The Politics of Unmixing: Riots, Segregation and Votes in India
by Diogo Bernardo Lemos
B.A. in Journalism and Contemporary History, July 2006, Queen Mary, University of London M.Sc. in Comparative Politics, October 2007, London School of Economics and Political Science
A Dissertation submitted to
The Faculty of The Columbian College of Arts and Sciences of The George Washington University in partial fulfillment of the requirements for the degree of Doctor of Philosophy
August 31, 2017
Dissertation directed by
Emmanuel Teitelbaum Associate Professor of Political Science and International Affairs
i The Columbian College of Arts and Sciences of The George Washington University certifies that Diogo Bernardo de Castilho Penha de Lemos has passed the Final
Examination for the degree of Doctor of Philosophy as of August 1st, 2017. This is the final and approved form of the dissertation.
The Politics of Unmixing: Riots, Segregation and Votes in India
Diogo Bernardo Lemos
Dissertation Research Committee
Emmanuel Teitelbaum, Associate Professor of Political Science and International Affairs, Dissertation Director
Henry E. Hale, Professor of Political Science and International Affairs, Committee Member
Irfan Nooruddin, Hamad bin Khalifa Professor of Indian Politics, Edmund A. Walsh School of Foreign Service, Georgetown University, Committee Member
ii © Copyright 2017 by Diogo Bernardo Lemos All rights reserved
iii Dedication
To Carolina
iv Acknowledgements
During the process of writing this thesis, I have incurred a long list of personal and intellectual debts. While I am grateful to all, I would like to express my special gratitude to those individuals who have had the strongest influence on the final product.
My largest debt is to my dissertation committee, whose graciousness took the edge off my relocation to Europe at the beginning of this project. My advisor, Manny
Teitelbaum, helped me make the difficult transition from unpolished graduate student into a hopefully more ‘sophisticated’ scholar. Intellectually, he pushed for this project to be broader than my initial conceptualization, which focused exclusively on the electoral effects of religious homogeneity at the constituency level. It was Manny who compelled me to consider the causes of constituency demography, which then led me to investigate the link between riots, unmixing and long-term electoral outcomes.
I have known Henry Hale since taking his terrific course on ‘Theories of Ethnic
Politics’ at the George Washington University. As a committee member, Henry has been one of the kindest and most insightful educators I have had the pleasure of know. Finally,
Irfan Nooruddin gave me early and critical inputs on issues of definition and conceptualization relating to Indian party politics. I would also like to thank Ajay Verghese and Adam Ziegfeld for serving as external readers for the project.
Previous versions of this project benefited from comments received at the 3rd Berlin
Graduate School in the Social Sciences, the 2016 Graduate Student Conference of the
v European Consortium for Political Research (ECPR), at Tartu University, Estonia, and the
45th Annual Conference on South Asia. Finally, I owe a debt of gratitude to the participants of a GW Comparative Politics Workshop, who provided helpful and detailed comments on chapter four of this dissertation.
This dissertation would not have been possible without the technical support and advice of several individuals. Among these I would like to highlight Raphael Susewind, whose name-matching algorithm enabled me to measure religious demography at the constituency level; Nuno Simarias, who introduced me to the scraping script that extracted information from the PDF-format Indian electoral rolls; Sarvesh Kumar, who executed these tasks to generate the contemporary estimates of religious demography for Delhi,
Bangalore, Chennai, Kolkata and Hyderabad; Seung Joon Paik and Johannes Zimmermann for their help with the statistical sections of this dissertation.
This project also benefited from the financial support of the Fundação para a
Ciência e Tecnologia, which funded me through the first years of my degree with a PhD studentship. Additional support was received from the Department of Political Science at the George Washington University and the Sigur Center for Asian Studies at the Elliott
School of International Affairs.
In addition to countless trips, my family and I moved across continents thrice, living in four different countries along the way. Such itinerant lifestyle would have been intolerable without the institutional support of the Berlin Graduate School for the Social
vi Sciences (BGSS) at Humboldt-Universität zu Berlin (where I was a guest researcher in
2014-2015), the American Institute of India Studies (AIIS) and the Department of Political
Science at the Jamia Millia Islamia in New Delhi (where I was affiliated in 2015-2016).
Thanks are also due to the Staatsbibliothek zu Berlin, the Nehru Memorial Library, the
Institute for Social and Economic Change in Bangalore, the Mumbai University Library and the Gujarat University Library in Ahmedabad.
Special recognition goes out to the politicians, consultants, bureaucrats, journalists, activists, academics and riot survivors who agreed to be interviewed for this project. Our friendly and candid conversations were the highlight of my field research. They contributed immensely to shape my understanding of Indian party politics. While this debt can never be repaid, I hope that this work will serve as a token of my appreciation.
In writing and researching this dissertation, I have relied on countless friends and family who have helped me in a variety of ways. When I hit a research wall, I turned to my friend Nuno Rocha, who possesses a preternatural disposition to make the impossible happen. He put me in contact with Maneesh Gulati, who fetched and scanned an old copy of the Census of India for this project. Shubangini Singh was my host, friend and enthusiastic culinary guide in Delhi. She took care of me when I became sick and looked after my girls when we all came to India in 2015. In my visits to Washington, I benefited from the hospitality of João Cabrita and Inês Lopes as well as Seung Joon Paik. My godparents, Tio Carlos and Tia Bita, supported and inspired me to conclude this study. My mother-in-law, Heide-Marie Seybert, released me from parental duties in Berlin so that I
vii could conduct field research in India. My parents, Ana Penha and Manuel Lemos, have instilled in their two children – my brother, Pedro, and I – the values and the education that
I hope will also come through in this work. They also provided much-needed financial support for this project in the bleakest periods and I am profoundly grateful for their kindness.
Lastly, I owe my deepest debt of gratitude to my closest family, Carolina Seybert, and our daughter Magali. Magali has filled me with the joy and love that powered me through this process. In Carolina, I have found much more than a dedicated wife and exemplary mother to our daughters (the second of whom she has carried during the final stretch of this dissertation). She has been my closest friend, my most trusted advisor and my most shrewd supporter. For all these reasons, I hold my decision to talk to the girl who changed the radio station in a crowded car as my best so far. It is to her that I dedicate this dissertation.
viii Abstract of Dissertation
The Politics of Unmixing: Riots, Segregation and Votes in India
Do ethnic riots have long-term electoral consequences? While strategic political calculations are said to play a key role in the production of ethnic riots, existing studies illuminate only how riots shape electoral competition in the short-term. Drawing on a study of Hindu-Muslim violence in India, this dissertation argues that ethnic riots may also be thought of as a particularly brutal spatial strategy, designed by political actors to violently refashion social geography in ways that highlight and fix an ethnic divide in the long-term. Briefly, I advance a two-part hypothesis: (1) recurrent and severe riots shift the ethnic composition of electoral constituencies, constructing homogeneous constituencies where relative heterogeneity had been the norm - following Brubaker I name this process 'ethnic unmixing' (Brubaker 1995; 1998); and (2) greater ethnic homogeneity at the constituency level promotes lasting electoral support for ethnic parties. This dissertation articulates and tests several hypotheses about the efficacy of this spatial strategy in promoting long-term electoral support for matching ethnic parties, employing a mixed methods research design that combines large-N statistical analysis with extensive in-depth case study research. In doing so, the dissertation utilizes original quantitative data on religious demography at the local level in India, extensive interviews, and archival data gathered during 13 months of field research in India.
ix Table of Contents
Dedication…..…………………………………………………………………………….iv
Acknowledgements………………………………………………………………………..v
Abstract…………………………………………………………………...... ix
List of Tables…….……………………………………………………...... xiii
List of Figures and Images………………….……………………..…………………….xiv
List of Abbreviations……..……………………………………………...... xv
Chapter 1: The Politics of Unmixing……………………………………………………..1
1.1 Introduction
1.2 The Puzzling Rise of the Hindu Right in India
1.3 The Argument
1.4 Calculated or Unintended?
1.5 Research Design and Chapter Outline
Chapter 2: Hindu-Muslim Riots and Religious Unmixing in India…………………...... 39
2.1 Introduction
2.2 Argument: Riots and Segregation
2.3 Hindu-Muslim Unmixing in India
2.4 Cross-Sectional Analysis
2.5 Time Series Analysis
2.6 Conclusion
x Chapter 3: Divide and Rule: The Politics of Unmixing in Mumbai…………………...... 80
3.1 Introduction
3.2 Setting the Context: the Shiv Sena at Crossroads
3.3 The Failure of Conventional Electoral Strategies
3.4 There’s a Pakistani Upstairs: the Mechanisms of Unmixing
3.5 Alternative Explanations
3.6 Conclusion
Chapter 4: Ethnic Unmixing and the Hindu Right’s Success in Urban India…………..115
4.1 Introduction
4.2 The Argument: Segregation and Ethnic Party Success
4.3 Hypotheses
4.4 Methods
4.5 Results
4.6 Conclusion
Chapter 5: Making Space for Votes: Unmixing and Dominance in Ahmedabad……..150
5.1 Introduction
5.2 Setting the Context: The Hindu Right in Ahmedabad
5.3 Riots, Segregation and Votes: The Politics of Unmixing in Ahmedabad
5.4 The Mechanisms of Unmixing: Explaining Enduring Success
5.5 Alternative Explanations for the BJP’s success
5.6 Conclusion
xi Chapter 6: Conclusion…………………………..………………………………………187
6.1 Re-visiting the Argument
6.2 Implications for Scholarly and Policy Debates
6.3 Generalizability
6.4 Limitations and Areas for Further Research
Reference List…….……………………………………………………………………..207
Appendix……………………………………………………..…………………………232
A.1 List of Names Extracted from the National Voter’s Service Portal for
Mumbai
A.2 Index of Isolation for India’s Seven Metro Cities in the Last Seven
General Elections for the State Legislative Assembly
A.3 Index of Dissimilarity for India’s Largest Cities + Municipal
Corporations in UP and Gujarat (AC-level Analysis)
A.4 Index of Dissimilarity for India’s Largest Cities + Cities in UP and
Gujarat (Part-level Analysis)
A.5 Maps: Electoral Constituencies in India’s 7 Largest Cities
A.6 Marginal Effects
A.7 Images
A.8 Interview Procedures
A.9 Map: Ahmedabad
xii List of Tables
Table 2.1 Possible Confounding Factors 62
Table 2.2 Bivariate Regression Results 63
Table 2.3 Tri-variate Regression Results 66
Table 2.4 Frequency and Intensity of Hindu-Muslim Riots in India’s 72 Seven Metro Cities
Table 3.1 Number of Seats Won by Major Parties in BMC Elections, 85 1948-2012
Table 4.1 Hindus, Muslims, SC/ST, Females and Male Illiteracy in India’s 130 Seven Metro Cities (Census of India 2011)
Table 4.2 Electoral Constituencies in India’s Metro Cities (2015) 131
Table 4.3 Cross-Sectional Analysis Results I 136
Table 4.4 Cross-Sectional Analysis Results II 146
xiii List of Figures and Images
Figure 1.1 Performance of the BJS (1952-1971) and the BJP (1984-2014) 8 in National Parliamentary Elections
Figure 1.2 Performance of the Shiv Sena in National Parliamentary 9 Elections (1971-2014)
Figure 1.3 Case Studies 30
Figure 2.1 Effect of Hindu-Muslim riots on Hindu-Muslim Segregation 64
Figure 2.2 Index of Isolation Change Between Mid-1980 and 2010s 75
Figure 2.3 Index of Isolation, Linear Results 1980s-2010s 76
Figure 3.1 Worst Affected Police Stations in 1992-93 Mumbai riots 111
Figure 4.1 Effect of Hindu Population on Hindu Right’s Support 138 (tested from 52 < X1 <78)
Figure 5.1 Number of Riots in Ahmedabad 1950-1993 151
Figure 5.2 BJP’s Electoral Performance in State Elections in Ahmedabad 153 (1980-2012)
Image 5.1 Hindu Rashtra Board in Ahmedabad 171
Image 5.3 A Typical Juhapura Street, Ahmedabad 250
Image 5.4 Card Playing on Election Day 251
Image 5.5 Hindu and Muslim Areas in Juhapura, Ahmedabad 252
xiv List of Abbreviations
ABVP Akhil Bharatiya Vidyarthi Parishad
AIADMK All India Anna Dravida Munnetra Kazagham
AIMIM All India Majlis-e-Ittehad-ul Muslimeen
AGNI Action for Good Governance and Networking in India
AMC Ahmedabad Municipal Corporation
B Index of Isolation
BMC Brihanmumbai Municipal Corporation
BKS Bharatiya Kamgar Sena
CSDS Center for the Study of Developing Society
D Index of Dissimilarity
DMK Dravida Munnetra Kazagham
ECI Electoral Commission of India
ENPV Effective Number of Party Votes
IHDS Indian Human Development Survey
JD Janata Dal
MAS Movement for Socialism
MLA Member of Legislative Assembly
MPCE Monthly Per Capita Expenditure
NES National Election Study
xv OBCs Other Backward Classes
ODM Orange Democratic Movement
OLS Ordinary Least Squares (Regression)
PNU Party for National Unity
RPI Republican Party of India
RSS Rashtriya Swayamsevak Sangh
SC Scheduled Caste
SDLP Social Democratic and Labour Party
SEC State Election Commission
ST Scheduled Tribe
TLA Textile Labour Association
xvi Chapter 1 The Politics of Unmixing
One of the recent trends in communal riots is the motivation of communal elements who engineer the riots with a view to making what are presently mixed localities into homogeneous ones. -- P.R. Rajgopal, Communal Violence in India, 1987
Ram Janmabhoomi may not be a live political issue. But its effects certainly are. -- Business Standard, Editorial, 2012
1.1 Introduction
What explains the rise and enduring success of ethnic parties?1 Can recurrent and severe ethnic riots turn an ethnic party into a major, long-lived player in the electoral landscape?2 While considerable attention has been paid to politics as a cause of riots, no work to date articulates theoretical and empirical connections between the production of ethnic riots and the rise of ethnic parties. This is surprising given that previous research has already pointed out that riots reverberate through the political system long after the
1 This project employs the terms ‘ethnic’ and ‘communal’ to describe Hindu-Muslim conflict in India. ‘Ethnic identities’ are conceptualized as identities based on descent-based attributes such as race, region, religion, caste, sect, language family, language, dialect, caste, clan, tribe or nationality of one’s parents or ancestors, or one’s own physical features (Chandra 2012). In India, Hindu- Muslim conflict is often described as 'communal,' with the term 'ethnic' reserved for caste, racially and linguistically distinct categories. This project adopts the broader conception of 'ethnic identity' used by influential political science literature on the Hindu- Muslim conflict in India that does not distinguish between 'communal' and 'ethnic' (Horowitz 1985; Wilkinson 2004; Varshney 2002). In turn, I refer to an 'ethnic party' as a party that is ideologically committed to the cause of one particular ethnic category to the exclusion of others and that receives most of its electoral support from its target ethnic category. This definition follows Chandra’s (2011) recent conceptual work on the notion of 'ethnic party' suggesting that a range of indicators, including but not restricted to a party's explicit issue positions and the composition of its electoral support, can be used to define an ethnic party. 2 Following Horowitz (2001), I understand an ‘ethnic riot’ as an episode of collective violence (though not necessarily deaths) between civilian members of one ethnic group and civilian members of another ethnic group, the victims chosen because of their ethnic category membership. This definition is broader than ordinary understandings insofar as it states nothing about the degree of organization, the scale of the violence or the goals of the participants in the violence. It also encompasses both large-scale episodes of violence, such as the 2002 Gujarat riots, and smaller outbursts that take place more often. In making this conceptual decision, I follow important work in the field of ethnic riots that argues that both 'bigger' and 'smaller' riots have the same fundamental characteristics, namely they are not spontaneous but instead fueled by the need to maintain and strengthen relationship with influential and useful people. See also Berenschot 2011.
1 debris has settled (Horowitz 2001; Kasara 2017). Moreover, this question has important policy implications for societies affected by recurrent and severe ethnic riots. If riots can trigger long-term shifts in electoral competition, then, they also pose a more alarming threat to democratic stability than previously thought.3
To address these questions, this dissertation examines the mercurial rise of the two main parties of the Hindu right – the Bharatiya Janata Party (BJP) and the Shiv Sena
– over the past three decades in India.4 Briefly, I argue that neither conventional accounts for the rise of ethnic parties nor existing explanations for the Hindu right’s success fully account for its electoral performance. Instead, I argue that the Hindu right’s enduring success has been the product of spatial strategies, which included violently refashioning
India’s social geography in ways that highlight and fix the Hindu-Muslim divide
(Deshpande 1995; Appadurai 2000; Oza 2007; Desai 2011). Such violent strategies reached a peak between the mid-1980s and early 1990s, when the Sangh Parivar (the family of Hindu nationalist organizations) revitalized a long-standing dispute over a religious site in Ayodhya, Uttar Pradesh.5
3 The idea that the rise of ethnic parties is a major threat to democratic stability is a recurrent theme of comparative politics research (see for example Rustow 1970, Dahl 1971, Lijphart 1977, Horowitz 1985, Chandra 2005). 4 I use the classification ‘Hindu right’ here to describe political parties organizing on the basis of religious differences and espousing the core ideological beliefs of Hindutva (see below). This conceptualization is differentiated from the economic Right by their focus on a Hindu sectarian agenda. While highly organized, the Hindu right is not entirely coherent (Oza 2007). Certainly, there are significant differences between the two parties analyzed in this dissertation – the Bharatiya Janata Party (BJP) and the Shiv Sena – in terms of history, regional scope, leadership style and organizational structure, electoral strategy and popular base. Yet, both the BJP and the Shiv Sena espouse the core principles of Hindutva (lit. Hindu-ness). Briefly, this is a term used by Hindu nationalist organizations and understood by others to signify the political ideology deriving from Hindu values and culture, especially the notion that India is a Hindu state (Hindu Rashtra). Proponents of Hindutva see India’s diversity as a source of weakness and portray religious minorities as outsiders who must adhere to national Hindu culture. 5 The Sangh Parivar was started by members of the Hindu right-wing, paramilitary Rastriya Swayamsevak Sangh (lit., the National Volunteer Organization, RSS) and includes, among other organizations, the Bharatiya Janata Party (BJP), the Vishva Hindu Parishad (VHP), the Bajrang Dal and Sewa Bharati (social service provision).
2 The argument developed in this dissertation unfolds in two parts. The first part contends that recurrent and severe riots shift the ethnic composition of electoral constituencies, constructing homogeneous constituencies where relative heterogeneity had been the norm. Following Brubaker’s seminal work (Brubaker 1995; 1998), I name this wholesale restructuring of peoples ‘ethnic unmixing.’ The second part argues that greater ethnic homogeneity at the constituency level promotes lasting electoral support for ethnic parties. Underlying this argument is a simple assumption: benefit-seeking voters will support the social category that makes them part of a winning coalition (Riker
1962; Bates 1974). The most effective way of doing so is by comparing the size of the identity categories in the electoral context (‘counting heads’) and then selecting the ethnic category that offers the most usefully sized coalition (Chandra 2004). By increasing residential segregation along ethnic lines, riots thus enable parties to enduringly raise the salience of its target ethnic category, consolidate the link between ethnic majoritarianism and clientelism and deploy other electoral strategies more efficiently. In this way, I argue that riots should be thought of not merely as a solution to short-term political challenges but also as way to promote resilient support for an ethnic party.
This dissertation’s exploration of the long-term electoral repercussions of ethnic riots contributes to scholarship on at least three areas of research within the social sciences: the study of Indian party politics; ethnic conflict and violence; and the literature on electoral political competition. First and foremost, my argument has important implications for those interested in India’s and, more broadly, South Asia’s politics. The rise of the Hindu right is arguably one of the most momentous transformations in India’s
3 electoral landscape of the past 20 years, one that has the potential to threaten its internal cohesion and stability. While many agree that Ayodhya was a turning point in the country’s political development, no systematic empirical work has so far linked this violent campaign to the rise of the Hindu right in India. By examining the link between communal riots, ethnic unmixing and the Hindu right’s enduring success, this dissertation shows how the intensification of Hindu-Muslim violence between the late 1980s and early 1990s paved the way for the subsequent rise of parties attempting to mobilize
India’s Hindu majority.6 Moreover, to the extent that it enhances our understanding of
India’s political development, this project also contributes to scholarship on other multiethnic and low-income democracies in the region as well as on India’s tense relationship with its nuclear-armed rival Pakistan.
Second, this study yields specific insights for the literature on ethnic violence.
While strategic political considerations are said to play a key role in the production of ethnic riots, previous works illuminate only how riots contribute to the short-term success of an ethnic party (Wilkinson 2004; Dhattiwala and Biggs 2012). This dissertation shows that riots can also help ethnic parties gain, maintain or increase their hold on power way beyond the first election after the violence. This insight also speaks to previous works on ethnic conflict suggesting that ethnic violence promotes the perpetuation or escalation of ethnic conflict and, hence, long-term identity construction (Fearon and Laitin 2000).
6 According to Varshney-Wilkinson data, between September 1990 and December 1995, there were 254 reported riots, in which 2827 people were killed, 5047 injured and 13082 arrested.
4 At the same time, it is important to stress that ethnic unmixing as presented in this study is not simply a less dramatic version of other forms of ascriptive violence that have received more attention in the literature, namely ‘ethnic cleansing,’ forced migrations and large-scale population ‘transfers’ (Horowitz 1985; 2001). Whereas these types of ethnic violence seek the extermination and expulsion of the ethnic ‘Other,’ ethnic unmixing following riots aims to segregate in ways that highlight and fix the ethnic divide. According to the political logic enunciated in this dissertation, riots are an efficient spatial strategy precisely because they lock-in the capacities and threats of target groups while fomenting solidarity among the ethnic majority. This, in turn, enables ethnic entrepreneurs to enduringly raise the salience of ethnic identities that favor them in political competition. As Renu Desai (2011, p. 115) tells us, the sharpening of spatial boundaries following riots “not only separates but also becomes a zone of engagement through violence, a zone where communal hostility is displayed to reinforce separateness, antagonism, and irreconcilability.” Ultimately, then, this study sheds analytic light on the concept of ethnic riots as well as its relationship to other types of ascriptive violence.
Finally, this dissertation offers a novel theory about the rise and enduring success of ethnic parties. In the past, scholars have emphasized factors such as rapid urbanization
(Huntington 1968; Adam 1979; Katzenstein 1979), institutional reforms (Van Cott 2003;
Chandra 2005), international factors (Esposito 1990), economic liberalization (Kohli
1997; Brumberg 2002; Chua 2004), the expansion of the middle classes (Chhibber 1997;
Blom Hansen and Jaffrelot 1998), patronage (Chandra 2004) and welfare provision
(Wickham 2002; Clark 2004; Thachil 2011) to explain their success. Yet, the role of
5 violence in promoting the long-term success of ethnic parties remains surprisingly under- theorized in the literature. This study of Hindu-Muslim violence in India reveals that ethnic riots may also be thought of as a long-term electoral strategy based on altering the ethnic demography of constituencies. My argument highlights the link between ethnic homogeneity at the constituency and support for a party seeking to mobilize the dominant ethnic category. In doing so, this analysis offers a novel perspective on long-standing debates on the relationship between ethnic context (i.e., demography) and ethnic conflict.7
Moreover, drawing on previous literature, I illustrate three different mechanisms through which ethnic unmixing builds resilient support for an ethnic party: it heightens the visibility of an ethnic divide, strengthens the link between an identity and access to public goods and facilitates the deployment of other electoral strategies. Ultimately, this dissertation suggests that ethnic demography at the constituency level takes precedence over other factors that have been previously associated with ethnic party success.
In the remainder of the chapter, I first explain why the rise of the Hindu right presents a challenge both for the literature on ethnic parties and for conventional explanations for the success of parties mobilizing the Hindu majority in India. I then outline the central argument of this dissertation linking ethnic riots to the rise and enduring success of ethnic political parties. Specifically, I present the argument that the
7 In broad lines, there is widespread support for the idea that ethnic context shapes electoral outcomes. Yet, the literature remains profoundly divided over the direction of this relationship. Proponents of the ‘threat’ hypothesis contend that the presence of a sizeable ethnic minority (therefore, a smaller ethnic majority) threatens the majority's social, economic and political position, resulting in interethnic prejudice and conflict (Blalock 1957; Fossett and Kiecolt 1989; Huckfeldt and Kohfeld 1989). In contrast, proponents of the ‘contact’ hypothesis predict that the presence of a sizeable ethnic minority improves intergroup relations (Allport 1954; Pettigrew 1998; Tropp and Pettigrew 2005). In its classic version, the contact hypothesis contends that contact with members of other ethnic categories provide individuals information about out-groups that can counteract pre-existing negative stereotypes about them and increase ethnic tolerance more generally. Subsequent work has offered alternative explanations for the link between contact and interethnic peace.
6 violence surrounding the Ayodhya agitation between the late 1980s and the early 1990s contributed to the long-term success of the Hindu right in India. In following section, I suggest that ethnic unmixing is not merely an accidental consequence of intense Hindu-
Muslim rioting but, in fact, constitutes a central goal of the violence. Next, I specify the research design employed by this dissertation to test this argument. Finally, I conclude with a brief outline of the remaining chapters of the dissertation.
1.2 The Puzzling Rise of the Hindu right in India
This dissertation is centrally concerned with the enduring rise and success of the
Hindu right in India. Two main factors make the rise of parties seeking to mobilize
India’s Hindu majority surprising. First, at birth, India possessed many of the characteristics generally thought to provide a fertile ground for the rise of parties attempting to mobilize its Hindu majority: a history of Hindu-Muslim violence, perpetuated by the protracted conflict with Pakistan; the arrival of large numbers of
Hindu refugees in the wake of Partition; a labor market divided along communal lines; and a significant and fast growing Muslim minority in the country (see Wilkinson 2004 for an overview of this literature). Yet, until the late 1980s, the Hindu right had little expression in India’s party system. In fact, the BJP, and its predecessor the Jana Sangh, did not cross the 10 percent mark in national (Lok Sabha) elections until the 1989 general elections, and even then, the BJP received only 11.36 percent of the popular vote.
Likewise, as Chapter 3 will outline in greater detail, the Shiv Sena suffered a succession of heavy defeats in the early 1990s, greatly diminishing its electoral standing in the western state of Maharashtra and its capital city, Mumbai.
7 Since then, both parties have enjoyed a sharp upswing in electoral fortunes. These rising electoral fortunes culminated in a historic victory in the 2014 general elections, in which the BJP won a majority in India’s national parliament – the first party to do so in
30 years. Similarly, the Shiv Sena, has enjoyed a steep electoral ascent and enduring success in Mumbai. Thus, this dissertation is foremost concerned with the following question: how did the BJP and the Shiv Sena catapult from marginal positions in the early
1980s into their current status as dominant players in Indian politics (Graph 1.1 and 1.2)?
35 300
30 250
25 200 20 150 15
100 10
5 50
0 0
Seats Won Percentage of Votes Pooled
Figure 1.1: Performance of the BJS (1952-1971) and the BJP (1984-2014) in National Parliamentary Elections8
8 The BJP was formed in 1980 by the leaders of the former the Hindu right-wing Bharatiya Jana Sangh (BJS). The latter was part of the Janata Party during 1977-80 - a grand coalition opposed to Indira Gandhi's emergency rule. For this reason, the 1977 and 1980 general elections were excluded from the graph.
8 2 20 1.8 18 1.6 16 1.4 14 1.2 12 1 10 0.8 8 0.6 6 0.4 4 0.2 2 0 0 1971 1980 1989 1991 1996 1998 1999 2004 2009 2014
Seats Won Percentage of Votes Pooled
Figure 1.2: Performance of the Shiv Sena in National Parliamentary Elections (1971-2014)
Second, existing explanations for the rise of the Hindu right in India cannot readily account for its spatially uneven performance. One group of authors attribute the
Hindu right’s rise to its ability to capture the anxieties and aspirations of the middle classes, which have expanded since the introduction of liberal market reforms in the
1990s (Chhibber 1997; Blom Hansen and Jaffrelot 1998).9 Yet, these accounts fail to account for disconcerting evidence that the Hindu right has remained a marginal player in states with high levels of human development (such as Kerala and Tamil Nadu), while faring substantially better in others with low levels in the same index (such as
Chhattisgarh, Jharkhand and Uttar Pradesh) (Gandhi et al. 2011).
9 The extent of the Indian middle classes’ expansion during this period is another point of contention given considerable definitional and measurement problems. According to Jaffrelot and Van der Veer (2008), the most optimistic assessment regarding the size of the Indian middle classes puts it at 200 million people, representing one-fifth of India’s population. Yet, a recent report by Credit Suisse, a global finances services firm based in Zurich, Switzerland, which used wealth rather than income to measure the Indian middle classes estimated it at 24 million people (Business Standard 2015). In any case, an upward trend in the size of the middle classes in India since the 1990s is confirmed by most studies.
9 Other scholars have emphasized how the Hindu right has relied on social services provided by its grassroots affiliates in the Hindu nationalist Sangh Parivar (the family of
Hindu organizations) to make unexpected inroads with low-caste and poor voters
(Katzenstein 1979; Gupta 1982; Shaikh 2005; Thachil 2011). However, this literature has highlighted that a welfare-based strategy cannot succeed in all political contexts.
Specifically, such ‘bridging work’ is more successful where the local public infrastructure is exceptionally inadequate (such as rural Chhattisgarh) and where poor communities have not been previously mobilized in either than caste or class identities
(Thachil 2011). Yet, as we shall see, the Hindu right has become a major player in contexts such as Mumbai and Ahmedabad, where both conditions are not present.
Finally, others have highlighted the Hindu right’s elevation of lower-castes within the party structure, following the Indian government’s decision in 1990 to implement the recommendations of the Mandal Commission on expanding the reservations for Other
Backward Classes (OBCs) (Yadav, Kumar and Heath 1999; Chandra 2004).10 However, it is well known that the Hindu right’s support for ‘social engineering’ has been reluctant at best. Certain Hindu right leaders, such as the former BJP president Murli Manohar Joshi and the Shiv Sena leader Bal Thackeray, were openly disdainful of promoting lower caste leaders to positions of prominence. Accordingly, the BJP’s record of empowering OBCs has been disappointing, even in states where it has traditionally enjoyed their electoral support such as Gujarat (Jaffrelot 2016).
10 Another popular argument is that the Hindu right surged due to the anger, and therefore consolidation, of higher castes at Mandal reforms. While there is abundant evidence that the Hindu right draws much of its electoral support from this section of society, existing data from the Center for the Study of Development Societies (CSDS) also show that it has made substantial gains with low castes and especially Other Backward Castes (OBCs) (Jaffrelot 2008; 2013; 2015; Jaffrelot and Verniers 2009). This suggests that the Hindu right appeals to a much broader audience than just high caste Hindus.
10 To be clear, my point here is not that variation in electoral support for the Hindu right refutes existing arguments. Rather, this brief elaboration suggests that none of these explanations can fully account for the variation in resilient support for the Hindu right.
Thus, in addition to the initial puzzle concerning the timing of its rise, this dissertation also seeks to address the fundamental about the uneven rise and enduring success of the
Hindu right in India. What differentiates those electoral contexts where the Hindu right has become a major, long-lived player from those where it continues to fare poorly?
1.3 The Argument
The central argument advanced in this dissertation is that recurrent and severe
Hindu-Muslims riots between the late 1980s and 1990s contributed to the Hindu right’s rise and enduring success in India.11 The intensification of Hindu-Muslim violence during this period resulted from the Sangh Parivar’s campaign for the construction of a temple dedicated to the Hindu deity Rama at the site of a mosque, the Babri Masjid, in Ayodhya,
Uttar Pradesh.12
The Ayodhya dispute was particularly well-suited for galvanizing Hindu sentiment behind the Hindu right. On the one hand, the Sangh Parivar’s attribution of sanctity to the site, by labeling it as Rama’s birthplace (‘Ram Janmabhoomi’), was designed to underline the unity of all Hindus irrespective of their caste and class
11 While the focus of this dissertation is on urban India, there is no reason to believe that the argument advanced in it will also not apply to a rural context (i.e, greater religious homogeneity in rural constituencies will also lead to resilient support for the Hindu right. However, to the extent that other strategies may be more effective in rural than in urban areas (see for example Thachil 2011), we may expect ethnic parties to draw less on ethnic unmixing in the former as an electoral strategy. 12 The dispute had existed at least since the 1885, when litigation had begun for the right to property in the area (Panikkar 1993). The dispute was then revitalized in 1949 when an idol of Ramlalla (‘infant Rama’) was mysteriously found inside the mosque. But during this period, Nehru and his secular allies in the Congress Party (INC) managed to defuse the tensions. The dispute remained dormant for the next forty years until the Sangh Parivar enlivened it in the early 1980s.
11 differences. It also typified the spatial practices of Hindutva elsewhere, involving an attempt to essentialize the nation-space by stressing its irreducible and exclusive affinity for Hindus alone (Deshpande 1995).13 On the other hand, the Parivar claimed that a Hindu temple had stood on this holy site and was supposedly demolished in 1528 at the orders of Babur, the founder of the Mughal dynasty, in order to make way for the Babri Masjid
(Jaffrelot 1996). This provided the Sangh Parivar with a vehicle for highlighting Muslim aggression against Hindus and their religion. Ayodhya therefore became a site for fomenting Hindu solidarity while also avenging the Muslim wrong (Panikkar 1993).
