The Confluence of International Pressure and Domestic Mobilization: Wartime Sexual Violence and Gender Quota Adoption

MATTIAS AGERBERG

Department of Political Science, University of Gothenburg (mattias.agerberg@gu.se)

ANNE-KATHRIN KREFT

Department of Political Science, University of Gothenburg (anne-kathrin.kreft@gu.se)1

Abstract

Violent conflict is highly gendered, affecting women differently than men. Besides being particularly exposed to the indirect consequences of conflict, women are often targeted in sexual violence used by government forces and rebel groups alike. While this kind of violence is commonly, and justifiably, discussed in terms of its adverse physical and psychological effects, we propose that prevalent sexual violence in conflict also elicits domestic mobilization and international pressure. Specifically, our theory operates as follows. First, consolidating international gender norms are particularly salient in conflicts that are visibly gendered. Highly politicized in the last decades, sexual violence has emerged as the foremost gender issue in conflict on the radar of international actors. Hence, where sexual violence is prevalent, (normative) international pressure on governments to adopt gender policies is particularly strong. Second, perceiving an attack on their physical integrity, rights and sexual autonomy, women mobilize politically. They make demands for greater representation in, and influence on, politics with the goal of improving societal conditions for themselves. Jointly, the pressures from above and below may push governments in conflict-affected states towards adopting gender policies. Put differently, visibly gendered conflict produces gendered outcomes. We test this theoretical framework in the case of gender quota adoption. Our empirical analysis reveals that states with widespread wartime sexual violence indeed adopt gender quotas sooner and at higher rates than states experiencing other civil conflicts and than states experiencing no conflict in the same period. We also find evidence in support of both causal mechanisms, and for the effectiveness of the instituted gender quotas in increasing women’s legislative representation.

1 Author order is alphabetical. Both authors contributed equally to the manuscript.

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Introduction Conflict can be gendered across different dimensions. Although women have been ac-

tive participants in armed groups around the globe, as combatants or in support roles (Henshaw

2015; Shekhawat 2015; Thomas & Bond 2015), fighting and killing continues to be male-dom-

inated (Jones 2004; Ormhaug et al. 2009). This draws men away from civilian life, leaving

women as heads of households, to fend for themselves and their families. As a result, women

are disproportionately exposed to the indirect adverse consequences of conflict, such as dis-

placement, poverty, malnutrition or the collapse of social infrastructure (Buvinic et al. 2013).

Another way in which conflict can be gendered – risen exponentially on the international secu-

rity agenda since the wars in Bosnia and Rwanda – is the widespread use of sexual violence

against women. Existing data shows that armed actors perpetrate sexual violence regardless of

national and cultural context, and its prevalence can be massive (Cohen 2013a; Cohen & Nordås

2014a).

Despite these adverse consequences, gender scholars have documented patterns of in-

creased women’s political, economic and social activity, active mobilization, and upheavals in

gender roles and relations across a diverse range of conflicts (Anderson 2016; Berry 2015; Fuest

2008; Meintjes et al. 2001; Tripp 2015; Wood 2008). These transformations extend also to

national politics: statistical analyses reveal higher shares of women’s seats in national legisla-

tures among states that have emerged from high-intensity civil conflict (Hughes 2009; Hughes

& Tripp 2015). How is it possible that women derive such gains under the extremely dire con-

ditions of civil conflict, every-day violence and insecurity?

In this paper, we depart from the premise that gains in women’s agency oftentimes do

not accrue despite civil conflict, and the violence to which it exposes women, but because of it.

Specifically, we propose that in a context of evolving global gender norms, wartime sexual

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violence elicits international pressure and domestic mobilization that help bring about change

for women. As even the most casual observer of international politics will agree, wartime sexual

has come to be a very visible and salient gender issue in conflict due both to its classification

as a war crime and its global politicization.1 A series of United Nations Security Council reso-

lutions (1820, 1888, 1960, 2106) have raised awareness of the issue among the global public

and policy-makers and have helped erode taboos and stigma surrounding victimization. As a

result, sexual violence has prompted an increasing number of reactions from domestic and in-

ternational actors.

Our theoretical argument incorporates these as parallel pressures on the government

from above and from below during and in the aftermath of conflict with prevalent sexual vio-

lence. First, emerging but unconsolidated global norms of women’s participation find dispro-

portionate application in conflict settings that are perceived to be particularly gendered. Given

its global politicization, the prevalence of sexual violence becomes a heuristic for international

actors in determining the gendered nature of a conflict and, hence, the need for a gender-sensi-

tive response. In brief, we expect that the more visibly “gendered” a conflict is (i.e. the more

prevalent wartime sexual violence is), the more likely international actors are to encourage the

(post-)conflict government to adopt gender policies. Second, the global normative framework

also facilitates women’s collective mobilization in response to the threat to their security and

interests that wartime sexual violence constitutes, as demonstrated in previous work (Kreft

2017b). We develop this line of argument further, suggesting that such mobilization takes on a

1 We emphasize that we do not claim that sexual violence is necessarily the most prevalent or the gravest vio-lence women experience in conflict. Women are subjected to many other forms of conflict-related violence, in-cluding but not limited to torture, mutilation, displacement and killings. Neither do we condone a hierarchy of victims based on the kind of violence experienced. Our reasons for focusing on conflict-related sexual violence derive from its indisputably gendered nature. The focus in this paper on sexual violence against women should further not be understood to suggest that sexual violence does not also happen against men (Grey & Shepherd 2013; Oosterhoff et al. 2004) or that women do not also perpetrate sexual violence (Cohen 2013b).

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distinctly political character, with demands for women’s greater political influence becoming a

core demand in this mobilization.

Empirically testing the diffusion of gender norms or the transformation of domestic gen-

der relations is often fraught with difficulty. Reliable cross-national data are scarce, especially

going back in time. Fortunately, gender quotas are a suitable indicator to test our theoretical

framework. In theoretical terms, introducing gender quotas is a straightforward and relatively

low-effort government response to pressures for increased women’s political representation and

participation. From a methodological standpoint, gender quotas are easy to operationalize,

measure and quantify. In extending the analysis to women’s legislative representation in a sec-

ond step, we are also able to make a statement about the effectiveness of these quotas in en-

hancing women’s descriptive representation.

Our theoretical approach also resolves the conflicting results of previous scholarship

investigating the relationship between conflict and gender quota adoption. In her exploratory

examination of the introduction and effectiveness of gender quotas in Africa, Aili Marie Tripp

(2015: ch. 8) suggests that states emerging from long and high-intensity internal conflict are

more likely to adopt quotas and also have more effective quotas than states unaffected by such

war. Her book describes in great detail how women’s movements emerge, grow and demand

women’s representation and participation in conflict, reinforced by international actors support-

ing these demands. By contrast, Sarah Sunn Bush’s (2011) survival analysis of a global sample

provides no evidence that conflict itself is associated with quota adoption – rather, it is interna-

tional pressure in post-conflict states that emerges as the crucial factor.

Our premise is that when we consider gendered outcomes of conflict, here in the form

of gender quota adoption, we should also look at the gendered nature of conflict. In this sense,

it is not sufficient to capture conflict as a dichotomy (conflict or no conflict, as in Bush 2011)

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or a scale of intensity, in terms of battle deaths (as implied by Tripp 2015; quantitatively oper-

ationalized e.g. in Hughes and Tripp 2015 on women’s legislative representation). Turning the

focus to sexual violence as a particularly visible and salient indicator of gendered conflict, our

results show, has explanatory merit. Almost all quota adoptions in civil conflict countries oc-

curred in connection with conflicts where sexual violence was prevalent. We also show that

countries that experienced conflicts with high sexual violence were more prone to adopt legal

gender quotas than countries that did not experience civil conflict.

In problematizing the roles of both international and domestic actors in responding to a

prevalent and horrendous phenomenon in war, sexual violence, we also make two other contri-

butions. First, more closely examining the response of international actors affords insight into

the conditions under which global gender norms find application and into how competing pro-

tection and participation imperatives may undermine their universal implementation. Second,

our discussion of the domestic mobilization response contributes to recent research highlighting

women’s agency in the face of victimization.

Pressure from Above: International Gender Norms Existing research has demonstrated the important role international pressure can play in

bringing about gains for women, especially in the political sphere. Tripp (2015) finds that in-

ternational actors and pressures were instrumental to the success of the women’s movements in

Uganda and Liberia in transforming the political landscape for women after conflict. Marie E.

Berry (2015) makes similar observations for women’s political mobilization and claim-making

in post-genocide Rwanda. International presence and pressure have also been linked to the

adoption of gender quotas in states emerging from civil war (Bush 2011). Globally, the condi-

tions for increased women’s political representation and participation have steadily improved

since the early 1990s. A long process of theorizing and renegotiating the essence of human

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rights culminated in a broadening of the human rights discourse to explicitly subsume women’s

rights within its framework (Fraser 1999). Accordingly, the 1995 Beijing Declaration and Plat-

form for Action emphasized a commitment to “removing all the obstacles to women's active

participation in all spheres of public and private life through a full and equal share in economic,

social, cultural and political decision-making” (United Nations Treaty 2015: 7).

Sustained transnational activism resulted in the authorization of UN Security Council

Resolution 1325 (2000), which has since been a key source of women’s political empowerment

in (post-)conflict situations. UNSCR 1325 calls for enhancing the participation of women in

conflict resolution and the post-conflict order as well as for gender-sensitive peace operations.

