation with the implementation of femicide legislation. These findings are consistent with previous research (Weldon 2006; Htun and Weldon 2012). According to Weldon
(2006),“descriptive representation” is important in improving the lives of marginalized groups, including women. “Descriptive representation, or the bodily presence of members of marginalized groups, helps to ensure that the final product reflects the perspective of the marginalized group, while also conferring legitimacy on the proceedings” (Weldon 2006: 56).
133 Female homicide rates and the percentage of females as supreme court judges also displayed the same number of positive and negative relationships. Similar to greater representation of seats in national parliament, a greater representation of women in
Supreme Court positions could lead to a decrease in female homicide rates in some countries in Latin America. While no previous research was found on correlations between gender equality in the judiciary and female homicide rates, gender equality in the judiciary is argued to improve women’s access to justice (Chiongson et al. 2011). As many countries in Latin America have been criticized for their failure to respond to femicide, an increase in the number of women in the judiciary could have an impact on the gender-responsiveness of courts (Chiongson et al. 2011).
A positive statistically significant relationship was also found between the percentage of females as supreme court judges and femicide legislation, suggesting that an increase in supreme court judges could have a positive impact on the introduction of legislation. While female employment in this influential position may have mixed effects on homicide rates, female supreme court judges may have a positive impact on the introduction of legislation to protect women from violence. This finding is consistent with Htun and Weldon’s (2012) analysis of VAW policy, where they found a statistically significant relationship between VAW policies and a strong female participation in the legislature.
This analysis also highlighted the importance of economic variables on the fluctuation of female homicide rates. GDP per capita displayed both negative and positive relationships with female homicide rates. More countries yielded positive results, contradicting the belief that increases in GDP per capita will result in lower rates of
134 female homicide. These results support the work of Chon (2013), who found that higher
GDP was related to an increase in sexual violence.
This study supports previous findings on the relationship between female employment and female homicide rates. Five of the six statistically significant relationships between female employment and female homicide rates in Latin American countries were positive. While female employment should reduce the rate of female homicides, as it reduces the dependency of the woman on a man for financial support
(known as the amelioration hypothesis), previous research has shown that this is not always the case (Russell 1975; Gartner et al. 1990; Whaley and Messener 2002). This research provides tentative support for the backlash hypothesis, suggesting that men may feel threatened by the growing participation of women in the workforce, which can lead to increased amounts of violence against women (Russell 1975). At the bivariate stage,
Palma-Solis et al. (2008) found associations between femicide rates and male and female unemployment respectively.
Relationships between female employment and femicide legislation were also found. Positive correlations between the two variables were found for five of the six countries with statistically significant relationships. This suggests that an increase in female employment may be related to the implementation of femicide legislation.
However, to the researcher’s knowledge, no literature currently exists on the employment of females and its potential impact on VAW or femicide legislation. The current study speculates that an increase of women in the workforce and the corresponding power that accompanies this would correlate with the introduction of femicide legislation as a result of a move toward gender equality within countries.
135 Overall, the results of the bivariate analysis suggest that variables can have different effects on female homicide rates and femicide legislation depending on the country analyzed. This finding is highlighted through the differing directions of statistically significant relationships between variables. Exceptions to this were male homicide rates and female precarious employment, whereby both variables only revealed positive statistically significant relationships with female homicide rates. This finding suggests that both variables have a consistent effect across countries on the rate of female homicide and reducing one or both of these variables may contribute to a decline in female homicide rates.
Original Contributions
This research makes a number of original contributions. It is the first study to assess the constructions of femicide legislation and the effectiveness of these constructions in Latin America globally. To the researcher’s knowledge, no previous studies have conducted a regional evaluation of the femicide legislation in Latin America or elsewhere. Results highlight the importance of evaluating legislation because legislation, as it is currently being enacted in Latin America, is not sufficient to reduce the rate of female homicide, at least in the short term. This research provides insight into femicide legislation in Latin America and the need for evaluations of femicide legislation more generally.
This research also analyzed social, cultural, and political factors that may be affecting female homicide rates and legislation in each of the 24 countries, the results of which suggest that female homicide rates are influenced by an intricate relationship of
136 variables. A variable may reduce female homicide rates in one country and increase female homicide rates in another. Thus, there is a need to assess which forces may cause a rise or decline of femicide rates within the particular context of each country.
This study is the first study to assess the relationship between precarious employment and female homicide rates. This study found several relationships between both male and female precarious employment and female homicide rates. The literature suggests economic tensions can increase the rate of homicides (Blau and Blau 1982;
Whaley and Messner 2002). It follows that precarious employment, which is typically low paying work, would be correlated with female homicide rates. Furthermore, in countries such as Mexico6, precarious employment of females, particularly maquiladora or factory work has been linked to the disappearances and killings of women (Wright
2001; Pantaleo 2010). More research is needed to further evaluate precarious employment and other variables and their relationship with female homicide rates.
Policy Implications
There are many recommendations for governments in Latin America that could improve the effectiveness of legislation. This study will focus on two main recommendations of femicide legislations in Latin America: legislation implementation and gender inequality, each of which will be reviewed below.
The implementation of femicide legislation has important implications for future policy developments in Latin America and was this study’s primary concern. As this research shows, femicide legislation in Latin America does not appear to reduce female
6 Mexico does not record precarious employment.
137 homicide rates. However, this research could not assess the degree to which countries were enforcing the legislation. A key limitation of this study is the inability to determine how countries are enacting legislation on the ground. If legislations are not being enforced, as the literature suggests, then it would follow that there would not be any significant difference in the rate of female homicides.
There are various explanations as to why legislation could be ineffectively implemented, which is commonly known as “policy slippage” (Murray and Powell 2009;
Shaw 2004:60). Reasons for policy slippage include the inadequacy of an institution to monitor enforcement, or an insufficient commitment of funds by the government (Murray and Powell 2009). Most notable, however, are the cultural or societal values, which are also the cause of femicide. Public support and normative values can substantially influence how successful the implementation of legislation is in practice. Unfortunately, this is also the most difficult barrier to overcome. Even if institutional support is present, legislation is unlikely to succeed unless there is a sincere commitment from all actors involved. Miguel Emilio La Rota, Colombia’s head of public policy and planning at the
Attorney General’s office, emphasizes this need for commitment when he acknowledged that alterations are needed in the way femicides are investigated “from the crime scene to the courtroom” (Moloney 2015).
If, however, countries were enforcing the legislation analyzed in this study, this research would suggest that legislation needed to be modified, as legislation has had no apparent impact on the rate of female homicides. Further evaluations of the implementation of femicide legislation should precede any modifications of femicide
138 legislation to assess their effectiveness in reducing female homicide rates. Thus, recommendations for future policy research are dependent, in part, on future research.
Gender inequality, the root of violence against women including femicide, has important implications for the development of femicide legislation. The indicators of gender inequality used in this study displayed mixed results on female homicide rates, but an increase in equality appeared to have a largely positive impact on the introduction of femicide legislation. Without a true commitment to increasing equality between men and women, violence that leads to femicide will continue. In addition to criminal sanctions, governments should implement support services and violence prevention initiatives.
Practices that acknowledge gender inequality and the barriers faced by women can reduce the number of women who suffer incessant violence before becoming victims of femicide. Promoting gender equality and empowering women is an integral part of protecting women from violence and should be given greater priority in Latin American countries.
Limitations and Future Research
Despite the contributions of this study, there were also limitations. Some of the limitations are associated with the modernity of the introduction of legislation. First, several countries that introduced legislation did so too recently to determine if they are effective in reducing female homicide rates. As homicide rates fluctuate from year to year, the true capability of the legislation will be more clearly visible as data on homicide rates becomes available for a longer time period. Future research could involve an
139 analysis of countries whose legislative developments could not be accurately measured at this time.
This research suggests that the next step should be an evaluation of the implementation of legislation. As previously noted, it is important to understand whether femicide legislation is being effectively implemented in each of the countries analyzed.
This research was not able to assess how or if countries are incorporating this legislation.
While previous literature has suggested that femicide legislation in Latin America remains largely unimplemented, or ineffectively implemented, to the researcher’s knowledge few empirical studies exist to support this claim. Research is needed to measure the degree to which difficulties in implementation exist within each country, as currently, it is unclear whether all of the countries analyzed experience this problem.
Specifically, single-country studies are needed to understand how femicide and its legislation work within the unique social and political context of each country. An in- depth analysis of a single country would be better equipped to assess why legislation may be ineffective. As the implementation of legislation is a complex process, all actors in this process need to be considered including politicians, police, public servants, social workers and domestic violence support staff, and non-governmental organizations. A comprehensive assessment of the system within each country is needed to understand why femicide legislation in Latin America remains ineffective. This information may provide insight into agency failures, funding issues, or social attitudes that may be hindering successful implementation of femicide legislation. Information regarding the effectiveness of legislation implementation, in combination with this present study, will
140 suggest future steps that countries in Latin America can take to protect women from femicide.
Research on femicide and its legislation must continue as this is a complex issue, requiring further macro-level studies to assess forces, including gender inequality, that may aggravate or mitigate perpetrators to commit these crimes. While this study included several important country-level variables, the sample size was too small for a multivariate analysis. More data is needed to assess how variables interact with femicide rates, legislation, and each other, within the unique social context of each country.
Results of the current research demonstrate the varying constructions of femicide across
Latin America. Definitions of femicide differ across countries and include different circumstances that can lead to the classification of femicide.
Overall, the results suggest that femicide constructions do not increase the effectiveness because legislation largely failed to reduce the rate of female homicide.
However, at present, it is unclear whether this is due to the nature of the legislation or its application. Further evaluations of femicide laws are needed to determine which type of legislation can most effectively reduce the rate of female homicides, both in Latin
America and globally. In countries with high impunity and few punishments for killing women, criminal justice measures including legislation, when properly implemented, may have an important preventative effect in reducing female homicides in Latin
America. Increased efforts are needed to promote gender equality within Latin American criminal justice systems and societies.