In addition to the campaign for the ‘liberation’ of a religious site from Muslim jurisdiction, the Parivar’s spatial strategies during the Ayodhya campaign included a series of public interventions: from the collection and consecration of bricks from villages across India (Ram Shila Puja) to the organization of a religious march by the BJP president, L.K. Advani, through north India to press for the demolition of the mosque
(Ram Rath Yatra).14 These interventions were designed to connect scattered localities throughout India with Ayodhya, the threatened place that must be protected against the other. As Deshpande (1995, p. 3224) argues, “if the locality is a mixed hindu-non-hindu one, then the threat can be very easily simulated; if the ‘other’ happens to be absent from
13 According to Deshpande (1995), the issue encapsulated the three ideological constructs that characterize the contemporary spatial strategies of Hindutva: the sacred site, involving struggles for a religious spot that can be turned into arenas of contest with the ‘other’; the neighborhood that is redefined as a threatened space that must be protected from the foreign ‘other’; and the pilgrimage that attempts to string together and multiply the effect of many places by joining them into the route of a journey. 14 In September-October 1989, the Sangh Parivar collected and consecrated bricks made of 'local earth' from villages across India to lay the foundation of the Ram Janamsthan Mandir in Ayodhya. The bricks were wrapped in saffron cloth, worshipped for several days, consecrated by pujar and carried in processions throughout the country to the radial spot at Ayodhya. Earth dug up in Ayodhya was also redistributed to different parts of India. Advani’s rath yatra departed from Somnath, Gujarat, on September 25, 1990, and planned to reach Ayodhya, 10,000 kilometers away on October, 30 1990. The yatra crossed the states of Gujarat, Maharashtra, Karnataka, Madhya Pradesh, Rajasthan, Haryana, Delhi. The triggered a wave of riots across India. As a result, Advani was arrested by the government of Bihar, before he reached Ayodhya. Yet, tens of thousands of activists continued the journey to the city and attempted to storm the mosque.
12 the locality, it is nevertheless portrayed as a threatened idyll permanently in danger of invasion.”
Consequently, with each of these spatial interventions, there was also an aggravation of Hindu-Muslim animosity, producing communal bloodshed across India
(Chandhoke 2000). The campaign culminated with the mosque’s demolition on
December 6th 1992 – exactly twenty-five years this year – resulting in the worst wave of
Hindu-Muslim rioting since partition. According to the Varshney-Wilkinson dataset, between September 1990 and December 1995, there were 254 reported riots, in which
2,827 people were killed, 5,047 injured and 13,082 arrested. As we shall see next, this wave of violence brought many localities into a larger grid of ideological dissemination and political action that contributed to the Hindu right’s rise in the Indian electoral landscape.
1.3.1 Existing literature on Ayodhya
Pointing out that there is a relationship between the Ayodhya agitation and the
BJP’s electoral success is not of course new. Previous scholars have already highlighted that the Ayodhya dispute changed the dynamics of electoral competition in India (Ludden
1996; Basu and Kohli 1997; Blom Hansen 1999; Hasan 2002; Brass 2003; Jaffrelot
2003). Paul Brass, for example, argues that the violence surrounding destruction of the
Babri mosque in 1992 prompted “a reorganization of the entire basis of the political system and political practices” (Brass 1994, p. 324). Similarly, Zoya Hasan contends that the campaign “led to a structural shift in the center of gravity in Indian politics from the
13 left of center to the right of center” (Hasan 2002, p. 11). L.K. Advani himself recently boasted about the contribution of the Ayodhya campaign to making the BJP a major, long-lived player in India’s electoral landscape:
People say that BJP and Bharatiya Jana Sangh achieved this position by raising issues like Ayodhya and Ram temple. I feel proud in admitting this and say that ours is not just a political movement but also a cultural movement (The Hindu 2013).
However, most systematic empirical work on the Hindu right’s rise in India emphasizes only short-term electoral implications of the Ayodhya agitation. According to this view, the ‘saffron wave,’ as implied by its very name, receded and gave way to new forms of mobilization. For example, Thomas Blom Hansen states that voters started to turn away from the Hindu right “less than a year after the demolition of the Babri Masjid”
(1999, p. 188). This argument conforms to the BJP’s poor performance in the assembly elections in several states in 1993.
Yet, at the same time, it is difficult to downplay the scale and longevity of the
Hindu right’s success following Ayodhya. In addition to becoming the major national opposition party to the Indian National Congress (henceforth, referred to as Congress simply), the BJP has since occupied power in several states and twice at the center (1998-
2004 and 2014-). As of 2016, it is India’s largest political party in terms of representation in the national government and state assemblies, and it is the world’s largest party in terms of primary membership. Similarly, since the early 1990s, the Shiv Sena has played a dominant role in Maharashtrian politics. This suggests the need to perceive the Hindu right’s rise less as a transitory and more as a lasting transformation in the Indian electoral
14 landscape. Did Ayodhya change India’s electoral politics? If so, why did its impact vary across different electoral contexts in India?
1.3.2 Communal Riots and Unmixing
To address these questions, I advance a two-part argument linking communal riots to the Hindu right’s enduring rise in India. The first part of my argument builds on previous formulations on ‘ethnic unmixing’ – the notion that intense ethnic violence triggers a process of spatial segregation between members of distinct ethnic communities.
For Brukaber (1995), these migrations occur not just in the context of ethnic war but also in ‘nationalizing states’ at times of supercharged mass ethnic nationalism. Subsequent authors (Kaufman 1996; Laitin 2004) have illustrated the general applicability of ‘ethnic unmixing’ in diverse contexts such as Armenia, Nigeria and Serbia. More recently,
Weidmann and Salehyan (2013) point out that, since the 2003 United States-led invasion of Iraq, Baghdad has changed from a city where Sunnis and Shias resided in mixed neighborhoods to one with well-defined religious neighborhoods. They argue that, even assuming that people have a preference for living with co-ethnics, violence can dramatically increase religious segregation.
The literature on Hindu-Muslim conflict in India already reflects this trend. In
2005, the Sachar Committee report – conducted at the request of Prime Minister
Manmohan Singh – concluded that episodes of communal violence since the late 1980s have prompted Muslims to search for safety in numbers. Recent ethnographic works further corroborate this conclusion: large-scale communal riots have accentuated spatial
15 segregation between Hindus and Muslims in India’s most riot-prone cities (Gupta 2011;
Blom Hansen 2001; Mahadevia 2002; Chandoke 2009; Gayer and Jaffrelot 2012).
Crucially, previous authors have also noted that the violence enabled the Hindu right to identify the interests of the Hindu majority with the imaginary of the cleansed space, a space without Muslim bodies (Deshpande 1995; Appadurai 2000; Contractor 2012).
1.3.3 Unmixing and the Hindu right’s enduring success
The second part of my argument then explores the long-term political implications of ethnic unmixing.15 Concretely, I hypothesize that high levels of segregation along an ethnic category creates a self-sustaining and reinforcing equilibrium in favor of parties mobilizing the ethnic majority. From the point of view of voters, high levels of ethnic segregation create two types of incentives for supporting ethnic parties.
The first is that high levels of segregation following riots increases the ‘visibility’ of an ethnic divide by causing the minority group’s peculiarities to stand out in clear contrast to the traits of the majority (Hawley 1944; van der Waal, de Koster & Achterberg 2013).
Indeed, previous authors have already argued that visibility of ethnic markers determines which cleavage will be the most relevant for social interactions and political life (van der
Berghe 1997; Hale 2004; Chandra 2006; 2012). Therefore, the consolidation of electoral constituencies along ethnic lines, enduringly raises the visibility of the ethnic divide
15 In fact, empirical research on the effect of local demography on inter-ethnic attitudes provides us with good reasons to believe that increasing ethnic segregation may promote support for ethnic parties. Allport (1954) and subsequent authors have argued that, under certain conditions, interethnic contact reduces prejudice by allowing people to correct false beliefs about members of other ethnic groups (Pettigrew 1998). Because living in diverse areas may increase interethnic trust it may also diminish support for ethnic-based parties (Kasara 2017). Moreover, previous work on ethnic politics suggests that ethnic homogeneity contributes to ethnic party success. Authors have suggested that it is easier for parties to make ethnic appeals to homogeneous electorates (Horowitz 1998) and that politicians may want to stick with a larger majority than incurring the risks and costs of mobilizing a smaller one (Ferree 2012). Bueno de Mesquita and his co-authors (2003) contend that “homogeneous cultures (…) probably creates a selection effect” (63). Finally, Glaeser and Shleifer (2005) show that James Michael Curley, a four-time mayor of Boston, used targeted redistributive policies to encourage non-target groups to leave the city, thereby shaping the electorate in his favor. They call this the ‘Curley effect.’
16 making it easier for an ethnic party to mobilize its target voters.
Second, high levels of segregation along an ethnic category following riots also reduces uncertainty about which political party is better placed to provide them access to crucial public goods. This argument draws on Chandra’s (2004) contention that voters in developing democracies routinely engage in ‘ethnic headcounts’ as a way of formulating electoral preferences. In such systems, elections become akin to an ‘ethnic census’ in which parties mobilizing larger ethnic categories have the best chance of winning across institutional designs.
However, unlike Chandra, I claim that this tendency is driven by expectations of access to public goods (‘pork’) rather than individualized transfers for electoral support
(‘patronage’).16 There are three main reasons for this. First, basic public goods often rank at the top of voter demands and dominate electoral rhetoric (Keefer and Khemani 2005;
Khemani 2010). This suggests that most voters prioritize the political party that offers them the best chance of accessing public, rather than private, goods. Second, there is also widespread evidence that politicians in India use their discretionary power to target public goods to their target voters and deny them to their opponents (Reddy and Seshadri
1972; Singh, Gehlot, Start and Johnson 2003; Wilkinson 2006). Finally, the provision of non-programmatic public goods is particularly attractive in electoral systems dominated by the logic of ethnic headcounts. This is so due to the intrinsic qualities of non-rivalry,
16 This follows the typology delineated by Stokes (2009). Dixit and Londregan (1996) refer to public goods transfers as ‘tactical redistribution.’ Diaz-Cayeros, Estevez and Magaloni (2009) employ a different terminology to distinguish between the distribution of private, excludable goods from public, non-excludable goods. In addition to the distinction between private and public transfers, they use categorize them according to the level of government discretion. Based on this definition, they describe ‘pork’ as “discretionary social transfers” (21).
17 non-excludability and lack of reversibility of public goods (Vaishnav and Sircar 2012).
Since parties cannot directly target supporters with ‘pork,’ it makes sense to direct them to those constituencies that are highly homogeneous in their target ethnic category
(Ejdemyr, Kramon and Robinson forthcoming). In this way, they can ensure that the largest number of their supporters benefits from the good, while minimizing the amount of opposition receiving access to it.
In turn, for voters, the non-excludable, non-rivalrous nature of public goods implies that their share of the good does not dilute with an increase in the size of the winning coalition. Instead, the expectation of being favored as part of a ‘core’ constituency, and hence the probability that a party will channel public goods to it, drives them towards parties mobilizing a large winning coalition (Cox and McCubbins 1986;
Dixit and Londregan 1996; Diaz-Cayeros, Estevez and Magaloni 2009).17 In fact, there is already ample evidence that ethnic homogeneous communities in multiethnic societies enjoy higher levels of public goods provision than their heterogeneous counterparts
(Alesina, Baqir and Easterly 1999; Banerjee, Iyer and Somanathan 2005; Habyarimana et al. 2007).
Similarly, previous studies show that Indian politicians typically target basic public goods – bijli, sadak and pani (lit., ‘electricity, roads and water’) – to ethnically homogeneous constituencies. Betancourt and Gleason (2000) show that districts with a
17 I recognize the intense debate about whether resources will be targeted towards ‘core’ or ‘swing’ voters (see, for example, Cox and McCubbins 1986; Dixit and Londregan 1996). However, my argument does require the actual delivery of resources to votes. Instead, the higher expectation of access of a public good in ethnically homogeneous constituencies is sufficient to drive this tendency of individuals to converge around parties mobilizing a matching ethnic category.
18 higher proportion of scheduled castes and Muslims receive lower inputs in health and education. Banerjee and Somanathan (2001) find evidence linking ethnic heterogeneity and poor public goods provision to underlying political incentives – districts that are ethnically fragmented are also likely to be politically fragmented, with elections in these districts having a larger number of contestants and a smaller vote share for the winning party. Finally, the Sachar Committee report (2006, p. 14) points that there is a clear and significant inverse link between Hindu-Muslim spatial segregation following riots and the availability of public infrastructures:
However, while living in ghettos seems to be giving them a sense of security because of their numerical strength, it has not been to the advantage of the Community. It was suggested that Muslims living together in concentrated pockets (…) has made them easy targets for neglect by municipal and government authorities. Water, sanitation, electricity, schools, public health facilities, banking facilities, anganwadis, ration shops, roads, and transport facilities — are all in short supply in these areas.
High levels of segregation also enable political parties to deploy other electoral strategies more efficiently, wasting little resources on the delivery of goods and distributing fewer resources to voters than if voters were dispersed across heterogeneous constituencies. Specifically, ethnic unmixing enables parties to identify the areas where pre-electoral violence is likely to yield the greatest electoral benefits and to provide social services in unfavorable settings. In this way, I argue that the consolidation of electoral constituencies in the wake of ethnic riots contributes to the long-term success of ethnic parties.
My argument complements, rather than contradicts, existing explanations for the
19 emergence and success of the Hindu right. While remaining sensitive to these arguments, my dissertation addresses missing links in each of these accounts: it contributes to a better understanding of the Hindu right’s uneven success among middle class voters across India, namely by emphasizing the role of ethnic segregation in helping parties appeal to their target voters; it shows how a welfare-based strategy can be efficiently deployed to unfavorable political contexts; and accounts for variation in support for the
Hindu right among Other Backward Classes (OBCs). In this way, this dissertation offers a novel theory about the rise of religious parties, illustrates the causal pathways linking violence and enduring electoral support, and lastly contributes to advance our understanding of the success of Hindu right parties in India.
1.4 Calculated or Unintended?
One crucial question concerns the issue of intentionality: are the long-term effects described here the result of a premeditated strategy or an involuntary, yet advantageous, result of the violence? In other words, should ethnic unmixing be considered as part of the repertoire of electoral strategies employed by the Hindu right? Here I contend that, while there may be different logics behind different riots, the evidence presented in the following chapters suggests that, in the severe riots that took place between the mid-
1980s and early 2000s, ethnic unmixing was not just a by-product of the violence but one of its central goals.
First, ethnic unmixing is woven into the history of modern South Asia. Population restructuring was a cornerstone of British ‘divide and rule’ policy, which was
20 methodically implemented to separate Hindus and Muslims in the subcontinent since the
Sepoy Mutiny in 1857 (Pandey 1990). The general opinion among the British colonial authorities was that widespread Hindu-Muslim solidarity among the sepoys (i.e., soldiers in the British Indian Army) was responsible for the anti-colonial rebellion. Communal differences had been rubbed by away by contact in the ranks, and instead a ‘unity of feeling’ had developed among soldiers (Stewart 1951). To prevent this from occurring again, the British colonial authorities decided to reorganize the Indian along communal lines, starting with the Bengal army and later with the Madras and Bombay armies (Bose and Jalal 1997). On this subject, the Chief of Staff in India, Sir W.R. Mansfield, wrote:
I am strongly of the opinion that Mussulmans should not be in the same company or troop with Hindus or Sikhs, and that the two latter should not be mingled together. I would maintain even in the same regiment all differences of faith with the greatest of care. There might be even hatred between two companies or troops.
The discipline of a native regime instead of being impaired would gain by it as regards the greater question of obedience to the commanding officer. The motto of the regimental commander and therefore of the commander-in-chief, must for the future be ‘Divide et Impera’” (Mansfield 1858, p. 54 cited in Stewart 1951).
This principle was then gradually applied to other spheres of government, including the introduction of separate electorates for Hindus and Muslims in local government bodies in 1882-83 and the formal introduction of ‘communal electorates’ at all levels of representation in 1909. Crucially, the man credited with coining the term
‘ethnic unmixing’ – Lord Curzon (Vice-Roy of India 1899-1905) – was also responsible for the first partition of India along religious lines: the 1905 Partition of Bengal. While
21 short-lived, this partition left an indelible mark on South Asian politics.18 For one thing, it marked the transformation of the Indian National Congress (INC) from a middle-class pressure group into a nationwide movement. The Hindus of Bengal regarded the partition as an attempt to stifle nationalism in Bengal and organized a movement to boycott the import of British goods. This campaign soon spread to the whole of India, prompting
Congress leaders to adopt ‘Swaraj’ (‘home rule’) as a programmatic demand for the first time in 1906. For this reason, Gandhi recalled the Partition of Bengal as the ‘real awakening’ of the Indian people to the cause of national independence: “For this we have to be thankful to Lord Curzon” (Gandhi 1909, n.d. cited in Parel 1997).
The partition of Bengal also aroused Hindu-Muslim antagonism: “Before 1905,
Hindu-Muslim hostility was not usually considered to be a major feature of Indian political life” (McLane 1965, p. 221). The partition of Bengal inspired demands for separate elections for Hindus and Muslims that were introduced in 1909. Finally, it served as a model for the 1947 Partition of British India: India was formed out of the majority Hindu regions and Pakistan from the majority Muslim areas. In order to generate homogeneous units, an estimated 200,000 people were murdered and 13 million forced to migrate from their homes between 1946-48 (Wilkinson 2004, p. 13).
Second, the exclusion of non-Hindus from India’s national territory is a core belief and goal of Hindutva (lit. ‘Hindu-ness’) – the political ideology that seeks to assert
Hindu hegemony in the Indian state and the Hindu way of life (Hindu Rashtra). The
18 Bengal was reunited in 1911 following widespread protests.
22 notion of territory is a key theme of Vinayak Damodar Savarkar’s work Hindutva: Who is a Hindu? (1923), the founding text for the ideology of Hindu nationalism. In this book,
Savarkar presents a vision of the Indian subcontinent that is divided into two clear camps, those who possess ‘Hindu-ness’ and those who do not. This vision is intrinsically spatial because the all-important criterion for possessing ‘Hindu-ness’ is that one’s ‘punyaboo’ or holy land should coincide with the geographical space of the Indus basin – “from the
(river) Indus to the Sea” (Savarkar 1923, p. 32). Members of other religious minorities – particularly Muslims, whose aggression is magnified by the precolonial history of
Mughal domination, the postcolonial conflict with Pakistan and militant Islam (Desai
2011) – are conceptualized as ‘outsiders’ who can never experience or comprehend the feeling of being part of the holy land (Misra 2004). In this way, Sarvarkar’s ideological construct provides a basis for the exclusion of the ‘threatening Other’ while legitimizing the irreducible and exclusive affinity of India’s territory for Hindus alone (Deshpande
1995).
Further elaborating on this theme, Guru Golwalkar exhorted Hindus to follow the example set by Nazi Germany by ‘purging the country’ of the ethnic Other (Golwalkar
1939).19 While Golwalkar did not explicitly advocate the use of violence, he declared that minorities wishing to stay in India faced two options:
The foreign races in Hindustan (…) must lose their separate existence to merge in the Hindu race, or may stay in the country, wholly subordinated to the Hindu nation, claiming nothing, deserving no privileges, far less any preferential treatment – not even citizen’s rights (Golwalkar 1939, p. 104-105).
19 Golwalkar was the second Rashtriya Sayamsevak Sangh (lit., ‘National Volunteer Organization,’ RSS).
23 In this sense, then, Golwalker imbued the effort to control and define India’s territory in exclusively Hindu terms with a dual meaning (Panikkar 1993). Hindus have the sole rightful claim to the national territory by virtue of their particular history, geographic location and culture (Oza 2007); yet, at the same time, the demand for the
Hindu national territorial also offers the promise of preferential treatment for the Hindu majority. This, as we shall see, constitutes a crucial component of the Hindu right’s electoral appeal today.
Third, the spatial exclusion of non-Hindus, particularly Muslims, has been a recurrent topic of speeches and public statements by senior figures of the Hindu right.
Welcoming the Ram Rath Yatra in Mumbai, in October 1990, the Shiv Sena founder Bal
Thackeray threatened to wipe out ‘the unholy green’ (the color used as a symbol of
Islam) if the temple construction was obstructed (Panikkar 1993). Following the 2002 riots, the Gujarat Chief Minister, Narendra Modi promised to relegate the ‘merchants of death’ from the state (Outlook 2002).20 He reiterated the claim in a campaign rally in
2007: “Land of Gujarat is such where I used to throw out the merchants of death” (The
Hindu 2007).
More recently, Giriraj Singh, senior BJP leader and member of Parliament for
Nawada constituency, Bihar, accused those opposed to Modi during the 2014 election campaign of acting on behalf of Pakistan. He added: “They have no right to live in India”
(Times of India 2014). Most worryingly, during the campaign, the International Working
20 The expression ‘merchants of death’ was in fact first used by Sonia Gandhi to describe Narendra Modi following the 2002 Gujarat pogrom. Yet, in this speech, used the same expression to refer to Muslims in the state.
24 President of the Vishva Hindu Parishad (lit., World Hindu Council, VHP), Pravin
Togadia, was caught by cameras offering advice to Hindus on how to evict Muslims from
Hindu-majority neighborhoods:
So where we have a majority, we (Hindus) should be brave enough to take the law in our hands and frighten them (Muslims). (…) This is an aggressive war strategy. (…) And go with stones and rocks, and burn tyres. Create the atmosphere of a riot (laughter). (…) Tell them: ‘Then get our building vacated and chase him off.’ (…) I’ve fought this fight for many years. Even if some don’t like it, move in this direction and fight on many fronts (Livemint 2014).
Fourth, consistent with Togadia’s advice, Muslims living in Hindu-dominated areas were most vulnerable during riots. If the aim of the violence was merely to raise the salience of Hindu-Muslim animosity as suggested by the literature on the pre-electoral logic of riots (Wilkinson 2004; Dhattiwala and Biggs 2012; Blakeslee 2013; Arcand and
Chakraborty 2013; Iyer and Shrivastava 2015), then we would expect raids into Muslim- majority localities to stir up communal tensions. However, this was not born out by the riots; on the contrary, reports on Hindu-Muslim riots suggest that the attacks were aimed primarily at Muslims who lived among Hindus. In the words of one scholar, researching the Mumbai 1992-93 riots: “Very rarely were any forays made into large parts of
Mumbai where Muslims were in a majority” (Gupta 2011, p. 22).
One possible explanation for this might be that it is easier and safer to target
Muslims where they were a minority. However, there are two reasons why we should expect something more to be at play here. The first is that intimidation did not seem to deter rioters from entering Muslim-majority localities. In fact, the routing of a Hindu
25 religious procession through a Muslim quarter is a time-tested means of instigating a communal riot and one that was recurrently employed during the Ayodhya dispute.
Sometimes, the following chants were heard during these processions: ‘Musulmano Ka ek hee sthan, Pakistan ya Kabristan’ (lit., Muslims have only two places, either Pakistan or the graveyard) (Dave Commission Report, Vol. I, p. 265 cited by Shani 2007). Second, the sheer size of the rioting mobs – often numbering in the thousands – suggest that
Hindu rioters had the manpower to engage in warfare with large groups of individuals.
However, the few cases where Hindu mobs attacked Muslim-dominated areas are associated with a specific goal – such as the killing of the former Congress Member of
Parliament, Ehsan Jafri, at the Gulbarg society, Ahmedabad, during the 2002 Gujarat riots.
Fifth, numerous Shiv Sena and BJP leaders were seen leading and/or directly participating in systematic attacks against residential and commercial property belonging to Muslims. For instance, in September 1990, witnesses saw elected leaders of the BJP directing attacks on the property of Muslims in Vadodaras’s walled city (Concerned
Citizens Tribunal 2002). In January 1993, a Shiv Sena leader led attacks against Muslim pockets in Mahim, Mumbai (ShriKrishna Commission Report 1998). He has since become a long-standing corporator for the area. Similarly, during the 2002 Gujarat riots, two BJP municipal corporators were seen inciting a crowd and shouting ‘Send Muslims to Pakistan’ in Vatva, Ahmedabad (Concerned Citizens Tribunal 2002). The official reports into the Mumbai and Gujarat also accuse Shiv Sena and BJP leaders of helping the mobs identify Muslim houses.
26 Finally, abundant evidence of prior planning and strategic design suggests that the
Sangh Parivar’s Ayodhya campaign sought to accomplish much more than to merely win elections in the early 1990s (Pannikar 1993; Jaffrelot 1996). Through this violent campaign, the Hindu right also attempted to generate a fundamental chasm between
Hindu and Muslims and, in this way, to consolidate and expand its electoral base. Ethnic unmixing provided an efficient and even intuitive means for accomplishing this goal given the past experiences of colonialism and Partition, the marked spatial connotations of Hindutva, and its enduring legacy in the social fabric of affected cities. Thus, to quote
Deshpande, there are few better examples than Ayodhya of attempts by politicians to turn an imagined into a real place in such a way that binds people to particular identities, and to the political consequences they entail:
The transformation of this rural small town (Ayodhya) from merely another geographically specific place into a heterotopia was the result of a conscious spatial strategy. There was nothing ‘natural’ about it (Deshpande 1995, p. 3221).
This is not to state that all riots are designed to produce ethnic unmixing. Indeed, it is entirely plausible that politicians may have different political incentives for promoting different Hindu-Muslim riots. Specifically, given the role of local incentives behind the violence (Wilkinson 2004), politicians may be more oriented by short-term goals in some riots, such as those occurring in the run-up to a particularly tight electoral race, than in others. In such cases, ethnic unmixing may indeed be a secondary, or even accidental, consequence of the riot. However, to the extent that riots serve strategic
27 electoral goals, we should expect politicians to seek to extend their benefits long after the violence has subsided.
1.5 Research Design and Chapter Outline
The rest of the dissertation is divided into five chapters, and employs a subnational and mixed methods approach to examine the link between Hindu-Muslim riots and the rise and enduring success of the Hindu right in India. India is ideally placed for shedding light on questions related to religion and politics. It is the world’s largest democracy and one of the most ethnically diverse countries in the world – birthplace to several of the world’s major religions, home to thousands of distinct castes and indigenous tribes, and 26 official language groups. It is also a federal parliamentary democracy composed of 29 states and 7 Union territories that operates according to the
Constitution of Indian, adopted on the 26th November 1949. These states and territories are divided into districts, which in turn are subdivided into national, assembly and municipal electoral constituencies, the primary units of analysis for this project. Nearly all electoral constituencies are governed by identical first-part-the-post, single-member district rules.21 This enables us to use data that explores great variation across and within
India’s subnational units while holding institutional and electoral design constant.
Within India, I focus on its seven largest cities: Mumbai, Delhi, Bangalore,
Hyderabad, Chennai, Kolkata and Ahmedabad. There are three reasons for this choice.
21 The exception are the municipal elections in Gujarat, where there are three candidates (one running in the general category, one for women quota and one for SC/ST category) for each electoral constituency.
28 First, cities afford us a relatively stable, evidence-rich and quantifiable unit of analysis.22
Second, previous research shows that Hindu-Muslim violence in India is primarily an urban phenomenon (Varshney 2002). Yet, Indian cities vary significantly in terms of communal violence: some cities, such as Mumbai, Hyderabad and Ahmedabad are riot- prone, whereas others, such as Delhi, Kolkata, Bangalore and Chennai are relatively peaceful. This study thus takes advantage of variation in patterns of Hindu-Muslim violence across Indian cities to study the link between ethnic violence and the enduring rise of ethnic parties. Lastly, these cities are distributed across India’s national territory and present different socio-demographic characteristics, thus affording us a diversified sample in each of the explanatory and causal variables.
22 It is true that the boundaries of cities have also expanded during this period but they have a smaller impact on this analysis because this section focuses on data aggregated at the city level. I will also include urban growth as one of the control variables in this analysis. Nonetheless, I recognize that future elaborations on the rise of the Hindu right in India may be able to address this issue through the use of sophisticated geographic information technology (GIS).
29
Figure 1.3: Case Studies
This project focuses on the two main parties of the Hindu right: the Bharatiya
Janata Party (BJP) and the Shiv Sena (SS). These two parties play a prominent role in
Indian politics both as the champions of the majority Hindu community in the country
(representing roughly 80 percent of the population) and as the main partners of the
National Democratic Alliance, which currently heads the national government. While
30 there are differences in scope and organization between them, both the BJP and the SS espouse the core principles of Hindutva (lit. Hindu-ness). For this reason, this project considers them jointly as the prime examples of ethnic parties seeking to mobilize the
Hindu majority in India.
It is also important to note that, while employing the broad ascriptive categories
‘Hindus’ and ‘Muslims,’ I recognize that both communities are internally differentiated.
In fact, from the viewpoint of the Hindu right, the purpose of violence among Hindus and
Muslims is precisely to promote a feeling of Hindu unity against alleged Muslim aggression. Thus, in addition to the rigid division of Hindus into the four main castes
(‘varna’) and multiple subcastes (‘jati’), there also important differences in terms of class, language, region, political outlook and ritualistic practices. Indian Muslims have also a variant of the caste system, according to which the Ashraf (‘nobles’) represent the elite groups, the Ajlaf (‘commoners’) are mostly descendants of converts from Hindu lower castes and the Arzal (‘despicable’) are Hindu Dalit (‘untouchables’) converts and their descendants. However, this caste system is less rigid than the Hindu variant and there is more scope for social mobility (Gayer and Jaffrelot 2012). Muslims are also divided along sectarian lines, particularly between Shias and Sunnis. Finally, like Hindus, there is significant variation among Muslims in terms of class, language, region, political outlook and ritualistic practices.
To empirically examine the argument, I employ a mixed methods research design that combines large-N statistical analysis with in-depth case study research. The
31 empirical chapters of the dissertation are structured into two sections corresponding to each of the steps of my causal claim. Each section is composed by a quantitative and a qualitative chapter. This structure follows the most conventional template for mixed methods research: a quantitative analysis examines the direction and significance of the relationship between variables and the qualitative explorations sheds light on the causal mechanisms as well as the robustness of the findings (King, Keohane and Verba 1994;
Mahoney 2010). Here, I briefly outline the remaining chapters of the dissertation:
1.5.1 Ethnic Riots and Ethnic Unmixing
The first part of the dissertation examines the link between communal riots and spatial segregation by religion. In chapter 2, I employ original data to conduct two statistical tests on the impact of communal riots on the degree of Hindu-Muslim segregation. First, I examine the statistical correlation between current level of Hindu-
Muslim segregation and the frequency and intensity of Hindu-Muslim riots across a large sample of Indian cities (n = 101). Due to the political sensitivity of religious demography in India, the government does not release disaggregated data on religion.23 To remedy this shortcoming, I employed big data analytics to generate estimates of religious demography at the municipal, assembly and parliamentary constituency level.
Specifically, I used novel computer software to extract and match electors in Indian electoral rolls according to their religious identity. These rolls are publicly available online thanks to recent transparency and e-government initiatives by the Election
Commission of India (ECI). The rolls contain information about voters’ names, age,
23 For example, the Census of India publishes only religious figures for whole cities, not for smaller enumeration units.
32 polling booth, ward (i.e., municipal constituency), assembly and parliamentary constituency. I then used a name-matching algorithm specifically developed for this purpose (Susewind 2014) to match the names of voters on electoral rolls to religious communities. This constitutes the largest available dataset of religious demography in
Indian cities, comprising over 51 million voters, 35,781 electoral booths, 1,389 municipal wards, 187 state assembly constituencies and 26 national assembly constituencies. The results presented on Chapter 2 provide compelling evidence for the existence of high levels of spatial segregation by religion in India’s largest cities. Most importantly, they show a positive and significant effect of communal riots on the level of residential segregation by religion. This finding is robust to possible confounders as well as controls for unobserved variation.
To complement this analysis, I then explored in greater detail the evolution of segregation across the seven Indian metro cities under scrutiny in this study. Given the difficulty in collecting fine-grained, time-series data on local demography, I use a proxy variable for this analysis: the number of Muslim candidates standing in a given constituency for State Assembly elections. The choice of this proxy variable is consistent with previous scholarship (Rudolph and Rudolph 1987; Dasgupta 2009; Heath, Verniers and Kumar 2015; Thakur 2015) and, as we shall see on chapter 2, with contemporary estimates of religious demography at the constituency level.
At the same, this proxy affords numerous advantages from a methodological viewpoint. First, the number of Muslim candidates in an electoral constituencies enables
33 us to examine alternative explanations for existing patterns of communal segregation, namely historical patterns of settlement and gerrymandering. Another benefit is the possibility of using scalable, fine-grained data that is publicly-available on the ECI’s website. Therefore, to measure this proxy, I matched the names of candidates on the
Statistical Reports of the last eight Legislative Assembly elections to a binary religious category: Muslim or no-Muslim. I then used the index of isolation (Massey and Denton
1988) – which measures the probability that members of two different communities share a spatial unit (in this case, the electoral constituency) – to examine the variation in Hindu-
Muslim segregation. The analysis shows that not only is the change in segregation by religion consistent with the intensification of Hindu-Muslim between the late 1980s and early 2000s but also that it agrees with the intensity and frequency of riots across India’s seven largest cities.
Finally, to illuminate the causal mechanisms underpinning the relationship identified by the previous statistical analyses, Chapter 3 examines why and how the Shiv
Sena promoted ethnic unmixing during and after the 1992-93 riots in Mumbai for its own electoral benefit. Mumbai affords us a unique opportunity to study the relationship between ethnic riots and ethnic unmixing for three main reasons. First, given its high values in both the dependent and crucial independent variables, Mumbai constitutes a
‘typical case study’ in this study – regarded by the qualitative methods literature as the most useful for unpacking causal mechanisms (Gerring 2007; Seawright and Gerring
2008; Beach and Pederson 2016). Second, scholars (Blom Hansen 2001; Gupta 2011;
Khan 2011; Contractor 2012) generally agree that the 1992-93 riots had a striking and
34 lasting impact on Hindu-Muslim segregation in Mumbai. Finally, as we shall see, the
1992-93 riots also marked a clear turning point for the Hindu right, particularly the local
Shiv Sena, in Mumbai.
The chapter employs extensive archival research along with interviews with riot victims, activists, journalists and politicians to illustrate two main points. First, politicians promote favorable ethnic demographies when they contemplate electoral marginalization.