The resolution has laid the groundwork for gender concerns, including gender equality and

women’s participation, to move from the sphere of soft policy to the hard policy realm of con-

flict and international security (Tryggestad 2009). After UNSCR 1325 was passed, procedural

changes in UN peacekeeping missions across contexts took off (Hudson 2005), references to

women in peace agreements increased (Bell & O'Rourke 2010), and a growing number of states

have developed national action plans of varying complexity based on the resolution (Gumru &

Fritz 2009). It is also increasingly common for UN peace operations to promote women’s par-

ticipation in the political process and to encourage the adoption of gender quotas, as Bush

(2011) illustrates. These patterns point to the important strengthening role international pressure

can play in enhancing women’s political representation in post-conflict settings.

This normative environment creates incentives for states experiencing or emerging from

civil war to signal a commitment to gender equality for two reasons: 1) because it comes along

with gains in prestige or status and 2) because states succumb to pressure by international actors,

including peace operations or international organizations and states providing multi- or bilateral

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aid. First, in complying with international gender norms, e.g. by adopting gender quotas, con-

flict-affected states may seek to enhance their position in the international social hierarchy and

signal a commitment to modernity (Towns 2012). This is a particularly useful strategy for gov-

ernments seeking to signal a break with a violent past in an effort to attract international good-

will and much-needed donor funding. Rwanda under Paul Kagame is the prime example of a

post-conflict regime successfully marketing itself as a promoter of gender equality and attract-

ing high amounts of foreign aid, following the 1994 genocide. In a similar vein, Bush (2011:

114-115) considers the adoption of gender quotas to be an important signal to the international

community of an ostensible commitment to liberal democracy – another normative force grow-

ing in international esteem and closely intertwined with principles of gender equality. In other

words, the emerging global normative framework surrounding women’s participation creates

incentives for governments to declare a commitment to women’s empowerment and represen-

tation, even in the absence of direct international pressures to adopt certain policies.

Second, western states earmark increasingly large sums of their official development

assistance for gender-related projects2 and gender concerns gain in prominence in foreign and

development policy. The OECD’s Development Assistance Committee, for example, treats

gender as a cross-cutting issue in international development policies and evaluates member

development policies accordingly (OECD 2014). USAID has a Gender Equality and Female

Empowerment Policy in place that applies to the entire development project cycle from policy

formulation to implementation (USAID 2012), while the European Union member states signed

a Gender Action Plan 2016-2020 emphasizing a “three-pronged approach through targeted ac-

tions, effective gender mainstreaming and political dialogue” in development policy (Union

2 http://www.oecd.org/dac/stats/aidinsupportofgenderequalityandwomensempowerment.htm

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2015: 6). The Nordic States and Canada in particular have an established reputation for empha-

sizing gender issues and women’s empowerment in their foreign and development policies,

with Sweden being the first state to officially adopt a feminist foreign policy in 2015 (Sweden

2017) and Canada recently committing to a feminist development policy.3 In this international

environment, the prospect of foreign aid pushes conflict-affected states to adopt some gender

equality priorities, while aid conditionality and technical development cooperation may serve

as an additional channel for the diffusion of global gender norms.

Yet another source of the diffusion of global gender norms in (post-)conflict states are

peace operations, which since the authorization of UNSCR 1325 are increasingly equipped with

mandates to help promote women’s participation in politics (Kreft 2017a). To situate these pro-

cesses in a more general context, situations of (post-conflict) political transition have been

deemed particularly amenable to the diffusion of international norms (Moravcsik 2000;

Simmons 2009). We are not arguing that these processes of norm diffusion necessarily entail

internalization or socialization; instead, governments of post-conflict states may choose to

adopt certain gender policies, such as quotas, for strategic reasons.

Naturally, our argument is temporally bounded. The global diffusion of gender quotas

began in the early 1990s (Towns 2012), paralleling the emergence of global gender norms sur-

rounding the Beijing Declaration and culminating in UNSCR 1325. In other words, only in the

period since 1990 have gender quotas become a tool available to states seeking to signal be-

longing to an international social order built increasingly around global norms of gender equal-

ity and women’s political participation.

3 http://international.gc.ca/world-monde/issues_development-enjeux_developpement/priorities-priorites/policy-politique.aspx?lang=eng

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Nonetheless, this normative commitment to women’s (political) participation remains

incomplete. A growing focus on sexual violence and women’s protection in global policy dis-

course and recent Security Council resolutions subsumed under the Women, Peace and Security

(WPS) framework risks distracting from the women’s participation prescriptions that were so

prominently entrenched in the original resolution 1325. Many of the follow-up UN Security

Council resolutions in the WPS framework (1820, 1888, 1960, 2106) do not emphasize the

importance of women’s participation alongside their need for protection. This raises the danger

of “diluting the crystallization of important norms on women, peace and security, which are

aimed at both empowering and protecting women” (Barrow 2010: 232).

The focus on protection, as juxtaposed with women’s participation, signifies also the

perseverance of traditional gender norms. This finds expression for example in persisting re-

sistance to gender equality within the United Nations system (Raven-Roberts 2005) and in

women peacekeepers’ preferential deployment to low-risk conflicts (Karim & Beardsley 2013).

Given this somewhat reluctant global commitment to women’s participation in (post-)conflict

settings, UNSCR 1325 has not yet been internalized by international actors and assumed “taken-

for-granted status,” i.e. its implementation remains variable and incomplete (Kreft 2017a: 138-

139).

Accordingly, Kreft (2017a) suggests that a “gendered” international response to a con-

flict is more likely when gender emerges as a particularly (visibly) salient issue in that conflict:

the likelihood of gender content in UN peacekeeping mandates is greater if a conflict has been

characterized by prevalent sexual violence. That sexual violence has emerged as a particularly

visible, globally mobilizing and even politicized gender issue in conflict is beyond a doubt. The

United Nations Security Council has passed several resolutions on wartime sexual violence

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specifically (1820, 1888, 1960, 2106), has since 2009 had a Special Representative of the Sec-

retary-General on Sexual Violence in Conflict in place, and hosts the inter-agency campaign

Stop Rape Now: UN Action Against Sexual Violence in Conflict. As a particularly illustrative

example at the country level, the UK hosted a celebrity-attended Global Summit to End Sexual

Violence in Conflict in 2014 and has with its Prevention of Sexual Violence Initiative been

heralded as a norm entrepreneur in the area of preventing sexual violence in conflict (Davies &

True 2017). International attention and responses to wartime sexual violence have reached such

levels that scholars have expressed concern that other kinds of violence or the underlying socio-

economic root causes of conflict are sidelined or ignored (Douma & Hilhorst 2012; Mertens &

Pardy 2017). Thus, in the international eye sexual violence has emerged as the gender issue in

conflict situations. We build on these insights to argue that the more evidently gendered a con-

flict is, in terms of the prevalence and “visibility” of sexual violence, the more likely interna-

tional actors are to initiate a gender-sensitive response to that conflict, and the more salient

global gender norms become also for the government in the conflict-affected state.

In sum, we expect that the consolidating international gender norms have a bearing on

conflict-affected states seeking to enhance their position in the international social hierarchy,

attract donor funding, and signal a commitment to liberalism and modernity. Given that the

global commitment to gender norms is still inconsistent, we expect stronger international (nor-

mative) pressure for gender quota adoption and increased women’s legislative representation

when gender emerges as a particularly salient issue in a conflict, i.e. when sexual violence is

prevalent. Yet, international actors are not the only source of pressure on governments in con-

flict-affected states. Previous scholarship has shown that women mobilize politically in a di-

verse set of conflict settings. We argue that one important driver of this mobilization is sexual

violence, owing to its indisputably gendered nature.

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Pressure from Below: Women’s Mobilization in Conflict A growing literature illustrates the many ways in which women frequently emerge as

resilient and transformative actors in conflict. Across civil wars, conflict dynamics and gen-

dered processes have yielded transformations in social institutions, interactions and networks,

including gender norms and relations (Wood 2008). Suddenly finding themselves heads of

households, women in different conflict settings assume greater responsibilities in the political,

social and economic spheres (Buvinic et al. 2013). Banding together to better cope with their

new realities during conflict, to put a stop to the fighting or to enhance their position in society,

women’s collective mobilization in vibrant movements or organizations is also a frequent fea-

ture of civil wars and their aftermaths (Anderson 2016; Berry 2015; Tripp 2015). These con-

testations of gender roles and transformations in gender norms are not limited to informal and

grass-roots developments.

Quantitative, cross-national studies have paid particular attention to gains in women’s

representation in the national legislature as a result of conflict. Employing cross-country OLS

regression, Melanie Hughes (2009) finds that for low-income states, a recent long, high-inten-

sity and center-seeking civil conflict is a better predictor of the share of women in the national

legislature in the year 2000 than any of the social and institutional indicators explaining

women’s representation in high-income democracies. A more sophisticated hierarchical growth

analysis of 48 African states between 1985 and 2010 (Hughes & Tripp 2015) likewise identifies

a link between high-intensity conflict and increased women’s legislative representation.

These two studies make an important contribution to our understanding of how conflict

may affect gender balances and relations in post-conflict politics. They suggest that the changed

gender roles and relations during war that the rich qualitative literature has identified have ram-

ifications extending spatially to high-level politics and temporally into the post-conflict period.