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157
APPENDICES
Appendix A Legislation Summary
Appendix B Coding for Dependent and Independent Variables
Appendix C Latin American Countries and Applicable Legislation
Appendix D Wilcoxon Signed-Rank Tests
Appendix E Mann-Whitney Table
Appendix F Bivariate Tables
Appendix A
158 Legislation Summary
Country Year
Argentina 2012
Bolivia 2013
Chile 2010
Colombia 2008
Costa Rica 2007
El Salvador 2010
Guatemala 2008
Honduras 2013
Nicaragua 2012
Mexico 2012
Panama 2013
Peru 2013
Venezuela 2007
Table 2. Coding for Dependent and Independent Variables
Variable Coding
159 Dependent Variable
Female Homicide Rate Continuous Measure (Per 100 000 pop)
Independent Variable
Legislation Enactment 1=yes 0=no (Year)
Additional Independent Variables
Male Homicide Rate Continuous Measure (Per 100 000 pop)
Intimate Partner Femicide Rate Continuous Measure (Per 100 000 women)
Femicide Rate Continuous Measure (Per 100 000 women)
Presence of VAW legislation 1=yes, 0=no (Year)
GDP per capita Continuous Measure (US dollar)
Gini coefficient for income Continuous Measure (0-100)
Armed Conflict 1=yes or recently resolved, 0=no
Employment to population ratio Continuous Measure (Percentage per population)
Vulnerable Employment Continuous Measure (Percentage per population)
Percentage of Female Judges Continuous Measure (Percentage per population)
Female Representation in Parliament Continuous Measure (Percentage per population)
160
Appendix C
Latin American Countries and Applicable Legislation
161
Country Name Legislation Date in Effect
Argentina Yes 2012
Bahamas No N/A
Barbados No N/A
Belize No N/A
Brazil Yes 2015
Chile Yes 2010
Colombia Yes 2008
Costa Rica Yes 2007
Cuba No N/A
Dominica No N/A
Dominican Republic No N/A
Ecuador No N/A
El Salvador Yes 2010
Guatemala Yes 2008
Jamaica No N/A
Mexico Yes 2012
Nicaragua Yes 2012
Panama Yes 2013
Paraguay No N/A
Peru Yes 2013
St. Lucia No N/A
Suriname No N/A
162
Uruguay No N/A
Venezuela Yes 2007
Appendix D
Wilcoxon Signed-Rank Tests
163
Wilcoxon signed-rank - Countries included by dependent variable
Female Homicide Rate
Costa Rica Colombia Chile Venezuela Guatemala
Intimate Partner Femicide Rate
Costa Rica Colombia Chile Nicaragua
Femicide Rate
Nicaragua
Male homicide Rate
Costa Rica Colombia Chile Venezuela Guatemala
164
Appendix D
Wilcoxon-signed Rank Tables
Chile
Ranksa Mean Sum of N Rank Ranks Female Negative 3b 2.00 6.00 Homicide Before Ranks – Female Positive Ranks 0c .00 .00 Homicide After Ties 0d Total 3 IPF Before - IPF Negative 1e 1.00 1.00 After Ranks Positive Ranks 3f 3.00 9.00 Ties 0g Total 4 Male Homicide Negative 3h 2.67 8.00 Before – Male Ranks Homicide After Positive Ranks 1i 2.00 2.00 Ties 0j Total 4 a. COUNTRY = CHILE b. HOMICIDE LEG BEFORE < HOMICIDE LEG AFTER c. HOMICIDE LEG BEFORE > HOMICIDE LEG AFTER d. HOMICIDE LEG BEFORE = HOMICIDE LEG AFTER e. IPF BEFORE LEG < IPF AFTER LEG f. IPF BEFORE LEG > IPF AFTER LEG g. IPF BEFORE LEG = IPF AFTER LEG h. MALE HOM BEFORE LEG < MALE HOMICIDE AFTER LEG i. MALE HOM BEFORE LEG > MALE HOMICIDE AFTER LEG j. MALE HOM BEFORE LEG = MALE HOMICIDE AFTER LEG
165
Test Statisticsa,b Female Male Homicide Homicide Before – Before – Female Male Homicide IPF Before - Homicide After IPF After After Z -1.633c -1.461d -1.105c Asymp. Sig. (2- .102 .144 .269 tailed) a. COUNTRY = CHILE b. Wilcoxon Signed Ranks Test c. Based on positive ranks. d. Based on negative ranks.
166
Colombia
Ranksa Mean Sum of N Rank Ranks Female Negative 0b .00 .00 Homicide Before Ranks – Female Positive Ranks 4c 2.50 10.00 Homicide After Ties 0d Total 4 IPF Before - IPF Negative 3e 3.33 10.00 After Ranks Positive Ranks 2f 2.50 5.00 Ties 0g Total 5 Male Homicide Negative 0h .00 .00 Before – Male Ranks Homicide After Positive Ranks 5i 3.00 15.00 Ties 0j Total 5 a. COUNTRY = COLOMBIA b. HOMICIDE LEG BEFORE < HOMICIDE LEG AFTER c. HOMICIDE LEG BEFORE > HOMICIDE LEG AFTER d. HOMICIDE LEG BEFORE = HOMICIDE LEG AFTER e. IPF BEFORE LEG < IPF AFTER LEG f. IPF BEFORE LEG > IPF AFTER LEG g. IPF BEFORE LEG = IPF AFTER LEG h. MALE HOM BEFORE LEG < MALE HOMICIDE AFTER LEG i. MALE HOM BEFORE LEG > MALE HOMICIDE AFTER LEG j. MALE HOM BEFORE LEG = MALE HOMICIDE AFTER LEG
167
Test Statisticsa,b
Female Male Homicide Homicide Before – Before – Female Male Homicide IPF Before - Homicide After IPF After After Z -1.826c -.674d -2.023c Asymp. Sig. (2- .068 .500 .043* tailed) a. COUNTRY = COLOMBIA b. Wilcoxon Signed Ranks Test c. Based on negative ranks. d. Based on positive ranks.
168 Costa Rica
Ranksa Mean Sum of N Rank Ranks Female Negative 6b 3.50 21.00 Homicide Before Ranks – Female Positive Ranks 0c .00 .00 Homicide After Ties 0d Total 6 IPF Before - IPF Negative 3e 4.67 14.00 After Ranks Positive Ranks 3f 2.33 7.00 Ties 0g Total 6 Male Homicide Negative 7h 4.00 28.00 Before – Male Ranks Homicide After Positive Ranks 0i .00 .00 Ties 0j Total 7 a. COUNTRY = COSTA RICA b. HOMICIDE LEG BEFORE < HOMICIDE LEG AFTER c. HOMICIDE LEG BEFORE > HOMICIDE LEG AFTER d. HOMICIDE LEG BEFORE = HOMICIDE LEG AFTER e. IPF BEFORE LEG < IPF AFTER LEG f. IPF BEFORE LEG > IPF AFTER LEG g. IPF BEFORE LEG = IPF AFTER LEG h. MALE HOM BEFORE LEG < MALE HOMICIDE AFTER LEG i. MALE HOM BEFORE LEG > MALE HOMICIDE AFTER LEG j. MALE HOM BEFORE LEG = MALE HOMICIDE AFTER LEG
169
Test Statisticsa,b Female Male Homicide Homicide Before – Before – Female Male Homicide IPF Before - Homicide After IPF After After Z -2.201c -.734c -2.366c Asymp. Sig. (2- .028* .463 .018* tailed) a. COUNTRY = COSTA RICA b. Wilcoxon Signed Ranks Test c. Based on positive ranks.
170
El Salvador
Ranksa Mean Sum of N Rank Ranks Female Negative 3b 2.00 6.00 Homicide Before Ranks – Female Positive Ranks 0c .00 .00 Homicide After Ties 0d Total 3 Male Homicide Negative 3e 2.00 6.00 Before – Male Ranks Homicide After Positive Ranks 0f .00 .00 Ties 0g Total 3 a. COUNTRY = ELSALVADOR b. HOMICIDE LEG BEFORE < HOMICIDE LEG AFTER c. HOMICIDE LEG BEFORE > HOMICIDE LEG AFTER d. HOMICIDE LEG BEFORE = HOMICIDE LEG AFTER e. MALE HOM BEFORE LEG < MALE HOMICIDE AFTER LEG f. MALE HOM BEFORE LEG > MALE HOMICIDE AFTER LEG g. MALE HOM BEFORE LEG = MALE HOMICIDE AFTER LEG
Test Statisticsa,b Female Male Homicide Homicide Before – Before – Female Male Homicide Homicide After After Z -1.604c -1.604c Asymp. Sig. (2- .109 .109 tailed) a. COUNTRY = ELSALVADOR b. Wilcoxon Signed Ranks Test c. Based on positive ranks.
171 Guatemala
Ranksa Mean Sum of N Rank Ranks Female Negative 3b 2.00 6.00 Homicide Before Ranks – Female Positive Ranks 0c .00 .00 Homicide After Ties 0d Total 3 Male Homicide Negative 3e 2.00 6.00 Before – Male Ranks Homicide After Positive Ranks 0f .00 .00 Ties 0g Total 3 a. COUNTRY = GUATEMALA b. HOMICIDE LEG BEFORE < HOMICIDE LEG AFTER c. HOMICIDE LEG BEFORE > HOMICIDE LEG AFTER d. HOMICIDE LEG BEFORE = HOMICIDE LEG AFTER e. MALE HOM BEFORE LEG < MALE HOMICIDE AFTER LEG f. MALE HOM BEFORE LEG > MALE HOMICIDE AFTER LEG g. MALE HOM BEFORE LEG = MALE HOMICIDE AFTER LEG
Test Statisticsa,b Female Male Homicide Homicide Before – Before – Female Male Homicide Homicide After After Z -1.604c -1.604c Asymp. Sig. (2- .109 .109 tailed) a. COUNTRY = GUATEMALA b. Wilcoxon Signed Ranks Test c. Based on positive ranks.
172
Nicaragua
Ranksa Mean Sum of N Rank Ranks IPF BEFORE Negative 3b 2.00 6.00 LEG - IPF Ranks AFTER LEG Positive Ranks 0c .00 .00 Ties 0d Total 3 FEMICIDE Negative 3e 2.00 6.00 RATE AFTER - Ranks FEMICIDE Positive Ranks 0f .00 .00 RATE BEFORE Ties 0g Total 3 a. COUNTRY = NICARAGUA b. IPF BEFORE LEG < IPF AFTER LEG c. IPF BEFORE LEG > IPF AFTER LEG d. IPF BEFORE LEG = IPF AFTER LEG e. FEMICIDE RATE AFTER < FEMICIDE RATE BEFORE f. FEMICIDE RATE AFTER > FEMICIDE RATE BEFORE g. FEMICIDE RATE AFTER = FEMICIDE RATE BEFORE
Test Statisticsa,b Femicide Before – IPF Before - Femicide IPF After After Z -1.604c -1.604c Asymp. Sig. (2- .109 .109 tailed) a. COUNTRY = NICARAGUA b. Wilcoxon Signed Ranks Test c. Based on positive ranks.
173 Venezuela
Ranksa Mean Sum of N Rank Ranks Female Negative 3b 2.00 6.00 Homicide Before Ranks – Female Positive Ranks 0c .00 .00 Homicide After Ties 0d Total 3 Male Homicide Negative 4e 2.50 10.00 Before – Male Ranks Homicide After Positive Ranks 0f .00 .00 Ties 0g Total 4 a. COUNTRY = VENEZUELA b. HOMICIDE LEG BEFORE < HOMICIDE LEG AFTER c. HOMICIDE LEG BEFORE > HOMICIDE LEG AFTER d. HOMICIDE LEG BEFORE = HOMICIDE LEG AFTER e. MALE HOM BEFORE LEG < MALE HOMICIDE AFTER LEG f. MALE HOM BEFORE LEG > MALE HOMICIDE AFTER LEG g. MALE HOM BEFORE LEG = MALE HOMICIDE AFTER LEG
Test Statisticsa,b Female Male Homicide Homicide Before – Before – Female Male Homicide Homicide After After Z -1.604c -1.826c Asymp. Sig. (2- .109 .068 tailed) a. COUNTRY = VENEZUELA b. Wilcoxon Signed Ranks Test c. Based on positive ranks.