Second, intense and frequent ethnic riots trigger two types of migratory flows: (1) an initial movement of people forced to flee their homes as a direct consequence of the violence; and (2) an unmixing cascade in search for ‘safety in numbers’ that trickles over many years after the violence. In this way, I argue that that severe and protracted ethnic riots are an effective, albeit brutal, means for producing ethnic unmixing that becomes a permanent feature of the electoral landscape.
1.5.2 Ethnic Unmixing and Ethnic Party Success
Part two of the dissertation examines the relationship between ethnic demography and the performance of ethnic parties. Chapter 4 draws on an original dataset of demographic variables and electoral results in India’s seven largest cities: Mumbai,
Delhi, Kolkata, Bangalore, Chennai, Hyderabad and Ahmedabad. In addition to the contemporary estimates of religious demography, I collected data on four other social indicators for this analysis – gender, caste, socio-economic status and age. Gender and age were collected using the information in the electoral rolls, whereas caste and socio- economic status were assembled from the 2011 Census of India. To measure caste, I
35 combined data on the two constitutionally recognized disadvantaged categories –
Scheduled Castes (SC) and Scheduled Tribes (ST). Since the Census does not include a specific question on income or consumption, I used ward-level data on male illiteracy as a blunt measure of socio-economic status following previous studies (Vithayathil &
Singh 2012; Sidhwani 2015). State election results were collected from the website of the
Election Commission of India (ECI) and municipal election results were collected from the respective State Election Commission’s (SEC).
The analysis lends strong support to the existence of a positive link between growing Hindu-Muslim segregation and the Hindu right’s success. The analysis shows that not only are Hindu-majority constituencies more likely to vote for the Hindu right but also that this likelihood increases with the size of the Hindu majority in a constituency. This finding is robust to additional covariates, as well as control for unobserved variation at the municipal and state constituency level.
Building on these results, Chapter 5 then examines the relation between communal riots, Hindu-Muslim unmixing and resilient support for the BJP in
Ahmedabad, the capital of the western Indian state of Gujarat. As in the case of Mumbai,
Ahmedabad provides us a typical, yet extreme, case in which to investigate the causal mechanisms underpinning the relationship between ethnic unmixing and the BJP’s enduring success. Drawing on extensive qualitative evidence collected during two stints of fieldwork in Ahmedabad (between June-July 2014 and November-December 2015), I first show how the BJP turned to ethnic unmixing as an electoral strategy due to its
36 limited means to expand its popular base without antagonizing its core elite base as well as the city’s incompatibility with a welfare-based strategy. I then show how these three phenomena – communal riots, religious unmixing and BJP success – have evolved alongside each other each since the mid-1980s in Ahmedabad.
Then, I outline the system of interacting parts that transforms ethnic unmixing into long-term ethnic party success. Specifically, I highlight three electoral effects of religious unmixing: (1) increased visibility of the Hindu-Muslim divide vis-à-vis other social categories; (2) consolidation of the link between religious identities and access to public goods; and (3) advantages in the deployment of other electoral strategies.
This investigation has three main implications for theory and policy on ethnic conflict. First, Ahmedabad’s trajectory provides us an insight into what may lie ahead for other riot-affected cities in India. Second, this chapter suggests that, from the politicians’ point of view, the goal of the violence is not to make the ethnic Other disappear but to push them towards ghettos, where the differences between groups can be permanently highlighted. Finally, this examination of Ahmedabad enables me to show that political parties have both short- and long-term incentives for the production of ethnic riots. Riots enable a party raise a salient ethnic category in the run-up to a competitive election but they also enable them to inscribe an ethnic divide in the spatial tissue of a city and, in this way, to turn it into a device of enduring power.
37 1.5.3 Conclusion
The dissertation’s conclusion offers some thoughts on the broader implications of the argument articulated in the dissertation. Specifically, I highlight how the findings of this dissertation contribute to the scholarly and policy debates on the rise of ethnic parties, the electoral incentives behind ethnic riots and Indian politics. I also outline the implications of these results for the future of India. I then undertake a brief discussion of two cases that could be further explored to test the external validity of the link between ethnic riots and the enduring rise of an ethnic party. The first example is the success of the Orange Democratic Movement (ODM) in Kenya following the 2007-08 wave of violence. The second example is the enduring rise of the Sinn Fein in Ireland following the intensification of Catholic-Protestant violence in the early 1970s. To conclude the dissertation, I outline two areas where further research is warranted: the conditions under which ethnic unmixing may fail to promote long-term support for an ethnic party and whether the argument advanced in this dissertation applies to parties seeking to mobilize other ethnic categories in India.
38 Chapter Two
Hindu-Muslim Riots and Ethnic Unmixing in India
Homogeneity is what rioters want, and growing homogeneity is what they get. -- Donald L. Horowitz, The Deadly Ethnic Riot, 2001
The violence has also proved a successful catalyst for the community’s ‘ghettoization.’ (…) Muslims cannot work, reside or send their children to schools in Hindu dominated localities. -- Human Rights Watch, Compounding Injustice, 2003
2.1 Introduction
The first part of this dissertation links ethnic riots to the unmixing of peoples along a matching ethnic category. Specifically, I argue that the intensification of Hindu-
Muslim violence between the late 1980s and early 2000s has shifted the religious composition of urban areas in India, constructing homogeneous constituencies where relative heterogeneity had been the norm. In my account, intense and frequent ethnic riots trigger two types of migratory flows: (1) an initial movement of people forced to flee their homes as a direct consequence of the violence; and (2) an unmixing cascade in search for ‘safety in numbers’ that trickles over many years after the violence. In this way, I argue that migrations of ethnic unmixing in the aftermath of riots produce demography shifts that become permanent features of the electoral landscape.
39 This chapter uses original quantitative data to address two questions related to this argument. First, to what extent did communal riots shape the distribution of Hindus and
Muslims in Indian cities? In other words, is there a positive and statistically significant relationship between the degree of Hindu-Muslim segregation – the dependent variable in this first part of the dissertation – and the intensity and frequency of communal riots in urban India.24 Second, does the evolution of Hindu-Muslim segregation in India’s metro cities closely follow the intensification of communal violence during the Ayodhya movement? If so, can riots be shown to have an independent effect on patterns of Hindu-
Muslim segregation, beyond historical patterns of segregation by religion and the re- delimitation of electoral constituencies in India in 2008?
Empirically evaluating the answers to these questions presents a number of problems related to data and measurement. Segregation is generally difficult to capture because its measurement requires fine-grained data on the distribution of ethnic categories within small areas (Kasara 2017). In India, this problem is further compounded by the government’s reluctance to release official data on religious demography (the last time the Census of India released ward-level figures on religion was 1961 and then only for some of the major cities).
This chapter seeks to remedy these shortcomings through an analysis of two novel sources of data. First, as a result of e-government and transparency initiatives, the
Election Commission of India (ECI) has made available online the electoral rolls for all
24 Residential segregation is defined here as the extent to which individuals of different social categories occupy localities characterized by different social compositions within a given geographical area (Reardon and O'Sullivan's (2004).
40 constituencies in India. The rolls contain crucial information about voters’ names, gender and age. Using a probabilistic algorithm that matches Indian names to specific religious categories (Susewind 2014), I created an original dataset that contains estimates of religious demography for all municipal, state and parliamentary constituencies in India’s seven largest cities, as well as all statutory cities in the northern states of Uttar Pradesh and Gujarat (N = 101). I then use this dataset to examine whether the frequency and intensity of Hindu-Muslim riots correlates with contemporary estimates of Hindu-Muslim segregation in urban India.
Second, to complement this analysis, I examine the evolution of segregation across India’s seven metro cities. Because it is difficult to collect scalable, fine-grained, time-series data on local demography, I use a proxy variable for this analysis – the number of Muslim candidates in a State Legislative Assembly constituency. As we shall see, this measurement is consistent with previous literature on Muslim voting preferences in India (Rudolph and Rudolph 1987; Dasgupta 2009; Heath, Verniers and Kumar 2015;
Thakur 2015) and fits also with the contemporary estimates of religious demography. In turn, this proxy enables us to examine how the argument stands up against the two main alternative explanations for existing patterns of communal segregation, namely historical patterns of settlement and gerrymandering. Moreover, since the detailed electoral results for all assembly elections in India are available on the ECI’s website, this proxy also has the advantage of providing us a using scalable, fine-grained, time-series data on local demography.
41 The results presented below suggest that communal riots and Hindu-Muslim segregation do in fact go hand in hand: the extent of segregation by religion in urban
India is positively correlated with the frequency and intensity of communal riots. This finding is robust to possible confounders as well as controls for unobserved variation.
The time-series analysis further confirms this result. It shows that Hindu-Muslim segregation in India’s seven metro cities has evolved consistently with the intensification of communal violence during recent decades. Finally, this examination suggests that the effect of communal violence on patterns of Hindu-Muslim segregation is independent of both historical levels of segregation and possible manipulation of constituency boundaries during the 2008 re-drawing of electoral constituencies in India.
The remainder of the chapter is organized as follows. I first outline a general argument about the link between communal violence and spatial segregation. I then situate this argument within the extant literature on segregation by religion in India. Next,
I discuss the sources of data, the case studies, the measurement details and the results of my cross-sectional analysis of the effect of communal riots on Hindu-Muslim segregation across India. I then present the data, the measurement details and the results of my time- series analysis of Hindu-Muslim segregation in India’s seven metro cities. Finally, I conclude with some thoughts about how these results might inform an investigation of the causal mechanisms linking ethnic violence and unmixing, which I take up in the following chapter.
42 2.2 Riots and Segregation
My argument linking ethnic riots and the accentuation of segregation by ethnic categories builds on Brubaker’s notion of ‘ethnic unmixing’ (1995; 1998). Brubaker argues that ethnic violence produces migratory flows that radically simplify the ethnic demography of departing and receiving areas by constructing relatively homogeneous populations where great heterogeneity had been the norm. He names these as migrations of ‘ethnic unmixing.’25 Brubaker observes that this wholesale restructuring of populations takes not only the spectacular form of refugee flows, forced migration, large-scale population ‘transfers’ or ethnic cleansing, but also less dramatic less flows that unfold over the long-term. Most importantly, he observers that migrations of ‘ethnic unmixing’ occur in the context of ethnic war but also in nationalizing states at times of
‘supercharged mass ethnic nationalism’ (Brubaker 1995, p. 192-194).
Subsequent studies have also found a consistent link between the occurrence of violence across ethnic lines and the production of migratory flows that radically simplify ethnic demography. Kaufman (1996) illustrates the general applicability of the concept in as diverse contexts as Armenia, Nigeria, Serbia and Rwanda. While refuting Kaufman’s vision of unmixing as a solution to conflict, Laitin (2004) notes that ethnic war has ‘a powerful effect’ on ethnic unmixing (Laitin 2004: 365). More recently, Weidmann and
Salehyan (2013) point out that, since the 2003 United States-led invasion of Iraq,
Baghdad has changed from a city where Sunnis and Shias resided in mixed neighborhoods to one with well-defined ethnic neighborhoods. They argue that, even
25 Incidentally, he borrowed the expression ‘ethnic unmixing’ from Lord Curzon, who as the Viceroy of India (1899-1905) oversaw the first partition of Bengal into Hindu- and Muslim-majority provinces.
43 assuming that people prefer living with co-ethnics, violence can dramatically increase ethnic segregation (Weidmann and Salehyan 2013).
However, little attention has been dedicated so far to the effects of ethnic riots on the spatial distribution of ethnic communities.26 This is surprising given the abundant evidence that riots are also a powerful means for restructuring ethnic demography.
According to one estimate, the number of post-riot refugees and internally displaced persons (IDPs) surpasses the number of officially reported deaths on average in a ratio of at least 100 to one (Horowitz 2001). For example, communal violence in Kenya in 2007-
2008 claimed over 1000 lives and left up to 600,000 individuals displaced (Adeagbo and
Iyi 2011). In 2010, clashes between ethnic Kyrgyz and Uzbeks in southern Kyrgyzstan killed more than 420 people and produced 300,000 internally displaced and over 111,000 refugees across the border in Uzbekistan (International Crisis Group 2012). Taking stock of this growing literature, Horowitz (2001, p. 441) concludes that these migrations are not merely a side effect of the frenzied violence, but one of the central goals of riots:
Every study finds that, with each outbreak of violence, the affected locality became more segregated. Nor is this surprising. The violence generally occurred where the two groups met. The parades that usually precipitated violence were intended partly to delimit territory claimed by each group.
26 To my knowledge, the only study that engages with the spatial repercussions of smaller episodes of ethnic violence is Kimuli Kasara’s (2016) working paper on ‘redistricting through violence.’ Her work shares important points of contact with the argument advanced in this dissertation, namely the central idea that political use violence to strategically alter the demographic composition of electoral constituencies to their benefit. However, she does not explore whether the effects of unmixing are short- or long-term. Instead, her main goal is to explore the conditions under which politicians are more likely to use this strategy. She concludes that politicians are more likely to use violent redistricting where it can sway electoral results and when their opponents supports are less likely to return if displaced by violence. These conclusions are largely corroborated by my work as we will see in the following chapters.
44 Building on these insights, I argue that severe and protracted ethnic riots are an effective, albeit brutal, means for producing ethnic unmixing. Specifically, I contend that ethnic riots trigger two types of migratory flows. The first consists of the initial movement of people forced to flee their homes as a direct consequence of the violence.
This flow is driven by push factors: migrants leave their homes due to a threat to their physical integrity or due to the severity of the damage caused to their property. These migrants are overwhelmingly members of the target ethnic category, though members of other ethnic categories, including members of ethnic categories peripheral to the conflict, may also be involved.
In most cases, these migrants simply relocate to another locality within the same city inhabited by a majority of their co-ethnics. In other cases, these migrants depart the settings of the violence and return to their home town or village where they can rely on a personal network of support. And in other cases still, these migrants find shelter in refugee camps located in or around the areas where the ethnic riot took place. They eventually relocate to other neighborhoods or, in the worst possible scenario, become permanent residents of the camps.
The second migratory flow corresponds to Brubaker’s description of the less dramatic migratory streams that persist in a steady trickle over the long-term. In this second migratory flow, the search for ‘safety in numbers’ plays a key role in the decision to relocate. For many, the violence provided indubitable proof of the state’s inability (or unwillingness) to keep peace between the hostile ethnic communities. As fears for their
45 future safety increase, individuals begin to privately invest in and prepare for further instances of violence. One of the most effective ways to ensure their safety in an ethnically charged environment is to move to an area dominated by co-ethnics. Yet, by doing so, they trigger a self-sustaining process: as more and more co-ethnics move out, those individuals left behind feel increasingly defenseless in a sea of potentially hostile ethnic others.27 This creates further incentives for co-ethnics to relocate.
Crucially, since majorities can become minorities in the context of locality, the search for ‘safety in numbers’ afflicts both the minority and majority communities. The influx of members of a minority community can thus create pressure in the reception area, thus leading to reciprocal outmigration of the members of the majority community, finally making both the sending and the receiving areas more homogeneous (Lake and
Rothchild 1996; Kaufman 1996; Horowitz 2001).
Beyond the search for safety in numbers, there are other factors contributing to ethnic unmixing following riots. Previous authors highlight numerous examples of physical intimidation of the remaining members of the ethnic minority to push them out
(see Horowitz 2001 for an overview). Previous work also suggests that the majority community can engage in economic boycotts of the minority group to further deteriorate the communal environment (Kaur 2005; Human Rights Watch 2003). Finally, there is also widespread evidence of growing discrimination against minority tenants and buyers
27 This follows in line with Schelling’s segregation model (1971): if individuals of one ethnic category see a significant increase in the critical mass of individuals of another ethnic category in their neighborhood, they might want to move out of the neighborhood in order to continue to live among co-ethnics. The result, Schelling argues, is total segregation on a salient ethnic category.
46 in housing markets (Basant and Shariff 2015; Susewind 2015). Riots aggravate negative perceptions that shape living preferences (i.e., who lives in the same building) and, in turn, market prices (i.e., the presence of the ethnic minority is regarded as a negative factor on property values).
To conclude, then, there are good theoretical reasons to anticipate that ethnic riots trigger a process of spatial segregation between the ethnic categories. This process occurs not only in the immediate aftermath of riots but tends to grow over time, in such a way as to become a permanent feature of affected localities. In the following sections, I test this hypothesis by exploring the case of Hindu-Muslim riots in urban India.
2.3 Hindu-Muslim Unmixing in India
The argument outlined in the previous section may sound familiar to scholars studying Hindu-Muslim conflict in India. Indeed, a growing scholarship already links the increasing spatial segregation of Muslims in urban Indian to protracted Hindu-Muslim
‘communal’ violence (see for example, Breman 1999; Hansen 2001; Mahadevia 2002;
Field et al. 2008; Chatterjee 2011). The Sachar Committee report on the status of Indian
Muslims – conducted in 2005 at the request of Prime Minister Manmohan Singh – highlighted the link between recent episodes of severe communal violence and growing segregation: “Fearing for their security, Muslims are increasingly resorting to living in ghettos across the country” (Sachar et al. 2006, p. 14). More recently, Gayer and
Jaffrelot (2012, p. 21) edited a volume on the marginalization of Muslims in Indian cities that reiterated the link between communal violence and increasing segregation:
47 And the intensification of these urban episodes of communal violence has redefined the geography of many a city during the last two decades, following the Ram Janmabhoomi Movement, the destruction of the Babri Masjid, the Mumbai Riots of 1992-93, or, more recently, the 2002 Gujarat pogrom.
At this point, it may thus seem pertinent to ask if there is a need for another study about the effect of Hindu-Muslim violence on patterns of Hindu-Muslim segregation in urban India? I contend there is. In addition to advancing a novel theory about this relationship, this chapter seeks to correct three important lacunas of the extant literature.
The first is a lack of quantitative empirics on segregation by religion in urban India. Most authors rely on interviews and ethnographic field work to make statements about the extent and causes of Hindu-Muslim segregation in India. Their emphasis on qualitative methods contrasts with the quantitative tradition of spatial segregation research in the
United States and Europe (see for example, Duncan and Duncan 1955; Winship 1978;
Massey and Denton 1988; Reardon and O’Sullivan 2004). It also lies in opposition to recent work on residential segregation by caste, gender and socio-economic status in
India (Khairkar 2008; Vithayathil and Singh 2012; Sidhwani 2015). There is thus an urgent need to align methodological approaches to segregation by religion in urban India with dominant practices of the broader scholarship on segregation.28
Second, the few existing analyses of segregation by religion in India have so far focused on single case-studies. For instance, previous scholars have studied the segregation of religious communities in Delhi (Dupont 2004), Pune (Mehta 1968, 1969),
28 In fact, Vithayathil and Singh (2012, p. 65) recommend that future studies of urban segregation in India include religion in their analyses: “At the very least, we encourage the Indian government to make religion and more specific education data available at the ward level, particularly for older censuses, now that data for Census 2011 has been collected and will be available shortly.”
48 Lucknow (Susewind 2015) and Ahmedabad (Field et al. 2008). However, there is a paucity of systematic cross-sectional quantitative data to evaluate residential segregation by religion across Indian cities.29 Moreover, much previous work focuses on cases with high levels of segregation by religion, dedicating little attention to negative cases. This can lead to a bias toward extreme cases on the dependent variable, which results in an
‘overethnized’ view of the social world (Brubaker 2004).
Finally, existing work tends to emphasize the experiences of Muslims following riots. This is comprehensible given that they constitute the primary targets of the post- independence violence. Yet, our understanding of post-riot segregation would be limited without an account of how communal violence has shaped the spatial distribution of other religious groups, particularly Hindus, who constitute the overwhelming majority (79.8%) in the country. Put in other words, Muslims are not segregating alone. The theoretical framework advanced in this chapter highlights that the processes of religious unmixing in the aftermath of riots involve both the minority and majority communities. In this way, my argument offers a comprehensive account of the effect of Hindu-Muslim riots, particularly between the late 1980s and early 2000s, on the increasing segregation between religious communities in urban India.
2.4 Cross-Sectional Analysis
The first step towards testing this argument involved measuring the degree of
29 The notable exception to this is Raphael Susewind’s recent work (2017). He uses the index of dissimilarity and three other adjusted indexes to measure Muslim segregation in the 11 Indian cities explored in the ethnographic volume edited by Laurent Gayer and Christophe Jaffrelot (2012). His research differs from mine in that he focuses on the degree of residential segregation of Muslims, as opposed to Hindus, and that he measures segregation at the booth level, whereas my work, as follows from the hypothesis advanced, focuses on constituency level segregation.
49 Hindu-Muslim segregation in urban India. This presented several methodological challenges since the Census of India, the single largest source of demographic data in
India, does not publish ward-level figures for religious demography. Other sources of data are either too large or too small to produce scalable and fine-grained estimates of religious demography. Indeed, due to a scarcity of reliable and publicly available religious subcity data, existing quantitative studies of religious demography in India are limited to the district level, the city level or the state level (Varshney 2002; Wilkinson
2004; Chandra 2004). Moreover, issues of timing, sample size and even wording make it difficult to cross-tabulate existing survey data on religious demography.
Fortunately, recent ‘open government initiatives’ by the Election Commission of
India (ECI) as well as advances in big data analytics have made it possible to explore a novel source of data: voter data on electoral rolls. The rolls, published online, contain information about voters’ names, age, polling booth and station, ward (i.e., municipal constituency), assembly and parliamentary constituency. This constitutes a breakthrough for studies of religious demography in India because the religious connotation of names in the electoral rolls can be exploited to create estimates of religious demography at the constituency level. In fact, previous studies have already extracted names from electoral rolls for this purpose (Field et al. 2008; Galonnier 2012). The novelty of the approach reported here lies in one crucial difference: whereas previous works coded the names in the electoral rolls manually, a consuming task both in terms of resources and time, I used computer software to extract the data from the rolls and then match the names of the rolls to religious communities.
50 2.4.1 Sources of Data
To test this argument, I use the State Assembly Constituency as my unit of analysis to generate a city-level index of Hindu-Muslim segregation. This choice presents advantages from the perspective of data analysis (since there is a paucity of locality-level data on riots) and is also congruent with my hypothesis: according to my formulation, riots shape the ethnic demography not only of affected areas, but also of neighboring localities where individuals move in search of safety in numbers. Therefore, riots shape segregation patterns throughout the entire city. There is another important methodological advantage in measuring segregation at the city-wide level: while the boundaries of electoral units rarely match those of Census, it is possible to aggregate both data generated from the electoral rolls and from the Census, as well as on Hindu-Muslim violence, up to the city-level. In this sense, then, the city provides us the most appropriate unit for examining the statistical impact of communal riots on Hindu-Muslim segregation.
I utilized three sources of data for this analysis. First, I extracted voter data from the May 2015 electoral rolls for five of India’s largest cities – Delhi, Bangalore,
Hyderabad, Chennai and Kolkata. To do so, I downloaded the respective PDF files from the Election Commission of India’s (ECI) website and then used an open source command script (‘pdftotext’) to convert voter data into usable comma-separated values
(CSV) format.
Once voter data had been extracted from the electoral rolls, I used a name-
51 matching algorithm to match the resulting names lists to specific religious categories
(Susewind 2014).30 This open-source algorithm probabilistically matches the names of voters to religious communities based on a reference list extracted from the website indiachildnames.com.31 This algorithm outputs the most plausible categorization and all potential alternatives as well as a certainty index that allows for flexible accuracy thresholds. Accuracy tests demonstrated that the algorithm’s positive predictive value
(i.e., the rate of accurate positive matches) stood at 95% while its negative predictive value (i.e., the rate of accurate negative matches) stood at 99%. Overall, 5% of names could not be classified and were discarded. The algorithm also possesses the advantage of scalability that enables researchers to examine voter lists across a vast number of electoral constituencies.
However, encryption of electoral rolls in Maharashtra and Gujarat, blocked attempts to extract voter data for the remaining two metro cities in India, Mumbai and
Ahmedabad. As a solution, I gathered voter names for Mumbai from the official National
Voter’s Service Portal (http://electoralsearch.in/). While efficient, this approach had three limitations.
30 It is important to note that name-matching algorithm is only as precise as the reference list against which the names are matched. The algorithm employed in this project did not yield information about intra-faith divergences (e.g., between Sunnis and Shias or between Christians and Protestants) or other relevant ethnic categories, such as caste, region or language. While access to this information would certainly provide fascinating detail, my argument highlights the effect of communal riots on segregation between two broad religious categories, Hindus and Muslims. This does not negate the possibility that there is also sharp spatial segregation within each of religious category. It is also important to note that the reference list employed in this analysis is more sensitive to North than South Indian names, leading to a higher number of discarded names in Bangalore and Chennai. Still, the number of discarded names in these two cities was marginal relative to the total names extracted.30 Finally, the matching of individuals to a religion on the basis of their personal names does not presuppose that they are practicing members of that religion. Yet, this is not necessary for the present analysis because my goal is not to measure religiosity but the religious composition of localities within cities. 31 A database that links roughly 23,000 names to gender and the religious categories Hindu, Muslim, Sikh, Christian, Jain, Parsi, and Buddhist.
52 First, the data collected from the National Voter’s Service Portal does not include information regarding voters’ polling booth and ward. This means that the lowest possible level of aggregation for Mumbai is the state assembly constituency (as opposed to the other cities, in which it was possible to collect information at polling booth level).
Second, the search engine at the National Voter’s Service Portal yields data by voter details (i.e., personal names or EPIC number) rather than by electoral constituency. Since it is not possible to know the names of all voters in Mumbai, the data collected represents a sample rather than the complete list of electors in Mumbai (again, as opposed to the other cities, in which the names of all voters were extracted from the electoral rolls).
Finally, using personal names to extract data from this website is a difficult (as a result of captcha tests) and time-consuming task. To maximize the volume of data collected with the minimum available resources, I searched a list of thirty-one common surnames associated with particularly religions in Mumbai City and Mumbai Suburban districts
(Annex I). I selected names in proportion to the overall percentage of the city according to the Census 2011 (Hindus, 65.99%; Muslims, 20.65%; Buddhists 4.85%; Jains 4.10%;
Christians 3.27%). Overall, I extracted 1,821,817 (17.86%) names out of a total
10,203,056 electors in Mumbai.
The third source of data for this analysis was a dataset of the number of Hindus and Muslims in all constituencies in Gujarat and Uttar Pradesh (Susewind and Dhattiwala
2014).32 This dataset, kindly shared with me by the authors, enabled me to generate aggregate estimates of religious demography for Ahmedabad. Moreover, given the small
32 The scholars used ‘Optical Character Recognition’ software to extract the data from the rolls.
53 number of metro cities in India, I employed the data in this dataset to generate estimates of religious demography for all the Census-listed ‘cities’ in Gujarat and Uttar Pradesh
(UP).33 This involved two steps. First, I used the Census of 2011 to identify the cities in these two states (n = 95). The largest city in the dataset is Surat, Gujarat (4,501,610 inhabitants) and the smallest is Kasganj, UP (101,277 inhabitants).34 Second, I used the
2008 Delimitation of India to identify the Vidhan Sabha (State Assembly) electoral constituencies in each of these 95 cities. I then collected voter data for each assembly constituency from the Susewind and Dhattiwala dataset and aggregated this data at the city-level. In total, together with the data that I extracted for India’s metro cities, I gathered estimates of religious demography for 101 large cities across India.
2.4.2 Outcome Variable (Hindu-Muslim Segregation)
To measure the degree of Hindu-Muslim segregation in urban India, I employed the index of dissimilarity (denoted by D), which has been hailed as the ‘workhorse’ of segregation indices for two-group comparisons (Duncan and Duncan 1955; Vithayathil and Singh 2012).35 D is a measure of evenness, that is, the degree to which members of categories are over- and underrepresented in different units (e.g., locality) relative to their overall proportion in the population (e.g., city). Specifically, ‘D’ is interpreted as the percentage of one of the two groups that would have to relocate within the city to produce an ‘even’ (unsegregated) distribution (White and Kim 2005). This index varies between 0
33 The Census of India classifies urban centers into four classes. Urban center with population of more than one lakh (1,00,000) is called a city and less than one lakh is called a town. Cities accommodating population between 1-5 million are called metropolitan cities and more than five million are mega cities. In this analysis, then, I explore patterns of Hindu-Muslim segregation on Indian cities, metropolitan cities and mega cities. 34 Census of India 2011. 35 The measure is defined by the following formula: D = ½ S − , where N1i = population of group 1 in ith unit, N2i = population of group 2 in ith unit, N1 = total population of group 1 in city, and N2 = total population of group 2 in city.
54 and 100: a dissimilarity index of 0 indicates total integration whereas a dissimilarity index of 100 indicates total segregation.
A note about the limitations of D is in order here (see Reardon and Firebaugh
2002 for a detailed discussion). First, the index of dissimilarity depends on the boundaries of the areal units, which often bear no necessary relationship to real-world interaction among population subgroups. For example, authors have highlighted that the use of artificially delineated boundaries in census data in the US constitutes a persistent source of bias in studies of segregation in American cities (O’Sullivan and Wong 2007).
Fortunately, my novel source of data for measuring religious demography enables me to work around this limitation. On the one hand, the electoral rolls are organized as geographically defined ‘Parts,’ each of which comprehends one or two housing blocks that roughly have 1000 voters.36 The resulting dataset is so fine-grained that we can reasonably assume that the measuring units confine close spheres of local interaction. On the other hand, there is an intrinsic relationship segregation at assembly constituency level and its electoral repercussions. In fact, the main goal of this chapter is to show that communal riots accentuate patterns of ethnic segregation across electoral constituencies, rather than the contested neighborhood. By using electoral units, I thus rule out the potential bias arising from artificially delineated boundaries.
The second challenge concerns what is known as the ‘checkerboard problem,’ whereby a grid landscape with clustered entirely segregated squares is not evaluated by
36 Each part is further organized into Sections and Households. Each Part has an identified Polling Station, where Electors cast their vote.
55 ‘D’ as more segregated than a grid with dispersed entirely segregated squares (White
1983; Morrill 1991). For this reason, authors often describe ‘D’ as an ‘aspatial’ measure of segregation, meaning that when the population of any two areal subunits are swapped, the index of segregation for the entire region examined remains unchanged. Two points should be said about this here. First, while there are multiple dimensions of segregation, no single measure can capture these multiple dimensions effectively to provide a comprehensive description of segregation (Massey and Denton 1988; Wong 2005).37
Given its simple interpretation, D offers a parsimonious and effective measure for examining the impact of communal riots on Hindu-Muslim segregation. Second, the question of spatiality is particularly relevant for studies that aim to examine the degree of contact or interaction between members of distinct ethnic categories. However, to the extent that my primary interest is on how riots shape the ethnic demography electoral constituencies, the fact that D remains the same when we swap the population of constituencies within the city does not challenge the validity of the analysis here.
Finally, it should be noted that ‘D’ is sensitive to the size of the underlying area units (Wong 1997). Specifically, smaller statistical enumeration units produce higher measured segregation levels. The reason for this is intuitive: smaller units tend to be more homogeneous than larger ones. Since the number of underlying units employed in my analysis varies across cities and levels of analysis, this raises the concern that variation in dissimilarity across cities is merely a reflection of the different sizes of the units.
37 According to Reardon and O'Sullivan's (2004) distinction between two primary conceptual dimensions of spatial segregation: (1) spatial exposure (or spatial isolation) and (2) spatial evenness (or spatial clustering). Spatial exposure refers to the extent that members of one group encounter members of another group (or their own group, in the case of spatial isolation) in their local spatial environments. Spatial evenness, or clustering, refers to the extent to which groups are similarly distributed in residential space.
56 To mitigate this problem, I adjusted the index of dissimilarity for each city by the mean size of electoral constituencies at each level of analysis.38 According to this measurement, the mean index of Hindu-Muslim dissimilarity at part-level is 54.61% across all the cities in the dataset. This means that roughly half the population across these cities would have to relocate to produce an unsegregated distribution between
Hindus and Muslims. This suggests that there is indeed a high level of Hindu-Muslim segregation across urban India. Across the dataset, the most segregated city in the dataset is Ahmedabad, Gujarat (D = 89%); whereas the least segregated city is Lalitpur, UP (D =
24 %). The complete dataset of dissimilarity indexes is provided in the annex to this dissertation.
2.4.3 Key Independent Variables (Killed and Incidence)
To measure the key independent variables – intensity and frequency of communal riots – I employed the Varshney-Wilkinson dataset on Hindu-Muslim violence in India,
1950-1995. The dataset provides comprehensive data on all Hindu-Muslim riots reported in the major Indian newspaper of record in the period 1950-1995, including information on location (village, town, district, state), casualties, and duration.
This dataset is particularly well-suited for testing the present argument for two reasons. First, the dataset aggregates riots at the city-level thus matching the unit of analysis employed here. Second, the dataset terminates in 1995 thus enabling us to examine how the riots taking place during the first four decades since independence have
38 The size-adjustment is computed as follows: (D * (Median City Unit/Median Dataset Unit)).
57 shaped the long-term patterns of residential segregation in urban India. This does not mean that the severe Hindu-Muslim riots that have occurred since the mid-1990s have not contributed to accentuate religious unmixing in these cities. However, my central contention is that the violence that occurred before 1995, and particularly between the late 1980s and early 1990s, shaped the long-term patterns of Hindu-Muslim segregation in urban India. Therefore, the cut-off point of 1995 fits the aims of this chapter. I collected data on two variables from the Varshney-Wilkinson dataset on Hindu-Muslim violence to measure, respectively, the degree of intensity and frequency of riots: Killed measures the number of individuals killed in each city; and Incidence measures the number of riots that occurred between 1950-1995 in each city. I expect the analysis to show that both Killed and Incidence have a positive effect on the degree of Hindu-
Muslim segregation across these cities.
2.4.4 The Logic of Control Variables
To test the impact of communal riots on the degree of Hindu-Muslim segregation,
I examine whether the relationship holds when controlling for variables measuring confounding effects. Here, I follow the approach that more careful multivariate analysis should focus on evaluating the impact of a key factor (in this case, communal riots) rather than explaining as much of the variation in the outcome variable as possible (Ray 2003;
Thachil 2011). This approach argues against including any and every variable that might have an impact on the outcome, the so-called ‘garbage-can’ or ‘kitchen-sink’ regression.