Yet, both studies look at conflict violence as a somewhat monolithic feature, focusing only on

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conflict intensity in terms of battle deaths. In addition, they consider gender quotas only as

control variables in their statistical models without empirically examining how they relate to

conflict. In this paper, we extend these investigations in two ways. First, we add greater nuance

by disaggregating the category “conflict” and focusing on the prevalence of wartime sexual

violence. Second, we examine in a first step the association between wartime sexual violence

and gender quota adoption and turn then, more briefly, to the question of women’s legislative

representation.

Our core theoretical “pressure from below” argument is that women mobilize politi-

cally in response to wartime sexual violence, which puts sustained pressure on governments to

increase women’s legislative representation. In developing this theoretical claim, we challenge

specifically existing explanations of women’s political gains during and after conflict, which

have prioritized demographic imbalances caused by male-dominated fighting on the one hand

and shifting opportunity structures for women on the other as core driving factors (Berry 2015;

Mazurana et al. 2005; Meintjes et al. 2001; Tripp 2015). Certainly, shifting gender roles arising

from shocks to the demographic make-up of societies – societies undergoing large-scale vio-

lence that changes people’s daily routines and needs, no less – will leave an imprint on women’s

agency. An absence of men, who in more patriarchal societies structure gender relations in both

private and public life, places new demands upon women in the economic, social and political

spheres in which they were previously marginalized. Nonetheless, we consider the sole focus

on the absence of men to be an incomplete explanation for women’s gains in agency. Women

in conflict also have urgent grievances of their own. In particular, women are vulnerable to

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sexual violence.4 We propose that women’s sustained mobilization in response to wartime sex-

ual violence results in demands for greater women’s influence on politics. The theoretical ar-

gument we lay out in the next section.

The Mobilizing Potential of Sexual Violence Sexual violence has been publicized in some conflicts more than in others – prominent

examples are the 1994 genocide in Rwanda, the conflict in Bosnia in the early 1990s or the civil

war in the Democratic Republic of the Congo since 1997. Yet, sexual violence in conflict takes

the form of a pervasive practice in many conflicts (Wood 2014). Recently aggregated datasets

reveal that sexual violence in conflict transcends regional, national and cultural boundaries,

types of conflict and is perpetrated by both state armies and rebel forces (Cohen 2013a; Cohen

& Nordås 2014b).

When sexual violence occurs on a large scale, it has tremendous consequences for the

actual and perceived safety of women, who face constant vulnerability in their communities

and their own homes (Leatherman 2011). Victims of sexual violence may experience a wide

range of adverse physical and psychological reactions, which may include infection with sex-

ually transmitted diseases, physical injury or disability, depression or suicidal intentions, and

social stigmatization (Stark & Wessells 2012). These adverse consequences of wartime sexual

violence are real, undeniable and worthy of extensive academic attention. Yet, women respond

to wartime sexual violence not only with trauma and passivity: cross-national statistical anal-

yses reveal evidence of women’s collective mobilization, in protests and women’s international

non-governmental organizations, in response to wartime sexual violence during conflict (Kreft

2017b).

4 Sexual violence in conflict occurs also against men, a phenomenon equally deserving of academic attention. As we do not expect sexual violence against men to be related to mobilization around women’s issues, however, it falls outside the scope of this paper.

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Accordingly, we theorize that women engage in collective mobilization, i.e. organize in

social movements or civil society organizations, in response to the threat to their security and

interests as women that wartime sexual violence constitutes. This expectation is in line with a

growing literature theorizing the mobilizing effects of threat (Almeida 2003; Berry 2015;

Goldstone & Tilly 2001; Johnson & Frickel 2011; Khawaja 1993; Loveman 1998; Shriver et

al. 2015; Tilly 1978; Van Dyke & Soule 2002). We hold with Kreft that mobilization occurs

also in response to the symbolic threat posed by sexual violence, even among women who may

not feel that their own bodily and sexual autonomy is immediately threatened: “an attack on

other women’s bodies and sexual autonomy is an attack both on the notion of women as indi-

viduals with rights and on women qua women” (2017b: 11). This means that mobilization does

not have to be thematically focused exclusively and narrowly on conflict-related sexual vio-

lence; it is likely to occur also more generally in response to the discrimination against women

in society and politics in which (sexual) violence against women is perceived to be rooted. A

second causal mechanism linking personal experiences of wartime sexual violence to political

mobilization may feed into collective mobilization: post-traumatic growth, i.e. personal growth

as the result of a cognitive re-evaluation of traumatic experiences (Tedeschi & Calhoun 2004).

In peacetime, this personal growth has resulted in increased civic and political activism among

some women victims of sexual violence (Burt & Katz 1987; Stidham et al. 2012).

Our theoretical expectation that women mobilize in response to wartime sexual violence

speaks also to a growing literature on the transformative effects of wartime violence. Historical,

experimental and survey-based studies in different cultural and regional settings have identified

associations between individual and community-level experiences of violence during conflict

and changes in political identities and increased pro-social behavior (Balcells 2012; Gilligan et

al. 2014; Voors et al. 2012) as well as increased political participation (Bellows & Miguel 2009;

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Luca & Verpoorten 2015; McDougal & Caruso 2012). The notion of transformative effects of

violence undergirds our theoretical framework, even though we are not able to subject this

mechanism to a systematic empirical test with available data.

Thus far, we have theorized that women mobilize in response to wartime sexual vio-

lence. This may take the form of organizing in victims’ associations, in humanitarian organiza-

tions more broadly conceived and in (feminist) women’s groups. What we have yet to formulate

is how and why we expect this mobilization to translate into the adoption of gender quotas and

women’s gains in national politics. How do we move from collective mobilization in civil so-

ciety to legal quota adoption? If our theoretical discussion captures reality reasonably well,

women who perceive a threat to their identities and interests in conflict situation will engage in

collective, contentious political action. Repeated violations of women’s rights, bodily auton-

omy and sexual self-determination will sow a desire for change. Politics is the crucial sphere to

which women need access in order to achieve legislative change guaranteeing their physical

integrity and their rights and liberties. The realization that status quo politics safeguards neither

peace nor women’s rights would then also spark specific activism to expand women’s political

access, representation and participation.

These patterns emerge e.g. in Tripp’s (2015) book on post-conflict politics in Africa, in

which she sketches how the women’s (peace) movements that emerged and grew during the

Ugandan and Liberian civil wars launched successful campaigns for an enhanced role of women

in the political sphere, including increased legislative representation. Women who organized

collectively during civil war sought to ensure that the changed gender roles and relations in

conflict were institutionalized when the violence had subsided and the conflict ended. Tripp

notes also that pressure from and lobbying of women’s organizations were important factors

affecting the implementation of legislative gender quotas in African states generally, and in

15

post-conflict states specifically. Her descriptive statistics suggest that such quotas are both more

likely to be adopted and more effective at increasing women’s legislative representation in Af-

rican states that emerged from conflict than in those that did not (ch. 8).

Likewise, in post-genocide Rwanda, women’s mobilization in grassroots groups to en-

sure basic needs were met soon transformed into more structured mobilization in official or-

ganizations, in demands and claim-making on the state, and in campaigns for enhanced political

representation and participation (Berry 2015). The 1990s in Colombia saw a surge in women’s

organizations, which mobilized around the gendered dimensions, outcomes and impacts of the

armed conflict and fundamentally shaped and transformed national political debates about the

conflict. The concerted efforts of women’s organizations were fundamental in expanding

women’s legislative representation and political influence and ensuring legislative change, in-

cluding the introduction of a gender quota in 2000 (Domingo et al. 2015). Miriam J. Anderson

(2016) similarly shows how cohesive women’s movements in different conflict settings have

used peace negotiations as a platform to make successful demands for greater representation

and participation. In sum, we argue that domestic women’s mobilization, sparked in large part

by wartime sexual violence, increases political interest among women, the supply of women

seeking political office, and demands of women’s organizations to facilitate the entry of women

into politics.

[Figure 1 about here]

In conjunction, international pressure and domestic women’s mobilization in situations

of conflict with prevalent sexual violence create incentives for governments to adopt gender

policies, such as gender quotas. We do not expect these macro-level patterns to diverge sub-

stantially based on whether the government or rebel groups perpetrate most of the sexual vio-

lence. For women, the threat to their security, interests and identity is real no matter who the

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perpetrators are. The international community, for its part, has been so focused on conflict-

related sexual violence as an egregious form of violence and a war crime that we do not expect

the identity of the perpetrators to play a role in international actors perceiving a conflict as

“gendered” and pushing for a gendered response. The confluence of pressures from below and

from above make the adoption of gender quotas more likely. These processes are visualized in

Figure 1. Based on these considerations, we develop the following hypotheses:

H1: States with conflicts with prevalent sexual violence adopt gender quotas sooner than

states emerging from conflicts with low or no reported sexual violence.

H2: States with conflicts with prevalent sexual violence adopt gender quotas sooner than

states not experiencing conflict in the same period.

Model and sample To test the empirical predictions of our hypotheses, we rely on event history modeling

(also called survival analysis). This is a statistical method frequently used in similar studies

(see Anderson & Swiss 2014; Bush 2011; Swiss & Fallon 2016). We apply a proportional haz-

ards model to estimate the likelihood of a quota being adopted in a country, given that it had

not already been adopted. The model allows us to estimate the effects of specific country char-

acteristics on the time to quota adoption, without having to assume a specific parametric form

for the distribution of the time until adoption (Box-Steffensmeier & Jones 2004). The propor-

tional hazards model parameterizes the hazard rate, ℎ(𝑡𝑡), in the following way:

ℎ(𝑡𝑡|𝑋𝑋𝑐𝑐) = ℎ0(𝑡𝑡)𝑒𝑒𝑋𝑋𝑐𝑐𝛽𝛽 (1)

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where ℎ0(𝑡𝑡) is an unspecified baseline hazard function. 𝑋𝑋𝑐𝑐 denotes a covariate matrix

for country c where one or more of the covariates may vary over time. Event history modeling

relies on creating a “risk set” of observations entering the analysis at a common starting point

and exiting the analysis either through experiencing the event (quota adoption in our case) or

by reaching the end of the analysis without experiencing the event.