174
Appendix E
Countries with Legislation Countries Without Legislation
Chile Argentina
Colombia Bahamas
Costa Rica Belize
Guatemala Brazil
Mexico Cuba
Nicaragua Dominica
Peru Dominican Republic
Venezuela Ecuador
Jamaica
Panama
Paraguay
Suriname
Saint Lucia
Uruguay
175
Appendix E
Mann-Whitney Tables
Ranks With/ Without Femicide Mean Sum of legislation N Rank Ranks Female NO 212 168.68 35761.00 Homicides YES 129 174.81 22550.00 Total 341
Test Statisticsa Female Homicides Mann-Whitney 13183.000 U Wilcoxon W 35761.000 Z -.556 Asymp. Sig. (2- .578 tailed) a. Grouping Variable: WITH/WITHOUT FEM LEG
176 Appendix F
Table 5. Spearman’s rho Correlations for Argentina
GDP Precarious Precarious Female Female Femicide Male per Employment Employment Employ Employ National Female Homicide Legislation Homicide capita Gini Males Females Males Females Parliament Judges Spearman's Female - 1.000 -.232 .860** .803** -.442 -.353 .672** .368 -.465 -.678** rho Homicide .809** . .388 .000 .000 .000 .087 .180 .004 .160 .094 .005 16 16 16 16 16 16 16 16 16 14 15 Femicide -.232 1.000 .056 .618** -.559* .331 .331 -.186 -.503* .174 .099 Legislation .388 . .831 .006 .020 .180 .180 .474 .039 .518 .705 16 18 17 18 17 18 18 17 17 16 17 Male - .860** .056 1.000 .737** -.596* -.494* .836** .491* -.647** -.836** Homicide .702** .000 .831 . .002 .001 .012 .044 .000 .045 .009 .000 16 17 17 17 17 17 17 17 17 15 16 GDP per - -.809** .618** -.702** 1.000 .582* .518* -.698** -.612** .558* .533* capita .868** .000 .006 .002 . .000 .011 .028 .002 .009 .025 .027 16 18 17 18 17 18 18 17 17 16 17 Gini - .803** -.559* .737** 1.000 -.800** -.723** .852** .801** -.716** -.786** .868** .000 .020 .001 .000 . .000 .001 .000 .000 .003 .000 16 17 17 17 17 17 17 17 17 15 16 Employment - -.442 .331 -.596* .582* 1.000 .819** -.823** -.896** .764** .840** Males .800** .087 .180 .012 .011 .000 . .000 .000 .000 .001 .000 16 18 17 18 17 18 18 17 17 16 17 Employment - -.353 .331 -.494* .518* .819** 1.000 -.795** -.906** .797** .856** Females .723** .180 .180 .044 .028 .001 .000 . .000 .000 .000 .000 16 18 17 18 17 18 18 17 17 16 17 177 Precarious - .672** -.186 .836** .852** -.823** -.795** 1.000 .827** -.862** -.922** Employ .698** Males .004 .474 .000 .002 .000 .000 .000 . .000 .000 .000 16 17 17 17 17 17 17 17 17 15 16 Precarious - .368 -.503* .491* .801** -.896** -.906** .827** 1.000 -.824** -.816** Employ .612** Females .160 .039 .045 .009 .000 .000 .000 .000 . .000 .000 16 17 17 17 17 17 17 17 17 15 16 Female - -.465 .174 -.647** .558* .764** .797** -.862** -.824** 1.000 .876** National .716** Parliament .094 .518 .009 .025 .003 .001 .000 .000 .000 . .000 14 16 15 16 15 16 16 15 15 16 15 Female - -.678** .099 -.836** .533* .840** .856** -.922** -.816** .876** 1.000 Judges .786** .005 .705 .000 .027 .000 .000 .000 .000 .000 .000 . 15 17 16 17 16 17 17 16 16 15 17 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
178
Spearman’s rho Correlation Brazil Correlationsa GDP Precarious Precarious Female
Female Male per Employment Employment Employ Employ National Female Homicide Homicide capita Gini Males Females Males Females Parliament Judges Spearman's Female 1.000 .746** .341 -.377 -.150 -.004 -.212 -.442 -.138 .577* rho Homicide . .001 .196 .184 .610 .988 .508 .150 .610 .024 16 16 16 14 14 14 12 12 16 15 Male Homicide .746** 1.000 .110 -.543* .043 .159 -.072 -.132 .027 .359 .001 . .673 .037 .879 .571 .816 .667 .917 .172 16 17 17 15 15 15 13 13 17 16 GDP per capita .341 .110 1.000 -.782** .063 .474 -.920** -.889** .401 .870** .196 .673 . .001 .825 .074 .000 .000 .099 .000 16 17 18 15 15 15 13 13 18 17 Gini -.377 -.543* -.782** 1.000 -.309 -.707** .949** .981** -.537* -.920** .184 .037 .001 . .262 .003 .000 .000 .039 .000 14 15 15 15 15 15 12 12 15 14 Employment -.150 .043 .063 -.309 1.000 .834** .154 .284 .785** .293 Males .610 .879 .825 .262 . .000 .632 .371 .001 .309 14 15 15 15 15 15 12 12 15 14 Employment -.004 .159 .474 -.707** .834** 1.000 -.518 -.404 .871** .664** Females .988 .571 .074 .003 .000 . .084 .192 .000 .010 14 15 15 15 15 15 12 12 15 14 Precarious -.212 -.072 -.920** .949** .154 -.518 1.000 .886** -.266 -.889** Employ .508 .816 .000 .000 .632 .084 . .000 .379 .000 Males 12 13 13 12 12 12 13 13 13 13 Precarious -.442 -.132 -.889** .981** .284 -.404 .886** 1.000 .011 -.818** Employ .150 .667 .000 .000 .371 .192 .000 . .971 .001
179 Females 12 13 13 12 12 12 13 13 13 13
Female -.138 .027 .401 -.537* .785** .871** -.266 .011 1.000 .450 National .610 .917 .099 .039 .001 .000 .379 .971 . .070 Parliament 16 17 18 15 15 15 13 13 18 17 Female Judges .577* .359 .870** -.920** .293 .664** -.889** -.818** .450 1.000 .024 .172 .000 .000 .309 .010 .000 .001 .070 . 15 16 17 14 14 14 13 13 17 17 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). a. COUNTRY = BRAZIL
180
Spearman’s rho Correlation Chile Correlationsa Intimate GDP Female Female Femicide Male Partner per Employment Employment National Female Homicide Legislation Homicide Femicide capita Gini Males Females Parliament Judges Spearman's rho Female 1.000 .000 .514* .532 .241 -.174 -.423 .166 .618* -.013
Homicide . 1.000 .042 .219 .368 .742 .103 .538 .011 .972 16 16 16 7 16 6 16 16 16 10 Femicide .000 1.000 -.341 -.779* .777** -.791* .469* .777** .463 .788** Legislation 1.000 . .181 .013 .000 .034 .050 .000 .053 .002 16 18 17 9 18 7 18 18 18 12 Male Homicide .514* -.341 1.000 .566 -.244 -.107 -.852** -.245 .248 -.676* .042 .181 . .143 .346 .819 .000 .344 .338 .022 16 17 17 8 17 7 17 17 17 11 Intimate .532 -.779* .566 1.000 -.750* 1.000** -.763* -.767* -.223 -.548 Partner .219 .013 .143 . .020 . .017 .016 .565 .127 Femicide 7 9 8 9 9 4 9 9 9 9 GDP per capita .241 .777** -.244 -.750* 1.000 -.821* .352 .977** .744** .890** .368 .000 .346 .020 . .023 .152 .000 .000 .000 16 18 17 9 18 7 18 18 18 12 Gini -.174 -.791* -.107 1.000** -.821* 1.000 .036 -.857* -.927** -.671 .742 .034 .819 . .023 . .939 .014 .003 .215 6 7 7 4 7 7 7 7 7 5 Employment -.423 .469* -.852** -.763* .352 .036 1.000 .313 -.110 .666* Males .103 .050 .000 .017 .152 .939 . .205 .664 .018 16 18 17 9 18 7 18 18 18 12 Employment .166 .777** -.245 -.767* .977** -.857* .313 1.000 .778** .897** Females .538 .000 .344 .016 .000 .014 .205 . .000 .000 16 18 17 9 18 7 18 18 18 12 181 Female National .618* .463 .248 -.223 .744** -.927** -.110 .778** 1.000 .250 Parliament .011 .053 .338 .565 .000 .003 .664 .000 . .434 16 18 17 9 18 7 18 18 18 12 Female Judges -.013 .788** -.676* -.548 .890** -.671 .666* .897** .250 1.000 .972 .002 .022 .127 .000 .215 .018 .000 .434 . 10 12 11 9 12 5 12 12 12 12 *. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed). a. COUNTRY = CHILE
182 Spearman’s rho for Colombia
Intimate GDP Precarious Precarious Female Female Femicide Male Partner per Employment Employment Employ Employ National Female Homicide Legislation Homicide Femicide capita Gini Males Females Males Females Parliament Judges Spearman' Female - s rho Homicide 1.000 -.594* .955** -.143 .891* .245 -.529* -.401 -.193 -.363 .083 -.805** * . .019 .000 .760 .000 .420 .043 .139 .490 .183 .779 .001 15 15 15 7 15 13 15 15 15 15 14 14 Femicide - .846* Legislation -.594* 1.000 -.717** .038 .661* .517* .782** .679** .829** .444 .866** * * .019 . .002 .917 .000 .007 .028 .000 .003 .000 .075 .000 15 18 16 10 18 15 18 18 17 17 17 17 Male - Homicide .955** -.717** 1.000 -.619 .924* .495 -.716** -.452 -.414 -.574* -.219 -.896** * .000 .002 . .102 .000 .072 .002 .079 .111 .020 .434 .000 15 16 16 8 16 14 16 16 16 16 15 15 Intimate -.143 .038 -.619 1.000 .139 -.267 .012 .418 .293 .350 .528 .190 Partner .760 .917 .102 . .701 .488 .973 .229 .444 .356 .117 .600 Femicide 7 10 8 10 10 9 10 10 9 9 10 10 GDP per 1.00 - -.891** .846** -.924** .139 .472* .644** .477 .659** .406 .885** capita 0 .568* .000 .000 .000 .701 . .027 .048 .004 .053 .004 .106 .000 15 18 16 10 18 15 18 18 17 17 17 17 Gini - 1.00 .245 -.661** .495 -.267 -.727** -.645** -.586* -.757** -.757** -.648** .568* 0 .420 .007 .072 .488 .027 . .002 .009 .022 .001 .001 .009 13 15 14 9 15 15 15 15 15 15 15 15
183 Employment - Males -.529* .517* -.716** .012 .472* .727* 1.000 .307 .625** .767** .293 .589* * .043 .028 .002 .973 .048 .002 . .216 .007 .000 .254 .013 15 18 16 10 18 15 18 18 17 17 17 17 Employment - .644* Females -.401 .782** -.452 .418 .645* .307 1.000 .346 .530* .538* .687** * * .139 .000 .079 .229 .004 .009 .216 . .174 .029 .026 .002 15 18 16 10 18 15 18 18 17 17 17 17 Precarious - -.193 .679** -.414 .293 .477 .625** .346 1.000 .914** .545* .594* Employ .586* Males .490 .003 .111 .444 .053 .022 .007 .174 . .000 .029 .015 15 17 16 9 17 15 17 17 17 17 16 16 Precarious - .659* Employ -.363 .829** -.574* .350 .757* .767** .530* .914** 1.000 .607* .784** * Females * .183 .000 .020 .356 .004 .001 .000 .029 .000 . .013 .000 15 17 16 9 17 15 17 17 17 17 16 16 Female - National .083 .444 -.219 .528 .406 .757* .293 .538* .545* .607* 1.000 .545* Parliament * .779 .075 .434 .117 .106 .001 .254 .026 .029 .013 . .029 14 17 15 10 17 15 17 17 16 16 17 16 Female - .885* Judges -.805** .866** -.896** .190 .648* .589* .687** .594* .784** .545* 1.000 * * .001 .000 .000 .600 .000 .009 .013 .002 .015 .000 .029 . 14 17 15 10 17 15 17 17 16 16 16 17 *. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed).