The variables included in this analysis are those that present potentially
58 confounding effects, i.e., those that are strongly associated with both the key explanatory factor (communal riots) and the dependent variable (Hindu-Muslim segregation) so as to influence the central relationship between the two. Moreover, the goal of this analysis is not to construct the model of several explanatory variables that best explains segregation.
Instead, my aim is to test whether the explanatory factor that I present as theoretically important for explaining the outcome does in fact have a substantive impact. Therefore, the control variables included in the models seek to determine whether this key relationship is spurious, rather than to control for possible effects on the outcome. More specifically, I will not include any and all variables that might affect the degree of Hindu-
Muslim segregation, but which are not theoretically expected to also influence the occurrence of communal riots.
The first important control deals with the effect of urbanization on the salience of ethnic antagonisms. An already voluminous literature argues that rural-to-urban migration provides fertile ground for the emergence of new group consciousness
(Huntington 1968; Appadurai 2002). Such theories would predict that more rapidly growing cities conduce to greater levels of Hindu-Muslim violence and higher levels of segregation by religion. This explanation is particularly relevant in the Indian context, where the urban population is expected to reach 40.76 percent of the total population by
2030 (United Nations Population Fund 2007). Fast urbanization has also been linked to the creation of ethnic enclaves: specifically, authors contend that rural-to-urban migrants tend to converge around co-ethnics as a way to benefit from mutual support networks and to keep a sense of identity (Chandra 2004). Therefore, to measure the effect of
59 urbanization on Hindu-Muslim dissimilarity, I employ the variable Urban Growth which calculates the population growth in each of the seven cities in the sample between 1951 and 2011, as reported by the Census of India.
The second control variable concerns what is known among social scientists as the ‘threat hypothesis.’ Advocates of this hypothesis contend that the presence of a sizeable ethnic minority threatens the majority’s social, economic and political position, resulting in interethnic prejudice and conflict (Blalock 1957; Fossett and Kiecolt 1989;
Huckfeldt and Kohfeld 1989). In the literature on ethnic conflict, this hypothesis has also been treated as a manifestation of the security dilemma: as the size of minorities increases so does the perception of the threat posed by those minorities to the majority community
(Posen 1993; Wilkinson 2004). Such concerns are often pronounced by Hindu right-wing politicians to unite ‘Hindus’ against an ethnic minority. For example, the current Prime
Minister of India, Narendra Modi, used the expression “hum paanch, hamare pachees”
(‘we are five and we will have 25 offspring’) following the 2002 Gujarat riots to rouse fears about the demographic growth of the Muslim community (Outlook 2002). Cities with larger Muslim populations may also have higher levels of Hindu-Muslim segregation for historical reasons or simply as an expression of individual preferences for homophily (Muslims prefer to live with other Muslims and therefore segregation by religion increases with their demographic weight). To measure the impact of Muslim population on segregation patterns, I employ a variable Muslim Population, which is defined as the percentage of the population identified as Muslim in each city by the 2011
Census of India.
60 Finally, it is also plausible that patterns of Hindu-Muslim violence and segregation map onto the landscape of urban poverty. Indeed, a considerable literature already suggests that poverty increases the likelihood of participation in a riot. The motivations for doing so can vary from the need to protect one’s family and property
(Scacco forthcoming), the lure of material benefits or an expressive logic, in which poverty produces such high levels of discontentment that people resort to violence out of frustration (Berkowitz 1962; Gurr 1970).
At the same time, there is increasing evidence that Muslims are disproportionately represented among the poorer sections of Indian society. Notably, the Sachar Committee
Report revealed that Muslim had the lowest average monthly per capita expenditure
(MPCE) among all communities in India (2006). This raises the concern that evidence of segregation by religion is, in fact, the result of the socio-economic alienation of the
Muslim community in India. Therefore, to measure the size of the poor in each city, I employ the variable Poor, which is defined as the total number Slum Households reported per city in the Census of India 2011.
61 Expected Impact
Potential Confounding Expected Impact on Hindu-Muslim Segregation Expected Impact on Hindu-Muslim Violence Variable
Fast urbanization promotes the creation of ethnic Rural-to-urban migrants are more predisposed to Urban Growth enclaves (+) violence (+)
Muslim Muslims live in clustered neighborhoods where they Hindus feel threatened in cities with high Muslim Population are in larger numbers (+) population (+)
Segregation by religion is merely a side-effect of Poverty The poor are more prone to rioting (+) socio-economic segregation (+)
Table 2.1: Possible Confounding Factors
2.4.5 Data Analysis and Results
According to the argument presented here, Hindu-Muslim riots accentuate the
degree of Hindu-Muslim segregation in urban India. It stands to reason that cities
registering higher levels of riots intensity and frequency will also have a higher degree of
Hindu-Muslim segregation. To test this hypothesis, I estimated simple bivariate models
using ordinary least squared analysis of the form:
D = b0 + b1(Key Independent Variable) (Equation 2.1)
Where D measures the index of Hindu-Muslim dissimilarity for each city and the
key independent variables are alternatively Killed and Incidence. I ran this regression by
measuring the value of D at state assembly level for all the large cities in the dataset with
more than one state assembly constituency (N = 24) and then at part level for all cities in
62 the dataset except Mumbai, since I lack part level data for it (N = 100). This break-up provides a work around the limitations of the data and D described beforehand as well as to test hypothesis among differently-sized groups of cities. Table 2.2 presents the results of this analysis.
Large Cities All Cities
Model 2.1 Model 2.2 Model 2.3 Model 2.4
Killed .018* .029**
(.007) (.009)
Incidence .420** .685***
(.125) (.132)
Constant 15.941 12.802 53.451 51.757
R2 .24 .34 .10 .22
N 24 24 100 100
Note: *p<0.05, **p<0.01, ***p<0.001. Standard errors in parentheses. Table 2.2: Bivariate Regression Results
As expected, the results suggest that there is a significant and positive relationship between the intensity and frequency of Hindu-Muslim riots and the degree of Hindu-
Muslim segregation in urban India. This effect is constant across the two city samples and across the two main independent variables: riots intensity and frequency. At the same time, the analysis suggests that the frequency of riots has a stronger and more significant effect on the degree of Hindu-Muslim segregation than the intensity of riots. To better
63 illustrate this relationship, I plotted the size-adjusted index of dissimilarity (Figure 2.1).
This shows that with the notable exception of Vadodara, the largest cities in India conform quite remarkably to the hypothesized pattern. In fact, if Vadodara is removed from the sample, the Pearson’s coefficient between riot incidence and Hindu-Muslim segregation jumps to over .44 and the relationship among the large cities in the dataset becomes statistically significant at the α .001.
Kanpur Hyderabad
40 Mumbai Ahmedabad
Kolkata Lucknow Meerut Bangalore 30
Allahabad Surat Aligarh Agra Delhi 20
sizeadjustedd Chennai Moradabad Vadodara
Saharanpur Ghaziabad Jamnagar Bareilly Bhavnagar 0 0 20 40 60 80 incidence
Figure 2.1: Effect of Hindu-Muslim riots on Hindu-Muslim segregation
The effect of Hindu-Muslim riots on Hindu-Muslim segregation becomes more significant as the size of the sample also increases. The weaker effect among the large cities in the datatset level may be due to a strong relationship between city size and riots so that larger cities also experienced more communal violence.
To test for this possibility, I ran a new correlation between city size and riots and
64 found there is a strong, positive and statistically significant relationship (at the α .001 level) between city size and the number of Hindu-Muslim riots. Thus, for example, while
Bangalore and Chennai are communally-peaceful cities in comparison to other large
Indian cities, they have experienced a greater number of both Killed and Incidence than many other cities in the sample. This, combined with their low levels of Hindu-Muslim segregation, may explain why the correlation is less significant among the large cities in the dataset. Nevertheless, the analysis shows a statistical significant relationship between
Hindu-Muslim riots and Hindu-Muslim segregation even among the large cities in the dataset. In this way, we may conclude that the analysis supports the hypothesis advanced here linking communal violence to Hindu-Muslim segregation.
2.4.6 Confounding Variables
It is plausible that any of the three variables specified earlier, Growth, Muslim
Population and Poverty is linked to both the intensity and frequency of riots in ways that renders the relationship of interest to be a product of spurious correlation. To examine the impact of these confounding variables, I estimated trivariate models for each variable using again ordinary least squared analysis:
D = b0 + b1(Key Independent Variable) + b2Control +e (Equation 2.2)
Where D measures the index of Hindu-Muslim dissimilarity for each city in the sample, the key independent variable is alternatively Killed and Incidence, and Control refers to one of the three confounders. Since the number of municipal corporations in the
65 sample is small, I ran these regressions across all the cities only. The results of the
models testing different specifications of Equation 2.2 are presented in Table 2.3.
Model 2.5 Model 2.6 Model 2.7 Model 2.8 Model 2.9 Model 2.10
Killed .029*** .024** .025** (.008) (.009) (.009)
Incidence .673*** .619*** .649*** (.128) (.134) (.149)
Urban -3.802* -3.415* Growth (1.620) (1.516)
Muslim .000 .000 Population (.000) (.000)
Poverty .000 -1.960 (.000) (.000)
Constant 56.736 54.722 51.949 50.518 53.436 52.245
R2 .16 .26 .14 .24 .15 .25
N 98 98 98 98 78 78
Note: *p<0.05, **p<0.01, ***p<0.001. Standard errors in parentheses. Table 2.3 Tri-variate Regression Analysis
The results of these regressions indicate strong support for the hypothesis
advanced in this chapter: both the frequency and intensity of riots have a strong effect on
the degree of Hindu-Muslim segregation. The relationship remains statistically significant
in each of the six models and does not diminish with the inclusion of any of the potential
confounding factor. As before, the analysis shows that Incidence has a larger and more
66 significant statistical effect on Hindu-Muslim dissimilarity than Killed. This suggests that, while both the frequency and intensity of riots shape segregation, the recurrence of
Hindu-Muslim violence has a stronger impact on patterns of segregation by religion in urban India. Finally, the impact of both Incidence and Killed is remarkably stable across the different model configurations, suggesting that it is not the product of a particular specification.
The substantive impact, statistical significance, and stability of the variables
Incidence and Killed across the analysis provides convincing evidence that the occurrence of Hindu-Muslim riots is associated with long-term patterns of Hindu-Muslim segregation in urban India. However, this cross-sectional does not get at the critical issues of temporality and causality. Do patterns of Hindu-Muslim segregation track patterns of communal violence in urban India? Can riots be shown to increase levels of Hindu-
Muslim segregation? To answer these questions, in the following section, I use time- series data on religious demography in India’s seven largest cities to examine the impact of communal riots on Hindu-Muslim segregation.
2.5 Time Series Analysis
If acquiring contemporary data on local religious demography in India presents major challenges, then the chances of encountering data to measure segregation by religion across time are vanishingly small. The Census of India stopped releasing ward level data on religion in 1961 (and even then, the data existed for only the largest cities) and other available datasets are constrained to specific localities within cities. The
67 Election Commission of India does keep an archive of old electoral rolls in Delhi but, according to my own investigation in Delhi between September-December 2015, the rolls on these archives do not go as far back as the early 2000s. Each State’s Election
Commission and District Election Officer may keep copies of these older rolls but, unfortunately, I was not granted access to the archives to confirm the existence of such rolls.
To remedy this shortcoming, I used a proxy variable for measuring local religious demography across time – the number of Muslim candidates in a State Legislative
Assembly constituency. Given that my main interest is on Hindu-Muslim segregation at the electoral constituency level, there are good reasons to believe that this is a good proxy for local religious demography. Whereas Hindu voters generally split across different parties and candidates, previous scholarship on Indian electoral politics has repeatedly shown that Muslims typically vote for Muslims candidates (Rudolph and Rudolph 1987;
Brass 2003; Dasgupta 2009; Heath, Verniers and Kumar 2015). In theory, then, the number of voter gained by Muslim candidates in a specific electoral constituency can offer us valuable insight into the size of the Muslim population in that constituency.
Yet, there are two reasons why the number of votes gained by Muslim candidates is not a very precise measure of local religious demography. First, existing work already shows that there is a strong strategic element to Muslim voting calculus: Muslims are indeed more likely to vote for Muslim candidates, but only when those candidates have a realistic chance of winning (Heath, Verniers and Kumar 2015). In this way, the number
68 of votes gained by Muslim candidates may underrepresent the size of the Muslim population in an electoral constituency.
Second, there is a weaker relationship between candidates’ religious identity and voting preferences in electoral contexts that are not sharply polarized along communal lines, especially where regional parties are important electoral players. Thus, for example, in Chennai, both Muslims and non-Muslim vote for the two major regional parties – the All India Anna Dravida Munetra Kazhagam (AIADMK) and the Dravida
Munetra Kazhagam (DMK). As a corollary of this, Muslims often vote for non-Muslim candidates in constituencies where there is a low proportion of Muslims, whereas non-
Muslim may vote for Muslim candidates in constituencies where Muslims form a significant part of the electorate. In fact, in my research I found that votes for Muslim candidates as a percentage of total votes in both Chennai and Kolkata – the two cities in the sample that are not polarized along communal lines – is far greater than the proportion of Muslims to the total population in these two cities recorded by the Census of India. Therefore, the number of votes gathered by Muslim candidates does not constitute a valid measure of local religious demography in such contexts.
At the same time, existing research demonstrates that as a result of Muslim preference for Muslim candidates, the number of Muslim candidates standing for election tends to increase with the size of the Muslims population in an electoral constituency
(Sharma and Jangam 1962; Heath, Verniers and Kumar 2015; Thakur 2015). This research shows that more Muslim candidates stand for election in constituencies where
69 Muslims form a majority. Crucially, parties seeking to mobilize non-religious categories
– such as the AIADMK and the DMK in Chennai – also field Muslim candidates in constituencies where Muslims form a significant proportion of the population. In this way, then, the number of Muslims candidates offers us a more accurate measure of local religious demography than the vote share of Muslim candidates in a given electoral constituency.
To test this intuition, I examined the correlation between the number of Muslim candidates in the latest Assembly elections and the contemporary estimates of religious demography presented above. A strong positive correlation between these two variables would be interpreted as a sign that the number of Muslim candidates in an electoral constituency is a good proxy for local religious demography. Indeed, the test revealed a strong and positive relationship between these variables at the lowest level of statistical significance (.001). This level of correlation convinced me to use the number of Muslim candidates in an electoral constituency in this time-series analysis for the evolution of patterns of Hindu-Muslim segregation in India’s seven metro cities.
Finally, it is also worth pointing out two additional advantages of using this proxy. The first is that the number of Muslim candidates running in an election enables us to examine how the argument fares against possible alternative explanations for existing patterns of communal segregation, namely historical patterns of settlement and gerrymandering. In 2008, India redrew the boundaries of state and national constituencies after a gap of three decades. A non-partisan commission conducted delimitation, but
70 several incumbent politicians were part of an advisory committee for the commission.
This has led to accusations of incumbents’ interference in the resulting delimitation: “The structure of the 26 seats in the suburbs of Mumbai as per the new delimitation exercise is such that most new constituencies would have a sizeable Hindutva vote bank” (Lalvani
2009, p. 18).39 Since my proxy measures local religious demography across time, it allows me to test whether current patterns of Hindu-Muslim segregation are the results of changes to constituency boundaries as well as historical patterns of segregation. A final benefit of using the number of Muslim candidates as a proxy in this analysis is the possibility of using scalable, fine-grained data that is publicly-available on the ECI’s website.
2.5.1 Sources of Data
To conduct this analysis, I collected the official Statistical Reports of General
Elections to State Legislative Assemblies (Vidhan Sabha) for the seven states in which
India’s seven metro cities are located: Maharashtra (Mumbai), Delhi (Delhi), Andhra
Pradesh (Hyderabad), Karnataka (Bangalore), Tamil Nadu (Chennai), West Bengal
(Kolkata) and Gujarat (Ahmedabad).40 To generate a time-series dataset, I collected the
Statistical Reports for the last seven State Assembly elections in these seven cities. The timeframe for these elections for each city was as follows: Mumbai (1985-2015), Delhi
(1983-2015), Hyderabad (1985-2014), Bangalore (1983-2013), Chennai (1984-2016),
39 However, there is little evidence to support this claim. In fact, a recent study matching old and new constituencies found that the redistricting process was politically neutral for the most part: "There is also no wider pattern of influence for specific parties" (Iyer and Reddy 2013, p. 18). 40 In 2014, Hyderabad became the joint capital of the newly-formed Telangana state and Andhra Pradesh. 2014 was also the latest Assembly Election in Andhra Pradesh; therefore, the electoral results for Hyderabad were still included in the Andhra Pradesh 2014 Statistical Report.
71 Kolkata (1987-2016) and Ahmedabad (1985-2012). This timeframe thus enables me to show the change in patterns of Hindu-Muslim segregation from the period preceding the
Ayodhya agitation until the latest Assembly Elections.
Finally, to measure the frequency and intensity of communal riots in these seven cities, I employed the Varshney-Wilkinson dataset of Hindu-Muslim violence in India,
1950-1995. Table 2.4 presents the figures for the incidence and the number of individuals killed in Hindu-Muslim riots in India’s seven largest cities. The dataset finishes in 1995 but if we account for the 2002 Gujarat pogrom – the only major incident of Hindu-
Muslim violence in the seven cities since the mid-1990s – then Ahmedabad emerges as the most riot-prone city in India in both the frequency and intensity of riots.
City Incidence Killed
Mumbai 37 1137
Ahmedabad 71 1119 (+700)41
Hyderabad 34 312
Delhi 14 72
Kolkata 19 58
Chennai 5 12
Bangalore 9 56
Table 2.4: Frequency and Intensity of Hindu-Muslim riots in India’s seven metro cities
41 The 700 deaths included within parentheses refer to the estimated number of fatalities in Ahmedabad during the 2002 Gujarat pogrom, according to the Human Rights Watch (2003).
72 2.5.2 Measurement Details
In line with the previous examination, I used the names of candidates on the
Statistical Reports to identify them according to two religious categories: Muslim and non-Muslim. I coded the names of candidates manually, using online sources to adjudicate cases where the religious identity could not be readily gleaned from the names of a candidate.42
To calculate segregation by religion for each of the seven cities across time, I used the index of isolation (denoted by B), which reflects the extent to which a minority person shares a unit area with another minority person (Massey and Denton 1988). More precisely, the index of isolation here measures the likelihood that a Muslim candidate is running in the same electoral constituency as another Muslim candidate in a given city.
When there are only two groups (as in this analysis), the index of isolation sums up to
100 per cent, so higher values of isolation indicate higher segregation. The index of isolation is computed as the minority-weighted average of the minority proportion in each area. 43
As readers may notice, this is a different measure of segregation from the one employed in the previous cross-sectional analysis (i.e., the index of dissimilarity). The reason for this change stems from the different nature of the two datasets employed in this chapter: whereas the previous dataset estimated local religious demography from the
42 In some cases, I found news reports that accounted for the number of Muslim candidates running in an election or referring specifically to the religious identity of a candidate. In other cases, I used the website www.indiachildnames.com (the same used by the name-matching algorithm) to adjudicate on whether the candidate is Muslim or non-Muslim. 43 The measure is defined by the following formula: B = S − , where xi is the minority population of area i, X is the sum of all xi (the total minority population) and ti is the total population of area i (Massey and Denton 1988).
73 names of all electors, this dataset measures local religious demography from the names of candidates only. As a result, the cross-sectional dataset was more fine-grained than the present time-series dataset, which includes several electoral constituencies without a single Muslim candidate. This constitutes a problem for the index of dissimilarity, given that it measures whether majority and minority populations are evenly distributed and thus it is particularly sensitive to the existence of null observations.
In turn, the index of isolation measures how geography isolated are Muslim candidates in India’s seven metro cities. It seeks to determine whether Muslim candidates converge on the same electoral constituencies, rather than if they are evenly distributed across all electoral constituencies in a city. In this way, the index of isolation provides a more accurate measure of Hindu-Muslim segregation in this time-series analysis.
2.5.3 Results
First, I calculated the change in the index of segregation between the first and the last State Assembly election in each of the seven cities (Chart 2.2). I find that the results of this analysis largely conform to the expectations of the theory advanced in this chapter:
Hindu-Muslim segregation has increased in India’s most riot-prone cities (Ahmedabad and Mumbai) and decreased in relatively peaceful cities such as Chennai, Kolkata and
Delhi. The clear outlier in this analysis is Hyderabad, where Hindu-Muslim segregation has decreased sharply despite the occurrence of relatively high numbers of riots and riot- deaths in recent decades (312 killed and 34 riots according to the Varshney-Wilkinson dataset of Hindu-Muslim violence in India, 1950-1995). Arguably, this is a result of the
74 fast-growing and sizeable Muslim population in the city. According to the Census of
India, the Muslim population in Hyderabad has increased from about 33 per cent in 2001 to 43.35 per cent in 2011. As the Muslim population has increased in this city with an already substantial Muslim minority, it is easy to imagine how Muslim candidates became less isolated in relation to the total candidates standing for elections in
Hyderabad.
25
20
15
10
5
0
-5
-10
-15
Mumbai Bangalore Chennai Ahmedabad Kolkata Hyderabad Delhi
Figure 2.2: Index of Isolation Change Between Mid-1980 and 2010s
I then calculated the index of isolation for each of the seven elections in these cities between the mid-1980s and the early 2010s. This analysis enabled me to test both for historical levels of segregation as well as the effect of constituency re-delimitation in
2008. Chart 2.3 reports the linear results of this analysis (a complete table of isolation indexes for each election is available in the annex).
75 50
45
40
35
30
25
20
15
10 1985 1990 1995 1999 2004 2009 2012
Linear (Mumbai) Linear (Bangalore) Linear (Chennai) Linear (Ahmedabad) Linear (Kolkata) Linear (Hyderabad) Linear (Delhi)
Figure 2.3: Index of Isolation, Linear Results 1980s-2010s
This analysis strongly corroborates the link between the intensification of communal violence in the late 1980s and early 1990s and the accentuation of Hindu-
Muslim segregation in India’s largest cities. First, the results remarkably conform to the conclusions of the previous cross-sectional examination: segregation by religion is lower in relatively peaceful cities (i.e., Chennai and Bangalore), and highest is the two riot- prone cities in the sample (i.e., Ahmedabad and Mumbai). Hyderabad comes in third place in terms of Hindu-Muslim segregation, followed by Delhi and Kolkata. This fits with both the frequency and intensity of riots in India’s metro cities (Table 2.4).
Second, I find that the trajectory of Hindu-Muslim segregation in this analysis provides strong support for the hypothesis advanced here that recurrent and severe communal riots produce religious unmixing: both Ahmedabad and Mumbai have an
76 upward slope in Hindu-Muslim segregation during this period of time, as opposed to the other cities in the sample. As before, the most significant exception to this pattern is
Hyderabad, where Hindu-Muslim segregation has decreased across this period.
Finally, this analysis suggests that the effects of communal violence on Hindu-
Muslim segregation is independent of both historical patterns of segregation and the re- drawing on electoral constituencies in 2008. First, one may point out that patterns of
Hindu-Muslim segregation across these seven cities have varied significantly over this period of time: in the early 1980s, neither Ahmedabad nor Mumbai were among the most segregated cities in the sample. Therefore, contemporary high levels of segregation by religion in these two cities cannot be attributed to previous patterns of Hindu-Muslim segregation. Second, the delimitation of constituencies in 2008 does not seem to have a significant impact on Hindu-Muslim segregation. In all the cities, the upward or downward trend identified in the period between the first election and delimitation continued after 2008. Ultimately, this suggests that the effect of communal riots on contemporary levels of Hindu-Muslim segregation in India’s largest cities is independent of both historical patterns of segregation and the re-drawing on electoral constituencies in
2008.
2.6 Conclusion
This chapter explored the impact of Hindu-Muslim riots on patterns of Hindu-
Muslim segregation. As shown in the sections above, there is a positive and statistically significant relationship between the frequency and intensity of communal violence and
77 the degree of Hindu-Muslim segregation across India’s largest cities. Analysis of time series data for India’s seven metro cities, further corroborated the finding that riots accentuated the unmixing of religious community in the city. Furthermore, it also demonstrates that the effect of riots on Hindu-Muslim segregation is independent of historical patterns of segregation and the re-drawing of electoral constituencies in 2008.
The substantive impact, statistical significance, and stability of the relationship across the analyses provides convincing evidence that the occurrence of Hindu-Muslim riots is associated with long-term patterns of Hindu-Muslim segregation in urban India.
However, the evidence presented above does not illuminate the causal mechanisms linking Hindu-Muslim riots and Hindu-Muslim segregation. It is important to understand why it is in the interest of politicians to promote ethnic unmixing as well as to examine why and when ethnic unmixing takes place following ethnic riots. In other words: (1) what are the conditions under which politicians find it useful to promote riots to shape the long-term ethnic demography of electoral constituencies; and (2) how dos riots translate into greater segregation among ethnic categories?
The following chapter tackles these questions by looking at variation in Hindu-
Muslim segregation in Mumbai, India’s largest city. The city was the stage for one of the worst episodes of Hindu-Muslim violence since independence, the 1992-93 riots, in which an estimated 900 people died (Shrikrishna Commission 1998). The chapter employs extensive archival research along with interviews with riot victims, activists, journalists and politicians to illustrate two main points: first, politicians find it useful to
78 promote favorable ethnic demographies when they contemplate electoral marginalization; second, intense and frequent ethnic riots trigger two types of migratory flows: (1) an initial movement of people forced to flee their homes as a direct consequence of the violence; and (2) an unmixing cascade in search for ‘safety in numbers’ that trickles over many years after the violence. In this way, I argue that that severe and protracted ethnic riots are an effective, albeit brutal, means for producing ethnic unmixing that becomes a permanent feature of the electoral landscape.
79 Chapter Three
Divide and Rule: The Politics of Unmixing in Mumbai
The political-cultural strategies of the Shiv Sena relied heavily on spatial tactics, which included violently rewriting urban space as sacred, national and Hindu space. -- Qudsiya Contractor, Unwanted in My City, 2012
I basically cannot forget one thing, that the Partition of this country was done on communal lines. Muslims asked for their own nation. Then leave us alone. -- Interview with Bal Thackeray, India Today, 1995
3.1 Introduction
Why do political parties turn to ethnic unmixing as an electoral strategy? How do ethnic riots produce long-term ethnic unmixing? To address these questions jointly, this chapter examines how the 1992-93 Mumbai riots enabled the Shiv Sena to enduringly tilt the city’s social geography to its electoral advantage. Specifically, I argue that the parlous state of the Shiv Sena in the early 1990s combined with its exhaustion of conventional strategies made ethnic unmixing a particularly attractive electoral strategy. Furthermore, I show that the 1992-93 riots in Mumbai triggered two types of migratory flows: (1) an initial movement of people forced to flee their homes as a direct consequence of the violence; and (2) an unmixing cascade in search of ‘safety in numbers’ that trickles over many years after the violence.
The 1992-93 Mumbai riots constitute a particularly compelling case in which to study the relationship between riots and unmixing for three main reasons. First, as shown
80 by the previous analysis, Mumbai has high values in terms of the frequency and intensity of riots as well as in terms of Hindu-Muslim segregation. The existence of high values on both the dependent and the independent variables makes Mumbai a ‘typical case study’ in this study – regarded by the qualitative methods literature as the most useful for unpacking causal mechanisms (Gerring 2007; Seawright and Gerring 2008; Beach and
Pederson 2016).44 Moreover, the Hindu-Muslim riots that rocked Mumbai between
December 1992 and January 1993 (followed by retaliatory bomb blasts in March 1993) were of unprecedented magnitude and ferocity.45 According to the official Commission of
Inquiry, headed by Justice B.N. Srikrishna, the final tally of casualties was 900 dead and
2,036 injured.46 Hence, long-time residents and scholars alike recognize the 1992-93 riots as a critical moment in Mumbai’s recent history (see, for example, Blom Hansen 2001,
Kaur 2005, Gupta 2011, Fernandes 2013).
Second, the 1992-93 riots had a striking and lasting impact on Hindu-Muslim segregation in Mumbai. Historically, Mumbai’s has always had clusters of residents from the same caste, religion, region, and language (Hansen 2001). This was a manifestation of the social organization of labor as well as the community-based networks that brought migrants into the city. Nevertheless, the borders delimiting these pockets were never
44 The logic behind this is simple: almost by definition, typical cases provide the best chance for showing that the mechanism identified in the studied case(s) is also present in the rest of the population of causally similar cases. It is important to note that ‘typical’ does not mean cases with average scores on the relevant dimension. According to Gerring (2007), if there is only one independent variable and there is a strong positive association between the dependent and independent variables, then a case with similar (high, low, or middling) values on both variables may be more typical than cases whose values lies closer to the mean. 45 The 1992-93 riots unfolded in two stages: during the first stage, between 6-12 December 1992, there was a rapid escalation of hostilities after Muslim protests (initially peaceful then violent) erupted throughout Mumbai; during the second stage, between 6-20 January 1993, there was a systematic attack by members of the Shiv Sena and other Hindutva organizations against Muslim men, women and children. The riots were followed by the retaliatory 12 March 1993 Mumbai Bombings, perpetrated by criminal groups with alleged help of gang lord Dawood Ibrahim and his D-Company syndicate, in which more than 300 people were killed. 46 As is often the case, the number of casualties may be significantly higher than those provided officially. The Human Rights Watch, for example, estimates that over 1,000 people died in the 1992-93 Riots in Mumbai (HRW 1996).
81 completely rigid and high population density always meant that the city was packed too tightly for these boundaries to endure (Fernandes 2013). Even buildings that restricted ownership to members of specific religious groups were known to have renters from other communities. Thus, in the early 1990s, there was a high degree of mixed housing along religious lines in Mumbai (Blom Hansen 2001; Khan 2011).
The 1992-93 riots radically changed this (Kothari & Contractor 1996; Eckert
1999; Hansen 2001; Robinson 2005; Gupta 2011; Khan 2011; Contractor 2012).47
Following the riots, Hindus started to relocate to Hindu-majority localities while Muslims began to move in large numbers to Muslim-dominated areas of Mumbai. Similarly, new building projects and colonies in Mumbai increasingly started to market themselves as the exclusive enclaves of a specific religious community. The riots also created rigid physical boundaries between religious communities. Today, Muslim-majority localities, such as Jogeshwari, are routinely called ‘mini Pakistans’ by Hindus elsewhere; and walls have been built in some localities to separate areas dominated by Hindus and Muslims.
Thus, according to several individuals I interviewed in Mumbai, Hindu-Muslim segregation is not only ongoing but also becoming acuter more than two decades after the riots.
Finally, the 1992-93 riots also marked a clear turning point for the Hindu right in
Mumbai. In the early 1990s, the Hindu right in Mumbai was in a state of turmoil: after a
47 While there is consensus among scholars and long-term residents of the city that the 1992-93 riots greatly accentuated the spatial segregation between Hindus and Muslims in the city, the consolidation of religious communities in Mumbai after the riots has not been recorded by any entity.
82 series of electoral setbacks, its internal cohesion was damaged and its electoral viability at risk. Yet, following the riots, the Hindu right emerged as the most powerful political force in the city. There is thus little doubt that the Shiv Sena’s involvement in the riots served its electoral interest. However, the Hindu right’s revival was not only dramatic but also long-lived. Since the riots, the Hindu right has maintained the control of
Brihanmumbai Municipal Corporation (BMC), the country’s richest municipal corporation, and remained a major player in both state and national elections in Mumbai.
While its success has attracted considerable attention, no systematic empirical study has so far examined how the 1992-93 riots contributed to the enduring rise of the Hindu right in the city. As we shall see, the argument that the Shiv Sena employed ethnic unmixing as an electoral strategy offers a more persuasive account of the 1992-93 Mumbai riots than existing alternative explanations for Hindu-Muslim violence in India.
This chapter proceeds as follows. The following section briefly outlines the Shiv
Sena’s arrival at an electoral saturation point in the early 1990s. I then explain why the party’s exhaustion of conventional electoral strategies prompted it to look for a viable alternative. The next section uses qualitative fieldwork, including extensive interviews with riot survivors, journalists, activists and politicians in Mumbai, to outline the mechanisms through which the 1992-93 riots produced an accentuation of Hindu-Muslim segregation in Mumbai. The fifth section examines how this argument fits with conventional explanations for communal violence in India. Finally, I conclude with the observation that the results of this examination prompt us to explore the relationship
83 between ethnic unmixing and ethnic party support, which I take up in the following chapters.
3.2 Setting the Context: the Shiv Sena at crossroads
Launched in 1966 as a radical sons-of-soil movement championing the interests of Marathi-speaking job seekers, the Shiv Sena (lit. ‘Shiv’s Army’) established itself rapidly on Mumbai’s political scene (Katzenstein 1979; Gupta 1982). In 1968, a mere year after the movement turned into a political party, the Shiv Sena became the second largest party in Mumbai’s civic body, the BMC (Table 3.1). In October 1970, the Shiv
Sena won a by-election for the Parel seat in the Maharashtra State Assembly (MLA), its first ever in the state legislature.48 During the 1970s, although never the most voted party in the city’s local civic elections, the Shiv Sena elected several of its Mayoral candidates to the BMC. Most of its councilor seats in the 1968 and 1973 elections were in the working-class constituencies in central Mumbai (Katzenstein 1979).
48 The seat had been vacated by the murder of Krishna Desai - a prominent member of the Communist Party of India (CPI) in Mumbai - allegedly by Shiv Sena men (Appadurai 2000; Blom Hansen 2001).