In our analysis, countries enter the risk set at year 1990, the start of the global wave of

gender quota adoption (Towns 2012). Countries continue in the analysis until they adopt a quota

or reach the end point of the analysis period in 2013, having not adopted a quota. Following

Bush (2011), we exclude long-term consolidated and developed democracies from our analysis

to make the sample more homogenous.5 Our final sample consists of 136 countries with a total

of 2,642 country-year observations.

Dependent variable Our main dependent variable is quota adoption. We used the Global Database of Quotas

for Women (available at quotaproject.org) and collected data on the year of adoption of a na-

tional legal quota. We focus on national legislative quotas since the adoption of these theoret-

ically should be subject to both pressure from below (women’s political mobilization) and

above (as a signal in response to international pressure and norms). In total, 57 countries in our

sample adopted a legislative quota between 1990 and 2013. Countries reaching the end of the

analysis period without adopting a quota are right-censored.

Independent variable Our argument holds that quota adoption is more likely in states that have experienced

conflicts with high prevalence of sexual violence. We use data from Cohen (2013a) and the

Sexual Violence in Armed Conflict (SVAC) dataset (Cohen & Nordås 2014a) to code all civil

5 Our base sample is the same as in Bush (2011), only dropping in size due to missing data.

18

conflicts between 1990 and 2013 as either high sexual violence conflicts (HSVC) or low sexual

violence conflicts (LSVC). Both datasets code the occurrence of rape (Cohen) and sexual vio-

lence (SVAC) on an ordinal scale with the following categories: no reported sexual violence,

isolated sexual violence, widespread sexual violence and massive sexual violence. Cohen’s data

are coded qualitatively based on US State Department human rights reports whereas the SVAC

data are equivalently coded based on documents of the US State Department, Amnesty Inter-

national and Human Rights Watch. Whereas Cohen’s data capture any conflict-related rape

committed regardless of perpetrator, the SVAC dataset contains only sexual violence that can

be attributed to a specific perpetrator (government or rebel group). More information on coding

rules is available in the respective codebooks.

As the dividing lines between widespread and systematic sexual violence are hard to

establish, and in order to present a more straightforward analysis, we recoded the variables in

the following way: Countries get the coding no civil conflict for all years if no civil conflict

occurred and for the years before conflict onset, if a conflict occurred later in the analysis pe-

riod. A country is coded as an LSVC case from the year of conflict onset if no sexual violence

was reported during the conflict or if only isolated cases of sexual violence were reported.6

Countries are coded as an HSVC case from the year of conflict onset, if there were reports of

widespread or systematic occurrence of sexual violence during the conflict.7 8 The conflict

countries keep the conflict coding (LSVC or HSVC) throughout the analysis period, regardless

of whether the conflict is still ongoing or has ended. An example will illustrate the approach:

Burundi enters the analysis in 1990 as a no civil conflict country. The Burundian civil war broke

6 This corresponds to a coding of 0 (no sexual violence) or 1 (isolated reports) in the Cohen (2013a) and Cohen and Nordås (2014a) datasets. 7 In Cohen (2013a) and (Cohen & Nordås 2014a) this corresponds to a sexual violence coding of 2 (wide-spread/common) or 3 (systematic/massive). 8 We use the highest reported occurrence of sexual violence from either dataset to classify the conflicts.

19

out in 1993. During the 13 years long war there were many reports of widespread and systematic

sexual violence (see Cohen (2013a); Cohen and Nordås (2014a)). The country is thus coded as

an HSVC case from 1993 onwards, and stays in the analysis up until 2005, when a national

legislative gender quota was introduced with the new constitution.

Below, we consider a number of different coding decisions for this variable and show

that our results are not dependent on a specific coding choice with regard to the starting year,

post-conflict period etc.9 In total, 24 countries in our sample experienced an LSVC, 37 experi-

enced an HSCV, and 75 countries did not experience a civil conflict during the analysis period.

Control variables To account for differences in economic development between countries in our sample,

we include logged GDP per capita (in current (2015) US dollars). Research suggests that the

quality of democratic institutions is related to women’s political representation, and potentially

to quota adoption (Paxton et al. 2010). We include a measure of the level of democracy that is

a combination of data from Polity IV and Freedom House, for maximum coverage (Hadenius

& Teorell 2005). The measure ranges from 0 to 10 (most democratic). Bush (2011) argues that

quota adoption is often a result of particular types of international pressure. To account for this,

we control for foreign aid dependence in the form of logged total official development assis-

tance,10 and for whether a liberalizing UN peace operation was present in a country in a given

year. The latter variable is a dichotomous indicator adopted from Bush (2011).11 12 In line with

9 We also consider a number of additional potential codings in the Appendix. These include for example coding the variable based on the first reported occurrence of sexual violence in each conflict, and only coding the varia-ble for a 10-year post-conflict period. None of these variations affect our main results. 10 These data are available at www.oecd.org/dac. 11 Since Bush’s analysis period ends in 2006, we used the same methodology (see Bush 2011: 119) to code the variable up to 2013. 12 Bush’s (2011) argument about international pressure has some resemblance to our argument. We include De-velopment assistance and Peacekeeping operations as controls to be able to distinguish our argument from Bush’s. In general, we do not claim to have good direct measures of our proposed mechanisms, and do not at-tempt to model these mechanisms directly.

20

previous studies (see Thames & Williams 2013), we also control for regional quota diffusion.

This variable is measured year by year as the percentage of countries in a region with a legal

gender quota.

All covariates mentioned in the previous section vary over time. We also include a num-

ber of covariates that are constant over the analysis period. Several studies have argued that

proportional electoral systems are associated with the adoption of gender quotas (e.g. Dahlerup

& Freidenvall 2005). We therefore include a three-category variable indicating if a country has

a proportional, majoritarian or mixed electoral system. The most obvious problem for our anal-

ysis would be a variable that is strongly related to both the likelihood of quota adoption and to

civil war (referring to both the likelihood and the type of violence during civil war). As discussed

above, the intensity of civil conflict has been linked to growth in women’s political representa-

tion (Hughes 2009; Hughes & Tripp 2015). We include an indicator variable that equals 0 if a

country did not experience a civil conflict during the analysis period, 1 if a country experienced

a low-intensity civil conflict (1,000 or fewer battle-deaths all recorded years), and 2 if a country

experienced a high-intensity conflict during the analysis period (more than 1,000 recorded bat-

tle deaths in any year).13 Finally, we include two variables that potentially could be related to

the gendered nature of conflict and/or the likelihood of quota adoption: Islamic heritage and

women’s civil liberties in 1990. The inclusion of the former variable accounts for the fact that

Muslim countries may have stronger patriarchal orders in general (see Inglehart & Norris 2003).

This is a dichotomous variable adopted from Bush (2011). The women’s civil liberties variable

is taken from the Varieties of Democracy dataset (V-dem)14. It is an index based on the V-dem

13 This classification is established in the literature (see Melander et al. 2016). 14 www.v-dem.net.

21

country experts’ assessment of women’s freedom of domestic movement, right to private prop-

erty, freedom from forced labor, and access to justice.15 We use each country’s value on this

variable for the year 1990 to indicate women’s standing in society at the start of our analysis

period.

We also conduct a number of additional analyses with only conflict countries. This lets

us control for different variables specifically related to the nature of the conflict. Here, we con-

trol for conflict duration (in years), and whether the conflict had an ethnic dimension (coded 0

for no ethnic dimension, 1 if the ethnic dimension was ambiguous, and 2 for a strong ethnic

dimension to the conflict)16. For the analyses including only post-conflict countries, we include

two additional dichotomous variables: whether the conflict ended with a rebel victory, and if

the conflict ended with a peace agreement. These two variables are based on Kreutz (2010).

Results To get an overview of the data, we begin by plotting the survival function for different

categories of countries. “Survival” here refers to a country not adopting a gender quota. Figure

2 shows Kaplan-Meier estimates17 plotted by different country-groups.

[Figure 2 about here]

Plot 1 shows the survival function for the full sample. The graph shows that over 40

percent of the countries in the full sample had adopted a quota at the end of the analysis period.18

Plots 2 and 3 compare countries with and without a civil conflict. Plot 3 also differentiates the

civil conflict-countries by conflict intensity. It is clear that the survival curves in plots 2 and 3

follow the same pattern, and that the survival curves do not deviate substantially from each

15 See Lindberg et al. (2014) for a discussion of the V-dem data and methodology. 16 This variable is adopted from Cohen (2013a) and based on the work of Fearon and Laitin (2003). 17 See Hosmer et al. (2011). 18 The time-point “0” here refers to the first time the non-conflict countries appear in the sample. In most cases this is the year 1990. For the conflict countries 0 refers to the year of conflict onset (or 1990 in the cases when the conflict started earlier than 1990).