184 Spearman’s rho Correlation for Costa Rica
Intimate GDP Precarious Precarious Female Female Femicide Male Partner per Employment Employment Employ Employ National Female Homicide Legislation Homicide Femicide Femicide capita Gini Males Females Males Females Parliament Judges Spearman's Female 1.000 .492 .664** .758** .929** .662** .010 .157 .546* -.570* -.278 .577* .533* rho Homicide . .053 .005 .004 .001 .005 .970 .561 .029 .027 .317 .019 .041 16 16 16 12 8 16 16 16 16 15 15 16 15 Femicide .492 1.000 .856** -.179 -.087 .862** .195 -.129 .830** -.561* -.752** .661** .870** Legislation .053 . .000 .540 .811 .000 .453 .609 .000 .024 .001 .003 .000 16 18 17 14 10 18 17 18 18 16 16 18 17 Male .664** .856** 1.000 .181 .333 .838** .324 .134 .864** -.693** -.484 .779** .832** Homicide .005 .000 . .553 .381 .000 .204 .608 .000 .003 .058 .000 .000 16 17 17 13 9 17 17 17 17 16 16 17 16 Intimate .758** -.179 .181 1.000 .842** -.292 -.203 .319 -.123 -.616* .238 .057 -.252 Partner .004 .540 .553 . .002 .311 .505 .266 .675 .033 .457 .847 .384 Femicide 12 14 13 14 10 14 13 14 14 12 12 14 14 Femicide .929** -.087 .333 .842** 1.000 -.382 -.333 .358 -.237 -.469 .150 .136 -.203 .001 .811 .381 .002 . .276 .381 .310 .510 .203 .700 .707 .574 8 10 9 10 10 10 9 10 10 9 9 10 10 GDP per .662** .862** .838** -.292 -.382 1.000 .289 -.076 .851** -.517* -.603* .801** .954** capita .005 .000 .000 .311 .276 . .260 .763 .000 .040 .013 .000 .000 16 18 17 14 10 18 17 18 18 16 16 18 17 Gini .010 .195 .324 -.203 -.333 .289 1.000 .429 .467 -.373 .215 .329 .167 .970 .453 .204 .505 .381 .260 . .086 .059 .155 .425 .197 .536
16 17 17 13 9 17 17 17 17 16 16 17 16
.157 -.129 .134 .319 .358 -.076 .429 1.000 .234 -.143 .255 .128 -.241 Employment .561 .609 .608 .266 .310 .763 .086 . .350 .597 .341 .614 .351 Males 16 18 17 14 10 18 17 18 18 16 16 18 17 Employment .546* .830** .864** -.123 -.237 .851** .467 .234 1.000 -.673** -.484 .655** .850** Females .029 .000 .000 .675 .510 .000 .059 .350 . .004 .057 .003 .000 16 18 17 14 10 18 17 18 18 16 16 18 17 Precarious - -.570* -.561* -.693** -.616* -.469 -.373 -.143 -.673** 1.000 .196 -.406 -.412 Employ .517*
185 Males .027 .024 .003 .033 .203 .040 .155 .597 .004 . .467 .119 .127 15 16 16 12 9 16 16 16 16 16 16 16 15 Precarious - -.278 -.752** -.484 .238 .150 .215 .255 -.484 .196 1.000 -.569* -.636* Employ .603* Females .317 .001 .058 .457 .700 .013 .425 .341 .057 .467 . .021 .011 15 16 16 12 9 16 16 16 16 16 16 16 15 Female .577* .661** .779** .057 .136 .801** .329 .128 .655** -.406 -.569* 1.000 .751** National .019 .003 .000 .847 .707 .000 .197 .614 .003 .119 .021 . .001 Parliament 16 18 17 14 10 18 17 18 18 16 16 18 17 Female .533* .870** .832** -.252 -.203 .954** .167 -.241 .850** -.412 -.636* .751** 1.000 Judges .041 .000 .000 .384 .574 .000 .536 .351 .000 .127 .011 .001 .
15 17 16 14 10 17 16 17 17 15 15 17 17 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
186 Spearman’s rho Correlation Dominican Republic
Correlationsa Intimate GDP Precarious Precarious Female Female Male Partner per Employment Employment Employ Employ National Female Homicide Homicide Femicide Femicide capita Gini Males Females Males Females Parliament Judges Spearman's Female 1.000 .869** .473 .782* .709** -.668* -.058 .593* .400 .131 .504 -.535 rho Homicide . .000 .284 .038 .003 .013 .845 .025 .140 .642 .056 .090 15 15 7 7 15 13 14 14 15 15 15 11 Male - .869** 1.000 .190 .571 .793** -.271 .592* .528* .295 .658** -.734** Homicide .820** .000 . .651 .139 .000 .000 .329 .020 .036 .268 .006 .007 15 16 8 8 16 14 15 15 16 16 16 12 Intimate .473 .190 1.000 .782** -.430 .450 .127 .140 .353 .717* -.295 .110 Partner .284 .651 . .008 .214 .224 .726 .700 .351 .030 .408 .779 Femicide 7 8 10 10 10 9 10 10 9 9 10 9 Femicide .782* .571 .782** 1.000 -.261 .083 .115 .304 .168 .383 -.098 -.310 .038 .139 .008 . .467 .831 .751 .393 .666 .308 .787 .416 7 8 10 10 10 9 10 10 9 9 10 9 GDP per - .709** .793** -.430 -.261 1.000 -.162 .737** .568* -.011 .887** -.758** capita .846** .003 .000 .214 .467 . .000 .534 .001 .017 .966 .000 .003 15 16 10 10 18 15 17 17 17 17 18 13 Gini -.668* -.820** .450 .083 -.846** 1.000 .298 -.795** -.394 -.341 -.727** .785** .013 .000 .224 .831 .000 . .301 .001 .147 .213 .002 .001 13 14 9 9 15 15 14 14 15 15 15 13 Employment -.058 -.271 .127 .115 -.162 .298 1.000 .339 -.473 -.629** -.090 .027 Males .845 .329 .726 .751 .534 .301 . .182 .064 .009 .732 .930 14 15 10 10 17 14 17 17 16 16 17 13
187 Employment - .593* .592* .140 .304 .737** .339 1.000 .385 -.136 .810** -.818** Females .795** .025 .020 .700 .393 .001 .001 .182 . .141 .617 .000 .001 14 15 10 10 17 14 17 17 16 16 17 13 Precarious .400 .528* .353 .168 .568* -.394 -.473 .385 1.000 .327 .591* -.229 Employ .140 .036 .351 .666 .017 .147 .064 .141 . .200 .012 .452 Males 15 16 9 9 17 15 16 16 17 17 17 13 Precarious .131 .295 .717* .383 -.011 -.341 -.629** -.136 .327 1.000 -.209 .034 Employ .642 .268 .030 .308 .966 .213 .009 .617 .200 . .420 .913 Females 15 16 9 9 17 15 16 16 17 17 17 13 Female - .504 .658** -.295 -.098 .887** -.090 .810** .591* -.209 1.000 -.812** National .727** Parliament .056 .006 .408 .787 .000 .002 .732 .000 .012 .420 . .001 15 16 10 10 18 15 17 17 17 17 18 13 Female - -.535 -.734** .110 -.310 .785** .027 -.818** -.229 .034 -.812** 1.000 Judges .758** .090 .007 .779 .416 .003 .001 .930 .001 .452 .913 .001 . 11 12 9 9 13 13 13 13 13 13 13 13 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). a. COUNTRY = DOMINICANREPUB
188 Spearman’s rho Correlation El Salvador Correlationsa GDP Precarious Precarious Female Female Femicide Male per Male Female Employ Employ National Female Homicide Legislation Homicide capita Gini Employment Employment Males Females Parliament Judges Spearman's Female - 1.000 .452 .881** .819** .570* .717** -.159 .158 .708** .740** rho Homicide .774** . .079 .000 .000 .001 .021 .002 .556 .559 .002 .002 16 16 16 16 15 16 16 16 16 16 15 Femicide - .452 1.000 .434 .753** .651** .624** .000 .170 .766** .741** Legislation .751** .079 . .093 .000 .001 .005 .007 1.000 .514 .000 .001 16 18 16 18 16 17 17 17 17 18 17 Male Homicide - .881** .434 1.000 .715** .534* .595* -.147 .082 .750** .732** .743** .000 .093 . .002 .002 .033 .015 .587 .761 .001 .002 16 16 16 16 15 16 16 16 16 16 15 GDP per capita - .819** .753** .715* 1.000 .889** .938** -.203 .189 .758** .916** .941** .000 .000 .002 . .000 .000 .000 .434 .468 .000 .000 16 18 16 18 16 17 17 17 17 18 17 Gini -.774** -.751** -.743** -.941** 1.000 -.818** -.836** .221 -.079 -.745** -.890** .001 .001 .002 .000 . .000 .000 .412 .770 .001 .000 15 16 15 16 16 16 16 16 16 16 16 Employment - .570* .651** .534* .889** 1.000 .913** -.107 .193 .592* .823** Males .818** .021 .005 .033 .000 .000 . .000 .684 .459 .012 .000 16 17 16 17 16 17 17 17 17 17 16 Employment - .717* .624 .595* .938** .913** 1.000 -.167 .163 .663** .865** Females .836**
189 .002 .007 .015 .000 .000 .000 . .522 .532 .004 .000 16 17 16 17 16 17 17 17 17 17 16 Precarious -.159 .000 -.147 -.203 .221 -.107 -.167 1.000 .671** -.114 -.164 Employ Males .556 1.000 .587 .434 .412 .684 .522 . .003 .664 .545 16 17 16 17 16 17 17 17 17 17 16 Precarious .158 .170 .082 .189 -.079 .193 .163 .671** 1.000 -.132 -.015 Employ .559 .514 .761 .468 .770 .459 .532 .003 . .615 .957 Females 16 17 16 17 16 17 17 17 17 17 16 Female - .708** .766** .750** .758** .592* .663* -.114 -.132 1.000 .877** National .745** Parliament .002 .000 .001 .000 .001 .012 .004 .664 .615 . .000 16 18 16 18 16 17 17 17 17 18 17 Female Judges - .740** .741** .732* .916** .823** .865** -.164 -.015 .877** 1.000 .890** .002 .001 .002 .000 .000 .000 .000 .545 .957 .000 . 15 17 15 17 16 16 16 16 16 17 17 *. Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed). a. COUNTRY = ELSALVADOR