84 Party 1948 1952 1957 1961 1968 1973 1978 1985 1992 1997 2002 2007 2012
INC49 47 56 54 59 65 49 25 46 83 48 61 76 65
Shiv Sena50 - - - - 42 39 21 74 70 103 97 89 103
Janata Party ------83 10 - - - -
BJP51 - - 2 5 6 15 - 13 14 26 35 28 31
Others 59 68 75 67 27 37 11 27 54 21 32 34 28
Total 106 124 131 131 140 140 140 170 221 221 227 227 227
Table 3.1: Number of seats won by major parties in BMC elections, 1948-201252
However, by the end of the 1970s, the Shiv Sena was losing its electoral appeal in
Mumbai. The main reason for this was the party’s support for Indira Gandhi’s state of
emergency from 1975 to 1977, which caused several activists to leave the party and
damaged its support base (Blom Hansen 2001). In the 1978 Assembly Elections, the
party was marginalized by potential alliance partners and failed to win even a single seat
in its erstwhile strongholds in Mumbai. Desperate to revive its fortunes, in 1979 the Shiv
Sena formed an electoral alliance with the Muslim League. Yet, the alliance collapsed
after less than a year, when both parties failed to win any seats in the 1980 Assembly
Elections.
The early 1980s saw the Shiv Sena reinvent itself as a Hindu right-wing party. As
Palshikar (2004) reminds us, Hindutva was always an incipient element of the Shiv
Sena’s ideological platform. Yet, from the 1980s onwards, the Sena started to project
49 Includes Congress-I 50 Includes MNS (after 2007) 51 Includes the Hindu Mahasabha (1957 and 1961) and the Jana Sangh (1968 and 1973) 52 This graph does shows only the total number of seats won by parties in each election. It does not show the alliances made between parties and independent candidates after the elections to form a majority in the BMMC.
85 itself as a Hindu nationalist force, only turning to Marathi pride when the appeal of the former was thought to be inadequate (Palshikar 2004). Two main factors determined this reconfiguration. First, in the early 1980s, numerous militant Hindu organizations took shape in Maharashtra and there was a first wave of violence between Hindus and
Muslims in India (Blom Hansen 2001). Due to its popularity among the Shiv Sena’s middle- and lower-middle-class support base, Hindutva could provide the party a viable vehicle for power. Second, the Shiv Sena realized that its pro-Marathi ideology failed to resonate with voters outside the big cities in Maharashtra, who had had little contact with state outsiders (Palshikar 2004). Thus, to win power at the state level, the Shiv Sena needed an ideological platform that appealed to a broader audience. Hindutva also fulfilled this requisite.
The Shiv Sena’s conversion into a Hindu right-wing party initially bore electoral fruits. In 1985, the Sena won 75 seats in the BMC, enabling it to rule Mumbai’s civic body for the first time on its own. The Shiv Sena’s control over the vast resources of the
BMC allowed it to consolidate its political structures and to strengthen its trade union wing, the Bharatiya Kamgar Sena (BKS), which became one of the dominant trade unions in Maharashtra. Circulation of the Shiv Sena’s weekly, Marmik (lit. ‘Sharp’), was greatly expanded and in 1987 the party launched a newspaper, Saamna (lit.
‘Confrontation’). In 1989, realizing the Shiv Sena’s popularity and dynamism, the BJP formed an alliance with it for Assembly Elections as well as the national Parliamentary
Elections.
86 Yet, the upswing in the Shiv Sena’s fortunes was short-lived. In the 1989
Parliamentary Elections, the Shiv Sen-BJP alliance won only ten seats. In the 1990
Maharashtra State Assembly elections, the Shiv Sena elected only 52 out of the 183 candidates it fielded (the BJP elected 42/104) and the Indian National Congress (INC) maintained its dominance with 38.17 percent of the popular vote (electing 141 candidates). The disappointing results created tensions within the alliance that erupted into violence between the student bodies of the two parties, the RSS-affiliated Akhil
Bharatiya Vidyarthi Parishad (ABVP) and the Shiv Sena’s Bharatiya Vidyarthi Sena
(Blom Hansen 2001). Finally, the alliance collapsed in early 1992.
In the 1991 national Parliamentary Elections, the Shiv Sena failed to go beyond the four seats it had won in 1989. To make matters worse, in December 1991, thirteen
Shiv Sena MLAs, including Chhagan Bhujbal, the former Mayor of Mumbai, defected to join the ruling Indian National Congress (INC). This defection dealt a major blow to Shiv
Sena’s cohesion and political strength (Blom Hansen 2001). In the following months, many local Shiv Sena men in Mumbai defected to the INC and former corporators who were not given a ticket ran as independents. Finally, in February 1992, the party suffered a major defeat in local elections, losing control of its jewel of crown, the BMC.
3.3 The failure of conventional electoral strategies
The difficulties of the Shiv Sena in the early 1990s were compounded by the fact that the party had already exhausted all conventional strategies for appealing to voters. To illustrate this, I briefly outline here the Shiv Sena’s use of four electoral strategies in
87 preceding years: programmatic linkages, pre-electoral violence, patronage and social welfare provision. This discussion aims to frame the Shiv Sena’s need for an alternative electoral strategy to revive its electoral fortunes.
3.3.1 Programmatic ties
From its inception, the Shiv Sena’s ideological and policy platforms has served two main constituencies: (1) the Marathi-speaking Hindus (‘Marathi Manus’); and (2)
Mumbai’s middle-classes. There is an obvious tension in this dual agenda in that the interests of these two groups are not coterminous.53 Initially, the Shiv Sena managed to conceal this tension by focusing on issues that resonated with both constituencies such as the party’s demand for preferential employment for Marathis (Katzenstein 1979; Gupta
1982). Moreover, the Sena’s modus operandi combined an ostensibly plebeian and popular idiom with the values and desires of respectability of Mumbai’s rising middle classes (Blom Hansen 2001). Fittingly, the party’s slogan during this period was ‘Sundar
Mumbai, Maratha Mumbai’ (lit. ‘Beautiful Mumbai, Mumbai for the Maharashtrians’). In this way, the Shiv Sena could initially draw electoral support from a cross-section of
Marathi-speakers from almost every class and from most income groups, except the very low and the very high (Gupta 1982).
However, it soon became clear that this tension was a source of trouble for the party. In the early 1970s, the Shiv Sena adopted a violent anti-immigrant and anti-slum stance, claiming that the immigrants were responsible for the disorder in the city
53 This analysis echoes Thachil’s (2011) description of the BJP’s difficulty in wooing low-income voters without alienating their cote voters.
88 (Mukhija 2002). While its hostility towards immigrants and slum dwellers helped to consolidate the Shiv Sena’s position with upper-caste and middle class Hindus, it also antagonized a significant section of Mumbai’s poor residents.
These tensions became clear once the party took control of the BMC. In 1985, the corporation announced a massive slum demolition program, entitled ‘Operation Slum- wreck.’ However, contrary to its assumptions, the party soon discovered slum dwellers were not just southern Indians and non-Hindus (Mukhija 2002). Many of them were low income Hindu Maharashtrians. The operation thus threatened to antagonize an important section of the Shiv Sena’s electoral support, eventually forcing the corporation to cancel it. Similarly, while the Shiv Sena claimed to have the interests of the Marathi people at heart, it often took the side of non-Marathi industrialists in Mumbai. In fact, during its tenure of the BMC, the Sena often praised them as ‘anna daatas’ (lit., ‘bread givers’), who provided jobs for millions of Maharashtrians (Shaikh 2004). The Shiv Sena’s conflicting agenda translated into an inability to fulfill the expectations it had generated among both the Marathi working and middle classes. Ultimately, disappointment with the
Shiv Sena played a crucial role in the party’s loss of the BMC in the 1992 local civic elections (Blom Hansen 2001).
3.3.2 Pre-electoral violence
Violence, both as a rhetorical style and as an actual practice, is an integral element of the Shiv Sena’s mobilization strategy. The need for violence meant that the Shiv Sena has always defined itself against a constitutive, if imprecise, ‘they’ (Eckert 1999). At the
89 party’s foundation, in 1966, this enemy was the South Indians, then the Communists, the
Dalits, the city elite and the North Indians. In the 1980s, the Shiv Sena adopted a radical anti-Muslim strategy. This shift was formally announced by the Shiv Sena’s leader, Bal
Thackeray, in a speech at Chowpatty Beach in Mumbai in April 1984. In it, Thackeray repeatedly called Muslims “a cancer on this country. Its only cure is operation…Oh,
Hindus, you take weapons in your hands and remove this cancer from its very roots”
(Thackeray 1984, p. 76 cited in Blom Hansen 2001).
This inaugurated a novel era of violent politics in Maharashtra. A few weeks after
Thackeray’s speech, on 17 May 1984, communal riots broke out in Bhiwandi, a city located 20km to the north-east of Mumbai. These were the first major riots to break out in
Mumbai since the period of Partition. During the first night of violence, hundreds of Shiv
Sena activists from Mumbai were transported on trucks to Bhiwandi, and so began the systematic killing, looting and burning of Muslim property (Engineer 1997). In the following days, the riots spread to Govandi, Pydhonie, Kherwadi, Jogeshwari and
Kamathipura in Mumbai. Official figures put the deaths at 278, the wounded at 1,115 and the number of those left homeless over 6,000 (Blom Hansen 2001).
The success of the Shiv Sena in the second half of the 1980s seems to confirm the expectations of the literature on the link between pre-electoral violence and votes
(Wilkinson 2004; Dhattiwala and Biggs 2012). As we have seen, in 1985, the Sena won the BMC for the first time on its own. The following years were marked by an increase in communal violence in Mumbai. Small-scale riots erupted in 1987 in Kamathipura, in
90 1989 in Dongri, Nagpada and Bhendi Bazaar and in 1990 in Mahim (Varshney 2002;
Robinson 2005). Crucially, in September-October 1990, the then President of the BJP,
L.K. Advani, embarked on a rath yatra (‘chariot journey’) across India to support the erection of a temple to the Hindu deity Rama on the site of the Babri Mosque in
Ayodhya, UP. The Rath Yatra stopped in Mumbai on September 29, 1990. The yatra left a trail of violence in its wake, including an estimated 166 communal riots (Panikkar
1993).
However, these episodes of violence failed to build a momentum for the Shiv
Sena in the three elections that followed in the early 1990s: the 1990 State Assembly elections; the 1991 Parliamentary elections; and the 1992 local civic elections. This mirrors the defeats suffered by the BJP in the 1993 state assembly elections, which were widely understood as a referendum on the BJP’s role in the Ayodhya agitations (Thachil
2011). Thus, while violence as a pre-electoral tactic contributed to the Shiv Sena’s success in the late 1980s, it now seemed to have reached a saturation point. For this reason, the Shiv Sena’s desperately needed to harness its ‘muscle power’ in ways that more efficiently translated into electoral success.
3.3.3 Patronage
The Shiv Sena has promoted, and to some extent benefited from, the introduction of new forms of patronage into Mumbai’s political landscape. While retaining its programmatic ambiguity, the party promoted into positions of public prominence members of lower-caste groups, predominantly from Marathi-speaking communities, as
91 well as young men from slum areas and lower middle-classes backgrounds (Blom Hansen
2001). The party also attracted a section of Mumbai’s working class by offering them the promise of patronage based on cultural-linguistic ties of Marathi speakers (Shaikh 2005).
In the 1980s, large numbers of Other Backward Classes (OBCs), who remained on the fringes of the Maharashtrian political establishment, saw in the Shiv Sena a vehicle for upward social mobility and access to resources (Blom Hansen 2001). Besides the opportunities intra-party advancement, the party’s aggressive methods and vindictive rhetoric made it attractive to young men from OBC communities. Shiv Sena’s militant opposition to Muslims and Dalits, especially by the Mahar community of neo-Buddhists, helped to define OBC identity and thus further added to its popularity among them
(Shaikh 2005). According to one estimate, in the early 1990s, OBCs formed almost 70 percent of Sena’s electoral support (Purandare 2012).
However, the Shiv Sena did not appeal directly to OBC communities nor did it try to style itself as a political home for the lower castes. In fact, Bal Thackeray opposed the idea of identifying the Shiv Sena with a lower-caste movement and openly disapproved of the rising assertiveness of OBCs within the party (Blom Hansen 2001).
The situation finally came to a head in 1990 over the Mandal Commission recommendation of 27 percent reservation quota for OBCs. Despite its large support base among OBCs, the Shiv Sena was the only party in Maharashtra that opposed the
92 implementation of the Commission’s recommendation. According to Blom Hansen
(2001, p. 97), the party’s stand was ‘politically and tactically suicidal’:
Had Thackeray operated according to a common ‘electoral instinct,’ undoubtedly Shiv Sena would have consolidated itself among these OBC communities.
The immediate result of the Shiv Sena’s opposition to Mandal was Chhangan
Bhujbal’s desertion into the INC. A member of the Mali (gardener) caste, Bhujbal had risen through the ranks of the BJP to become a two-time mayor of Mumbai. He was also one of the earliest Members of the Legislative Assembly (MLAs) of the Shiv Sena, elected from Mazgaon (South Mumbai) in 1985 and 1990. He had considerable political clout among OBCs and he was held up as by the party as its prime example of sensitivity to OBCs (Blom Hansen 2001). His defection thus punctured a major hole in the Shiv
Sena’s electoral base. But it also served as a comment on the Sena’s brand of plebeian politics (Lele 1995). Ultimately, the Shiv Sena’s loss of the BMC in 1992 painfully brought home the limitations of its use of patronage as an electoral strategy.
3.3.4 Social Welfare Provision
Lastly, but not least, the Shiv Sena has also developed a wide network of local units, commonly known as ‘shakhas’ (lit. ‘branches’), that provide a variety of services to constituents.54 Borrowing this strategy from the Hindu nationalist Rashtriya
Swayamsevak Sangh (RSS), the Sena quickly established this network in both middle-
54 The Shiv Sena borrow this strategy from the Hindu nationalist Rashtriya Swayamsevak Sangh), who built a network of dedicated volunteers running shakhas throughout the country.
93 class and low-income areas in Mumbai following its foundation in 1966 (Blom Hansen
2001). The shakhas are led by a shakha pramukh (lit. ‘chief’) and a community organizer, the gata pramukh, that are expected to provide a wide range of community services to their localities (Bedi 2016).
They organize religious festivals and cultural programs and they position themselves as the centers for redressing grievances, from family disputes to problems with landlords (Gupta 1982). The shakhas also provide a variety of social services to local communities in Mumbai. These services range from cleaning up the gutters before the monsoon, arranging blood banks, health camps and free ambulances, to securing water or electricity connections. In fact, one of the Shiv Sena’s most repeated slogans is that it is committed to ‘80 percent social work, and 20 percent politics’ (Outlook India
2014). Finally, the shakhas have also played a crucial role in spreading rumors and mobilizing people for action, be it for violence, elections, or during festivals (Shaikh
2005). Thus, the Shiv Sena’s shakhas have been successful in projecting themselves as the representation, if not the heart, of the neighborhood.
In terms of both their numbers and dynamism, there is little question that the shakhas have been the Shiv Sena’s main instrument for appealing to the poor in Mumbai.
Shaikh (2005) describes how the party used the shakhas to ensconce itself in the working- class neighborhoods of Mumbai. Similarly, Blom Hansen (2001) argues that the Shiv
Sen’s political successes – particularly its survival in a political wilderness between 1975 and 1984 – owed greatly to this network of local welfare services.
94 At the same time, it is important to note that the shakha grid preceded the early
1990s. In fact, there is extensive evidence that the shakhas played a crucial role as
‘centers of local command’ of the Shiv Sena during the 1992-93 Mumbai riots
(Srikrishna Commission 1998). Thus, while the social service functions performed by the
Shiv Sena shakhas were important for its popularity, this strategy was not sufficient to prevent the party’s defeat in elections for all levels of government in the early 1990s.
Moreover, it is important to highlight that the Shiv Sena was not alone in offering these services. Other agencies, like government and non-governmental organizations, communist unions and religious groups also provided social services in Mumbai. They did so without requiring that the recipient of such services convert to the religion or accept the political or social agenda of the service provider (Shaikh 2005). There is also no evidence of the Shiv Sena’s superiority in terms of service provision (Blom Hansen
2001). It thus seems that welfare provision had already been extensively deployed by the
Shiv Sena with mixed results up to the early 1990s.
3.3.5 The Turn to Unmixing
The Shiv Sena’s activities following its defeat in the 1992 civic elections indicate its desire to find an alternative electoral strategy. In April, the party underwent a major reshuffling. All shakha pramukhs in the greater Mumbai region were removed along with several district supervisors. Months later, Thackeray proposed that the Israeli intelligence service, Mossad, be invited to train and equip Shiv Sena’s own antiterrorist squad.
Finally, in July 1992, Thackeray announced that he would abandon the Shiv Sena’s leadership. This forced senior party leaders to vow allegiance to him and prompted a
95 dramatic display of support from the Sena rank-and-file. Eventually, having reaffirmed his authority, Thackeray accepted to retain his position as Shiv Sena’s ‘army commander.’ Yet, it was clear that the party’s cohesion and clout had been damaged the defeats and convulsions of recent months.
The opportunity to re-energize the party finally presented itself on the night of
December 6th 1992, when thousands of Muslims took to the streets of Mumbai in protest against the demolition of the Babri Masjid in Ayodhya, UP. In the occasion, the Shiv
Sena combined its considerable muscle power with spatial tactics. Specifically, the party used the opportunity presented by the riots to violently rewrite Mumbai’s space as one purified of Muslim bodies (Appadurai 2000). According to a study conducted by the
NGO Youth for Unity and Voluntary Action (YUVA) in Jogeshwari East, the evictions and dispossession that took place during the riots amounted to a case of ‘planned segregation’ (Kothari and Contractors 1996). In an interview covering the Shiv Sena’s role during the 1992-93 Mumbai riots, Thackeray himself publicly linked the use of violence to the desire to root out Muslims from Mumbai’s urban fabric:
If their heart is in Pakistan, and their body is here, we don't want Muslims here. There is no compromise on this issue. I will not tolerate any traitor belonging to any caste or religion. But Muslims must prove their credibility. Suppose there are Pakistani extremists living in their neighbourhood, I want the Muslims to tell the police. (…) I will kick them out. They have got to be chucked out (India Today 1995).
This statement is telling because the nationalist credentials that Muslims are expected to prove are considered especially offensive by them. They include singing
96 ‘Vande Mataram’ (a song that was by-passed as the national anthem of India in 1950 for equating the nation with Hinduism), shutting down madrasa schools, and discarding ‘the minority community veil’ (burqa) (Times of India 2014). Thus, by insisting upon these credentials, Thackeray was certain to produce a spatial schism between the two communities. In the words of riot survivor, who I interviewed in Mumbai in October
2015, his strategy was a clear reproduction of an old colonial policy:
Divide and rule. Simple thing. The Shiv Sena did the same to Hindus and Muslims.
3.4 There’s a Pakistani upstairs: the mechanisms of unmixing
The spatial separation between Hindus and Muslim that took place following the
1992-93 riots was so complete that Naresh Fernandes, a Mumbai journalist who covered the riots for The Times of India, described it to me in November 2015 as a case of ‘oil and water.’ The process of ethnic unmixing in Mumbai had three fundamental characteristics.
First, according to several of the individuals I interviewed in Mumbai, religious unmixing has engulfed the entire city and occurred at all socio-economic brackets. Second, the accentuation of segregation between Hindus and Muslims mitigated the influence of other inter-community categories in the spatial distribution of individual in Mumbai.
Thus, since the riots, the “highly differentiated Muslim sects and communities in the city have undoubtedly become more spatially concentrated than ever before” (Blom Hansen
2001, p. 160). Finally, the consolidation of religious communities following the 1992-93 riots was not a single mass movement of people from one locality to the other.
97 Instead, the 1992-93 riots triggered two types of migratory flows: (1) an initial movement of people forced to flee their homes as a direct consequence of the violence; and (2) an unmixing cascade in search for ‘safety in numbers’ that trickles over many years after the violence. Here, I outline the mechanisms underpinning each of these migratory flows.
3.4.1 Unmixing during the riots
The viciousness of the attacks, particularly during the second stage of the riots, triggered a wave of panic among the Muslim community in Mumbai.55 The Justice
Srikrishna Report, directly charges Shiv Sena leaders and municipal corporators for leading or participating in attacks on Muslim individuals and property. During the night of 6th January, in affluent Malabar Hill and middle-class Borivali, Muslim residents scrambled to unscrew the nameplates on their doors and in their lobbies, hoping to deceive potential attackers (Fernandes 2013). In the low-income area of Deonar (Eastern
Suburbs), one interview subject who I spoke to in November 2015 told me that Muslim residents took shifts on night watches for rioters going from house to house with lists of
Muslim names. Witnesses, who I interviewed in Mumbai between October-November
2015, reported hearing the rioters shouting the following slogan:
Musalmanoon ke do hi sthaan, Pakistan ya kabristan (Muslims have only two places to live in: Pakistan or the graveyard)
55 While there are no precise statistics on the number of women raped and sexually abused, reports from Indian NGOs indicate that such attacks were widespread and disproportionately affected Muslim women (HRW 1996). According to witnesses, Muslim mothers watched as their sons were pulled from their homes, slain or burned alive while mobs of cheering Hindus danced around the blazing bodies (New York Times 1993). Mosques and Muslim stores were firebombed. The Srikrishna Commission Report also makes clear that children were also not spared in the violence. Thus, many city residents retain gruesome memories of the riots. A 78-year-old Muslim businessman, who witnessed the violence in M.R.A. Marg, broke down during our interview and told me: ‘People who saw the riots will never forget them.’
98 After that night, many Muslims sought refuge with family members in Muslim- majority areas in Mumbai. According to one interview subject, Muslims were easy targets in areas where they were in a minority. But rioters were reluctant to enter Muslim- majority areas where they would certainly face retaliation from Muslims. Thus, many
Muslims sought refuge in areas where their large numbers provided them safety. This triggered a concentration of Muslims in areas where they were already in the majority, namely in south and central Mumbai, and in Jogeshwari West, Kurla, Malvani (Malad) and Govandi in Mumbai Suburban (Khan 2011).
Others found shelter with their Hindu neighbors. For example, a trustee of Action for Good Governance and Networking in India (AGNI) in Bandra West, told me in
November 2015 how individuals in middle-class buildings turned against each other:
One lady in their building went up to the police and told them: ‘There’s a Pakistani leaving upstairs. So, the next day, my son didn’t tell me anything; he just said he was going out to take care of some business, and went up to their house and said: ‘Pack your things. You will stay with us. I will take you to the hospital if you need (one member of the family was pregnant). It’s very sad but they will let me pass if I drive. They will not let you but they will let me.’ I was very proud of him because he knew that he didn’t need to ask me for permission. He knew that I had no trouble letting them stay in our house.
In the following weeks, many Muslims were also forced to flee due to the destruction of their houses and businesses. One refugee from a chawl in Central Mumbai told me how her house was ransacked and destroyed by people she knew. The furniture the family kept was burnt and whatever cash and jewelry they had was stolen. As a consequence, they had to stay on a refugee camp during the riots. Another refugee told
99 me how the Hindu families in her building were taken out and their properties protected during the riots. Only then, did the rioters attack the building. For most refugees, the most painful memory of the riots was later seeing their belongings used by their neighbors
(Khan 2011). In all, nearly 10,000 houses were demolished or burnt and more than
100,000 became refugees in their own city, seeking shelter in rudimentary relief camps set up in safe neighborhoods (Engineer 1993). According to the Srikrishna Commission
Report (2006), there was no need of opening refugee camps for Hindus as all refugees were Muslims.
In some cases, walls were erect and boards put up saying, ‘Minorities not wanted’
(Engineer 1993, p. 507). For example, in Palvadi at the heart of Dharavi, one of
Mumbai’s largest slum areas, Muslim and Tamil Hindu families had lived together for generations. During the riots, a wall was erected between the Hindu-dominated Naya
Chawl and the predominantly Muslim Nawab Nagar. Residents were sorted according to their religious so that the two areas became ‘only Hindu’ or ‘only Muslim.’ Since then, most Tamil Hindu families have moved out of Naya Chawl, leaving the area almost entirely to Muslims (Saglio-Yatzimirsky 2013).
Finally, there was also significant out-migration from the city of Mumbai during the 1992-93 riots. According to police accounts, more than 200,000 people, both Hindus and Muslims, fled the city during the riots (Engineer 1993). Special trains were provided to take these refugees to Bihar and Uttar Pradesh. One area that received large numbers of refugees immediately after the outbreak of violence was Mumbra, Thane district. One
100 survivor who was living in Shivaji Nagar in the suburb of Jogeshwari, a mixed neighborhood, was advised to leave the area after the first wave of riots (Peer 2015). He moved his wife and children to his in-law’s house in Mumbra, Thane district, overnight.
He stayed there for the rest of January (and eventually decided to relocate there).
3.4.2 Unmixing after the riots
After the violence subsided, many Mumbai residents went back to their former residences. A large section of the population who had left the city during the riots returned to the city. However, many workers did not deem it safe enough to bring their families back so only the males returned. Likewise, many Hindus and Muslims who during the riots moved to areas dominated by members of their religious category returned to their homes.
Yet, it soon became clear that the process of religious unmixing that the riots had unsettled continued to trickle in more subtle ways in the following years. One of the more conspicuous signs of this second migratory flow was the distressed sale of properties at rates far below market rates (Peer 2015). Indeed, after the end of the riots, many Muslims preferred making a loss in the property market than to remain in the areas where they were in a minority. A municipal corporator from a ward in Central Mumbai, who I interviewed in November 2015, explained their decision in the following terms:
After the riots, people were in fierce scare. They left because they were not feeling safe anymore in Hindu areas. They saw the riots, demolitions, murders, rapes. All they wanted was to live in safety with members of their community.
101 The search for ‘safety in numbers’ has indeed been one of the most enduring legacies of the 1992-93 riots in Mumbai. During my fieldwork, I asked several Muslim interviewees in Mumbai if they would ever return to their former mixed neighborhoods.
Almost universally, their reply was negative. For some respondents, it took many years to settle in a Muslim-majority neighborhood after the 1992-93 riots so they were not willing to move again. Other respondents highlighted that Muslims continued to face harassment in mixed neighborhoods and they pointed out that their co-ethnics are still moving to
Muslim-dominated areas even after all these years. Still others expressed the fear that they might not survive a new riot if they found themselves alone in a Hindu-majority locality. In general, those who had witnessed violence firsthand were also the most reluctant to return to a Hindu-majority locality. This feeling was captured by one respondent, a 37-year-old garment maker from Reclamation, who told me in November
2015: “We have already survived the riots once. We might not be lucky the next time.”
Since the search for ‘safety in numbers’ involves local level dynamics, many
Hindus, too, felt compelled to move to Hindu-majority neighborhoods in the aftermath of the riots. According to a municipal corporator from a Muslim-majority ward in Mumbai, who I interviewed in October 2015, the riots changed Hindu perceptions about Muslims:
This distrust of a particular community is one of the very sad effects of the riots. They think that if a Muslim lives in their society, there will problems because Muslims are uncouth, they fight, etc.
102 The relocation of Hindus from Muslim-majority areas and of Muslims from
Hindu-majority areas heightened the sense of fear and isolation of those who stayed behind, thus further increasing the pressure for the consolidation of communities. In this way, the search for ‘safety in numbers’ has become a self-reinforcing dynamic that has built up over time, eventually resulting in increasing levels of Hindu-Muslim segregation in Mumbai.
Other factors have also contributed to religious unmixing in Mumbai since the
1992-93. Interview subjects on both sides highlighted harassment as an important factor shaping their decision to relocate. Many Muslims interviewees told me that they were called by the derogatory name ‘landya’ and that they were told to ‘go back to Pakistan.’
Similarly, Hindu interview subjects who I interviewed between October-November 2015 reported being abused in Muslim-majority neighborhoods:
My aunt used to live in a slum in Reclamation, Nargish Dutt Nagar, but recently she had to move out due to the harassment she was facing because she is a Hindu, living in a Muslim-majority area. Her children were teased, they used to throw stones at them. I think it is a case of ‘you are doing this to us so we are also doing this to you.’
Other respondents mentioned that, after the riots, there was a concerted boycott campaign against Muslims shops and businesses, further pushing them out of mixed neighborhoods. In this case, too, pamphlets and lists were circulated naming shops and businesses to be boycotted suggesting that this was also part of a systematic effort to unmix certain localities (Blom Hansen 2001). Individuals that I interviewed in Mumbai also reported intimidation and boycott in employment and, even a growing separation
103 between Hindus and Muslims at the school level. One school teacher I interviewed in
Bandra West in October 2015 argued that changes in the school body are symptomatic of wider transformations in the locality:
In the Catholic Missionary schools in Bandra, the majority of students are Muslims. Why? They are the only schools that accept Muslims. Also, many Hindu families have moved outside of the neighborhood. So, the missionary schools have to take in the Muslims because otherwise they would have no students.
Finally, my fieldwork in Mumbai yielded further evidence of widespread discrimination against Muslims in the housing market. One municipal corporator explained this as ‘a case of attach me not.” According to him, the riots helped to corroborate and popularize negative stereotypes of Muslims as ‘problem makers.’ The production and reproduction of such stereotypes played an important role in the social spatialization of Muslims since their presence in a building or locality becomes a drawback from the perspective of prospective investors. In line with this, several interview subjects knew or had heard stories about Muslims who were denied the right to rent or buy property due to their religious identity. One tenant in South Mumbai told me in November 2015 the following the story:
In my sister’s building in Vile Parle an old lady wanted to sell her flat. It happened that she got the best deal from a Muslim lady. She is dress like this (Hindu-style of clothing), wears a bindi (a red dot worn in the forehead) and you cannot tell her religion by her first name. When she was writing the contract, the moment she wrote in the paper her last name (a Muslim-sounding name), they said: ‘Oh, actually, you cannot buy this flat because of this or that.’
104 To conclude, then, ethnic unmixing following the 1992-93 in Mumbai riots extended far beyond the initial movement of people forced to flee their homes as a direct consequence of the violence. Due to their magnitude and ferocity, the riots also triggered a processed of unmixing between Hindus and Muslims that continues in a steady trickle until today. In both migratory flows, the search for ‘safety in numbers’ played a pivotal role in individuals’ decision to relocate to a locality dominated by members of their religious community. However, physical harassment, economic boycotts and discrimination in housing markets also contributed to accentuate residential segregation between Hindus and Muslims in Mumbai following the 1992-93 riots. Finally, the process of religious unmixing that followed the 1992-93 riots in Mumbai was distinctive in that it involved not only the lower income areas of the city but also its upscale neighborhoods. In this way, the 1992-93 riots enduringly accentuated Hindu-Muslim segregation in Mumbai.
3.5 Alternative Explanations
How does this account of the 1992-93 Mumbai riots hold up against alternative explanations for Hindu-Muslim violence in India? While the literature generally agrees that there are political incentives behind these violent conflagrations, scholars emphasize different factors to explain the occurrence of communal riots in India (see for example,
Brass 1997; 2003; Varshney 2002; Wilkinson 2004; Field et al. 2008). Here, I examine the 1992-93 Mumbai riots through the prism of three dominant explanations: electoral competition, social capital and competitive real estate markets.56
56 The SriKrishna Commission Report (2006) also excludes the following immediate causes: class conflict, economic competition between Hindus and Muslims, decline in employment in organized sector and density of population.
105 3.5.1. Electoral Competition
In recent years, much ink has been spilled about the level of electoral competition in forthcoming elections and the production of Hindu-Muslim riots in India (Wilkinson
2004; Wilkinson and Haid 2009; Dhattiwala and Biggs 2012; Blakeslee 2014). For this literature, ethnic riots are a particularly effective and brutal method for elite-dominated ethnic parties to raise the short-term salience of one ethnic category so as to build a winning political competition. According to this logic, three factors increase the likelihood of communal riots: (1) the proximity of an election; (2) the existence of a bipolar party system in which minorities have less influence in determining which party wins; and (3) anti-minority, elite-dominated ethnic party incumbency.
These three conditions were only weakly observed or entirely absent in the case of the 1992-93 Mumbai riots. The first Maharashtra legislative elections after the riots, which the Shiv Sena-BJP alliance won, did not take place until more than two years after the riots in February-March 1995. Therefore, the riots took place roughly at half cycle between the previous and the following elections. From that perspective, they are as much a product of the previous electoral result as of the electoral strategies for the following elections. Moreover, the extreme volatility of Indian party politics during the early 1990s suggests that salient social categories were highly fluid during this period.
Significantly, in 1993, following heavy defeats in the Madhya Pradesh and Himachal
Pradesh legislative elections, the BJP began to shift emphasis from religious into social- economic issues (Jaffrelot 1996). Similarly, the next national parliamentary elections, when the BJP took power at the center for the first time, took place in 1996, three years
106 later. Finally, the next local civic elections, in which the Shiv Sena regained control of the BMC (until today), which, as we have seen, was the party’s bastion, did not occur until more than five years after the riots in 1997.
The party system in Maharashtra and Mumbai was not bipolar. According to the effective number of party votes (ENPV) – the measure used by Wilkinson in his analysis of competition and riots (2004) – the party system in the 1990 Maharashtra legislative elections was highly fragmented (ENPV = 5). The value remains high even we add the vote share of the Shiv Sena and the BJP (ENPV = 4.3). The degree of competition was even higher in the 1992 BMC elections, where the BJP and the Shiv Sena, competing without an alliance, faced stiff competition from the INC, the Republican Party of India
(RPI) and Janata Dal (JD) (ENPS = 6.7).57 Moreover, representing roughly 20 percent of
Mumbai’s population, Muslims formed an important segment of the electorate in the city.
Finally, neither the Shiv Sena nor the BJP were in power at any level of government during the 1992-93 Mumbai. This suggests that while the riots contributed to the Hindu right’s success in ensuing elections, this relationship did not follow the expectations of the literature liking low levels of electoral competition to the occurrence of Hindu-Muslim riots.
57 I calculated the effective number of party seats due to lack on data on vote share for each party.
107 3.5.2 Social Capital
Another argument links the occurrence of Hindu-Muslims riots to the existence of networks of ‘civic engagement’ between the two communities, a form of social capital
(Varshney 2002; Chidambaram 2012). These networks can be broken down into two categories: associational forms of engagement and everyday forms of engagement.