22

other. Plot 4 instead groups the conflict countries by LSCV and HSCV. The graph shows a clear

divergence between the groups: at the end of the analysis period about 30 percent of the LSVC-

countries had adopted a quota, while the share of HSVC-countries is about 80 percent. This

provides suggestive evidence in favor of our hypotheses: while civil conflict in general does

not seem to be strongly related to quota adoption, states experiencing civil conflicts with high

prevalence of sexual violence seem much more prone to adopt gender quotas. However, to rule

out alternative explanations, a more careful analysis is needed. We therefore now turn to the

regression models.

Table 1 reports the results for our main specifications of the event history analysis. We

report exponentiated coefficients, equaling the hazard ratio. “Hazard” here refers to the likeli-

hood of quota adoption in a given year. A hazard ratio of 1 indicates that the hazard rate is

unchanged after a one-step increase in the independent variable. A hazard ratio of less than 1

equals a decrease in the hazard rate, while a hazard ratio of more than one indicates an increase

(and hence an increased likelihood of quota adoption). Model 1 is our baseline model, including

only the sexual violence (SV) variable. The results suggest that compared to countries/years

with no civil conflict (the reference category) quota adoption is strongly positively associated

with HSVC. LSVC is negatively associated with quota adoption (�̂�𝛽 = 0.452), but the estimate

does not reach statistical significance (𝑝𝑝 = 0.112). Model 2 adds all covariates to the model.

Although this increases the standard errors for the HSVC estimate, the point estimate in model

2 is larger (�̂�𝛽 = 3.44,𝑝𝑝 = 0.024). The estimate suggests that quota adoption in a given year is

3.5 times more likely for countries/years in this category, compared to the “no conflict cate-

gory”. Model 3 codes the SV-variable only for the post-conflict period.19 Previous studies have

19 That is, the SV-variable takes on its value for LSVC or HSVC only after the conflict has ended. End years are based on Cohen (2013a) and Cohen and Nordås (2014a). The sample includes a few conflicts that were termi-nated in the late 80s. These countries still enter the analysis (and their post-conflict period) in year 1990 in this model.

23

suggested that this period is strongly associated with transformation for women’s legislative

representation (e.g. Hughes & Tripp 2015). This makes sense as with the end of conflict often

come changes in political systems and institutions. Considering only the post-conflict period

makes the HSVC estimate even stronger (�̂�𝛽 = 4.46,𝑝𝑝 = 0.002), while the estimate for LSVC

is basically unchanged. The control variables give some support for Bush’s (2011) overall ar-

gument: more foreign aid and liberalizing peacekeeping operations are in general positively

associated with quota adoption, although the estimates do not always reach statistical signifi-

cance. In line with previous research, proportional and mixed electoral systems are also posi-

tively associated with quota adoptions (Dahlerup & Freidenvall 2005).

[Table 1 about here]

To be able to control for variables more directly related to conflict characteristics, mod-

els 4 and 5 are restricted to conflict countries. Model 4 considers the conflict sample over the

entire analysis period, divided into HSVC-countries and LSVC-countries. Apart from control-

ling for aid flows and peacekeeping operations, this model also controls for whether the conflict

had an ethnic dimension. The results reinforce the findings from the previous models: the co-

efficient for HSVC (5.303) suggests that countries in this group were almost 5.5 times more

likely to adopt a gender quota in a given year, compared to the LSVC-group (which is now the

reference category). In model 5, each country enters the analysis at the year of conflict end.

This model is thus only concerned with the post-conflict period, and only includes conflicts that

ended between 1985 and 2013.20 This model also adds two covariates related to conflict termi-

nation: whether the conflict ended in rebel victory and if there was a peace agreement.21 In

20 Since we include fewer covariates in this model, we are able to extend the analysis period a few years back in time to include conflicts that were terminated in the late 80s. 21 Both variables are potentially related to large-scale transformations of the political system.

24

addition, this model also controls for the conflict duration. The coefficient for HSVC again

comes out strongly positive and highly significant.

In summary, the results in this section speak strongly in favor of our hypotheses. States

with conflicts where the prevalence of sexual violence is high are much more prone to adopt

gender quotas than both countries that did not experience civil conflict and countries that expe-

rienced conflicts where sexual violence did not play a major role. We also show that the main

results are not dependent on whether we consider the whole conflict period or only the post-

conflict years, or if we compare only conflict countries or use the full sample. Figure 3 illus-

trates the main findings based on model 2 from Table 1 by plotting the covariate-adjusted sur-

vival functions for different country-groups.

[Figure 3 about here]

On the Causal Mechanisms While prevalent wartime sexual violence emerges as a strong predictor of gender quota

adoption in the statistical analysis, the results only reveal macro-level patterns. Here, we present

evidence in support of our two causal mechanisms. In terms of increased international attention

and pressure in HSVCs, recent research shows that peacekeeping is more likely in conflicts

where sexual violence is prevalent than in conflicts where it is not (Kreutz & Cardenas 2017).

In order to gain greater empirical leverage on our theorized international (normative) pressure

mechanism, we combined data on references to wartime sexual violence in, and the gender

content of, UN peacekeeping operation mandates (Kreft 2017a) with wartime sexual violence

and gender quota adoption data (Appendix D). This juxtaposition reveals greater UN peace

operation presence in conflicts with prevalent sexual violence, higher attention to women's par-

ticipation in UNPKO mandates when sexual violence is explicitly acknowledged, and higher

rates of gender quota adoption when sexual violence is high, and here in particular when sexual

25

violence is explicitly acknowledged in UNPKO mandates. These patterns lend suggestive evi-

dence to our hypothesized causal mechanism of pressure from above and the greater salience

of global gender norms in HSVCs.

In practice, this international pressure can take different forms. In Kosovo, for example,

the interim administration UNMIK imposed a gender quota in 2000, which has since remained

in place.22 In the Democratic Republic of the Congo, the successive UN missions initiated col-

laborations with women’s civil society organizations with the goal of improving the electoral

process for women in 2004, providing research and recommendations to political parties.23 The

DRC adopted a gender quota in 2011. Collaboration with women’s civil society actors and

governments in order to enhance women’s political participation is a frequent feature of UN

missions, as e.g. in Liberia (UNMIL)24, Mali (MINUSMA)25 and Sudan (UNAMID)26. In all

cases, women’s political empowerment is mentioned alongside – or is even explicitly linked to

– the adverse consequences of conflict on women, in particular sexual and gender-based vio-

lence.

With questions of women’s mobilization in response to wartime sexual violence still

under-researched, our discussion of this mechanism is somewhat more tentative. First, it is

striking that all three cases analyzed in Tripp’s study of women’s agency and mobilization dur-

ing conflict (2015) were HSVC countries that subsequently adopted gender quotas. In two of

these in particular (Uganda and Liberia), Tripp identifies strong and effective domestic

women’s mobilization around gender issues and a greater role for women in political decision-

making, coupled with international actor involvement. Similar patterns have been observed in

22 https://www.ndi.org/sites/default/files/Gender-Assesment-report-eng.pdf (p. 9) 23 http://www.un.org/en/peacekeeping/documents/10year_impact_study_1325.pdf (p. 18) 24 https://unmil.unmissions.org/office-senior-gender-adviser 25 https://minusma.unmissions.org/en/mandate-gender-unit 26 https://unamid.unmissions.org/gender-advisory-unit

26

Colombia, where much women’s mobilization has occurred specifically around the gendered

nature of the armed conflict (Domingo et al. 2015). In Bosnia, women’s humanitarian organi-

zations transcending conflict lines and supporting women victims of the war, including but not

limited to sexual violence, emerged (Boric 1997). What began as humanitarian organizations

during the war assumed a more decidedly political agenda in the post-war period and were

instrumental in the fight for inclusion of a gender quota in the national election law of the post-

conflict order (Jennichen 2009).

In her study combining cross-national statistical analysis and qualitative interview data

in Colombia, Kreft (2017b) finds evidence of women’s mobilization in civil society organiza-

tions and protests in response to wartime sexual violence. In Colombia, some women’s organ-

izations, e.g. la Ruta Pacífica de las Mujeres and Mujeres en la Lucha, emerged specifically in

response to an upsurge in (especially sexual) violence against women. La Ruta has since dedi-

cated abundant efforts to documenting and making visible violence against women in the Co-

lombian conflict while simultaneously transforming the role and perception of women in the

armed conflict from that of victims to that of political actors for peace. Many of the major

women’s civil society organizations work also with victims’ associations all over the country,

several of which are composed of or include sizeable numbers of sexual violence victims.

Kreft’s interviews overall provide evidence in support of mobilization in response to threat and,

more suggestively, of post-traumatic growth.

This discussion lends support to our hypothesized causal mechanisms. There remain,

however, alternative explanations to be considered. The next section aims at dealing with what

we regard as the most important statistical challenges to our results.

27

Robustness The proportional hazards model, used in our empirical analysis, rests on the assumption

that the covariates are multiplicatively related (“proportional”) to the hazard. That is, the hazard

functions are assumed to be proportional over time. Fortunately, this assumption is testable

(Box-Steffensmeier & Jones 2004). One standard way of testing the proportional hazards (PH)

assumption is to look at the correlation between the (scaled) residuals of the model and some

function of time (see Box-Steffensmeier & Zorn 2001). The aggregated (across covariates) co-

variance between the residuals and survival time gives a global test for the PH-assumptions for

a model. A rejection of the null hypothesis is treated as evidence that the PH-assumption is

violated. The global test for our full model (model 2, Table 1) yields 𝑝𝑝 = 0.062, i.e. an almost

significant result (the full results are available in the Appendix). A closer examination of the

individual covariates shows that the conflict intensity-variable might violate the PH-assump-

tion. A common way of addressing this problem is to include an interaction effect between the

offending covariate and time27 (Box-Steffensmeier & Zorn 2001). Model 1 in Table 2 shows

the results for our main independent variable in the full model, with the added interaction be-

tween conflict intensity and time. Model 2 adds two more time interactions for the two next

likeliest offenders of the PH-assumptions, Foreign aid and Islamic heritage. The global PH-

test for these new specifications are also shown in the table. In sum, including the time interac-

tions does not change the results for the SV-variable, but makes the global PH-test nowhere

near significant.