190 Spearman’s rho Correlation Guatemala Correlationsa GDP Precarious Precarious Female Female Femicide Male per Male Female Employ Employ National Female Homicide Legislation Homicide capita Gini Employment Employment Males Females Parliament Judges Spearman's Female - 1.000 .567 .719* .240 -1.000 -.500 1.000 -1.000 .270 .069 rho Homicide 1.000 . .143 .045 .568 . . .667 . . .518 .872 8 8 8 8 2 3 3 2 2 8 8 Femicide .567 1.000 .000 .846 -.393 -.764* -.764* -.791* -.479 .713 -.512* Legislation .143 . 1.000 .000 .441 .027 .027 .034 .277 .001 .035 8 18 9 18 6 8 8 7 7 18 17 Male .719* .000 1.000 -.483 1.000 -1.000 -.200 1.000 -1.000 -.489 .566 Homicide .045 1.000 . .187 . . .800 . . .181 .112 8 9 9 9 2 4 4 2 2 9 9 GDP per .240 .846 -.483 1.000 -.429 -.690 -.714* -.571 -.180 .636 -.502* capita .568 .000 .187 . .397 .058 .047 .180 .699 .005 .040 8 18 9 18 6 8 8 7 7 18 17 Gini -1.000 -.393 1.000 -.429 1.000 .800 .600 .300 .500 .093 .101 . .441 . .397 . .104 .285 .624 .391 .862 .848 2 6 2 6 6 5 5 5 5 6 6 Male -1.000 -.764* -1.000 -.690 .800 1.000 .881 .543 .771 -.531 .799* Employment . .027 . .058 .104 . .004 .266 .072 .175 .017 3 8 4 8 5 8 8 6 6 8 8 Female -.500 -.764* -.200 -.714* .600 .881 1.000 .429 .714 -.679 .850 Employment .667 .027 .800 .047 .285 .004 . .397 .111 .064 .008 3 8 4 8 5 8 8 6 6 8 8 Precarious 1.000 -.791* 1.000 -.571 .300 .543 .429 1.000 .739 -.826* .867* Employ Males . .034 . .180 .624 .266 .397 . .058 .022 .012
191 2 7 2 7 5 6 6 7 7 7 7 Precarious -1.000 -.479 -1.000 -.180 .500 .771 .714 .739 1.000 -.639 .686 Employ . .277 . .699 .391 .072 .111 .058 . .122 .089 Females 2 7 2 7 5 6 6 7 7 7 7 Female .270 .713 -.489 .636 .093 -.531 -.679 -.826* -.639 1.000 -.436 National .518 .001 .181 .005 .862 .175 .064 .022 .122 . .081 Parliament 8 18 9 18 6 8 8 7 7 18 17 Female Judges .069 -.512* .566 -.502* .101 .799* .850 .867* .686 -.436 1.000 .872 .035 .112 .040 .848 .017 .008 .012 .089 .081 . 8 17 9 17 6 8 8 7 7 17 17 *. Correlation is significant at the 0.05 level (2-tailed). a. COUNTRY = GUATEMALA
192 Spearman’s rho Correlation Mexico Correlationsa Female Femicide Male GDP per Armed Male Female Female National Female Homicide Legislation Homicide capita Gini Conflict Employment Employment Parliament Judges Spearman's Female Homicide 1.000 .376 .942** .161 .085 .141 -.352 .244 .435 -.262 rho . .167 .000 .567 .828 .615 .198 .380 .105 .346 15 15 15 15 9 15 15 15 15 15 Femicide .376 1.000 .410 .618** -.274 -.277 -.475* .618** .650** -.097 Legislation .167 . .115 .006 .476 .265 .047 .006 .003 .710 15 18 16 18 9 18 18 18 18 17 Male Homicide .942** .410 1.000 .347 .050 .031 -.437 .469 .485 -.126 .000 .115 . .188 .898 .908 .090 .067 .057 .641 15 16 16 16 9 16 16 16 16 16 GDP per capita .161 .618** .347 1.000 -.483 -.753** -.867** .881** .864** .493* .567 .006 .188 . .187 .000 .000 .000 .000 .045 15 18 16 18 9 18 18 18 18 17 Gini .085 -.274 .050 -.483 1.000 .518 .350 -.467 -.412 -.546 .828 .476 .898 .187 . .154 .356 .205 .271 .128 9 9 9 9 9 9 9 9 9 9 Armed Conflict .141 -.277 .031 -.753** .518 1.000 .778** -.610** -.709** -.584* .615 .265 .908 .000 .154 . .000 .007 .001 .014 15 18 16 18 9 18 18 18 18 17 Male -.352 -.475* -.437 -.867** .350 .778** 1.000 -.733** -.910** -.453 Employment .198 .047 .090 .000 .356 .000 . .001 .000 .068 15 18 16 18 9 18 18 18 18 17 Female .244 .618** .469 .881** -.467 -.610** -.733** 1.000 .818** .501* Employment .380 .006 .067 .000 .205 .007 .001 . .000 .041 15 18 16 18 9 18 18 18 18 17 Female National .435 .650** .485 .864** -.412 -.709** -.910** .818** 1.000 .432
193 Parliament .105 .003 .057 .000 .271 .001 .000 .000 . .083 15 18 16 18 9 18 18 18 18 17 Female Judges -.262 -.097 -.126 .493* -.546 -.584* -.453 .501* .432 1.000 .346 .710 .641 .045 .128 .014 .068 .041 .083 . 15 17 16 17 9 17 17 17 17 17 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). a. COUNTRY = MEXICO
194 Spearman’s rho Correlation Ecuador Correlationsa GDP Precarious Females Female Male per Employment Employment Precarious Employ National Female Homicide Homicide capita Gini Males Females Employ Males Females Parliament Judges Spearman's Female 1.000 .476 .515* -.182 .463 .646** .157 .717** .501 .409 rho Homicide . .062 .041 .552 .071 .007 .576 .003 .057 .363 16 16 16 13 16 16 15 15 15 7 Male Homicide .476 1.000 -.237 .471 .776** .672** .096 .655** -.333 -.426 .062 . .360 .089 .000 .003 .724 .006 .207 .293 16 17 17 14 17 17 16 16 16 8 GDP per capita - .515* -.237 1.000 -.093 .128 .212 .150 .890** .494 .849** .041 .360 . .000 .722 .626 .431 .579 .000 .177 16 17 18 14 17 17 16 16 17 9 Gini -.182 .471 -.849** 1.000 .352 .062 -.316 -.075 -.825** -.250 .552 .089 .000 . .217 .834 .271 .799 .000 .550 13 14 14 14 14 14 14 14 14 8 Employment .463 .776** -.093 .352 1.000 .868** .350 .829** -.255 -.250 Males .071 .000 .722 .217 . .000 .184 .000 .340 .550 16 17 17 14 17 17 16 16 16 8 Employment .646** .672** .128 .062 .868** 1.000 .287 .868** -.016 .000 Females .007 .003 .626 .834 .000 . .281 .000 .954 1.000 16 17 17 14 17 17 16 16 16 8 Precarious .157 .096 .212 -.316 .350 .287 1.000 .419 .102 -.200 Employ Males .576 .724 .431 .271 .184 .281 . .106 .708 .634 15 16 16 14 16 16 16 16 16 8 Precarious .717** .655** .150 -.075 .829** .868** .419 1.000 .048 -.325 Employ Females .003 .006 .579 .799 .000 .000 .106 . .861 .432
195 15 16 16 14 16 16 16 16 16 8 Female National - .501 -.333 .890** -.255 -.016 .102 .048 1.000 .475 Parliament .825** .057 .207 .000 .000 .340 .954 .708 .861 . .196 15 16 17 14 16 16 16 16 17 9 Female Judges .409 -.426 .494 -.250 -.250 .000 -.200 -.325 .475 1.000 .363 .293 .177 .550 .550 1.000 .634 .432 .196 . 7 8 9 8 8 8 8 8 9 9 *. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed). a. COUNTRY = ECUADOR
196 Spearman’s rho Correlation Nicaragua
Intimate GDP Precarious Precarious Female Female Femicide Male Partner per Male Female Employ Employ National Female Homicide Legislation Homicide Femicide Femicide capita Employment Employment Males Females Parliament Judges Spearman's Female 1.000 -.338 .534* -.699 -.636 -.486 -.162 .009 .515 .296 -.070 -.658 rho Homicide . .201 .033 .054 .124 .056 .678 .983 .105 .377 .804 .227 16 16 16 8 7 16 9 9 11 11 15 5 Femicide -.338 1.000 -.447 .646* .822** .646** .522 .522 . . .637** .853* Legislation .201 . .072 .044 .007 .004 .122 .122 . . .006 .031
16 18 17 10 9 18 10 10 11 11 17 6
Male .534* -.447 1.000 -.900** -.833* -.010 -.200 -.527 .840** .527 .042 -.971** Homicide .033 .072 . .001 .010 .970 .580 .117 .001 .096 .878 .001 16 17 17 9 8 17 10 10 11 11 16 6 Intimate -.699 .646* -.900** 1.000 .650 .709* .543 .600 -.872 .300 .654* .853* Partner .054 .044 .001 . .058 .022 .266 .208 .054 .624 .040 .031 Femicide 8 10 9 10 9 10 6 6 5 5 10 6 Femicide -.636 .822** -.833* .650 1.000 .983** 1.000** .900* -.316 1.000** .915** .912* .124 .007 .010 .058 . .000 . .037 .684 . .001 .011 7 9 8 9 9 9 5 5 4 4 9 6 GDP per -.486 .646** -.010 .709* .983** 1.000 .794** .127 .315 .518 .691** .912* captia .056 .004 .970 .022 .000 . .006 .726 .345 .102 .002 .011 16 18 17 10 9 18 10 10 11 11 17 6 Gini -.200 . -.400 1.000** . .200 -1.000 1.000 -1.000 -1.000 -.500 . .800 . .600 . . .800 . . . . .667 . 4 4 4 2 1 4 2 2 2 2 3 1 Male -.162 .522 -.200 .543 1.000** .794** 1.000 .309 -.667 .429 .280 1.000** Employment .678 .122 .580 .266 . .006 . .385 .102 .337 .466 .