According to these arguments, where such networks of civic engagement are interethnic, they constrain the polarizing strategies of political parties; where they are missing or intraethnic, they make societies vulnerable to the ethnic disorders and violence. While both forms of civic engagement promote communal peace, associational forms are said to be sturdier in the face of political parties’ attempts to foment communal violence.
Unfortunately, there is a paucity of data on the degree and nature of civic ties in
Mumbai in 1992-93, but some rudimentary conclusions can be drawn from the available information. In regards to associational forms of engagement, existing evidence provides mixed results. While there is no official data on the number and distribution of Shiv Sena shakhas across Mumbai, previous studies suggest that they were omnipresent in low and lower-middle neighborhoods (Blom Hansen 2001; Palshikar 2004; Shaikh 2005). This would suggest that the Shiv Sena indeed relied on intraethnic associational ties to turn the demolition of the mosque in Ayodhya into a full-blown Hindu-Muslim riots between
December 1992 and January 1993. This account is further corroborated by the findings of the Srikrishna Commission Report into the riots:
The shakhas in different jurisdictional areas turned into centers of local commands. (…) From 8th January 1993 at least there is no doubt that the Shiv Sena and Shiv Sainiks took the lead in organizing attacks on Muslims and their properties under the guidance of
108 several leaders of the Shiv Sena from the level of Shakha Pramukh to the Shiv Sena Pramukh Bal Thackeray who, like a veteran General, commanded his loyal Shiv Sainiks to retaliate by organised attacks against Muslims (Srikrishna Commission Report, vol.1).
This argument offers a potent explanation for the 1992-93 Mumbai riots but it also raises a series of difficult questions. First, are we to assume that there were simply no interethnic civic organizations in the affected localities? This seems unlikely given the high density of civic organizations in Mumbai (Zerah 2007). While the role of shakhas as facilitators of violence seems beyond doubt, it is unclear whether intraethnic associational ties mattered because they prevailed over other organizations or were merely instrumental when the riots broke out.
Another question concerns the spatial distribution of the violence. While the shakhas were concentrated in the lower and middle-income localities of Mumbai, the
1992-93 riots were distinctive it that they engulfed the entire city, including its well-to-do neighborhoods in south and west Mumbai. What explains the occurrence of violence in areas of the city where the Shiv Sena had little to none street presence? In other words, social capital arguments fail to explain the logic underpinning violence in localities with weaker intraethnic associational ties. Though the dynamism and organizational qualities of the shakhas may have brought Mumbai to the brink of chaos in 1992-93, it is also important to understand the local dynamics behind the occurrence of ethnic riots. My argument, I contend, provides a more complete explanation of why and how the eruption of violence in some Mumbai localities was then selectively targeted to other, more peaceful, parts of the city.
109 In regards to everyday forms of civic engagement, the evidence clearly renders the social capital argument obsolete. According to Varshney (2002), interethnic propinquity at the neighborhood level has a positive effect on tolerance and therefore a negative effect on conflict. Yet, communal riots typically affect mixed localities. The reasons for this were already clear in the 1984 Bhiwandi-Bombay riots:
It has often been said that living together can mitigate prejudices and ensure better integration between various communities. These riots did not bear this out; on the contrary, they negated this assumption. Muslims in their own mohallahs like Mahgiri and Rabori did not suffer much as they could beat back the invaders, but those who lived surrounded by Maharashtrians suffered the most. One unfortunate result of this riot was to strengthen the tendency of people to live in separate community-wide bastis (Engineer 1997, p. 321).
In this way, the propensity of mixed areas to violence provides additional support to my argument that the riots intended, at least partly, to increase the spatial segregation between Hindus and Muslims in Mumbai. In line with this, Gupta (2011, p. 22) identifies a similar pattern in the 1992-93 riots in Mumbai:
The attacks were aimed primarily at Muslims who lived among Hindus and were therefore a minority in those localities. Very rarely were any forays made into large parts of Mumbai where Muslims were in a majority.
The findings of the Srikrishna Commission Report (2006) into the 1992-93 riots further corroborates this idea. The Report identified 26 police stations badly affected
110 during the riots (Map 3.1).58 These police jurisdictions are overwhelmingly situated in areas of south and central Mumbai, which due to historical patterns of settlement and high population density promoted a high level of interethnic propinquity. Thus, the spatial patterns of the 1992-93 riots do not support arguments emphasizing the link between the degree and nature of civic ties and the occurrence of riots.
Figure 3.1: Worst Affected Police Stations in 1992-93 Mumbai riots (SriKrishna Commission Report)
58 The stations were: Colaba, Cuffe Parade, Azad Maidan, M.R.A. Marg, Dongri, Pydhonie, L.T. Marg, V.P. Marg, D.B. Marg, Gamdevi, Tardeo, Nagpada, Agripada, Byculla, Bhoiwada, Kalachowkey, Rak, Antop Hill, Mahim, Kurla, Dharavi, Deonar, Ghatkopar, Kherwadi, Nirmal Nagar and Jogeshwari
111 3.5.3 Competitive Real Estate Markets
A final strand of arguments present communal violence as an efficient, albeit brutal, means of vacating highly valuable property in the context of heightened struggles over property (Appadurai 2000; Field et al. 2008). Specifically, this scholarship highlights the role of the Bombay Rent Control Act of 1948 in enabling industrial workers to remain in chawls at low rents. Because property rights were based on tenancy of chawl units, and chawl residents could not easily be bought out, these valuable properties were not fully available in the property markets. Therefore, Hindu-Muslim riots enables politicians and developers to forcefully evict religious minorities from industrial neighborhoods in the heart of cities like Mumbai and Ahmedabad.
There is much to commend this argument in the case of the 1992-93 Mumbai riots. First, the riots coincided with a period of heightened tensions over scarce property in Mumbai. In fact, by the mid-1990s, Mumbai was said to be the most expensive city in the world (Blom Hansen 2001). Moreover, from the 1970s onwards, there was a sharp decline in the mill factories of central Mumbai, thus making this area of the city highly attractive for real estate developers (Appadurai 2000). Second, as depicted in Map 3.1, the geography of the violence also coincides with the mill districts of Mumbai. Thus, areas with a great number of chawls such as Byculla, Tardeo and Dharavi, were also the stage for some of the worst episodes of violence during the 1992-93 Mumbai riots.
Finally, these areas saw great numbers of distressed sales of properties by Muslims following the riots (Gupta 2011).
112 However, the Srikrishna Commission Report (2006) makes clear that the 1992-93
Mumbai riots cannot simply be explained in terms of rising interest in Muslim-owned property:
There is also no evidence to suggest that the riots on such large scale could have been engineered by builders or land–grabbers, though land–grabbing may have occurred on certain occasions as a consequence of riots.
While recognizing the Shiv Sena’s growing entanglement in Mumbai’s real estate brokerage networks, Blom Hansen (2001) also notes that the link between violence and property was opportunistic rather than causative. Ultimately, we may point out again that the 1992-93 riots were not limited to chawls or even to the mill districts of Mumbai.
Instead, they spread to different types of buildings and localities within the city. From this perspective, and given the predominance of violence in mixed localities, one may argue that the violence maps better onto the distribution of religious diversity within the city rather than the particular type of tenement of localities within Mumbai.
3.6 Conclusion
This chapter maintains that the 1992-93 riots were part of a Shiv Sena’s strategy to restructure Mumbai’s social geography to its electoral advantage. To support this argument, I have outlined the Shiv Sena’s precarious position in the early 1990s and its need for an alternative electoral strategy. I have also described how Mumbai’s ethnic demography has changed since the 1992-93 riots and illustrated the mechanisms linking riots to ethnic unmixing. Finally, I have contended that this argument offers a more
113 convincing account of the 1992-93 Mumbai riots than conventional explanations on
Hindu-Muslim riots in India.
However, this elaboration is incomplete without an examination of the long-term advantages of ethnic unmixing for political parties. Specifically:
1. Why does ethnic homogeneity at the constituency level contribute to the long-
term success of parties matching a matching ethnic category?
2. Does this argument contradict conventional wisdom on ethnic categories as viable
basis for minimum winning coalitions? Specifically, why should voters support
parties who include oversized ethnic coalitions?
The next two chapters tackle these two questions by looking at variation in support for the Hindu right across India’s seven largest cities. First, I draw on a newly available source of demographic data in India – voter names on electoral rolls – to build a cross- sectional dataset of religious demography and electoral preferences at constituency level.
Statistical analysis of this data shows that not only are Hindu-majority constituencies more likely to vote for the Hindu right but also that this likelihood increases with the size of the Hindu majority in a constituency. The following chapter on Ahmedabad then illuminates the causal mechanism between ethnic homogeneity at constituency level and lasting support for the Hindu right in urban India.
114 Chapter Four
Ethnic Unmixing and the Hindu Right’s Success
In short, successful spatial strategies are able to link, in a durable and ideologically credible way, abstract (imagined) spaces to concrete (physical) spaces. -- Satish Deshpande, Communalising the Nation-State, 1995
The Government thinks that the Hindus have no right to ask for even basic rights while other religious communities shout loud and get special treatment from this very Government. (…) This is because Muslims and other minorities usually vote en bloc while Hindus are divided. Once Hindus get united, the government would start caring for them. -- Madhukar Dattarya Deoras, speech at the Second International Hindu Conference, 1979
4.1 Introduction
The second part of this dissertation builds on the insights of the previous chapters to examine the relationship between ethnic unmixing and the success of ethnic political parties. Specifically, I now address the central question of this dissertation concerning the long-term electoral repercussions of ethnic riots. Can the consolidation of electoral constituencies along communal lines in the wake of Hindu-Muslim riots contribute to the enduring success of the Hindu right in urban India?
This chapter proposes a simple answer to this question. I argue that high levels of
Hindu-Muslim segregation in urban India creates a self-sustaining and reinforcing equilibrium in favor of parties mobilizing the Hindu majority. For voters, high levels of segregation along communal lines enduringly increases the visibility of religious
115 identities and reduces uncertainty about which political party is better placed to provide them access to crucial public goods. For parties, high levels of Hindu-Muslim segregation enable them to deploy electoral strategies more efficiently, wasting little resources on the delivery of goods and distributing fewer resources to voters than if voters were dispersed across heterogeneous constituencies. In this way, I argue that the consolidation of electoral constituencies in the wake of Hindu-Muslim violence has contributed to the long-term success of the Hindu right in some of India’s largest cities.
The argument that ethnic unmixing contributes to the success of oversized ethnic coalitions complements traditional approaches to the triumph of the Hindu right in India.
Scholars examining this phenomenon have emphasized a variety of factors such as the dividends of pre-electoral violence (Wilkinson 2004; Dhattiwala and Biggs 2012), the rise of the middle classes and the consolidation of elite vote (Chhibber 1997; Hansen and
Jaffrelot 1998), patronage (Chandra 2004; Huber and Suryanarayan 2016), and, more recently, social service provision (Jaffrelot 2003; Thachil 2011). Yet, while demography is a recurrent theme of the scholarship on Indian politics, relatively little systematic empirical work has been paid to the relationship between religious demography and the success of the Hindu right in India.
To address this gap in the literature, I examine variation in electoral support for the two main parties of the Hindu right – the Bharatiya Janata Party (BJP) and the Shiv
Sena – across India’s seven largest cities (maps in the annex). In this chapter, I draw on a newly available source of demographic data in India – voter names on electoral rolls – to
116 generate estimates of religious demography at constituency level. Using these estimates as well as electoral data and other relevant independent variables, I assembled an original dataset covering over 50 million individuals, 1,025 municipal wards and 187 state assembly constituencies in India’s seven largest cities. This constitutes the largest available subcity dataset of electoral and demographic variables in India’s electoral constituencies, affording us a unique opportunity to study the link between ethnic demography and the success of ethnic parties.
The results presented below suggest a strong positive link between growing
Hindu-Muslim segregation and the Hindu right’s success. The analysis shows that not only are Hindu-majority constituencies more likely to vote for the Hindu right but also that this likelihood increases with the size of the Hindu majority in a constituency. This finding is robust to additional covariates, as well as control for unobserved variation at the municipal and state constituency level.
In the sections that follow, I first outline a theory linking increasing ethnic segregation and the success of parties mobilizing large ethnic coalitions. In the following section, I lay out a series of hypotheses based on the foregoing discussion. I then discuss the data collection and methods employed by this project to this test the hypotheses. In the following section, I present empirical results of the analysis of the relationship between demographic context and electoral outcomes in India’s seven largest cities.
Finally, I conclude with a discussion of the limitations of this analysis and suggestions for future avenues of research.
117 4.2 The Argument: Segregation and Ethnic Party Success
The main goal of this section is to demonstrate that high levels of segregation along an ethnic category can contribute to the electoral success of an ethnic party. The argument presented here incorporates both demand- and supply-side considerations in explaining the success of ethnic parties. To reflect this, the following sections examine the link between segregation and ethnic party success for voters and political parties.
4.2.1 Voter incentives
That voters can be mobilized on the basis of ethnic identities is by now an established intuition on the literature on political parties (Riker 1962; Bates 1974; Olzak
1983; Posner 2004; Chandra 2004). In the past, scholars have shown how parties raise the salience of ethnic issues and identities among the electorate by casting minor incidents under a communal light (Brass 1997), by igniting pre-electoral violence (Wilkinson
2004), by emphasizing solidarity among co-ethnics (Hansen Blom 2001) and even by influencing voters through rumor and suggestion (Thachil 2011). However, for the most part, this literature has focused only in party strategies to raise the short-term salience of ethnic issues and identities. Here, I argue that political parties can enduringly raise the salience of its preferred ethnic category vis-à-vis other potentially viable categories by violently inscribing an ethnic divide in the spatial layout of an urban landscape. I present two arguments to support this claim.
118 First, I contend that high levels of segregation along an ethnic category following riots increases the ‘visibility’ of an ethnic divide.59 This argument builds on the insight that the visibility of ethnic markers determines which cleavage will be the most relevant for social interactions and political life (Van der Berghe 1997; Hale 2004; Chandra 2006;
2012). In general, visible attributes are those that can be ascertained through superficial data sources, such as name, speech, physical features, and dress (e.g., a name can provide insight into an individual’s religion). Yet, visibility tends to increase with the number of sources that contain information about an attribute or with the congruence of an ethnic category with important exogenous factors. Territorial concentration constitutes one of the most important factors contributing to the greater visibility of an ethnic category
(Bates 1974; Hechter 2000; Hale 2004).
This line of reasoning echoes Hawley’s (1944) argument that strong concentrations of ethnic minorities – implied by high levels of ethnic segregation – causes the group’s peculiarities to stand out in clear contrast to the traits of the majority.
In turn, this may arouse negative feelings towards them among the majority population because they are perceived as internally cohesive out-group, fueling fears of a strange, ominous “parallel society” (Hawley 1944). Hawley’s argument is supported by various subsequent studies on the subject (Esser 1986; Jiobu and Marshall 1971; Lieberson 1961;
Taylor 1979; Van der Waal, de Koster, Achterberg 2013).60
59 Following Chandra (2006), I refer to ‘visibility’ in the sense that “some information about an individual’s ethnic identity categories – and the categories to which she does not belong can be obtained through superficial observation. 60 A second version of this argument holds that interethnic contact diminishes racial prejudice and its corollaries under certain conditions – the so-called ethnic contact theory (Allport 1954; 1979; Tropp and Pettigrew 2005). This argument would also predict that high levels of ethnic segregation conduce to ethnic party success. These arguments stand in contrast to the ethnic threat theory, which claims that that high levels of ethnic segregation are expected to be accompanied by relatively low levels of support for anti- immigrant parties, as high levels of segregation indicate that ethnic groups hardly confront each other (Blalock 1957; Fossett and Kiecolt 1989; Huckfeldt and Kohfeld 1989).
119 Therefore, I contend that the concentration of an ethnic minority in certain localities of cities lends credibility to ethnic parties’ claims about the existence of an ‘us- them’ divide. In other words, it is easier for parties to mobilize the electorate around an ethnic category when there are sharp spatial lines separating the members of that identity from those that do not possess the require ethnic category. Such dynamics are particularly intense when these spaces of relegation for the ethnic minorities acquire the analytic characteristics of a ‘ghetto’ – such as now exist in riot-prone cities in India.61
Second, high levels of segregation along an ethnic category following riots also reduces uncertainty about which political party is better placed to provide them access to crucial public goods. My argument shares important ground with Chandra’s (2004) contention that voters operating under severe information constrains engage in ‘ethnic headcounts’ as a way to formulating voting preferences. Given such conditions, elections become akin to an ‘ethnic census’ in which parties mobilizing larger ethnic categories have the best chance of winning elections across institutional designs. Our conclusions are similar – parties mobilizing large ethnic categories win elections – but our explanations for this effect are different. Whereas Chandra emphasizes the individualized dispensation of state resources (‘patronage’), I contend that voters’ expectations of access to non-programmatic public goods (‘pork’) drive this tendency.
There are three main reasons to emphasize the distribution of public goods in this
61 Following Gayer and Jaffrelot (2012), I understand these as follows: an element of social and/or political constraint over the residential options of a given population; the class and caste diversity of these localities, which regroup individuals of different social backgrounds on the basis of ethnic or religious ascribed identities; the neglect of these localities by state authorities, translating into a lack of infrastructures, educational facilities, etc; the estrangement of the locality and its residents from the rest of the city; the subjective sense of closure of residents relative to the rest of the city.
120 regard. First, basic public goods often rank at the top of voter demands and dominate electoral rhetoric (Keefer and Khemani 2005; Khemani 2010). This suggests that most voters – those who do not stand a chance of receiving private transfers of goods in exchange for their electoral support – will prioritize the political party that offers them the best chance of accessing public goods. Indeed, as far back as the early 1960s, scholars noted that voters considered their Member of the Legislative Assembly (MLA) not as a legislator or even representative, but as a reliable intermediary: “He is there to divert the benefits in the direction of his constituents” (Bailey 1963, p. 25). This also explains why politicians need to exclude certain social categories from their mobilization efforts in the first place: given the existence of limited public resources, electors cast their vote with a view towards preferential treatment.62 They know that the delivery of a public good to their constituency will also inevitably mean its denial to another. Therefore, they want politicians to be clear about not just who they will benefit in power but also who they will discriminate against.
Accordingly, there is also widespread evidence that politicians in India use their discretionary power to target public goods to their target voters and deny them to their opponents (Reddy and Seshadri 1972; Planning Commission 2003; Singh, Gehlot, Start and Johnson 2003). Wilkinson (2006) points out that studies done on major Centrally
Sponsored Schemes (CSSs) administered through the states have consistently found that many recipients of small scale infrastructural projects (such as housing, latrines, and wells) are chosen on the basis of political affiliation. Yet, this does not necessarily imply
62 I thank Henry Hale for raising this point.
121 that such goods will be delivered. Many projects are abandoned after the elections and those that are eventually delivered stand out for their ‘poor quality’ (Wilkinson 2006).63
Finally, the intrinsic qualities of non-rivalry, non-excludability and lack of reversibility of public goods renders them blunt instruments for attracting or mobilizing voters (Vaishnav and Sircar 2012). For example, if the government builds a public school in an urban locality, this will benefit all residents of the area whether they are supporters of the party in power or not. Therefore, politicians will often face difficult choices about the most efficient way to distribute ‘pork’ across constituencies.
However, in systems operating under the logic of ethnic headcounts, voters who do not possess the target ethnic category can be easily identified as ‘opposition voters.’64
Parties can thus assume that this faction’s support is out of reach for them, and, it is not worth directing public funds to constituencies that have significant percentages of such non-co-ethnics. In turn, the provision of public goods to electoral constituencies that are homogenous on a party’s target ethnic category stands out as a particularly effective mobilization strategy.65 Specifically, politicians can ensure that the largest number of
63 Moreover, he notes that politicians will frequently begin projects before elections as a way of signaling their intentions to voters but they will then abandon these projects after the elections, with the consequence “that a village or ward may have a foundation stone but no bridge, or a tube well but no power to run it” (Wilkinson 2006, p. 7). 64 This follows the intense debate between scholars who argue that politicians will prioritize redistribution to their ‘core’ supporters and authors who contend that resources will be targeted to ‘swing’ voters (see, for example, Cox and McCubbins 1986; Dixit and Londregan 1996). Yet, I argue that it does not make sense to apply this framework to ethnic parties because they generally operate under a zero-sum logic, dividing the electoral into those who possess the target ethnic attribute and those that do not. While an ethnic party can receive the support from voters that do not possess the target ethnic attribute, their electoral strategy is primarily aimed at courting only those voters who possess it. 65 To be sure, my point is not that ethnic homogeneity is the only factor determining party choices about redistribution. Previous authors have also associated it with levels of socio-economic development, the degree of electoral competition and the existence of bureaucratic autonomy of the state prior to the enlargement of the franchise (Kitschelt and Wilkinson 2007). Yet, to the extent that the relationship between ethnic homogeneity and public goods provision is considered “one of the most powerful hypothesis in political economy” (Banerjee, Iyer and Somanathan 2005, p. 639), constituency homogeneity plays a key role in party decisions about redistribution strategy and, in turn, in shaping electoral outcomes.
122 their potential voters benefits from the good, therefore maximizing their distribution of public goods as campaign expenditure. At the same time, this strategy produces a self- sustaining and reinforcing tendency because voters in highly homogeneous constituencies will also recognize the benefits of supporting the party mobilizing the largest ethnic category. Specifically, by voting for a party mobilizing a large ethnic category, they are increasing their chances of access to crucial public goods.
In fact, there is already ample evidence that ethnic homogeneous communities in multiethnic societies enjoy higher levels of public goods provision than their heterogeneous counterparts (Alesina, Baqir and Easterly 1999; Banerjee, Iyer and
Somanathan 2005; Habyarimana et al. 2007). Studies of redistribution in India, too, suggest that politicians in power target ‘pork’ to ethnic homogeneous constituencies.
Betancourt and Gleason (2000) show that districts with a higher proportion of both scheduled castes and Muslims receive lower inputs in health and education. Banerjee and
Somanathan (2001) find evidence linking ethnic heterogeneity and poor public goods provision to underlying political incentives – districts that are ethnically fragmented are also likely to be politically fragmented, with elections in these districts having a larger number of contestants and a smaller vote share for the winning party. Finally, the Sachar
Committee report (2006, p. 23) points that there is a clear and significant inverse link
Muslim spatial segregation following riots and the availability of public infrastructures:
Poor roads and lack of proper transport, sanitation, water, electricity and public health facilities pervade Muslim concentration areas.
123 To conclude, then, I argue that high levels of segregation along an ethnic category creates powerful incentives for parties to target public goods to constituencies with the largest number of their target ethnic voters. This, in turn, generates among voters the expectation of being favored as part of a party’s ‘core’ constituency, resulting in greater levels of popular support in homogeneous constituencies along a matching ethnic category. Ultimately, this self-sustaining and reinforcing tendency contributes to the long-term success of an ethnic party.
4.2.2 Party incentives
As we saw above, ethnic homogeneity at the constituency level enables political parties to distribute public goods to their target ethnic category more efficiently than they would if co-ethnics were spread out across heterogeneous constituencies. In addition to this, the accentuation of segregation along an ethnic category also contributes to ethnic party success in two other important ways.
First, it helps parties better calibrate the deployment of other electoral strategies, such as the provision of social services or even the production of pre-electoral ethnic violence (Thachil 2011; Brass 1997; Wilkinson 2004). For example, high levels of constituency ethnic homogeneity provide parties and their supporters discernible markers about ‘friendly’ and ‘enemy’ zones during violence (Chandhoke 2009; Berenschot 2011).
Others (Robinson 2005; Thomas 2015) point out that the increasing ‘ghettoization’ of
Muslims in urban Indian consolidates other everyday forms of domination by the majority community: “Indeed, the reorganization of urban space in the wake of such
124 horrifying riots could permit more effortlessly the production and maintenance of inequitable procedures for containing violence by the state” (Robinson 2005, p. 55).
Second, ethnic homogeneity also enables parties to spend fewer resources at election-wide level than if they simply bought votes on an individualized basis across heterogeneous constituencies (Stokes 2009; Vaishnav and Sircar 2012). This is because it is easier to target potential voters if they are concentrated in clearly identifiable constituencies, than spread out across a city. Moreover, my argument holds even when there is no or deficient distribution of public goods after elections. The expectation of access of a public good is sufficient to drive this tendency of individuals to converge around large ethnic majorities.
4.2.3 Conclusion
To sum up, then, I argue that high levels of segregation along an ethnic category can contribute to the electoral success of an ethnic party. From the point of view of voters, ethnic unmixing enduringly increases the visibility of religious identities and reduces uncertainty about which political party is better placed to provide them access to crucial public goods. For parties, high levels of Hindu-Muslim segregation enable them to deploy electoral strategies more efficiently, wasting little resources on the delivery of goods and distributing fewer resources to voters than if voters were dispersed across heterogeneous constituencies.
Finally, it is worth stressing that the goal of this chapter is to establish the
125 relationship between a contextual variable – ethnic segregation – and the success of ethnic parties. Therefore, I do not claim to provide an explanation for the multiple motivations that may underlie a voter’s preference for one ethnic party over another, ethnic or not. Rather, my aim is simply to show that, for the reasons enunciated above, ethnic unmixing contributes to the success of ethnic parties.
4.3 Hypotheses
This section presents a series of hypotheses to test the argument advanced by this chapter to account for the success of the Hindu right in India. Specifically, I link high levels of Hindu-Muslim segregation to the success of two parties mobilizing India’s
Hindu majority. Throughout this empirical analysis, I use the degree of ethnic homogeneity at constituency level as a local measure of segregation. This formulation yields the following primary hypothesis:
H1: An increase in Hindu homogeneity at the constituency level has a
positive and significant effect on the Hindu right’s electoral success.
A sub-hypothesis was then formulated to determine if support for the Hindu right remains constant across the whole range of Hindu percentage in an electoral constituency. This hypothesis examines whether there is a positive relationship between
Hindu demography and Hindu right success even when Hindus represent an overwhelming majority in a constituency.
H2: The likelihood of BJP success increases as Hindu population also
increases across the whole range of Hindu percentage in an electoral
126 constituency.
Previous scholarship on redistribution in India also has also found that the delivery of public goods varies with the party system (Chhibber and Nooruddin 2004).
Concretely, the authors show that states with two-party competition provide more public goods than states with multiparty competition because they must build cross-cleavage coalitions. Similarly, Wilkinson (2004) argues that the incentives for religious polarization are greatest in those seats where electoral races are closest – the assumption being that low competition implies an expectation of Hindu right success. According to this view, its success may thus be a result of the party system rather than the degree of ethnic homogeneity. To explore the relationship between the ethnic homogeneity, the party system and the Hindu right, I thus formulated the following hypotheses:
H3a: The level of electoral competitiveness has a negative and significant
effect on the Hindu right’s electoral success.
H3b: The level of electoral competitiveness has a more significant effect
than ethnic homogeneity on the Hindu right’s electoral success.
The general model above was then expanded to include other covariates to test both for the accuracy of the models and their influence on Hindu right vote share relative to Hindu population. Previous work provides convincing evidence that lower status groups are less likely to support the Hindu right (Jaffrelot 1998; Kumar 2013). I thus expect that two constitutionally recognized disadvantaged categories – the Scheduled
Castes (SC) and the Scheduled Tribes (ST) – have a negative impact on support for the
127 Hindu right. Previous scholarship also highlights a negative relationship between socio- economic status and Hindu right vote (Thachil 2011; Harriss 2005; Falcao 2006). Yet, recent evidence suggests this trend may be changing as more poor voters support the
Hindu right (Thachil 2011; Jaffrelot and Kumar 2015). I thus expect low socio-economic status to have only a weak to negative effect on support for the Hindu right.
H4a: An increase in the percentage of SCs and STs in an electoral
constituency has a negative and significant effect on the Hindu right’s
share of votes across electoral contexts.
H4b: An increase in the percentage of poor voters in an electoral
constituency has a negative and significant effect on the Hindu right’s
share of votes across electoral contexts.
Finally, I include two other demographic variables that have been associated with
Hindu right support: percentage of females in an electoral constituency and age of voters.
In regards to the former, previous research points out that women are less likely to support the BJP (Chhibber & Verma 2014). In contrast, recent years have seen growing interest in the Hindu right’s popularity among India’s youth. For example, Kumar argues that the electoral success of the BJP in the early 1990s can be credited to its strong support amongst the urban poor (2013). These insights yielded the following two hypotheses:
H5: An increase in the percentage of females in an electoral constituency
has a negative and significant effect on the BJP’s share of votes across
128 electoral contexts.
H6: An increase in the mean age of voters in an electoral constituency has
a negative and significant effect on the BJP’s share of votes across
electoral contexts.
4.4 Methods
To examine these hypotheses, I draw on an original, subnational dataset of electoral constituencies in seven of India’s largest cities: Mumbai, Delhi, Kolkata,
Bangalore, Ahmadabad, Chennai and Hyderabad.66 Table 1 presents the demographic indicators for these seven cities. There are three reasons for this sample selection. The first is practical: cities afford us a relatively stable, evidence-rich and quantifiable unit of analysis. They also comprehend a large number of municipal, state and national constituencies (Table 2).
Second, these cities vary in three factors that have been previously associated with the salience of ethnic categories, namely urban growth, size of minority community, history of communal violence and an ethnically divided labor market. Finally, these cities are distributed across India’s national territory and present different socio-demographic characteristics. This case selection seeks to establish the internal validity of the hypothesis while also maximizing the potential for generating external validity.
66 At the moment, I am still collecting religious demographic data for Mumbai. Therefore, this data was not included in the present analysis.
129
MALE POPULATION HINDUS MUSLIM SC/ST FEMALES CITY ILLITERACY (2011) (%) (%) (%) (%) (%)
Mumbai 12,478,447 65.99 20.7 7.5 45.9 8.7
Delhi 11,007,835 81.7 12.9 15.9 46.5 9
Chennai 4,646,732 81.3 9.4 16.9 49.7 7.9
Bangalore 8,425,970 79.4 13.4 13.2 48.5 8.9
Hyderabad 6,809,970 70 27 4.9 48.9 14.4
Ahmadabad 5,577,940 83 13.8 11.9 47.3 9.6
Kolkata 4,496,694 74.7 23.3 4.5 38.4 7.7
India - 80.5 13.4 25.2 44.4 17.8
Table 4.1: Hindus, Muslims, SC/ST, Females and Male Illiteracy in India’s Seven Metro Cities (Census of India 2011)
The dependent variable in this analysis is Hindu right electoral success. I used two measurements for the dependent variable: (1) the combined vote share of the BJP and the
SS in an election; and (2) a dummy variable measuring the success or failure of a candidate from one of these two parties (1 = success; 0 = failure). The purpose of these two measurements is to capture both detailed information about the relationship between the independent and dependent variables in the analysis and to examine whether this translates into actual electoral success. While I analyze these indicators separately, I expect strong support for the hypothesis advanced in this chapter to involve a positive relationship between ethnic homogeneity and Hindu right success in both indicators.
In general, municipal wards fit neatly into state assembly constituencies that, in turn, fit into national parliamentary constituencies. This enables us to aggregate
130 demographic variables from the bottom up to test the relationship between ethnic context and ethnic party support at the three different levels of government. However, the small number of national parliamentary constituencies in these seven cities (Table 2) does not enable us to test the relationship at the largest level of aggregation. State election results were collected from the website of the Election Commission of India (ECI) and municipal election results were collected from the respective State Election
Commission’s (SEC).
City State Municipal Constituencies Assembly Constituencies National Constituencies
Mumbai Maharashtra 227 36 6
Delhi Delhi 272 70 7
Chennai Tamil Nadu 200 16 3
Bangalore Karnataka 198 10 4
Hyderabad Andhra Pradesh 150 15 2
Ahmadabad Gujarat 64 14 2
Kolkata West Bengal 141 17 4
Total - 1252 178 28
Table 4.2: Electoral Constituencies in India’s Metro Cities (2015)
To measure the level of electoral competitiveness, I use Laakso and Taagepara’s
2 (1979) formula for the effective number of parties: n = 1/S(si) , where n is the effective number of parties and s is the percentage of votes received by party i. There are two potentially relevant dimensions of competition: (1) constituency competition; (2) election-wide competition. While the overall level of competition in an election might shape expectations about access to goods, parties and voters must also take into account
131 the level of competition within constituencies. Given the emphasis given to local contextual factors in my account, I expect constituency competition to be particularly important towards explaining electoral outcomes. For this reason, I used two measures of electoral competitiveness corresponding to the two levels of competition: For the first measure, I collected the vote shares for all parties running in each electoral constituency at each level of government in each of these seven cities. For the second measure, I collected vote shares for all parties running in a municipal or assembly election in each of these seven cities.
The key challenge facing this analysis was the measurement of religious demography at the constituency level. Indeed, due to a scarcity of reliable and publicly available religious subcity data, existing quantitative studies of religious demography in
India are limited to the district level, the city level or the state level (Varshney 2002;
Wilkinson 2004; Chandra 2004). To remedy this shortcoming, I examined a novel source of data made available by recent ‘open government initiatives’ by the Election
Commission of India (ECI) as well as advances in big data analytics.
Specifically, the ECI now publishes online the electoral rolls for Indian voters.
The rolls contain information about voters’ names, age, polling booth, ward (i.e., municipal constituency), assembly and parliamentary constituency. This constitutes a breakthrough for studies of religious demography in India because the religious connotation of names in the ‘electoral rolls’ can be exploited as a source of data for individual religious background. They thus enable us to create estimates of religious demography at the constituency level. In the past, several studies have extracted names
132 from electoral rolls by hand for this purpose (Field et al. 2008; Galonnier 2012).
However, whereas these authors coded names by hand – a consuming task both in terms of resources and time – I used computer software to extract the data from the rolls and examine them using a name-matching algorithm specifically developed for this purpose
(Susewind 2014).