Lastly, we add two more controls (keeping all three time interactions): first we include

regional dummies to account for the fact that the occurrence of civil conflicts (and also the

27 Here we include time as a linear variable.

28

adoption of gender quotas) often have been regionally concentrated (for example to Sub-Sa-

haran Africa). In the final model, we include an indicator variable for whether a country was

involved in an interstate conflict during the analysis period.28 Several countries that experi-

enced a civil conflict during the analysis period were also involved in interstate conflicts (like

Ethiopia and Iraq), and we want to make sure that this does not affect our results. As shown in

the results for models 3 and 4, adding these additional controls does not change our main results.

Additional robustness checks are available in the Appendix.

Quota effectiveness in civil-conflict countries We have demonstrated that quota adoption is strongly associated with conflicts with

high prevalence of sexual violence. One natural question to ask is if these quotas actually in-

creased women’s political representation. While several studies have found that gender quotas

can have positive effects on women’s numerical presence in national legislatures (e.g. Tripp &

Kang 2008), other studies show that this is not always the case (Hughes 2009; Paxton et al.

2010). In this section, we briefly consider the question of whether the high frequency of quota

adoption in HSVC-countries resulted in a higher presence of women in national legislatures.

Figure 4 shows the development in the share of women in parliament from 1997 (the

year from which the majority of our sample is covered in the data) to 2013, for the different

country groups.

[Figure 4 about here]

It is clear from Figure 4 that the improvement in women’s political representation has

been most pronounced in HSVC-countries. From 1997 to 2013 the share of women in parlia-

ment grew from about 8 to 20 percent in this group. To account for potential confounding fac-

tors behind this increase, we specify a number of growth curve models, estimating the “effect

28 This variable was coded based on the V-dem expert data and the SVAC dataset.

29

of time” in different country groups. For details and exact model specifications, see the Appen-

dix.

The results, shown in Table 3, indicate that non-conflict years (the reference category)

on average are associated with a 0.6 percentage point growth in female political representation

(model 1). The interaction effect shows that the average growth is estimated to be significantly

higher in the HSVC category by about 0.27 percentage points (0.610 + 0.270 = 0.88 in total).

Adding the controls in model 2 does not substantially affect the results. Model 3 adds a time-

interaction with an indicator equaling 1 if a country had a legislative quota in a given year. The

results indicate that the average growth was 0.34 percentage points higher during years where

countries had a gender quota. The inclusion of this variable also makes the HSVC-interaction

insignificant. This suggests that the higher growth in the HSVC group may be attributable to

the higher frequency of quota adoption in this group. All in all, this provides suggestive evi-

dence that the quotas (at least partly) managed to improve women’s political representation.

[Table 3 about here]

Conclusions Our results strongly suggest that when considering certain outcomes, all civil conflicts

are not the same. In particular, our argument proposes that when considering gendered out-

comes, one has to take the gendered nature of conflicts into account. In this paper, we focus on

wartime sexual violence as a very visible indicator of gendered conflict and on gender quota

adoption as a gendered outcome. For the purpose of statistical analysis, gender quotas have the

dual benefit of being easily quantifiable and having clear gender implications. The reasons for

considering sexual violence as a dimension of gendered conflict are two-fold. First, wartime

sexual violence has received unprecedented levels of global attention in recent years, in partic-

ular since the authorization of UNSCR 1325 on Women, Peace and Security and its follow-up

30

resolutions. In conjunction with the reluctant consolidation of global women’s participation

norms, we propose, this has made sexual violence a heuristic for international actors in deter-

mining the gendered nature of a conflict and the need for a “gendered” response and resolution.

Second, wartime sexual violence constitutes a particularly salient grievance for women, both

because of the severity of the violence and because it targets women specifically as women.

Guided by theories emphasizing the mobilizing effect of threat, we argue that wartime sexual

violence elicits women’s collective mobilization around an array of women’s issues, including

demands to expand women’s political access, representation and participation.

In conjunction, we argue, international (normative pressures) and domestic (mobiliza-

tion) responses to wartime sexual violence urge governments to adopt gender quotas in or after

conflict. We test the empirical predictions of this theory, using survival analysis to model gen-

der quota adoption among countries that did not experience conflict, countries that experienced

conflict with low prevalence of sexual violence and countries that had conflicts with high prev-

alence of sexual violence between 1990 and 2013.

The difference between conflicts with high prevalence of sexual violence and conflicts

where sexual violence did not play a major role is striking: Out of the 31 conflict-countries that

adopted a gender quota during our analysis period, 27 are countries that experienced a conflict

with widespread sexual violence. Our analysis shows that this pattern cannot easily be explained

by other factors, like conflict intensity or pre-conflict levels of gender equality. Our analysis

also shows that HSVC-countries were more likely to adopt a gender quota than countries that

did not experience a civil conflict during the analysis period. The results are strong both sub-

stantively and statistically and provide evidence in favor of both H1 and H2, which qualitative

and descriptive statistical evidence further corroborates. Finally, we have provided suggestive

evidence that these quotas actually did improve female political representation: the recent

31

growth in the share of women in parliament in HSVC-countries is clear (Figure 4), and our

analysis suggests that quotas played an important part in this improvement.

Simultaneously, our study exposes the limitations of global gender norms and their uni-

versal application. Our theory expects international pressure for women’s political participation

to be stronger when conflict is gendered in a very visible way, i.e. when sexual violence is

widespread. Our empirical results lend support to this notion. Yet how suitable a heuristic is

sexual violence for determining how gendered a conflict really is? The focus on sexual violence

in public awareness and policy discourse has reached such dimensions that it has been described

as fetishization (Meger 2016), all but obscuring other forms of gender-based violence (Douma

& Hilhorst 2012; Meger 2016; Mertens & Pardy 2017). Interesting questions in this context are

to what extent domestic and international understandings of the central gender issues in con-

flicts align, where domestic women’s organizations and international (aid) priorities clash, and

what the implications for our results are. Future research may e.g. take a closer look at how

effective gender quotas and women’s increased descriptive representation in conflict-affected

states are at addressing gender inequalities, discrimination and violence against women.

32

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38

Figure 1. Model of wartime sexual violence and quota adoption.

39

Figure 2. Estimated survival function for different groups of countries.

0.00

0.25

0.50

0.75

1.00

0 105 15 20 25

All countries

(1)

0.00

0.25

0.50

0.75

1.00

0 105 15 20 25

No civil conflict

Civil conflict

(2)0.

000.

250.

500.

751.

00

0 105 15 20 25

No civil conflict Low-int. con.

High-int. con.

(3)0.

000.

250.

500.

751.

00

0 105 15 20 25

No civil conflict LSVC

HSVC

(4)

Prop

ortio

n w

ith n

o qu

ota

Analysis time

Kaplan-Meier survival estimates

40

Table 1. Civil conflict and quota adoption Full sample Conflict countries

(1) (2) (3) (4) (5) HSVC 2.726*** 3.442** 4.460*** 5.303*** 6.990*** (3.71) (2.26) (3.15) (3.44) (3.24) LSVC 0.452 0.430 0.422 Ref Ref

(-1.59) (-1.45) (-1.61)

No civil conflict Ref Ref Ref

GDP/capita (logged) 1.001 0.999 (0.01) (-0.01)

Level of democracy 1.023 0.977 (0.37) (-0.37)

High-intensity conflict 0.445 0.485 0.875 0.909 (-1.35) (-1.49) (-0.34) (-0.14) Low-intensity conflict 0.674 0.756 Ref Ref (-0.71) (-0.67)

No civil conflict Ref Ref Peacekeeping operation 2.244* 2.035 2.874** 0.687

(1.81) (1.37) (2.05) (-0.48) Foreign aid (logged) 1.196* 1.199* 1.357** 1.339

(1.92) (1.71) (2.12) (1.03) Regional quota diffusion 1.018 1.022* (1.56) (1.85)

Islamic heritage 1.185 1.132 (0.58) (0.40)

Women's civil liberties (1990) 0.733 0.440 (-0.46) (-1.19)

Proportional electoral system 3.358*** 4.126*** (3.64) (3.83)

Mixed electoral system 2.350** 3.095***

(2.38) (2.81)

FPTP Ref Ref Conflict duration 1.026

(0.57) Ambiguous ethnic dimension 0.505 0.314 (-1.33) (-1.35) Ethnic dimension 0.750 0.563

(-0.71) (-0.82) No ethnic dimension Ref Ref

Rebel victory 1.724

(0.60) Peace agreement 1.770

(0.82)

N 2642 2642 2642 989 466 Countries 136 136 136 55 38 Log likelihood -253.6 -240.9 -240.5 -96.22 -49.15 Note: Exponentiated coefficients. Z-statistics in parentheses. Estimated from Cox proportional hazard regressions using robust standard errors and the Efron method for ties. HSVC and LSVC in model 3 is coded only for the post-conflict pe-riod. Model 4 contains only conflict countries, and model 5 is estimated for the post-conflict period in countries where the civil conflict ended during the analysis period. * p < 0.1, ** p < 0.05, *** p < 0.01.