197 9 10 10 6 5 10 10 10 7 7 9 3 Female .009 .522 -.527 .600 .900* .127 .309 1.000 -.180 .821* .630 1.000** Employment .983 .122 .117 .208 .037 .726 .385 . .699 .023 .069 . 9 10 10 6 5 10 10 10 7 7 9 3 Precarious .515 . .840** -.872 -.316 .315 -.667 -.180 1.000 .671* .462 -1.000 Employ .105 . .001 .054 .684 .345 .102 .699 . .024 .153 . Males 11 11 11 5 4 11 7 7 11 11 11 2 Precarious .296 . .527 .300 1.000** .518 .429 .821* .671* 1.000 .656* 1.000 Employ .377 . .096 .624 . .102 .337 .023 .024 . .028 . Females 11 11 11 5 4 11 7 7 11 11 11 2 Female -.070 .637** .042 .654* .915** .691** .280 .630 .462 .656* 1.000 .874* National .804 .006 .878 .040 .001 .002 .466 .069 .153 .028 . .023 Parliament 15 17 16 10 9 17 9 9 11 11 17 6 Female -.658 .853* -.971** .853* .912* .912* 1.000** 1.000** -1.000** 1.000** .874* 1.000 Judges .227 .031 .001 .031 .011 .011 . . . . .023 . 5 6 6 6 6 6 3 3 2 2 6 6
198 Spearman’s rho Correlation Belize Correlationsa Female Male VAW GDP per Male Female Female National Female Homicide Homicide Legislation capita Employment Employment Parliament Judges Spearman's Female Homicide 1.000 .471 .491 .487 .400 .800 -.516* .113 rho . .065 .054 .055 .600 .200 .041 .688
16 16 16 16 4 4 16 15 Male Homicide .471 1.000 .415 .471 .400 .800 -.307 .009
.065 . .098 .057 .600 .200 .231 .973
16 17 17 17 4 4 17 16
VAW .491 .415 1.000 .862 .775 .775 -.865 .686
Legislation .054 .098 . .000 .225 .225 .000 .003 16 17 18 18 4 4 18 16 GDP per capita .487 .471 .862 1.000 .800 1.000 -.723 .762 .055 .057 .000 . .200 . .001 .001 16 17 18 18 4 4 18 16 Male Employment .400 .400 .775 .800 1.000 .800 -.316 1.000 .600 .600 .225 .200 . .200 .684 . 4 4 4 4 4 4 4 3 Female Employment .800 .800 .775 1.000 .800 1.000 -.316 1.000 .200 .200 .225 . .200 . .684 . 4 4 4 4 4 4 4 3 Female National -.516* -.307 -.865 -.723 -.316 -.316 1.000 -.649 Parliament .041 .231 .000 .001 .684 .684 . .007 16 17 18 18 4 4 18 16 Female Judges .113 .009 .686 .762 1.000 1.000 -.649 1.000 .688 .973 .003 .001 . . .007 . 15 16 16 16 3 3 16 16 *. Correlation is significant at the 0.05 level (2-tailed).
199
Spearman’s rho Correlation Panama Correlationsa GDP Precarious Female Female Femicide Male per Male Female Precarious Employ National Female Homicide Legislation Homicide capita Gini Employment Employment Employ Males Females Parliament Judges Spearman's Female 1.000 . .724** .538* -.550* .566* .611* -.439 .524* -.205 -.561* rho Homicide . . .002 .038 .034 .028 .016 .102 .045 .483 .030
15 15 15 15 15 15 15 15 15 14 15 Femicide . 1.000 .196 .545* -.408 .375 .545* -.341 .443 .077 -.365
Legislation . . .466 .019 .104 .125 .019 .166 .066 .769 .164
15 18 16 18 17 18 18 18 18 17 16
Male - .724** .196 1.000 .873** .739** .854** -.613* .780** -.551* -.831** Homicide .859** .002 .466 . .000 .000 .001 .000 .012 .000 .033 .000 15 16 16 16 16 16 16 16 16 15 16 GDP per - .538* .545* .873** 1.000 .858** .962** -.799** .880** -.146 -.767** capita .983** .038 .019 .000 . .000 .000 .000 .000 .000 .577 .001 15 18 16 18 17 18 18 18 18 17 16 Gini -.550* -.408 -.859** -.983** 1.000 -.877** -.948** .796** -.879** .393 .748** .034 .104 .000 .000 . .000 .000 .000 .000 .132 .001 15 17 16 17 17 17 17 17 17 16 16 Male - .566* .375 .739** .858** 1.000 .931** -.902** .851** -.187 -.614* Employment .877** .028 .125 .001 .000 .000 . .000 .000 .000 .473 .011 15 18 16 18 17 18 18 18 18 17 16 Female - .611* .545* .854** .962** .931** 1.000 -.826** .926** -.138 -.716** Employment .948** .016 .019 .000 .000 .000 .000 . .000 .000 .597 .002 200 15 18 16 18 17 18 18 18 18 17 16 Precarious -.439 -.341 -.613* -.799** .796** -.902** -.826** 1.000 -.670** .025 .454 Employ Males .102 .166 .012 .000 .000 .000 .000 . .002 .923 .077 15 18 16 18 17 18 18 18 18 17 16 Precarious - .524* .443 .780** .880** .851** .926** -.670** 1.000 -.199 -.601* Employ .879** Females .045 .066 .000 .000 .000 .000 .000 .002 . .445 .014 15 18 16 18 17 18 18 18 18 17 16 Female -.205 .077 -.551* -.146 .393 -.187 -.138 .025 -.199 1.000 .743** National .483 .769 .033 .577 .132 .473 .597 .923 .445 . .002 Parliament 14 17 15 17 16 17 17 17 17 17 15 Female -.561* -.365 -.831** -.767** .748** -.614* -.716** .454 -.601* .743** 1.000 Judges .030 .164 .000 .001 .001 .011 .002 .077 .014 .002 . 15 16 16 16 16 16 16 16 16 15 16 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). a. COUNTRY = PANAMA
201 Spearman’s rho Correlation Peru Correlationsa Intimat e GDP Female Female Femicide Male Partner per Armed Male Female Precarious Precarious National Homicid Legislatio Homicid Femicid Femicid capit Confli Employme Employme Employ Employ Parliame Female e n e e e a Gini ct nt nt Males Females nt Judges Spearman's rho Female 1.000 . .772** .632 -.316 -.206 .039 .053 -.222 -.399 -.134 -.086 -.244 .091 Homicide . . .001 .368 .684 .480 .894 .856 .465 .177 .647 .771 .422 .758
14 14 14 4 4 14 14 14 13 13 14 14 13 14
Femicide . 1.000 . -.828* -.828* .545* -.408 .125 -.174 -.172 . . .152 .426 Legislation . . . .042 .042 .019 .104 .621 .552 .556 . . .560 .100 14 18 14 6 6 18 17 18 14 14 16 16 17 16 Male .772** . 1.000 -.200 -.800 -.073 .078 -.306 -.007 -.257 .306 .319 -.098 .419 Homicide .001 . . .800 .200 .804 .792 .287 .982 .396 .288 .266 .751 .136 14 14 14 4 4 14 14 14 13 13 14 14 13 14 Intimate .632 -.828* -.200 1.000 .829* -.771 .700 . .359 .154 -.400 .400 .339 -.700 Partner .368 .042 .800 . .042 .072 .188 . .553 .805 .600 .600 .510 .188 Femicide 4 6 4 6 6 6 5 6 5 5 4 4 6 5 Femicide - 1.000 -.316 -.828* -.800 .829* 1.000 .943* . .051 .564 .400 1.000** .555 -1.000** ** * .684 .042 .200 .042 . .005 . . .935 .322 .600 . .252 . 4 6 4 6 6 6 5 6 5 5 4 4 6 5 GDP per 1.00 - -.206 .545* -.073 -.771 -.943** .000 .733** .728** .556* .539* .668** .608* capita 0 .838** .480 .019 .804 .072 .005 . .000 1.000 .003 .003 .025 .031 .003 .012 14 18 14 6 6 18 17 18 14 14 16 16 17 16
202 Gini - .039 -.408 .078 .700 1.000** .838* 1.000 -.149 -.841** -.817** -.521* -.425 -.683** -.465 * .894 .104 .792 .188 . .000 . .568 .000 .001 .039 .101 .004 .070 14 17 14 5 5 17 17 17 13 13 16 16 16 16 Armed .053 .125 -.306 . . .000 -.149 1.000 .051 .051 -.492 -.492 -.152 -.332 Conflict 1.00 .856 .621 .287 . . .568 . .862 .863 .053 .053 .560 .208 0 14 18 14 6 6 18 17 18 14 14 16 16 17 16 Male .733* - -.222 -.174 -.007 .359 .051 .051 1.000 .912** .410 .396 .639* .203 Employme * .841** nt .465 .552 .982 .553 .935 .003 .000 .862 . .000 .165 .181 .019 .506 13 14 13 5 5 14 13 14 14 14 13 13 13 13 Female .728* - -.399 -.172 -.257 .154 .564 .051 .912** 1.000 .402 .377 .591* .109 Employme * .817** nt .177 .556 .396 .805 .322 .003 .001 .863 .000 . .174 .204 .033 .722 13 14 13 5 5 14 13 14 14 14 13 13 13 13 Precarious -.134 . .306 -.400 .400 .556* -.521* -.492 .410 .402 1.000 .952** .545* .354 Employ .647 . .288 .600 .600 .025 .039 .053 .165 .174 . .000 .036 .196 Males 14 16 14 4 4 16 16 16 13 13 16 16 15 15 Precarious -.086 . .319 .400 1.000** .539* -.425 -.492 .396 .377 .952** 1.000 .521* .260 Employ .771 . .266 .600 . .031 .101 .053 .181 .204 .000 . .047 .350 Females 14 16 14 4 4 16 16 16 13 13 16 16 15 15 Female .668* - -.244 .152 -.098 .339 .555 -.152 .639* .591* .545* .521* 1.000 .228 National * .683** Parliament .422 .560 .751 .510 .252 .003 .004 .560 .019 .033 .036 .047 . .413 13 17 13 6 6 17 16 17 13 13 15 15 17 15 Female .091 .426 .419 -.700 -1.000** .608* -.465 -.332 .203 .109 .354 .260 .228 1.000 Judges .758 .100 .136 .188 . .012 .070 .208 .506 .722 .196 .350 .413 .