This open-source computer algorithm probabilistically matches the names of
Indian voters to religious communities based on a reference list extracted from the website indiachildnames.com.67 This algorithm outputs the most plausible categorization and all potential alternatives as well as a certainty index that allows for flexible accuracy thresholds. Accuracy tests demonstrated that the algorithm’s positive predictive value
(i.e., the rate of accurate positive matches) stood at 95% while its negative predictive value (i.e., the rate of accurate negative matches) stood at 99%. Overall, 5% of names could not be classified and were discarded (Susewind 2014: 9). The algorithm also possesses the advantage of scalability that enables researchers to examine voter lists across a vast number of electoral constituencies.68
In addition to these fine-grained estimates of religious demography, I also collected data for four other social indicators – caste, socio-economic status, gender and
67 A database that links roughly 23,000 names to gender and the religious categories Hindu, Muslim, Sikh, Christian, Jain, Parsi, and Buddhist. 68 The main disadvantage of this name-matching algorithm is that it fails to capture important variation both within and across religious categories. On the one hand, the algorithm does not capture intra-faith divergences, e.g., between Sunnis and Shias or between Christians and Protestants. In some cities, these divergences are more salient that those between main religious categories (e.g., Lucknow in the case of Sunnis and Shias). On the other hand, there is a possibility that individuals matched to a particular religious community on the basis of their names may not in fact be practicing members of that community. Yet, I contend that for this possibility does not invalidate the present analysis because it does not concern individual preferences but the contextual effect of Hindu demography on electoral outcomes.
133 mean age (Table 2). I used two measures to examine the relationship between low caste status and support for the Hindu right. The variable (pLowCaste) combines Census data on scheduled caste (SC) and scheduled tribe (ST) population. Both SCs and STs have been the most excluded and discriminated groups, they have been afforded similar constitutional rights in the form of affirmative action policies. However, this yields very few observations at the state level since Census ward units cannot always be aggregate to higher levels of electoral competition. To overcome this challenge, I created a dummy variable for a constituency’s reservation category (1 = seat reserved for ST/ST; 0 = general seat). I expect reservation to have a negative effect on the Hindu right’s success.
In regards to socio-economic status (pPoor), the Census does not include a specific question on income or consumption. Instead, this project uses data on male illiteracy as a blunt measure of socio-economic status, as done by previous studies
(Vithayathil & Singh 2012; Kumar 2013). Indeed, due to female exclusion from schooling among many middle and upper class households, female literacy fails to correlate strongly with socio-economic status in the Indian context.
Finally, I collected voter information included in the electoral rolls to measure the last two demographic variables: gender and mean age. The variable pFemale represents the percentage of female voter in an electoral constituency and the variable mean_Age constitute the mean age of the voters listed in the electoral rolls for each constituency.
These hypotheses were tested using two models: 1) Logit model to examine the
134 relationship between the dummy variable for Hindu right success and the independent variables; and (2) an Ordinary Least Squares (OLS) regression, run as a linear probability model, to quantify the percentage effect of independent variable(s) on the BJP’s vote share. The electoral rolls for Mumbai, Ahmedabad and Hyderabad did not include information about the corresponding municipal ward. Therefore, the final municipal dataset includes data from four Indian cities: Delhi, Kolkata, Chennai and Bangalore; whereas the final state dataset includes data all seven cities. Observations at the lower level of measurement, i.e., the municipality, that did not match the state level were also dropped from the dataset. These observations correspond to municipal constituencies that do not fully fit within state constituencies as well as those state constituencies that contain more than one municipal level constituencies. Lastly, other municipal level data is also missing due to problems scraping the information from electoral rolls or missing
Census data. Taken together, these factors explain why there is a significantly smaller number of observations at the municipal level than the total number of municipal wards in these seven cities reported above.
4.5 Results
The statistical analysis demonstrated a strong, significant association between the percentage of Hindus in a constituency and the Hindu right’s success across both municipal and state constituencies (Table 3). This finding was robust to additional covariates and was also the most significant effect in both models. Overall, the two OLS models explains more than 50 percent of the variation in electoral outcome which seems fairly substantial given that it does not include specific campaign issues or party
135 platforms. These results provide strong support for the main hypothesis advanced in this
chapter: support for the Hindu right increases with the number of Hindus in a municipal
and state constituency.
(1) Mun_Logit (2) Mun_OLS (3) State_Logit (4) State_OLS
Hindu Pop. (%) 5.07210*** .35014*** 6.99991*** 0.32337***
Constituency -0.43506** -0.09038*** .33728 -0.01756 Competition Election -0.97870 -0.01636 -1.91550*** -0.19583*** Competition
Low Caste (%) -0.17781 -0.01444 . .
Poor (%) 1.91084 0.07032 . .
Reservation -0.52580 -0.04012* -1.77610** -0.06409
Female (%) -5.03748 -0.53628 33.34757* 1.51595**
Mean Age 25.59942** 1.58065*** -48.00134 -3.71620***
Number of Obs. 415 414 159 150
R2 0.5886 0.5362
Note: * p < .05, ** p < .01, *** p < .001; constant not displayed.
Table 4.3: Cross-Sectional Analysis Results I Table 4.3: Regression Analysis Results
For a detailed examination of these conclusions, I then examined the municipal
data for four cities – Delhi, Kolkata, Bangalore and Ahmedabad.69 Three findings were
revealed: Ahmedabad had a very strong, positive and equally significant association of
69 Hyderabad was excluded from the municipal level analysis due to inexistence of ward level estimates of religious demography for the city. The data did not render a complete analysis of Hindu percentage for Chennai due to multicollinearity and/or insufficient observations. The meanAge variable was also missing for Ahmedabad.
136 +21.0%; Bangalore had a strong, positive and significant association of +12.2% higher
Hindu right electoral success for every 10% increase in Hindu population (p-value 0.000,
R-squared 0.2451); and Delhi had a weak but positive association of 4.7% (p-value
0.083, R-squared 0.0891). Finally, the data showed a positive, yet insignificant, relationship between the size of the Hindu population in a constituency and Hindu right’s success in Kolkata.
The sub-hypothesis H2 was tested by running regressions across the range of
Hindu population values to determine both effect and significance.70 This test showed that the “breaking point” at which Hindu population is no longer a statistically significant factor in determining municipal outcomes is 77 percent. This same test was also used to evaluate whether or not the effect of X1 on outcome varies or remains constant as Hindu population increases. The range of regressions that could be tested in this manner was limited (due to insufficient observations and/or multicollinearity at low values of Hindu population) to 53 ≤ X1 ≤ 77. Across this range, the effect was found to vary from a low of 4.5% to a high of 11.3%. The variation does not appear to trend up or down; support for the BJP first dips down and then rises (Figure 3).
To test Hindu population <53 >77, three additional regressions were run with the
BJP vote share as the dependent variable instead of the dummy variable. All three regressions exhibit a strong and significant positive association between Hindu population and Hindu right vote share, even when Hindu population is very high and
70 Since the tests were numerous, I did not include any output.
137 almost ‘homogenous.’ For the general effect, vote for the Hindu right increases by 4.8% for every 10% increase in percentage of Hindu population; when Hindu population > 77 vote for the Hindu right increases by 4.5%; when regressing for Hindu population <53, however, the effect is stronger, at 5.8%.
12.0%
10.0%
8.0%
6.0%
4.0% % Effect on Outcome* 2.0%
0.0% 50 55 60 65 70 75 80 % X1 Ethnicity * (Approximate % increase in likelihood of ethnic party winning for every 10% increase in X1 population).
Figure 4.1: Effect of Hindu Population on Hindu right’s Support (tested from 52 < X1 <78)
Overall, then, the results at municipal level suggest that: i) Hindu population plays a positive role, at the municipal level, in the ethnic party’s electoral outcomes whenever the Hindu population composes 77% or less of the voting district’s general population; ii) it is likely that Hindu population is still significant at high levels (i.e. >77%) but the evidence is weaker and still open to some degree of interpretation; iii) there is a strong and significant positive association between Hindu population and Hindu right vote share, even when Hindu population is very high and almost homogenous. This analysis
138 thus lead us to reasonably conclude that the data supports the main hypothesis advanced by this paper.
The analysis also provided considerable support for the remaining hypotheses. As expected, the level of electoral competition has a negative effect on the Hindu right’s success (yet, this was not supported by the state level logit model). Interestingly, however, the significance of this relationship varies with the level of government. At the municipal level, the intra-constituency competition is negative and significantly correlated to the Hindu right’s success, whereas election-wide competition has an insignificant effect. The situation is reversed at the state level: intra-constituency competition is not significant, whereas election-wide competition has a negative and significant effect on the Hindu right’s success.
This result is intuitive given the power asymmetries in the organizational structure of local and state administration. At the municipal level, corporators are important problem solvers of first resort, whereas the office of the mayor is largely a symbolic position. In contrast, the members of the state legislature (MLA’s) have limited power to attract local infrastructure and implement policy relation to that of a state’s Chief
Minister. This asymmetry is particularly acute if the Chief Minister is from another political party. Therefore, for voters, the election-wide result plays greater role in shaping their voting preferences than at the municipal level.
139 Crucially, the negative and significant effect of electoral competition on the
Hindu right support does not mitigate the relationship between ethnic homogeneity and the dependent variable. In fact, Hindu population continues to have a strong and significant effect on Hindu right success when both types of competition are included in the model. Therefore, the analysis refutes H3b thus increasing our confidence about the link between ethnic homogeneity and Hindu right success.
In my analysis, neither the percentage of low caste/tribal voters nor the percentage of poor voters had a significant effect on support for the Hindu right. As expected, the effect was negative for the former and weak but positive for the latter. This conveys the success of the Hindu right in winning over poor voters in recent elections. Nonetheless, the analysis does not imply that this is a stable trend. On the other hand, the variable
‘reservation’ had a negative and significant effect on Hindu right success in two models, suggesting that the Hindu right does less well in constituencies that are reserved for
SC/ST candidates. The percentage of females was found to have a negative, significant effect on the Hindu right’s success only at the state level. Finally, my analysis of age data revealed a mixed picture: mean age is shown to have a positive and significant effect at the municipal level, but a negative and significant effect at the state level. These effects were particularly strong in the logit models. These results may be interpreted as evidence that voters change preferences per the electoral level. Concretely, proximity to the elected representative may play a larger role at the municipal level than the economic aspirations that are associated with youth support for the Hindu right.
140 4.5.1 Alternative Explanations
The argument that rising levels of Hindu-Muslim segregation contributes to the success of ethnic parties contrasts with traditional approaches to the triumph of the Hindu right in India. One prominent strand of scholarship stresses the promotion of communal violence in the run-up to elections as a brutal, albeit efficient, means of emphasizing interreligious cleavages over intra-Hindu caste differences (Wilkinson 2004; Dhattiwala and Biggs 2012; Blakeslee 2013; Arcand and Chakraborty 2013; Iyer and Shrivastava
2015). While the measurement of communal violence is a topic of endless controversy, anecdotal data suggests that pre-electoral violence is not a sine-qua-none condition for the Hindu right’s success (Varshney 2002; Wilkinson 2004; Thachil 2011). For example, communal violence was conspicuously absent from the electoral campaign leading to
Hindu right’s historic victory in 2014. Similarly, scholars have pointed out that a strategy of violence promotion does not always spell electoral success for the Hindu right. For example, the agitations of the late 1980s and early 1990s were repudiated by voters in
Uttar Pradesh and Madhya Pradesh (Jaffrelot 1996). Moreover, there was no major outbreak of Hindu-Muslim violence in the seven cities under scrutiny since the 2002
Gujarat riots. On this basis, we can rule out this hypothesis without having to include a control variable for pre-electoral violence in the ensuing statistical analysis.
Another group of authors link the Hindu right’s success with its ability to capture the concerns and aspirations of India’s elites (Chhibber 1997; Blom Hansen and Jaffrelot
1998; Huber and Suryanarayan 2016). This argument has much to recommend itself.
Data from the National Election Study (NES) conducted by the Centre for the Study of
141 Developing Societies (CSDS), shows that the BJP draws considerable support from the upper castes and middle class voters.71 Likewise, previous authors highlight the Shiv
Sena’s success in capturing the aspirations of Mumbai’s elites (Blom Hansen 2001;
Shaikh 2005). The combined votes of middle classes and the caste elites also have the capacity to tip elections in the Hindu right’s favor, particularly in the urban areas where they both conflate. A focus on the voting preferences of India’s socio-economic elites yields the following two hypotheses:
H7a: An increase in the percentage of middle class voters at the
constituency level has a positive and significant effect on the Hindu right’s
electoral success.
H7b: An increase in the percentage of upper caste voters at the
constituency level has a positive and significant effect on the Hindu right’s
electoral success.
I calculated the percentage of middle class and upper caste voters as the percentage of the total population minus the previous estimates of SC/ST voters and poor voters, respectively. My estimators thus yield the relationship between the non-low caste and non poor voters and support for the Hindu right. This is a reasonable assumption given that the literature has varying definitions of the middle class. In fact, some authors link the success of the BJP to a ‘neo middle classes’ made up of Other Backward Classes
(OBCs) that are relative newcomers to the urban economy (Jaffrelot 2014).
71 Though are divergent views about the exact definition and size of these middle classes, estimates range from 30 million to approximately 300 million people. Even using the most generous estimates of the group’s size, the middle class comprises less than 30 percent of the population (Deutsche Bank 2010).
142 A final strand of scholarship emphasizes the role of organizations affiliated to the
Hindu right in promoting its electoral success. These arguments fall into two categories.
The first argues that interreligious associational networks of civic engagement, such as business associations, professional organizations or neighborhood clubs, mitigate the potential for ethnic conflict (Varshney 2002). According to this argument, the less organized networks that cut across ethnic boundaries, the easier it is for politicians to polarize religious communities. The second explanation contends that grassroots affiliates has enable the Hindu right to make unexpected inroads among India’s lower-caste, tribal and indigenous voters (see Katzenstein 1979; Gupta 1982; Blom Hansen 2001; Shaikh
2005; and Thachil 2011). Social provision enables the Hindu right to engage in nontransactional mobilizational activities, such as organizing cultural events and influencing voters through rumor and suggestion, without alienating its core elite constituents. This discussion yields the following two hypotheses:
H8a: Lower levels of interreligious civic life has a positive and significant
effect on the Hindu right’s electoral success.
H8b: Higher levels of social service provision through grassroots
affiliates of the Hindu right has a positive and significant effect on the
Hindu right’s electoral success.
I used two measures for interreligious civic life. First, I collected the results on questions on individual participation in civil society from the Indian Human
Development Survey (IHDS) 2011-12 for each of the cities under scrutiny. I then
143 calculated the median from the sample and inserted this city-wide figure for all the observations from the respective city. However, there are two potential problems with this measurement: (1) though randomly sampled, the number of respondents to the survey was very small for each city (ranging from 124 in Hyderabad to 518 in Delhi); and (2) the
IHDS only examines civic life in a quantitative, rather than in a qualitative sense. Yet,
Varshney (2002) argues that civic life is conducive to communal peace only when organizations cross ethnic boundaries. Thus, to increase confidence over my conclusions,
I collected data for a second measure of interreligious social capital.
Concretely, I counted the number of members in either the Hindu nationalist
Rashtrya Swayamsevak Sangh (‘National Volunteer Corps’) or the shakhas
(‘neighborhood branch’) associated with the BJP, the SS or the RSS on each city on the social network ‘Facebook.’72
To measure social service provision by grassroots affiliates in the Sangh Parivar, I collected region-wide figures on welfare projects from the RSS’s Official 2014 Seva
Disha report, obtained on the RSS’s website online. These figures present the total number of projects undertaken by the Rashtriya Seva Bharati, the registered non-profit organization that coordinates social services in the fields of education, healthcare, social organization and self-reliance, particularly among urban slums (Chidambaran 2012). The
Seva Disha report divides the country into 38 units. These units vary greatly in
72 ‘Shakha’ is a term used to denote the daily gathering of all Swayamsevaks of a particular neighborhood at a common meeting place for one hour. The daily programs of a Shakha consist of physical exercises, patriotic songs, group discussions on various subjects, particularly related to politics and Hindu nationalism.
144 geographical extent: e.g., Gujarat is present as one unit in the report, whereas West
Bengal is divided into North and South Bengal. With Delhi’s exception, these units also do not match the borders of the cities under scrutiny in this chapter. Thus, it is impossible to ascertain, from the figures provided in the report, the number of projects that take place exactly in each city. This instructs us to use caution in our interpretation of these data. At the same time, the Seva Disha figures provide the best available data for social service provision in India (Thachil 2011; Chidambaran 2012). Moreover, one could argue that the sheer disparities between regions can provide insight into the distribution of welfare projects by the grassroots affiliates in the Sangh Parivar. To cite one example, in
2009, Gujarat – a region that includes the city of Ahmedabad – had 722 Seva Bharati projects, whereas South Karnataka – a region that includes the city of Bangalore – had
9662 projects. This significant disparity suggests that the Sangh Parivar undertakes more welfare projects in Bangalore than in Ahmedabad.
145 (1) Mun_Logit (2) Mun_OLS (3) State_Logit (4) State_OLS
Hindu Pop. 6.64786*** 0.32154*** 10.94430*** 0.51417*** (%)
Middle Class 3.60171 0.53472*** . .
Upper Caste 2.03482 0.05070 . .
IHDS 97.97209*** 6.72575*** 113.78040*** 9.37071***
Hindu 50.74688*** 4.17222*** 35.37364*** 2.89884*** Organizations
Seva Disha -0.00097*** -0.00006*** -0.00142*** -0.00012***
Number of 763 618 159 150 Obs.
R2 0.6519 0.6917
Note: * p < .05, ** p < .01, *** p < .001; constant not displayed.
Table 4.4: Cross-Sectional Analysis Results II
Using the same statistical analysis employed previously, I tested the relationship between the Hindu right’s electoral success, the degree of Hindu homogeneity at the constituency level and these alternate explanations. The results confirmed our previous conclusions (Table 4). High levels of Hindu homogeneity have a positive and significant effect on the electoral success of the Hindu right. Again, this finding was robust to additional covariates. Overall, the explanatory power of the model increased with the inclusion of variables accounting for alternative explanations (R2 = 65% and 69%, respectively). This analysis thus lead us to confirm that the data supports the main hypothesis advanced by this paper.
146 My analysis also provided strong support for H8a linking interreligious civic life and Hindu right electoral success. Specifically, participation in organizations was found to have a positive and significant correlation with support for the two parties across all models. The provision of welfare by grassroots affiliates in the Sangh Parivar was also found to have a significant effect on Hindu right success but, contrary to the expectations, this effect was negative. However, as noted before, this data may be biased. Therefore, more detailed city-level data on social service projects would be necessary to provide an accurate test of its effect on Hindu right success. Finally, my analysis demonstrated that, as expected, the percentage of middle class and upper caste voters has a positive impact on Hindu right success but this relationship only yielded a significant value for middle class voters in the municipal OLS test.
4.6 Conclusion
In this chapter, I have argued that high levels of Hindu-Muslim segregation contribute to the success of Hindu right.73 For voters, high levels of segregation along communal lines enduringly increases the visibility of religious identities and reduces uncertainty about which political party is better placed to provide them access to crucial public goods. For parties, homogeneous constituencies enable them to deploy other electoral strategies more efficiently, wasting little resources on the delivery of goods and distributing fewer resources to voters than if voters were dispersed across heterogeneous constituencies. In this way, I argue that the consolidation of electoral constituencies in the
73 The term ‘oversized coalition’ is the common term employed by the literature to describe the success of parties mobilizing a larger than necessary winning coalition (Hershey 1973; Serritzlew, Skjaeveland and Blom-Hansen 2008; Stepan, Linz and Yadav 2011; Van der Veen and Laitin 2012; Ferree 2012). Therefore, I use the terms ‘large’ and ‘oversized’ interchangeably throughout this chapter.
147 wake of Hindu-Muslim violence has contributed to the long-term success of the Hindu right.
The statistical analysis reported here provided support to the main hypothesis advanced by this chapter: Hindu-Muslim segregation has a positive and strong effect on the electoral success of the Hindu right increases. This analysis also showed that there is also a strong and significant positive association between Hindu population and Hindu right vote share even when Hindu population is very high and almost homogenous. This finding is robust to additional covariates, as well as control for unobserved variation at the municipal, state and national constituency level. The analysis also showed that electoral competition has a negative and significant impact on Hindu right success (albeit the relevant arena of competition varies with the level of government). In turn, participation in intrareligious civic associations has a positive and significant impact on the success of the BJP and the SS.
This chapter contributes to the existing literature in two important ways. First, it provides an explanation for the success of parties mobilizing oversized ethnic coalitions.
Most existing studies of ethnic electoral competition assume that parties mobilizing minimum winning coalition stand the best change of electoral success. These studies fail to explain the empirical fact that oversized ethnic coalitions exist. By examining the success of the Hindu right in India, this chapter shows that the likelihood of success of parties mobilizing oversized ethnic coalitions increases with the degree of ethnic homogeneity at the constituency level.
148 Second, this chapter offers an explanation for this relationship that emphasizes the provision of public goods in ethnic homogeneous constituencies. While considerable attention has been dedicated to the causal mechanisms linking homogeneity to high levels of public goods, there is still a paucity of systematic empirical research into its electoral implications. This chapter thus contributes to this important literature by showing that public goods provision in ethnic homogenous constituencies contributes to the success of ethnic parties.
To illustrate the mechanisms underpinning this relationship, in the following chapter, I draw on a detailed study of India’s most riot prone city: Ahmedabad. The chapter employs extensive archival research along with interviews with riot victims, activists, journalists and politicians to illustrate two main points: first, the voters seek public goods and this has contributed to the Hindu right’s success in the city; second, the ruling Hindu right has systematically targeted public goods to Hindu-majority areas while denying them to the Muslim-majority areas. In this way, I argue that that severe and protracted ethnic riots are an effective, albeit brutal, means for producing ethnic unmixing that then contributes to the long-term electoral success of ethnic parties.
149 Chapter Five
Making Space for Votes: Unmixing and Dominance in Ahmedabad
The Ram Janmabhoomi movement was the event that transformed politics in the state. -- Aakar Patel, Executive Director of Amnesty International India, 2012
By instituting this power relationship through the means of habitat, the ghetto has become a spatialized device of power. -- Charlotte Thomas, What Juhapura Tells Us About Being Muslim in Modi’s India, 2015
5.1 Introduction
How does ethnic unmixing contribute to the enduring success of an ethnic party?
This chapter undertakes a close study of Ahmedabad – the capital of the western state of
Gujarat – to illuminate the link between riots, ethnic unmixing and the enduring success of an ethnic party. I argue that the BJP has relied heavily on spatial tactics, which included violently rewriting the Ahmedabad’s social geography along communal lines, to dominate the city’s politics since the late 1980s. Specifically, I highlight three electoral effects of religious unmixing: (1) it has increased the visibility of the Hindu-Muslim divide vis-à-vis other social categories; (2) it has consolidated the link between religious identities and access to crucial public goods; and (3) it has helped the BJP deploy other electoral strategies more efficiently than if its target voters were spread out across heterogeneous constituencies. In this way, I argue that religious unmixing following recurrent and intense communal riots since the mid-1980s has contributed to the BJP’s enduring success in Ahmedabad.
150 In important ways, Ahmedabad embodies the tensions at the heart of this dissertation. First, though the city was relatively peaceful in communal terms during the pre-independence period, Hindu-Muslim violence has surged since the late 1980s. Major riots broke out in 1985, 1990, 1991, 1992, and 1993 (Chart 5.1). By 1995, according to the Varshney-Wilkinson dataset on Hindu-Muslim violence in India, Ahmedabad had already the second largest number of riot deaths in India. After the 2002 Gujarat pogrom, the worst episode of Hindu-Muslim violence in independent India, Ahmedabad has become the most affected Indian city in terms of Hindu-Muslim violence.74
18
13
9
5 4 4 3 3 3 3 2 1 1 1 1
1950 1951 1969 1970 1971 1973 1982 1984 1985 1986 1987 1990 1991 1992 1993
Figure 5.1: Number of Riots in Ahmedabad 1950-1993 (Source: Varshney-Wilkinson dataset)
Second, Ahmedabad has seen a profound accentuation of Hindu-Muslim segregation over the last decades. To be sure, the two communities have always occupied discrete spaces due to the traditional residential morphology known as the pol (Shani
74 While there is considerable debate about the exact title to describe the wave of destructive communal assaults that broke out in Gujarat from 27 February 2002, most scholars refer to it as a pogrom, that is, an assault by one community on another in which the government turns a blind eye or even supports the attackers (Spodek 2010).
151 2007).75 These residential clusters were then reproduced in the newer parts of the city with most housing societies identifying with a specific caste and religious community
(Chandhoke 2009).76 However, these enclaves were small and located in close proximity to each other producing a mosaic-like urban structure. In fact, until the late 1980s, different religious communities ‘lived in a rather promiscuous way’ within each locality in Ahmedabad (Jaffrelot and Thomas 2012, p. 45).
Since the 1980s, however, there has been a dramatic segmentation of Ahmedabad along communal lines (Mahadevia 2002; Shani 2007; Chatterjee 2008; Chandhoke 2009;
Jaffrelot and Thomas 2012). The most emblematic symbol of this transformation is the emergence of what residents and scholars commonly describe as ‘Muslim ghettos’ over recent decades.77 This slide from a mosaic-like urban structure to the nearly-complete ghettoization of Muslims in Ahmedabad, corroborated by the previous statistical analysis, constitutes a dramatic reversal in patterns of Hindu-Muslim segregation.
Thirdly, even though Gujarat’s politics always had a conservative bent, the Hindu right was not traditionally a major political player in the city. In the first decades after independence, the Congress kept the city in firm grasp. Then, between 1985 and 1990, the Congress vote collapsed and the BJP surged. In 1987, the BJP took control of the
75 A pol is a housing cluster – generally a lane – in which a homogenous group of individuals reside along the lines of caste and religious community. 76 Scholars typically divide Ahmedabad’s social geography into three distinct areas: (1) the Walled City (the old core of the city); (2) the industrial belt in the eastern suburbs of the city; and the Western Suburbs, across the Sabarmati river. 77 Following Gayer and Jaffrelot (2012), I use the term ‘ghetto’ to describe spatial formations that have five fundamental characteristics: “an element of social/or political constraint over the residential options of a given population; the class and caste diversity of these localities, which regroup individuals of different social backgrounds on the basis of ethnic or religious ascribe ascribed identities; the neglect of these localities by state authorities, translating into a lack of infrastructures, educational facilities, etc.; the estrangement of the locality and its residents from the rest of the city, due to lack of public transportation as well as limited job opportunities and restricted access to public spaces beyond the locality; the subjective sense of closure of residents, related to objective patterns of estrangement from the rest of the city.”
152 Ahmedabad Municipal Corporation (AMC) for the first time.78 In 1989, the BJP won its first national parliament (Lok Sabha) seat from Ahmedabad. Likewise, between 1985 and
1990, the party’s vote share in the city in state elections (Vidhan Sabha) jumped from
19.70 percent to 44.79 percent. Crucially, the BJP’s rise in Ahmedabad has also been remarkably enduring. Since 1995, the BJP has recurrently pulled over 50 percent of the vote and won two-third majorities of seats in the city (Graph 5.2).
100.00 90.00 80.00 70.00 60.00 50.00 40.00 30.00 20.00 10.00 0.00 1980 1985 1990 1995 1998 2002 2007 2012
Constituencies Won % Share of Vote %
Figure 5.2: BJP’s electoral performance in State Elections in Ahmedabad (1980-2012)
Ultimately, then, Ahmedabad affords us a typical, yet extreme, case for studying the link between riots, segregation and votes.79 As we shall see in the following sections,
78 The BJP ruled the municipal body continuously until 2000, when, despite winning a majority of seats across Gujarat’s six municipal corporations, it lost control of both the Ahmedabad and the Rajkot corporations. The BJP regained control of the two cities in 2005 and has been in power ever since (Desai 2016). 79 Here, one must clarify the distinction between ‘typical and ‘extreme’ case studies. Whereas the former exemplifies a usual cross- case relationship, the latter demonstrates unusual values of the dependent or the independent variable relative to some univariate relationship (Seawright and Gerring 2008). In the words, the former is a case that lies somewhere along the regression line, whereas the former is an observation that lies far away from the mean of a given distribution. Crucially, as Gerring (2007) reminds us, ‘typical’ does not mean a case with average scores on the relevant dimension. Instead, if there is a strong positive association between the
153 these three transformations are part of the same causal chain. Given that the relationship between these three variables is well explained by the existing model of the long-term repercussions of ethnic riots, Ahmedabad then provides ideal conditions for exploring the system of interacting parts that transforms ethnic unmixing into long-term ethnic party success.
Towards this aim, I draw on extensive qualitative evidence collected during two stints of fieldwork in Ahmedabad (between June-July 2014 and November-December
2015). In the following section, I briefly outline the context for the BJP’s employment of ethnic unmixing in Ahmedabad. I then show how these three phenomena – communal riots, religious unmixing and BJP success – have evolved alongside each other each since the mid-1980s in Ahmedabad. Next, I illustrate the mechanisms linking religious unmixing to the BJP’s enduring electoral success in Ahmedabad. The following section then examines alternative explanations for the rise and enduring success of the BJP in
Ahmedabad from the late 1980s onwards. Finally, I conclude with some thoughts about how the implications of this chapter for theory and policy on ethnic conflict.
5.2 Setting the Context: The Hindu Right in Ahmedabad
The Sangh Parivar has been active in Gujarat for several decades.80 At the beginning of the century, its prospects in the state looked particularly promising, given that Gujarat’s feudal agrarian structure and conservative character of social life were
dependent and independent variables, then a case with similar (high, low, or average) values on the crucial variables may be more typical than cases whose values lies closer to the mean (Gerring 2007; Seawright and Gerring 2008; Beach and Pederson 2016). Ahmedabad is thus presented here as an onliner case, albeit one with extreme values on both the dependent and independent variables. 80 The first RSS shakha (branch) in Gujarat opened its activities in 1938 (Ghassem-Fachandi 2012)
154 understood to provide a fertile ground for Hindu mobilization (Shah 1998). However, until the 1960s, Ahmedabad was not known as a communally-sensitive city.81 There were some violent conflagrations in the pre-independence period; yet, for the most part, these did not take a communal coloration.82 Crucially, there was no Hindu-Muslim riot at
Partition and few Muslims left the city to Pakistan during this period (Jaffrelot and
Thomas 2012).83
Following independence, the state unit of the Jana Sangh, the forerunner of the
BJP, came into existence in Gujarati shortly after the party’s birth in 1951 (Shah 1998).
The Jana Sangh’s leadership, and its main base of social support, were drawn from sections of the urban middle class and upper castes, Brahmins, Vanias and Rajputs
(Kshatriyas). According to the 1931 census, these groups castes formed 4 per cent, 3 per cent and 5 per cent of the population, respectively (Shani 2007). In the urban setting of
Ahmedabad, Brahmins traditionally held white-collar jobs, Vanias were merchants and generally wealthier than Brahmins and Rajputs (Kshatriyas) were descendants of the ruling families who ruled Gujarat in the past (Shani 2007).
While socially superior, these groups were inferior in numerically terms. Thus, in the 1950s and 1960s, the Jana Sangh’s performance was poor, even amongst these
81 During the first half of the twentieth century, Ahmedabad was an important center for both the Indian struggle for independence and labor movement. Such prominence owes greatly to Mahatma Gandhi, who settled in the city between 1917 and 1930. In 1920, he founded in Ahmedabad the Majoor Mahajan Sangh (lit, Textile Labor Association or TLA), one of India’s most prominent labor unions. 82 During the mass protests against the Rowlatt Act in 1919, textile workers burned down 51 government buildings across the city in protest at a British attempt to extend wartime regulations after the First World War. In the 1920s, textile workers and teachers went on strike, demanding civil rights and better pay and working conditions. In 1930, Gandhi initiated the Salt Satyagraha from Ahmedabad by embarking from his ashram on the Dandi Salt March. The city's administration and economic institutions were rendered inoperative in the early 1930s by the large numbers of people who took to the streets in peaceful protests, and again in 1942 during the Quit India Movement. 83 However, communal incidents were reported in both 1941 and 1946.
155 groups, and it could hardly secure even one per cent of the votes (Shah 1998). During this period, its leaders tried to rally popular support by organizing public meetings, dealing with issues related to hostility towards Muslim and the degeneration of Hindu culture, but these rarely attracted a crowd of more than one hundred persons (Shah 1998). Indeed, as late as 1968, a book on Ahmedabad’s urban history emphasized that “the most tragic problem of modern Indian political history – the communal problem – has fortunately played only a small role in the history of Ahmedabad” (Gillion 1968).
Ironically, the first major outbreak of communal violence in Ahmedabad took place a year later. The violence lasted a week but left 660 people dead and 6742 houses destroyed (Chandhoke 2009). These riots exhibited many of the elements of political design that were to become customary in subsequent episodes of Hindu-Muslim violence, such as the selective targeting of Muslims houses (Desai 2011). There is also evidence that, despite their limited duration, the 1969 communal riots triggered an incipient migration of Muslims out of Hindu-majority areas in search for safety (Chandhoke 2009).
Interestingly, the Jana Sangh’s first electoral successes in Ahmedabad came after the riots: in 1972, the party won its first state assembly seat in the city (constituency number
68: Ellis Bridge) and in 1975 it increased this margin by one (constituency numbers 70:
Shahpur and 75: Khadia). These constituencies were located in western and central
Ahmedabad, areas typically inhabited by affluent and high caste Hindus.
However, the newly-formed BJP failed to build on these early successes in the early 1980s. In fact, in both the 1980 and 1985 state elections, the party won only one
156 seat (75: Khadia) in Ahmedabad. By contrast, the Congress (I) party emerged revitalized in these elections, winning 10 out of a total of 12 seats in the city in both elections. The
Congress’s triumph owed to its forging of a new electoral alliance that came to be known
KHAM – an acronym for Khastriyas, Harijans (Dalits), Adivasis (tribals) and Muslims.