41

Figure 3. Covariate-adjusted survival functions for different groups of coun-tries. Based on model 2, Table 1.

.2.4

.6.8

1C

ovar

iate

adj

. sur

viva

l fun

ctio

n

0 10 205 2515Analysis time

No civil conflict LSVCHSVC

42

Table 2. Robustness checks

1 time- interaction

(1)

3 time- interactions

(2)

Regions control

(3)

International con. control

(4) HSCV 4.199* 4.170* 3.478* 4.261*

(1.75) (1.95) (1.74) (1.79)

LSCV 0.387 0.416 0.349 0.469

(-1.12) (-1.10) (-1.36) (-0.90)

No civil conflict Ref Ref Ref Ref

Time interactions 1 3 3 3

Full controls Yes Yes Yes Yes

N 2642 2642 2642 2642

Countries 136 136 136 136

Log likelihood -233.5 -230.0 -218.1 -226.8 Note: Exponentiated coefficients. Z-statistics in parentheses. Estimated from Cox proportional hazard regressions using robust standard errors and the Efron method for ties. Control variables are identical to model 2, Table 1. Conflict intensity is interacted with time in all models. Model 2-4 also adds Foreign aid and Islamic heritage as time-interactions. Model 3 controls for Geographical region, and model 4 controls for whether a country was involved in an International conflict during the analysis period. * p < 0.1, ** p < 0.05, *** p < 0.01.

43

Figure 4. Growth in female political representation over the analysis period.

510

1520

Wom

en in

par

liam

ent (

%)

1995 2000 2005 2010 2015Year

No civil conflict LSVCHSVC

44

Table 3. Growth curve models (1) (2) (3) Time 0.610*** 0.571*** 0.482***

(0.0599) (0.0637) (0.0631)

HSVC * Time 0.270** 0.251** 0.126

(0.114) (0.110) (0.100)

LSVC * Time -0.0578 -0.0522 0.00567

(0.106) (0.111) (0.113)

Gender quota * Time 0.342***

(0.128)

Controls No Yes Yes

N 2111 2111 2111

Countries 134 134 134

Log likelihood -5773.6 -5760.0 -5728.4 Note: Models estimated using hierarchical modeling, including random intercept and random slope (Time) effects.. Ro-bust standard errors clustered at the country level shown in parentheses. Control variables include GDP/Capita (logged), Level of democracy, Conflict intensity, Women’s civil liberties (1990), Electoral system, and Islamic heritage. * p < 0.1, ** p < 0.05, *** p < 0.01.

Appendix A – Descriptive statistics

Table 5. Included countries.

Country Civil conflict Quota Country Civil conflict Quota Country

Civil conflict Quota

Afghanistan HSVC 2004 Guatemala LSVC Qatar Albania Guinea LSVC Romania Algeria HSVC 2012 Guinea-Bissau LSVC Russia HSVC Angola HSVC 2005 Guyana 2000 Rwanda HSVC 2003 Argentina 1991 Haiti HSVC 2012 Sao Tome and Principe Armenia 1999 Honduras 2000 Saudi Arabia Azerbaijan LSVC Hungary Senegal HSVC 2010 Bangladesh HSVC 2004 India HSVC Seychelles Barbados Indonesia HSVC 2003 Sierra Leone HSVC Belarus Iran LSVC Slovakia Benin Iraq HSVC 2005 Slovenia 2005 Bhutan Israel LSVC Solomon Islands Bolivia 1997 Ivory Coast HSVC Somalia HSVC 2004 Bosnia and Herze-govina HSVC 2000 Jamaica South Africa LSVC Botswana Jordan 2003 Sri Lanka LSVC Brazil 1997 Kazakhstan Sudan HSVC 2008 Bulgaria Kenya 1997 Suriname Burkina Faso 2009 Korea, South 2004 Swaziland 2005 Burma Myanmar HSVC Kyrgyzstan 2011 Syria LSVC Burundi HSVC 2004 Laos Tajikistan HSVC Cambodia LSVC Latvia Tanzania 1995 Cameroon Lebanon LSVC Thailand LSVC Cape Verde 2010 Lesotho 2005 Togo Central African Republic HSVC Liberia HSVC 2005 Trinidad and Tobago Chad LSVC Libya HSVC 2012 Tunisia Chile Macedonia 2002 Turkey LSVC China LSVC 2007 Madagascar Turkmenistan Colombia HSVC 2011 Malawi Uganda HSVC 1995 Comoros Malaysia Ukraine Congo, Democratic Republic of HSVC 2011 Maldives Uruguay 2009 Congo, Republic of the HSVC 2007 Mali LSVC Uzbekistan HSVC 2004 Costa Rica 1996 Mauritania 2012 Vanuatu Croatia LSVC Mauritius Venezuela Cuba Mexico 2002 Vietnam Cyprus Moldova Yemen LSVC Czech Republic Mongolia 2011 Zambia Djibouti HSVC 2002 Morocco LSVC 2011 Zimbabwe HSVC 2013 Dominican Republic 1997 Mozambique HSVC Namibia Ecuador 1997 Nepal HSVC 2007 Egypt Nicaragua LSVC 2012 El Salvador LSVC 2013 Niger 2000 Eritrea Nigeria LSVC Estonia Pakistan HSVC 2002 Ethiopia HSVC Panama 1997

Fiji Papua New Guinea HSVC

Gabon Paraguay 1996 Gambia Peru HSVC 1997 Georgia HSVC 2011 Philippines LSVC Ghana Poland Note: LSVC/HSVC refers to low- and high sexual violence conflicts, respectively. Quota refers to the year a country adopted a law regarding a gender quota in the national parliament.

Table 6. Descriptive statistics

Obs Mean Std. Dev. Min Max

GDP/Capita (log) 4471 7.153906 1.291802 3.513131 11.4797 Level of democracy 4324 5.055625 3.099755 0 10 Peacekeeping operation 4932 0.0227088 0.1489888 0 1 Foreign aid (log) 4542 4.587565 1.867534 0 10.00256 Quota diffusion 4742 12.67673 17.80232 0 75 Islamic heritage 4932 0.2919708 0.454715 0 1 Women's civil liberties (1990) 4861 0.5602663 0.2599226 0.0186818 0.9589177 Women in parliament (%) 2400 14.35414 9.653285 0 63.8 International conflict 4932 0.1581509 0.3649194 0 1 Gender quota 4723 0.1514139 0.3611205 0 1

Obs Percent

Civil conflict No conflict 3291 67.60 LSVC 642 13.19 HSVC 935 19.21 Conflict intensity No conflict 2952 59.85 Low-intensity 684 13.87 High-intensity 1296 26.28 Electoral system FPTP 2088 42.34 Proportional 1872 37.96 Mixed 972 19.71

Table 7. Proportional hazards test

𝝆𝝆 𝝌𝝌𝟐𝟐 𝑷𝑷 > 𝝌𝝌𝟐𝟐 HSVC 0.15638 0.53 0.4682

LSVC -0.13150 0.43 0.5113

GDP/capita (logged) -0.02124 0.03 0.8733

Level of democracy -0.06404 0.26 0.6115

High-intensity conflict 0.38073 4.82 0.0281

Low-intensity conflict 0.31928 4.80 0.0284

Peacekeeping operation 0.04650 0.09 0.7594

Foreign aid (logged) -0.17051 2.03 0.1538

Regional quota diffusion -0.15567 1.60 0.2059

Islamic heritage 0.20402 2.22 0.1365

Women's civil liberties (1990) -0.00783 0.00 0.9575

Proportional electoral system -0.04977 0.16 0.6912

Mixed electoral system -0.08893 0.53 0.4682

Global test 21.59 0.0620

Note: Test based on model 2, Table 1.

Appendix B - Additional robustness checks

To further check the reliability of our results we consider a number of additional different speci-fications and codings in addition to our main results. We re-estimate our full event-history model (model 2 , Table 1), with all control variables included, but several different variations. The results from these robustness checks are reported in Table 8.

Table 8. Additional robustness checks

First occurrence of SV

(1)

10-yr post-conf. period

(2)

Only 10-yr post-conf. period

(3)

Krook quota-codings

(4) HSVC 3.769** 2.775*** 5.258*** 4.320** (Ref: No civil conflict) (2.48) (2.60) (3.75) (2.25) LSVC 0.407 0.157* 0.260 0.463

(-1.57) (-1.83) (-1.30) (-1.13) Full controls Yes Yes Yes Yes

N 2642 2642 2642 2597 Countries 136 136 136 136 Log likelihood -239.3 -241.5 -241.3 -210.6 Note: Exponentiated coefficients. Z-statistics in parentheses. Estimated from Cox proportional hazard regressions using robust standard errors and the Efron method for ties. Control variables are identical to model 2, Table 1. Model 1 codes the SV-variable based on the first reported occurrence of sexual violence. Model 2 uses the main SV-variable coding (model 2, Table 1), but limits the post-conflict period to 10 years. In Model 3 the SV-variable is coded only for a 10-year post-conflict period. Model 4 uses the main SV-variable coding (model 2, Table 1), but codes quota adoption based on Krook (2009). * p < 0.1, ** p < 0.05, *** p < 0.01.