203 14 16 14 5 5 16 16 16 13 13 15 15 15 16 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). a. COUNTRY = PERU
204 Spearman’s rho Correlation Paraguay Correlationsa
Intimate Partner VAW GDP Precarious Precarious Female Female Male Femicid Femicid Legislatio per Male Female Employ Employ National Female Homicide Homicide e e n capita Gini Employ Employ Males Females Parliament Judges Spearman's Female 1.000 .412 .739 .288 -.523* -.332 .511 -.715** -.672** .201 .226 -.614* -.673** rho Homicide . .113 .058 .531 .037 .209 .062 .003 .006 .472 .419 .015 .006 16 16 7 7 16 16 14 15 15 15 15 15 15 Male - .746 .412 1.000 .167 .024 -.157 -.029 -.496 .879** .799** -.843** -.827** Homicide .914** ** .113 . .693 .955 .546 .000 .001 .914 .051 .000 .000 .000 .000 16 17 8 8 17 17 15 16 16 16 16 16 16 Intimate .739 .167 1.000 .850** . -.333 .143 -.101 -.033 .283 .517 -.404 .000 Partner .058 .693 . .004 . .381 .736 .796 .932 .460 .154 .281 1.000 Femicide 7 8 9 9 9 9 8 9 9 9 9 9 8 Femicide .288 .024 .850** 1.000 . -.133 .143 -.176 .233 .100 .417 -.349 .109 .531 .955 .004 . . .732 .736 .650 .546 .798 .265 .358 .797 7 8 9 9 9 9 8 9 9 9 9 9 8 VAW - -.523* -.157 . . 1.000 .101 .561* .560* -.126 -.047 .462 .436 Legislatio .363 n .037 .546 . . . .691 .183 .019 .019 .630 .857 .062 .091 16 17 9 9 18 18 15 17 17 17 17 17 16 GDP per - capita -.332 -.914** -.333 -.133 .101 1.000 .721 -.053 .482* -.966** -.872** .825** .808** ** .209 .000 .381 .732 .691 . .002 .840 .050 .000 .000 .000 .000 16 17 9 9 18 18 15 17 17 17 17 17 16
205 Gini - 1.00 .511 .746** .143 .143 -.363 -.538* -.832** .693** .604* -.858** -.750** .721** 0 .062 .001 .736 .736 .183 .002 . .047 .000 .004 .017 .000 .002 14 15 8 8 15 15 15 14 14 15 15 15 14 Male - Employm -.715** -.029 -.101 -.176 .561* -.053 .538 1.000 .548* .095 .084 .108 .330 ent * .003 .914 .796 .650 .019 .840 .047 . .023 .728 .757 .690 .212 15 16 9 9 17 17 14 17 17 16 16 16 16 Female - Employm -.672** -.496 -.033 .233 .560* .482* .832 .548* 1.000 -.447 -.450 .701** .768** ent ** .006 .051 .932 .546 .019 .050 .000 .023 . .082 .080 .003 .001 15 16 9 9 17 17 14 17 17 16 16 16 16 Precarious - .693 .201 .879** .283 .100 -.126 .095 -.447 1.000 .844** -.800** -.731** Employ .966** ** Males .472 .000 .460 .798 .630 .000 .004 .728 .082 . .000 .000 .002 15 16 9 9 17 17 15 16 16 17 17 16 15 Precarious - .604 .226 .799** .517 .417 -.047 .084 -.450 .844** 1.000 -.749** -.714** Employ .872** * Females .419 .000 .154 .265 .857 .000 .017 .757 .080 .000 . .001 .003 15 16 9 9 17 17 15 16 16 17 17 16 15 Female - National -.614* -.843** -.404 -.349 .462 .825** .858 .108 .701** -.800** -.749** 1.000 .917** Parliamen ** t .015 .000 .281 .358 .062 .000 .000 .690 .003 .000 .001 . .000 15 16 9 9 17 17 15 16 16 16 16 17 15 Female - Judges -.673** -.827** .000 .109 .436 .808** .750 .330 .768** -.731** -.714** .917** 1.000 ** 206 .006 .000 1.000 .797 .091 .000 .002 .212 .001 .002 .003 .000 . 15 16 8 8 16 16 14 16 16 15 15 15 16 *. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed). a. COUNTRY = PARAGUAY
207 Spearman’s rho Correlation Uruguay Correlationsa Intimate GDP Precarious Precarious Female Female Male Partner per Male Female Employ Employ National Female Homicide Homicide Femicide Femicide capita Gini Employment Employment Males Females Parliament Judges Spearman's Female 1.000 -.303 -.500 -.500 -.304 -.011 -.331 -.247 .083 -.183 -.275 -.086 rho Homicide . .292 .667 .667 .291 .971 .269 .417 .798 .569 .342 .780 14 14 3 3 14 13 13 13 12 12 14 13 Male -.303 1.000 1.000** .800 .336 -.495 .170 .025 -.152 -.396 .338 -.304 Homicide .292 . . .200 .221 .072 .562 .931 .621 .180 .218 .290 14 15 4 4 15 14 14 14 13 13 15 14 Intimate -.500 1.000** 1.000 .829* .714 -.486 -.314 -.174 .588 -.886* .516 . Partner .667 . . .042 .111 .329 .544 .742 .219 .019 .295 . Femicide 3 4 6 6 6 6 6 6 6 6 6 6 Femicide -.500 .800 .829* 1.000 .071 -.429 -.600 -.232 .294 -.886* .037 . .667 .200 .042 . .879 .397 .208 .658 .571 .019 .937 . 3 4 6 7 7 6 6 6 6 6 7 6 GDP per - -.304 .336 .714 .071 1.000 .884** .882** -.878** -.229 .617** -.164 capita .621* .291 .221 .111 .879 . .010 .000 .000 .000 .413 .006 .544 14 15 6 7 18 16 16 16 15 15 18 16 Gini -.011 -.495 -.486 -.429 -.621* 1.000 -.248 -.427 .324 .745** -.150 .590* .971 .072 .329 .397 .010 . .372 .112 .259 .002 .580 .021 13 14 6 6 16 16 15 15 14 14 16 15 Male -.331 .170 -.314 -.600 .884** -.248 1.000 .895** -.851** .123 .570* .103 Employment .269 .562 .544 .208 .000 .372 . .000 .000 .661 .021 .705 13 14 6 6 16 15 16 16 15 15 16 16 Female -.247 .025 -.174 -.232 .882** -.427 .895** 1.000 -.804** .111 .557* .082 Employment .417 .931 .742 .658 .000 .112 .000 . .000 .694 .025 .762
208 13 14 6 6 16 15 16 16 15 15 16 16 Precarious - .083 -.152 .588 .294 .324 -.851** -.804** 1.000 .075 -.603* .227 Employ .878** Males .798 .621 .219 .571 .000 .259 .000 .000 . .790 .017 .415 12 13 6 6 15 14 15 15 15 15 15 15 Precarious -.183 -.396 -.886* -.886* -.229 .745** .123 .111 .075 1.000 .030 .363 Employ .569 .180 .019 .019 .413 .002 .661 .694 .790 . .915 .183 Females 12 13 6 6 15 14 15 15 15 15 15 15 Female -.275 .338 .516 .037 .617** -.150 .570* .557* -.603* .030 1.000 -.308 National .342 .218 .295 .937 .006 .580 .021 .025 .017 .915 . .246 Parliament 14 15 6 7 18 16 16 16 15 15 18 16 Female -.086 -.304 . . -.164 .590* .103 .082 .227 .363 -.308 1.000 Judges .780 .290 . . .544 .021 .705 .762 .415 .183 .246 . 13 14 6 6 16 15 16 16 15 15 16 16 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). a. COUNTRY = URAGUAY
209 Spearman’s rho Correlation Suriname Correlationsa Female Intimate Partner Female Seats in Homicide Male Homicide Femicide GDP per capita National Parliament Female Judges Spearman's Female Homicide 1.000 .403 .357 .337 -.099 .444 rho . .121 .385 .202 .725 .097 16 16 8 16 15 15 Male Homicide .403 1.000 -.167 .271 -.523* .491 .121 . .693 .311 .046 .063 16 16 8 16 15 15 Intimate Partner Femicide .357 -.167 1.000 .455 -.536 .162 .385 .693 . .187 .110 .678 8 8 10 10 10 9 GDP per capita .337 .271 .455 1.000 -.326 .808 .202 .311 .187 . .201 .000 16 16 10 18 17 16 Female Seats in National -.099 -.523* -.536 -.326 1.000 -.439 Parliament .725 .046 .110 .201 . .102 15 15 10 17 17 15 Female Judges .444 .491 .162 .808 -.439 1.000 .097 .063 .678 .000 .102 . 15 15 9 16 15 16 *. Correlation is significant at the 0.05 level (2-tailed). a. COUNTRY = SURINAME
210 Spearman’s rho Correlation Venezuela Correlationsa Female GDP Seats in Femicide VAW per Armed Male Female Precarious Precarious National Female Legislatio Male Legislatio capit Conflic Employmen Employmen Employ Employ Parliamen Female Homicide n Homicide n a Gini t t t Males Females t Judges Spearman' Female 1.000 .320 .751** .428 .061 .310 -.428 -.252 .677* -.018 .121 .330 .052 s rho Homicide . .287 .003 .145 .843 .456 .145 .482 .032 .953 .695 .294 .873 13 13 13 13 13 8 13 10 10 13 13 12 12 Femicide .840* .320 1.000 .706** .217 . -.217 .093 .869** -.220 -.684** .614** .837** Legislation * .287 . .005 .387 .000 . .387 .742 .000 .397 .002 .009 .000 13 18 14 18 16 8 18 15 15 17 17 17 16 Male .751** .706** 1.000 .378 .512 .262 -.378 .127 .927** -.477 -.354 .763** .618* Homicide .003 .005 . .182 .061 .531 .182 .709 .000 .084 .214 .002 .024 13 14 14 14 14 8 14 11 11 14 14 13 13 VAW - .428 .217 .378 1.000 .308 . -.186 .435 .102 .306 .390 . Legislation 1.000** .145 .387 .182 . .246 . . .507 .106 .697 .232 .121 . 13 18 14 18 16 8 18 15 15 17 17 17 16 GDP per .061 .840** .512 .308 1.000 -.405 -.308 .066 .807** -.256 -.572* .716** .806** capita .843 .000 .061 .246 . .320 .246 .830 .001 .338 .020 .003 .000 13 16 14 16 16 8 16 13 13 16 16 15 15 Gini 1.00 .310 . .262 . -.405 . -.400 -.600 .120 .024 -.152 -.048 0 .456 . .531 . .320 . . .505 .285 .778 .955 .719 .910 8 8 8 8 8 8 8 5 5 8 8 8 8 Armed -.428 -.217 -.378 -1.000** -.308 . 1.000 .186 -.435 -.102 -.306 -.390 . Conflict .145 .387 .182 . .246 . . .507 .106 .697 .232 .121 . 211 13 18 14 18 16 8 18 15 15 17 17 17 16 Male -.252 .093 .127 -.186 .066 -.400 .186 1.000 .280 -.642* -.346 .257 .141 Employmen .482 .742 .709 .507 .830 .505 .507 . .312 .013 .226 .374 .645 t 10 15 11 15 13 5 15 15 15 14 14 14 13 Female .807* .677* .869** .927** .435 -.600 -.435 .280 1.000 -.550* -.541* .754** .693** Employmen * t .032 .000 .000 .106 .001 .285 .106 .312 . .042 .046 .002 .009 10 15 11 15 13 5 15 15 15 14 14 14 13 Precarious -.018 -.220 -.477 .102 -.256 .120 -.102 -.642* -.550* 1.000 .556* -.604* -.300 Employ .953 .397 .084 .697 .338 .778 .697 .013 .042 . .021 .013 .259 Males 13 17 14 17 16 8 17 14 14 17 17 16 16 Precarious - .121 -.684** -.354 .306 .024 -.306 -.346 -.541* .556* 1.000 -.490 -.884** Employ .572* Females .695 .002 .214 .232 .020 .955 .232 .226 .046 .021 . .054 .000 13 17 14 17 16 8 17 14 14 17 17 16 16 Female .716* .330 .614** .763** .390 -.152 -.390 .257 .754** -.604* -.490 1.000 .556* National * Parliament .294 .009 .002 .121 .003 .719 .121 .374 .002 .013 .054 . .031 12 17 13 17 15 8 17 14 14 16 16 17 15 Female .806* .052 .837** .618* . -.048 . .141 .693** -.300 -.884** .556* 1.000 Judges * .873 .000 .024 . .000 .910 . .645 .009 .259 .000 .031 . 12 16 13 16 15 8 16 13 13 16 16 15 16 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). a. COUNTRY = VENEZUELA