Models 1-3 considers different coding choices for the main independent variable (the SV-varia-

ble). In model 1 the SV-variable takes on value 0 for non-conflict countries/years. At the conflict onset the variable takes on value 1 (LSCV). In HSCV-countries the variable takes on value 2 (HSVC) from the first year where widespread or systematic sexual violence was reported, and onwards. The difference compared to the main coding (model 2, Table 1) is that some conflicts start out as LSVC but then changes to HSVC (after the first reports of widespread or systematic sexual violence). In model 2 the SV-variable keeps it “conflict coding” (LSVC or HSVC) up to 10 years after the conflict was terminated (and not indefinitely). This affects conflicts that ended early in our analysis period. For example, a con-flict that ended in 1995 is coded as LSVC or HSVC from the conflict onset, up until 2005. Model 3 limits the SV-variable only to a 10-year post-conflict period. This means that only conflicts that ended during our analysis period (38 in total) are coded as non-zero, and only for a 10-year post-conflict period. All conflict-years are thus coded as zero. Neither of these coding decisions affect the main results. It is worth noting that the most conservative coding of the SV-variable (model 3) gives the strongest coeffi-

cient (𝛽𝛽� = 5.343, 𝑝𝑝 = 0.000). Model 4 uses the main coding of the SV-variable but instead considers a slight variation of the

coding of the quota-variable. Our main quota-coding considers the year where a formal legislative quota law was passed in a country (based on information obtained from the Quota Project). As a robustness

check, we compared our codings to Krook (2009: 227-238).1 In some cases identifying the exact year of adoption for a quota is not straightforward and our main coding regarding the adoption-year differs from Krooks in some cases (15 cases in total). For example, political parties in Morocco made an “hon-orary agreement” in 2002 which reserved 30 seats for women in lower house. This quota regulation was codified in the new electoral law in 2011 (increasing the number of reserved seats to 60). We code the “year of adoption” in this case as 2011, while Krook (2009) codes it as 2002. For the robustness check we use Krook’s quota-codings in all cases where our codings differ. The estimates from model 4 show that this variation does not change our main results.

We also consider a different coding of the conflict intensity variable. Instead of using the ordinal variable, we use the log of the highest number of battle deaths recorded in a single year during the conflict. The variable is based on data from Cohen (2013) and Cohen and Nordås (2014). This gives us a more nuanced measure of conflict intensity. Using this new measure we re-estimate model 4 from Table 1. While we lose a few observations due to missing data, our main results are intact; this, again, suggests that conflict intensity is not a threat to our main findings.

Table 9. Controlling for battle deaths

Only conflict

countries HSVC 6.359***

(Ref: LSVC) (3.41)

Peacekeeping operation 3.058**

(2.15)

Foreign aid (logged) 1.322*

(1.76)

Ambiguous ethnic dimension 0.543

(Ref: No ethnic dimension) (-1.20)

Ethnic dimension 0.744 (-0.66) Max battle deaths (logged) 0.951

(-0.44)

N 930

Countries 51

Log likelihood -80.94 Note: Exponentiated coefficients. Z-statistics in parenthe-ses. Estimated from Cox proportional hazard regressions using robust standard errors and the Efron method for ties. Control variables are identical to model 2, Table 1. * p < 0.1, ** p < 0.05, *** p < 0.01.

Lastly, we consider a disaggregated version of the SV-variable. Here we use the original catego-

ries from Cohen (2013) and Cohen and Nordås (2014), distinguishing between no civil conflict, civil conflict with no sexual violence, isolated cases of sexual violence, widespread sexual violence and sys-tematic sexual violence. The results, presented in Table 10, goes in the expected direction: compared to

1 We looked at the tables ”Reserved seats” and “Legislative quotas in single or lower houses of parliament”, and the “Year adopted” for each quota.

countries with no civil conflict, quota adoption is much more common in connection to conflicts with widespread or systematic sexual violence.

Table 10. Disaggregated sexual violence

Sexual vio-lence disaggre-

gated Civil conflict (No SV) 0.598

(Ref: No civil conflict) (-0.67)

Isolated SV 0.327

(-1.51)

Widespread SV 3.140**

(1.95)

Systematic SV 4.204**

(2.25)

Full controls Yes

N 2642

Countries 136

Log likelihood -240.5 Note: Exponentiated coefficients. Z-statistics in parenthe-ses. Estimated from Cox proportional hazard regressions using robust standard errors and the Efron method for ties. Control variables are identical to model 2, Table 1. * p < 0.1, ** p < 0.05, *** p < 0.01.

Appendix C - Growth curve models

The full specification for the growth model (model 3, Table 3) is the following:

𝑦𝑦𝑐𝑐𝑐𝑐 = 𝛽𝛽0𝑐𝑐 + 𝛽𝛽1𝑐𝑐𝑡𝑡 + 𝛽𝛽2𝑆𝑆𝑆𝑆𝑐𝑐𝑐𝑐 + 𝛽𝛽3𝑄𝑄𝑐𝑐𝑐𝑐 + 𝛾𝛾1(𝑆𝑆𝑆𝑆𝑐𝑐𝑐𝑐 × 𝑡𝑡) + 𝛾𝛾2(𝑄𝑄𝑐𝑐𝑐𝑐 × 𝑡𝑡) + 𝑋𝑋′𝑐𝑐𝑐𝑐𝜆𝜆 + 𝜀𝜀𝑐𝑐𝑐𝑐 , (2) 𝛽𝛽0𝑐𝑐 = 𝛿𝛿00 + 𝑈𝑈0𝑐𝑐 , 𝛽𝛽1𝑐𝑐 = 𝜂𝜂10 + 𝑆𝑆1𝑐𝑐 .

where 𝑦𝑦𝑐𝑐𝑐𝑐 is the share of women in the national parliament in country c at time t, 𝑆𝑆𝑆𝑆𝑐𝑐𝑐𝑐 is an indicator of conflict (no conflict, LSVC or HSVC) in country c at time t, and 𝑄𝑄𝑐𝑐𝑐𝑐 is an indicator of whether country c had a gender quota at time t. (𝑆𝑆𝑆𝑆𝑐𝑐𝑐𝑐 × 𝑡𝑡) and (𝑄𝑄𝑐𝑐𝑐𝑐 × 𝑡𝑡) are interaction terms with time (t) interacted with conflict and gender quota, respectively. 𝑋𝑋′𝑐𝑐𝑐𝑐 is a vector of covariates (time-varying and time-constant), and 𝜀𝜀𝑐𝑐𝑐𝑐 is the level 1 error term. 𝛽𝛽0𝑐𝑐 consists of two parts: 𝛿𝛿00, the overall fixed intercept and 𝑈𝑈0𝑐𝑐, the variance around this intercept. 𝛽𝛽1𝑐𝑐 is the estimated slope variance between countries for time (t), consisting of the average slope for time (𝜂𝜂10) and the variance around this slope (𝑆𝑆1𝑐𝑐).

Appendix D – UN peacekeeping operations

Table 10. UNPKOs (civil conflicts ongoing 1999-2014)

Peacekeeping operation Location Year

Gender content in UN-PKO mandates

Reference to sexual violence in UNPKO

mandate Quota

adoption Sexual

violence MONUC DRC 1999 1 2011 HSVC UNTAET East Timor 1999 1 2011 HSVC UNMIK Kosovo 1999 0 2000 HSVC UNAMSIL Sierra Leone 1999 1 HSVC UNAMA Afghanistan 2002 2 2004 HSVC UNMISET East Timor 2002 1 2011 HSVC MINUCI Cote d'Ivoire 2003 1 HSVC UNMIL Liberia 2003 2 Yes 2005 HSVC ONUB Burundi 2004 2 Yes 2004 HSVC UNOCI Cote d'Ivoire 2004 2 HSVC MINUSTAH Haiti 2004 2 2012 HSVC UNMIS Sudan 2005 2 Yes 2008 HSVC UNMIT Timor-Leste 2006 2 HSVC UNAMID Sudan 2007 3 Yes 2008 HSVC MONUSCO DRC 2010 1 Yes 2011 HSVC UNMISS South Sudan 2011 2 Yes 2011 HSVC UNISFA Sudan 2011 0 2008 HSVC UNSMIS Syria 2012 0 LSVC MINUSMA Mali 2013 2 Yes 2015 LSVC MINUSCA Central African Republic 2014 2 Yes HSVC No UNPKO Indonesia 2003 HSVC No UNPKO Iran LSVC No UNPKO Iraq 2005 HSVC No UNPKO Nepal 2007 HSVC No UNPKO Pakistan 2002 HSVC No UNPKO Pakistan 2002 HSVC No UNPKO Sri Lanka LSVC No UNPKO Thailand LSVC No UNPKO Yemen LSVC Note: Gender content codings from Kreft (2017) in the following way: 0 – no mention of gender or women; 1 – mention of women or gender, but not in the context of women’s participation, agency or gender equality (mostly women’s protection only); 2 – some mention of women’s participation, agency or gender equality, extending to part of the mandate; 3 – mention of women’s participa-tion, agency or gender equality in most or all aspects of the mandate

References

Cohen, D. K. (2013) Explaining Rape during Civil War: Cross-National Evidence (1980–2009). American Political Science Review 107(03): 461-477.

Cohen, D. K. & Nordås, R. (2014) Sexual violence in armed conflict Introducing the SVAC dataset, 1989–2009. Journal of Peace Research 51(3): 418-428.

Kreft, A.-K. (2017) The gender mainstreaming gap: Security Council resolution 1325 and UN peacekeeping mandates. International Peacekeeping 24(1): 132-158.

Krook, M. L. (2009) Quotas for women in politics gender and candidate selection reform worldwide, Oxford ; New York, Oxford ; New York : Oxford University Press.