212 Spearman’s rho Correlation Jamaica Correlationsa Intimate GDP Precarious Precarious Female Female Male Partner per Male Female Employ Employ National Female Homicides Homicides Femicide capita Employment Employment Males Females Parliament Judges Spearman's Female 1.000 .569 -1.000 .297 -.866 -.866 -.334 .411 -.447 .623 rho Homicides . .110 . .437 .333 .333 .380 .272 .315 .073 9 9 2 9 3 3 9 9 7 9 Male .569 1.000 -.500 .335 -.400 .000 .034 -.040 -.150 .585 Homicides .110 . .667 .343 .600 1.000 .926 .913 .723 .076 9 10 3 10 4 4 10 10 8 10 Intimate -1.000 -.500 1.000 -.483 -.314 -.143 .086 .899* -.334 -.527 Partner . .667 . .187 .544 .787 .872 .015 .419 .145 Femicide 2 3 9 9 6 6 6 6 8 9 GDP per capita .297 .335 -.483 1.000 -.600 -.033 -.048 -.593* -.081 .915 .437 .343 .187 . .088 .932 .869 .026 .775 .000 9 10 9 18 9 9 14 14 15 16 Male -.866 -.400 -.314 -.600 1.000 .733* -.821* -.306 .109 -.702* Employment .333 .600 .544 .088 . .025 .023 .504 .816 .035 3 4 6 9 9 9 7 7 7 9 Female -.866 .000 -.143 -.033 .733* 1.000 -.643 -.324 -.164 -.182 Employment .333 1.000 .787 .932 .025 . .119 .478 .726 .639 3 4 6 9 9 9 7 7 7 9 Precarious -.334 .034 .086 -.048 -.821* -.643 1.000 .223 .560 .114 Employ .380 .926 .872 .869 .023 .119 . .444 .073 .710 Males 9 10 6 14 7 7 14 14 11 13 Precarious .411 -.040 .899* -.593* -.306 -.324 .223 1.000 .369 -.497 Employ .272 .913 .015 .026 .504 .478 .444 . .264 .084 Females 9 10 6 14 7 7 14 14 11 13
213 Female -.447 -.150 -.334 -.081 .109 -.164 .560 .369 1.000 -.095 National .315 .723 .419 .775 .816 .726 .073 .264 . .757 Parliament 7 8 8 15 7 7 11 11 15 13 Female Judges .623 .585 -.527 .915 -.702* -.182 .114 -.497 -.095 1.000 .073 .076 .145 .000 .035 .639 .710 .084 .757 . 9 10 9 16 9 9 13 13 13 16 *. Correlation is significant at the 0.05 level (2-tailed). a. COUNTRY = JAMAICA
214 Spearman’s rho Correlation Cuba Correlationsa Female Male GDP per Male Female Female National Female Homicides Homicides capita Employment Employment Parliament Judges Spearman's Female Homicides 1.000 .675* -.656* .281 -.156 -.662* .224 rho . .016 .020 .501 .713 .019 .718 12 12 12 8 8 12 5 Male Homicides .675* 1.000 -.206 -.135 -.783* -.142 .494 .016 . .499 .729 .013 .643 .320 12 13 13 9 9 13 6 GDP per capita -.656* -.206 1.000 .908** .768** .966** .741 .020 .499 . .000 .002 .000 .092 12 13 17 13 13 17 6 Male Employment .281 -.135 .908** 1.000 .848** .902** .334 .501 .729 .000 . .000 .000 .518 8 9 13 13 13 13 6 Female Employment -.156 -.783* .768** .848** 1.000 .742** -.741 .713 .013 .002 .000 . .004 .092 8 9 13 13 13 13 6 Female National -.662* -.142 .966** .902** .742** 1.000 .810 Parliament .019 .643 .000 .000 .004 . .050 12 13 17 13 13 18 6 Female Judges .224 .494 .741 .334 -.741 .810 1.000 .718 .320 .092 .518 .092 .050 . 5 6 6 6 6 6 6 *. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed). a. COUNTRY = CUBA
215
Spearman’s rho Correlation Dominica Correlationsa Female Intimate Partner Female National Homicides Male Homicides Femicide GDP per capita Parliament Female Judges Spearman's rho Female Homicides 1.000 .500 .621 .188 -.083 .390 . .082 .100 .538 .787 .187 13 13 8 13 13 13 Male Homicides .500 1.000 .134 .349 -.406 .202 .082 . .752 .243 .169 .508 13 13 8 13 13 13 Intimate Partner .621 .134 1.000 .452 -.064 -.158 Femicide .100 .752 . .261 .880 .709 8 8 8 8 8 8 GDP per capita .188 .349 .452 1.000 .054 .470 .538 .243 .261 . .838 .066 13 13 8 18 17 16 Female National -.083 -.406 -.064 .054 1.000 .156 Parliament .787 .169 .880 .838 . .579 13 13 8 17 17 15 Female Judges .390 .202 -.158 .470 .156 1.000 .187 .508 .709 .066 .579 . 13 13 8 16 15 16 a. COUNTRY = DOMINICA
216
Spearman’s rho Correlation Bahamas Correlationsa Female Male VAW GDP per Male Female Female National Homicide Homicide Legislation capita Employment Employment Parliament Spearman's Female Homicide 1.000 .475 .232 -.164 -.754 -.406 -.321 rho . .140 .492 .629 .084 .425 .366 11 11 11 11 6 6 10 Male Homicide .475 1.000 .759 -.056 -.829* -.543 -.772 .140 . .004 .863 .042 .266 .005 11 12 12 12 6 6 11 VAW Legislation .232 .759 1.000 .525* -.732* -.282 -.734 .492 .004 . .025 .039 .499 .001 11 12 18 18 8 8 17 GDP per capita -.164 -.056 .525* 1.000 -.167 .310 -.169 .629 .863 .025 . .693 .456 .518 11 12 18 18 8 8 17 Male Employment -.754 -.829* -.732* -.167 1.000 .714* .722 .084 .042 .039 .693 . .047 .067 6 6 8 8 8 8 7 Female Employment -.406 -.543 -.282 .310 .714* 1.000 .289 .425 .266 .499 .456 .047 . .530 6 6 8 8 8 8 7 Female National -.321 -.772 -.734 -.169 .722 .289 1.000 Parliament .366 .005 .001 .518 .067 .530 . 10 11 17 17 7 7 17 *. Correlation is significant at the 0.05 level (2-tailed). a. COUNTRY = BAHAMAS
217 Spearman’s rho Correlation Barbados Correlationsa Female Male GDP per Male Female Precarious Employ Precarious Employ Female National Homicides Homicides capita Employment Employment Males Females Parliament Spearman's Female Homicides 1.000 -.179 -.207 -.180 -.611 .100 -.462 -.138 rho . .578 .519 .670 .108 .873 .434 .668
12 12 12 8 8 5 5 12 Male Homicides -.179 1.000 .176 .750* .800 -.300 .616 .352 .578 . .566 .020 .010 .624 .269 .239 12 13 13 9 9 5 5 13 GDP per capita -.207 .176 1.000 -.569* .357 .881 .552 -.178 .519 .566 . .042 .231 .004 .156 .479 12 13 18 13 13 8 8 18 Male Employment -.180 .750* -.569* 1.000 .448 .108 .358 .271 .670 .020 .042 . .124 .799 .384 .371 8 9 13 13 13 8 8 13 Female -.611 .800 .357 .448 1.000 .595 .479 .123 Employment .108 .010 .231 .124 . .120 .230 .688 8 9 13 13 13 8 8 13 Precarious Employ .100 -.300 .881 .108 .595 1.000 .577 .756* Males .873 .624 .004 .799 .120 . .134 .030 5 5 8 8 8 8 8 8 Precarious Employ -.462 .616 .552 .358 .479 .577 1.000 .325 Females .434 .269 .156 .384 .230 .134 . .432 5 5 8 8 8 8 8 8 Female National -.138 .352 -.178 .271 .123 .756* .325 1.000 Parliament .668 .239 .479 .371 .688 .030 .432 . 12 13 18 13 13 8 8 18 *. Correlation is significant at the 0.05 level (2-tailed).
218 a. COUNTRY = BARBADOS
Spearman’s rho Correlation St Lucia Correlationsa Female Male VAW GDP per Male Female Female National Female Homicide Homicide Legislation capita Employment Employment Parliament Judges Spearman's Female Homicide 1.000 .514 -.062 .038 -.503 .286 .564 .441 rho . .050 .826 .894 .204 .493 .036 .114 15 15 15 15 8 8 14 14 Male Homicide .514 1.000 .093 .407 -.168 -.310 .170 .447
.050 . .742 .132 .691 .456 .562 .109 15 15 15 15 8 8 14 14 VAW Legislation -.062 .093 1.000 .862 .153 .267 .152 .772 .826 .742 . .000 .673 .456 .562 .000 15 15 18 18 10 10 17 17 GDP per capita .038 .407 .862 1.000 -.116 .304 .399 .898 .894 .132 .000 . .750 .393 .113 .000 15 15 18 18 10 10 17 17 Male Employment -.503 -.168 .153 -.116 1.000 -.410 -.283 -.162 .204 .691 .673 .750 . .240 .429 .656 8 8 10 10 10 10 10 10 Female Employment .286 -.310 .267 .304 -.410 1.000 .376 .242 .493 .456 .456 .393 .240 . .285 .501 8 8 10 10 10 10 10 10 Female National .564 .170 .152 .399 -.283 .376 1.000 .576 Parliament .036 .562 .562 .113 .429 .285 . .020 14 14 17 17 10 10 17 16 Female Judges .441 .447 .772 .898 -.162 .242 .576 1.000 .114 .109 .000 .000 .656 .501 .020 . 219 14 14 17 17 10 10 16 17 a. COUNTRY = STLUCIA
220
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