These groups represented 55 per cent of Gujarat’s population (Shani 2007). Under this new electoral strategy, the Congress (I) began to support plans to extend reservations of government jobs and university places for lower and backward castes and selecting candidates from these groups. Thirteen out of the twenty-two ministers in the party’s cabinet in 1980 were from the KHAM group (Shani 2007); fourteen out of the twenty
Congress (I) cabinet in 1985 were members of KHAM (Spodek 1989).
The political success of the KHAM alliance had the paradoxical effect of pushing some groups among the middle classes towards the BJP. Specifically, the political assertiveness of lower and backward castes was a source of concern for the Patidars
(Patels), who comprised 12 per cent of the state’s population (Shani 2007). Originally a peasant caste (Shudras), the Patidars had gradually strengthened their social position and taken positions of dominance both within the government and the professional classes
(Shani 2007). They thus felt threatened by the growing numbers of educated and professionally trained Dalits, particularly in Ahmedabad where many had already joined the urban middle class (Shani 2007). This antagonism reached a peak during the anti- reservations caste riots that erupted in Ahmedabad in December 1980 and again in
February 1985.
157 In the early 1980s, then, electoral competition in Ahmedabad was thus becoming sharply polarized around socio-economic lines with the BJP representing the social and economic elites and the Congress (I) projecting itself as the advocate of the oppressed groups. Yet, as is evident from the 1980 and 1985 electoral results, this type of polarization was not favorable to the BJP in purely numerical terms. As we shall see next, the contradiction between its core constituency and the need to expand its popular support base, prompted the BJP to carve out, quite literally, its electoral space in
Ahmedabad.
5.3 Riots, Segregation and Votes: The Politics of Unmixing in Ahmedabad
In the early 1980s, the BJP in Ahmedabad was at a crossroads. On the one hand, it was increasingly becoming the party of choice of the socially superior yet numerically inferior group of individuals who felt anxious about the social and political achievements of the lower and backward castes. On the other hand, the electoral success of the KHAM strategy made it clear to the BJP that it would not be able to win power without expanding its popular support base to members of the lower and backward castes.
The means at its disposal for achieving such delicate balance were dreadfully limited. Encompassing programmatic and clientelistic linkages were out of the question since those were already being employed by the Congress (I) and besides they were likely to alienate the BJP’s elite core constituency. Ahmedabad was also an unfavorable setting for a welfare-based service given that the poor had already been actively mobilized electorally both on class and caste lines. As late as February 1981, Schedule Castes (SCs)
158 medical students had managed to mobilize to their struggle 7,500 mill workers who observed a two-day strike (Shani 2007). The remaining option for the BJP was violence: it enabled the BJP to bring lower caste Hindus under its fold without sacrificing its ideological and programmatic loyalty to the Ahmedabad elites.
Yet, a central contention of this dissertation is that the intensification of Hindu-
Muslim riots in Ahmedabad between 1985 and 2002 was not only a short-term electoral strategy. Rather, recurrent and severe communal violence provided the BJP with a means to establishing itself as a major, long-lived political player in Ahmedabad. To support this argument, I now illustrate the close relationship between communal violence, Hindu-
Muslim unmixing and the BJP’s enduring rise in Ahmedabad.
5.3.1 1985-2002: The Making of the Communalized City
Even after the 1969 riots many Hindus and Muslims continued to live in mixed neighborhoods in Ahmedabad (Chandhoke 2009). Until the 1980s, if a social cleavage dominated Ahmedabad’s social geography, then it was the division between the affluent and upper-caste western areas (on the left bank of the Sabarmati river), the crowded
Walled City and the impoverished and neglected Industrial belt (to the east of the city)
(Jaffrelot and Thomas 2012). The 1970s also saw a proliferation of slums, particularly in eastern Ahmedabad and its periphery, where Dalits and Muslims stayed in close proximity. Moreover, until the mid-1980s, Muslims were often able to buy residential and commercial properties in western Ahmedabad, and upper-middle-class Muslims even bought residential properties in Hindu neighborhoods (Desai 2011).
159 The 1985 riots burst this pattern of residential settlement in Ahmedabad.
Interestingly, the violence began in February as caste-based violence on the issue of reservation for the scheduled and backward castes. State Assembly elections were then held on 5 March, in which the Congress (I), as noted before, won comfortably. On 11
March, the new cabinet was sworn in. Then, on 19 March, a group of Hindus unexpectedly attacked Muslims in Dariapur (Walled City) killing three people and injuring eight (Spodek 1989). This incident triggered a sustained bout of Hindu-Muslim rioting that lasted until July, leaving 275 people dead, thousands injured, tens of thousand homeless and a loss of property and trade estimated at Rs. 2,200 crores (US$ 1.75 thousand million) (Spodek 1989). Professor Juzar Bandukawala, a retired physics professor whose house was destroyed during the 2002 progrom, told me in an interview in December 2015 that the scale of the violence is today often underestimated:
The riot is 1985 was very bad, very cruel. The only difference between 1985 and 2002 is that then the press was suppressed.
Following the riots, there was extensive migration of both Hindus and Muslims from mixed localities into parts of Ahmedabad dominated by their own community
(Shani 2007; Desai 2011). Residents of the Muslim-majority Naginapol reported that they were attacked by residents of neighboring Hindu-majority Vadigam, shouting ‘Muslims should go,’ and ‘This is a Hindu Raj – come out and bow down’ (Shani 2007, p. 113). In some cases, localities became physically divided as the exclusive enclave of either
Hindus or Muslims:
160 After the 1985 riots the Bapunagar area (in eastern Ahmedabad) was partitioned. The local residents call one part ‘Pakistan’ and the other ‘Hindustan’ or ‘diamond-nagar’. (…) By the end of the 1990s only Muslims lived in Morarji Chowk, which until 1985 used to be a mixed locality of both Hindus and Muslims (Shani 2007, p. 127).
In a bid to prevent further segregation along communal lines, the Congress- dominated Municipal Corporation passed the Prohibition of Transfer of Immovable
Property and Provision for Protection of Tenants from Eviction from the Premises in
Disturbed Areas Act 1986 (Breman 2004). The legislation prevented a member of one religious from community from selling his property to a member of another religious community if the property lay within what was considered a ‘disturbed areas’ (one where violence would be likely to take place during communal violence) (Desai 2011).
However, in practice, the measure failed to stem the tide of unmixing between Hindus and Muslims. In fact, today, some argue that, by institutionalizing state interference into property deals, the Act has provided legal cover for communal segregation.84
Following the 1985 riots, the Sangh Parivar also began to exploit Hindu-Muslim segregation more explicitly to build Hindu unity. Billboards proclaiming Hindu- dominated areas as ‘Hindus rashtras,’ usually erected by the local chapters of the VHP, started appearing across Ahmedabad (Kumar n.d., cited by Jaffrelot and Thomas 2012).
Similarly, after the riots, the VHP began to circulate “a map of (Ahmedabad) with saffron and green markers (the former signifying the Hindu and the latter the Muslim area) and
84 Specifically, the district collector’s power to restrain any property transaction that he construes as a violation of the Act has been used as a tool to prevent Muslims from buying property in Hindu-majority areas (Khan 2012). At the same time, the sale of Muslim property in riot-affected areas continues to take place through underhand deals that involve losses on the side of Muslim sellers. Since winning state power in 1995, the BJP has added even more areas to the list of disturbed areas in Ahmedabad, fueling speculation that the Act is being used to further consolidate Hindus and Muslim segregation.
161 pressurized these families to evacuate their properties and relocate to Muslim-dominated areas” (Kumar n.d., cited by Jaffrelot and Thomas 2012).
This trend was further accentuated by the escalation of communal violence at the turn of the decade.85 In 1990, large-scale riots again broke out in Ahmedabad triggered off by L.K. Advani’s political-religious march through north India to support the construction of a temple on the site of the Babri Masjid in Ayodhya (i.e., Ram Rath
Yatra).86 Between April-December 1990, there were 1400 communal incidents in
Ahmedabad, which left officially 224 people dead and 775 injured. Between January-
April in the following year, nearly 120 riots took place in Ahmedabad, leaving 38 people dead and 170 injured.
As expected, recurrent communal violence during this period produced a radical accentuation of Hindu-Muslim segregation. According to previous research, “the few isolated pockets of mixed housing colonies were finally destroyed in 1990” (Yagnik and
Sheth 2011, p. 243).
The demolition of the Babri Mosque in Ayodhya in December 1992 again triggered large-scale riots in Ahmedabad. Groups of 200 to 1,000 men, took to the street with tridents, swords, spears and petrol bombs, shouting ‘Musulman ko Kato Maro’ (lit.,
Cut and Kill the Muslims) and attacking all buildings that were not marked as owned by
Hindus (Jaffrelot and Thomas 2012). This time, however, the communal violence was not
85 Specifically, Hindu-Muslim riots broke out in Ahmedabad in 1986, 1987 and 1989 (Chandhoke 2009). 86 The procession began in Somnath, Gujarat on 25 September and stopped in Ahmedabad on the next day.
162 restricted to the Walled City and eastern Ahmedabad but spread also to low-income areas in western Ahmedabad, including Vejalpur and Juhapura (Desai 2011). In total, 292 persons were killed and countless property lost during the violence (Chandhoke 2009).
For Father Credic Prakash, a human rights activist who worked for 42 years in the city I interviewed in November 2015, the aftermath of the Babri Masjid demolition marked a new era of self-segregation between Hindus and Muslims in Ahmedabad:
The demolition of the mosque created a lot of ghettoization. This was the first time that among the Muslims there was a feeling that we need to be together to protect ourselves.
As with previous riots, this wave of ethnic unmixing contributed to the electoral successes of the BJP. In 1995, the party not only won 11 out of the 12 assembly constituency seats in Ahmedabad but also its local elections. In the late 1990s, Hindu-
Muslim confrontations once again erupted in the Walled city (curfew was imposed in
Dariapur, Kalupur, Saraspur, Gheetkanta, Dagbarwad and Vadigam in 1999) and in the industrial area (Karanj, Gomtipur, Shalam and Jamalpur) (Jaffrelot and Thomas 2012).
5.3.2 After 2002: Consolidating Spatial Communalism
Against this backdrop, the 2002 pogrom may be thought of as the final nail in the coffin of interethnic propinquity in Ahmedabad. The violence was triggered by an incident on 27 February involving Hindu kar sevaks (lit., volunteers) returning from
Ayodhya and Muslims in Godhra, Gujarat. Amidst the chaos, four trains coaches caught fire, killing 59 people, including women and children. The next day, groups of Hindus began a systematic and brutal attack against Muslims across the state. In Ahmedabad
163 alone, 700 Muslims lost their lives and almost 7,000 were rendered homeless (Chandhoke
2009).
As before, incidents of violence were more likely to occur in integrated neighborhoods (Field et al. 2008). Specifically, the neighborhoods of Naroda Gaon and
Naroda Pattiya, the sites of the most brutal attacks in Ahmedabad, used to be mixed communities of Hindus and Muslims. In the early hours of 28 February, an armed mob of several thousand attacked the Muslim residents killing at least 65 people within minutes
(Human Rights Watch 2002). Homes and religious sites were systematically looted and burned using gas cylinders (Human Rights Watch 2002).
While there was widespread physical violence, the prime focus of rioters in 2002 seemed to be Muslim property. According to Ghassem-Fachandi (2009), an anthropologist who witnessed the violence in Ahmedabad, rioters continued to rampage even after Muslims had evacuated their houses:
From all sides people were throwing stones at a compound in front of us, from the roofs of adjacent houses, from the street, from behind a large tree decorated with hundreds of ‘Hindu’ flags, which suggested there was another adjacent temple. I asked if there are any Muslims inside. Another man said ‘They already left last night’ (Ghassem-Fachandi 2009, p. 39).
Crucially, he points out that the rioters were also not interested in making material profit out of these attacks. He was particularly struck by identifying individuals of humble backgrounds destroying expensive items, such as scooters and loudspeakers, that
164 they may never be able to afford in their lifetime. He concludes: “No one kept any item.
It was about destruction in a dramatic fashion” (Ghassem-Fachandi 2009, p. 41-42).
Even sacred sites and historical monuments were not immune from the attack. In the city of Ahmedabad alone, fifty-five religious structures were attacked on the first day of violence (Ghassem-Fachandi 2009). In Isanpur, a famous 500-year-old mosque, which was an Archeological Survey of India monument, was destroyed with the help of cranes and bulldozers. Similarly, the tomb of the famous seventeenth-century Urdu poet Shah
Wali Gujarati, located just outside the city’s main police headquarters, was destroyed on
2 March and a make-shift Hindu temple with a saffron flag was briefly put in its place
(Spodek 2010). On 3 March, that temporary shrine was leveled and by 5 March, the site was permanently paved over. Furthermore, as Rowena Robinson (2005) points out, contrary to previous episodes of Hindu-Muslim riots, Muslim places of worship that were destroyed in 2002 have not been rebuilt.
Finally, there is also extensive evidence that members of the Sangh Parivar and the BJP encouraged attacks against Muslims and their property. For example, one BJP
Member of the Legislative Assembly (MLA) was seen leading an attack that destroyed
Salatnagar, a mixed Dalit-Muslim slum in Isanpur. According to a local social worker, he had long-term strategic political incentives for doing so: “He is against Salatnagar; he is not getting votes from here and he wanted to build a new colony at this place five years ago” (Berenschot 2013, p. 161-162).
165 As in other major communal riots in India, the violence triggered a search for safety in numbers that prompted Muslims to relocate to areas where they were already in large numbers (see for example Mahadevia 2002; Chandhoke 2009; Desai 2011; Jaffrelot and Thomas 2012). Similarly, walls and gates have been erected around Muslim ghettos to separate them from nearby Hindu colonies. But perhaps the most conspicuous change post-2002 is that, this time, middle-class Muslims have also joined the migration.
This transformation is conspicuous in Juhapura, where roughly half of the city’s
Muslim population resides today (Desai 2011). Prior to the 2002 violence, Juhapura already had already started to become a Muslim ghetto (Jaffrelot 2014). Yet, its residents were in the lower socio-economic brackets of the city’s Muslim community (Jaffrelot and
Thomas 2012). Following 2002, more affluent members of the community – including judges, businessmen, professors and doctors – started to look for safety in Juhapura too, after realizing that Muslims living in middle-class pockets such as Paldi, Judges
Bungalow and Gulbarg Society were also targeted.87 Moreover, the flow of affluent
Muslims to these spaces of relegation seems to have gathered pace with the appearance of private schools and hospitals that cater to their needs. As one resident put it to me in an interview taken in December 2015:
We will never move out of Juhapura. Even the elite doesn’t want to go back because if something goes wrong, here is the safest place to be.
87 For Jaffrelot and Thomas (2012), Juhapura is a Muslim ghetto in the true sense of the word because it is a bounded, isolated and marginalized sociospatial formation that gathers people purely on the basis of religion, irrespective of class and other social factors.
166 Finally, in line with the previous examination, the ghettoization of Muslims after
2002 coincides with a long period of BJP rule in Ahmedabad. In fact, the BJP has not only won the state election immediately after the pogrom in 2002 but also the two following elections (2007 and 2012). In all three elections, its winning margin has remained comfortable: in 2002 and 2007, the party won 10 and 8 out of 12 seats in
Ahmedabad, respectively; and in 2012, the BJP won 13 out of 15 seats in the city, thereby increasing its share of constituencies from both 2002 and 2007.
As a result, Narendra Modi, who took over as Chief Minister shortly before the riots and left in 2014 to prepare his successful bid for Prime Minister of India, has become the longest serving head of government in Gujarat. Meanwhile, the Congress has not been able to pull above 30 per cent of the vote, its presence restricted to minority- dominated seats in the city (i.e., Dariapur and Danilimda). In sum, then, the 2002 pogrom represented the culmination of the causal chain between communal riots, Hindu-Muslim segregation and the BJP’s enduring success in Ahmedabad.
5.4 The Mechanisms of Unmixing: Explaining Enduring Success
So far, I have demonstrated how recurrent and intense communal riots have shifted patterns of Hindu-Muslim segregation that, in turn, have contributed to the BJP’s enduring success in Ahmedabad. The next step in this examination illustrates the mechanisms that converted ethnic unmixing into resilient electoral support for the BJP.
Specifically, I argue that communal unmixing has benefited the BJP in Ahmedabad in three crucial ways: (1) it has increased the visibility of the Hindu-Muslim divide vis-à-vis
167 other social categories; (2) it has consolidated the link between religious identities and access to crucial public goods; and (3) it has helped the BJP deploy other electoral strategies more efficiently than if its target voters were spread out across heterogeneous constituencies.
5.4.1 Visibility
As discussed in the previous chapter, previous scholarship has pointed out that the visibility of an ethnic marker correlates strongly with the polarization of political life along that ethnic category (van der Berghe 1997; Hale 2004; Chandra 2006; 2012).
Moreover, existing research already suggests that strong concentrations of ethnic minorities – implied by high levels of ethnic segregation – are a crucial factor in raising the visibility of an ethnic category (Hawley 1944; Bates 1974; Hechter 2000; Hale 2004).
In line with these insights, I hereby illustrate how the ghettoization of Muslims in
Ahmedabad since the mid-1980s has enabled the BJP to enduringly raise the visibility of its target ethnic category (i.e., Hindus), thus contributing to its lasting success in the city.
Indeed, over recent decades, the boundaries between Hindu- and Muslim- dominated areas have multiplied – either because these neighborhoods have sharply consolidated around pre-existing roads (Jaffrelot 2014) or due to the erection of walls and gates that keep the religious Other out of sight.88 It is now customary for Ahmedabad’s residents to designate these boundaries as ‘borders’ and refer to Hindu-majority areas as
88 The confining of Muslims to clearly restricted areas is particularly evident in Juhapura, which is located seven kilometers away from the city center. To the east, the area is surrounded by an extremely busy junction, and is separated from neighboring Hindu dwellings by barbed wire and ditches that were built after 2002 (Thomas 2015). To the north, Juhapura is encased by buildings finished in 2013 that house the city’s police and public servants. To the south, water treatment facilities ensnared the neighborhood. Finally, to the west, Juhapura opens on a four-lane axis, the Sarkej Road, leading outside of the city.
168 ‘Hindustan’ and Muslim-majority areas as ‘Pakistan’ or ‘Little Pakistan.’ Rickshaw drivers of different religious backgrounds often take different routes through the city, avoiding localities and neighborhoods dominated by the religious Other (Desai 2011). In one recent incident, an official police report identified a Muslim-dominated housing enclave in Vatva as ‘Pakistan.’ Commenting on the issue, police inspector Barkat Ali
Chavda said:
The writer wrote ‘Pakistan’ as the address in FIR (First Information Report) because it was dictated to us by the city control room. This is quite normal here. Those who live there also identify themselves as residents of Pakistan (Times of India 2015).
This new segregation between Hindus and Muslims is not only a matter of separation but also antagonism, since Pakistan is India’s ‘enemy’ (Chandhoke 2009;
Desai 2011). In fact, BJP politicians in Ahmedabad are known to drawn upon this association during their speeches on the campaign trail. A case in point is the 2005 municipal elections, during which Modi campaigned on Ahmedabad’s streets using inflammatory anti-Muslim slogans such as ‘Bring an end to Congress’s Mughal rule.
Vote for the BJP,’ which attacked Congress’ Muslim candidate who was the mayor of the city during 2003-2005 (Desai 2011, p. 119). In another high-profile case, Amit Shah, the current President of the BJP, and an MLA for the neighboring constituency of Naranpura, referred to Juhapura as ‘mini-Pakistan’ (Khan 2012b).
The BJP’s efforts to reproduce Ahmedabad’s communalized space into enduring political salience have also included more explicit attempts to claim and rename the city’s
169 space as Hindu. In a bid to obliterate the city’s Islamic history, the Sangh Parivar has pushed for the renaming of Ahmedabad as ‘Karnavati’ after a Hindu king, Karan Dev, who is said to have established a settlement in the proximity of the modern city in the 11th century.89
Similarly, many Hindu-majority localities in Ahmedabad are now claimed to be part of Hindu Rashtra by boards that multiply around election period (Figure 5.1). These boards read, for example, ‘Welcome to Hindu Rashtra’ or ‘You are now entering
Saraspur village of Hindu Rashtra’ (Jaffrelot and Thomas 2012). In April 2017, with the
2018 state elections already in mind, boards have once again sprung up across
Ahmedabad in localities such as Krishna Nagar, Meghaninagar, Shahibaug and Anupam cinema areas of Ahmedabad (Sinha 2017).
89 The Ahmedabad Municipal Corporation (AMC) first passed a resolution in May 1990 and forwarded to the state government to re- baptize the city as Karnavati. When it returned to power in the AMC in October 2000, the Congress passed another resolution (246) that canceled this. Three days after that law minister Ashok Bhatt staged a dharna outside the AMC to protest the decision and demanded that the city be renamed Karnavati. But since then, the issue has not been settled (Times Of India). Similarly, during the BJP-Shiv Sena rule in 1996, Bombay was renamed Mumbai to honor a local goddess.
170
Image 5.1: Hindu Rashtra board in Ahmedabad. The board translates as: “Welcome to Meghaninagar locality, Of Naroda district, Of Karnavati metropolitan city, Of the Hindu Rashtra. Vishva Hindu Parishad, Secretary: Vasantbhai Patel, M: 9898703892, Bajarang Dal” (Source: Sinha 2017)
5.4.2 Access to Public Goods
In line with the argument outlined on chapter 4, ethnic unmixing also reduces uncertainty about which political party will provide voters access to crucial public goods.
Specifically, under the logic of ‘ethnic headcounts,’ ethnic unmixing creates two main incentives for strategic voters to support a party mobilizing the ethnic majority: it increases voters’ confidence about which party will win elections and it also provides them with information about which constituencies will receive a greater share of public goods (i.e., those dominated by the party’s target ethnic category). In this way, I argue that religious unmixing creates strategic incentives for Hindu voters, the demography majority in Ahmedabad, to converge around the party mobilizing the Hindu electorate,
171 i.e., the BJP.90 To illustrate this point, I now provide evidence of the BJP’s extensive use of ‘pork’ in Ahmedabad.
We may begin by pointing out that the BJP’s electoral formula in Gujarat has been founded upon a portrayal of Muslims as enemies and the party as the only political force capable of protecting the interests of the Hindus. This formula involves attempts to discredit the electoral opposition, particularly the Congress, for discriminating against the
Hindu majority in favor of the non-Hindu minority (Breman 2004). According to such narrative, the BJP is expected to materially reward the Hindu majority while also facilitating revenge against Muslims (Baxi 2002). For example, in a speech delivered on the campaign trail shortly following the 2002 carnage, Chief Minister Narendra Modi implicitly linked anti-Muslim violence to the social and economic advancement of
Hindus and BJP rule:
We are dubbed Hinduwadi because we have allocated Rs eight crore towards the development of Becharaji (a temple town). Is it our fault? Are we communal? (…) If Gujarat is to be developed then an economic system has to be developed where every child born in Gujarat gets educations, manners and employment. And for this, those who are multiplying population at a rapid rate (a veiled reference to the Muslim community) will need to learn a lesson (Outlook 2002).91
There is also extensive evidence that the Muslim community has done worse in recent years in Gujarat than in other states in India. According to the Sachar Committee
90 According to the 2011 census, 83% of the population in Ahmedabad is Hindu, 2.5% Jain, 13.8% Muslim and 0.72% Christian. 91 Since then, this speech has become infamous for Modi’s portrayal of refugee camps sheltering the Muslim victims of the riots as ‘baby-producing centers.’
172 Report (2005), Gujarat ranks 14th in terms of the proportion of Muslim children aged 6-
14 enrolled in schools, 7th in terms of Muslim poverty incidence (poverty incidence is 34 per cent for Gujarati Muslims, which is better than many states but almost double the state’s average of 18 per cent) and 11th in terms of outstanding amounts in bank savings.
The only indicator where Gujarati Muslims rank first among all Indian state is the contraceptive prevalence rate (58 per cent of couples of reproductive age practice some form of contraception).
Recent research has also revealed that Gujarati Muslims are least likely among all communities to get organized sector as well as salaried jobs and that the work- participation ratio for Hindus is 10 per cent higher than Muslims, suggesting better employment (Singh 2011). Most strikingly, in the five years between round 55 (1999-
2000) of the National Survey Sample (NSS) and round 61 (2004-2005), the unemployment rate among urban Muslims has increased from 18 to 52. According to the
61st NSS round, urban poverty among Muslims in Gujarat is 800 per cent higher than among high-caste Hindus and 50 per cent higher than among OBCs in the state.
In Ahmedabad’s communally divided space, the growing socio-economic marginalization of Muslims is amplified through space. In recent years, the AMC has invested significant amounts in developing the city’s public infrastructure. According to a senior town planner of the Ahmedabad Urban Development Authority (AUDA), 80 per cent of Ahmedabad’s 2002 Development Plan (DP) has been implemented, including zoning regulations, improved road networks, the construction of an innovative Bus Rapid
173 Transport System (BRTS), a massive redevelopment plan for the Sabarmati Riverfront, a
Slum Electrification Scheme, the creation of new green spaces and social infrastructure
(Raje 2013). There is also evidence that the AMC has allocated increasing amounts to improving healthcare (representing 10-12 percent of its annual budget) and currently has a wide network of 70 medical centers throughout the city consisting of family welfare centers, dispensaries, maternity homes and general hospitals (Ramani et al. 2005).
Yet, for the most part, these investments are concentrated on the Hindu-majority parts of the city, which enjoy good roads, thorough and constant supply of electricity, potable water, sewage lines and good transport links. In contrast, Muslim ghettos in
Ahmedabad such as Juhapura, Bombay Hotel and Maqdoomnagar stand out for their estrangement from the city center and neglect by municipal authorities. For example, transport links to Muslim-dominated areas are so poor that their residents cannot even afford to travel to work in other parts of Ahmedabad (Jaffrelot 2014). In these spaces of relegation, residents often complaint about inexistent or irregular water and electricity supply as well as the paucity of education and medical facilities. In some areas, this baffling contrast in access to public amenities between Hindu- and Muslim-majority localities is visible to the naked eye by looking across the wall that demarcates the boundary between the two communities. For a retired railway employee living in
Muslim-dominated Sajid Row Houses, there can only be one explanation for the existence of such constant and striking contrast:
What more can explain the reality than the fact that ours is a Muslim colony and theirs is not (Desai 2013)?
174 Finally, there is also evidence of political design and intentionality in the deprivation of public services to Muslim-majority areas across Ahmedabad. In Juhapura
– where there is no street lighting, gardens or parks, no transport links to the center, no public hospitals and public schools cover only 10 per cent of the educational needs of inhabitants (Thomas 2015) – there is a large police presence. Moreover, while there is poor water supply to the area, in February 2017, the AMC announced plans to build another sewage plant in Juhapura (Mehta 2017). There are already three sewage plans in the locality, which are the source of many respiratory and digestive illnesses as well as infiltrating the soil with toxic solutions (Thomas 2015). As a result, residents of Juhapura often keep their doors and window closed to avoid the polluted air released by the existing sewage treatment plants. Commenting on the decision, Congress councilor Haji
Asrarbeg Mirza, blamed the Corporation’s inability to find another area in the city to set up on its political leadership:
This is being done intentionally to target Muslims. Muslims here are forced to live in segregated localities like Juhapura and then made to suffer due to such decisions made by the BJP-ruled civic body (Ahmedabad Mirror 2017).
5.4.3 Other Electoral Strategies
Finally, ethnic unmixing also facilitates the deployment of other electoral strategies pursued by Indian political parties to recruit voters. In this regard, we may distinguish between four primary types of strategies frequently employed by parties: programmatic, clientelist, pre-electoral violence and welfare-based strategies. Since programmatic redistributive linkages address the population in general, there is not much
175 that we can say about it in the context of local ethnic unmixing. Moreover, we have already seen how ethnic unmixing has enabled the BJP to selectively target public goods to Hindu-dominated constituencies, while depriving Muslim-majority ones. Therefore, this final section focuses on the electoral implications of acute Hindu-Muslim segregation for the remaining electoral strategies: pre-electoral violence and social welfare provision.
Ethnic unmixing assisted the deployment of pre-electoral violence during the
2002 pogrom in at least two crucial ways. First, patterns of Hindu-Muslim segregation emerging from previous episodes of communal violence oriented the geography of anti-
Muslim violence in Ahmedabad. Indeed, previous research shows that, throughout
Gujarat, Muslims living in ‘mixed communities’ were hit the hardest (Human Rights
Watch 2003) and that Muslims were more likely to killed where they were a larger minority (Dhattiwala and Biggs 2012). This also fits with the previous description that
Muslim-majority areas such as Juhapura were largely by-passed by rioters, whereas
Muslim enclaves within Hindu-majority localities – such as Naroda Patia and Gulbarg
Society – were the sites of the deadliest massacres in Ahmedabad. This suggests that ethnic entrepreneurs used demographic context – namely, the presence a large Muslim minority – as an indicator of the degree of competition faced by the BJP in the forthcoming elections. In this way, ethnic unmixing in Ahmedabad helped rioters to selectively target areas where pre-electoral violence could be more efficiently deployed to promote the BJP’s short-term success.
176 Second, ethnic unmixing also provides rioters with specific combat advantages.
On the one hand, it is easier – and safer – to attack isolated minority enclaves in majority- dominated localities than when communities are dispersed in a mosaic-like pattern or concentrated in large ghettos. Indeed, such demographic imbalances are at the root of the security dilemma that triggers ethnic unmixing in the first place. As one riot survivor in
Juhapura told me, the Hindus saw him as ‘easy target’ because he was the only Muslim in his locality. On the other hand, increasing Hindu-Muslim segregation, and the ensuing concentration of Muslims in congested pockets, enables rioters to use less discriminatory weapons – such as throwing petrol bombs over a wall or making a gas cylinder explode inside a mosque (Human Rights Watch 2002; Chandhoke 2009).
Ethnic unmixing also provides specific benefits to parties relying on the private provision of social services by grassroots affiliates to recruit voters. Such benefits are crucial to ensure the success of such strategy in unfavorable contexts such as
Ahmedabad. As discussed above, the city is particularly hostile to such strategies, given that its poor had previously been mobilized along the lines of class and caste and that it constitutes a relatively dense environment in terms of welfare service provision
(including those provided by the local public infrastructure). By sorting the electoral according to the relevant ethnic category, religious unmixing helps parties selectively target these services to the constituencies where they might yield greater electoral results.
Though verification of this point would require a more detailed study of the BJP’s reliance on a welfarist strategy in Ahmedabad, the absence of Hindu social service
177 providers in Muslim ghettos suggests that the two factors go indeed hand in hand.92 It is also worth pointing out that the number of grassroots affiliates of the Sangh Parivar in
Gujarat is small. According to the RSS’s Seva Disha Report (2014), the total number of service projects in Gujarat in 2014 was 1067 much smaller than the identical figure for
Kerala (7176), ‘Lower’ Tamil Nadu (9363) or Jharkhand (8090). Ultimately, this suggests that the concentration of Muslims from different parts of the state in ghettos in
Ahmedabad’s periphery may also have a knock-on effect on its deployment of the strategy in other regions of the state.
5.5 Alternative Explanations for the BJP’s success
Recent contributions to the literature on the BJP’s rise identify alternative factors that might explain its enduring success in Ahmedabad. This section discusses the limitation of the two most prominent alternatives – the breakdown of inter-ethnic civic institutions and the rise of the ‘neo middle classes’ – and seeks to illustrate how ethnic unmixing complements each of these explanations.93
5.5.1 The breakdown of inter-ethnic civic institutions
One prominent hypothesis is that the closure of Ahmedabad’s textile mills since the late 1970s has increased the vulnerability of the city’s laboring poor and, hence, pushed them away from the city’s secular institutions, the Congress Party and the Textile
Labour Association (TLA) (Varshney 2002; Mahadevia 2002; Breman 2004; Chatterjee
92 There are, however, a number of Muslim organizations providing social services to these areas (Jaffrelot and Thomas 2012). 93 I have excluded from this discussion the ethnic party’s electoral strategies since the previous section has already showed how ethnic unmixing enhanced the benefits of pre-electoral violence and social service provision. It is also worth noting that no major riot has broken out in Ahmedabad since 2002.
178 2012). This argument is backed by evidence that the number of regular full-time mill workers in the city decreased from 1,70,000 in the early eighties to 70,000 in 1995, thus affecting 5,50,000 of the 30,00,000 (18 per cent) population of the city (Mahadevia
2002). These workers had to settle for lower daily-wage jobs that are, generally, unregistered and unregulated (Mahadevia 2002). The decline of TLA also deprived them of mediated access to resources from the state (Breman 2004). Perceiving them to be siding with the industrialists, these workers blamed both the TLA and Congress for the deterioration of their economic prospects (Berenschot 2011). Finally, the informalization of Ahmedabad’s laboring poor eroded both the TLA’s and the Congress’s worked-based networks of political mobilization (Berenschot 2011).
However, published statistics do not necessarily suggest that large-scale de- industrialization led to a decline in the standard of living of workers in Ahmedabad
(Breman 2004). The Annual Surveys by the National Council of Applied Economic
Research (NCAER) reveal that the number of households in the city below the poverty has come down from 28.6 per cent in 1988 to 11.4 per cent in 1995-96 (when the BJP first won state power). In fact, Gujarat was the leading state in India in terms of reduction of poverty levels in urban areas during the periods 1987-93 and 1993-99 (Bhatt 2003).
National Sample Survey (NSS) data also indicates that unemployment among males in
Ahmedabad has decreased from 6.3 per cent in 1983 to 4.4 per cent in 1993-94
(Mahadevia 2002). Most significantly, the NSS (1997) indicates that the percentage of
179 regularly employed has increased faster than self-employed in the city (Mahadevia
2002).94
Moreover, previous scholarship suggests that inter-communal interaction among mill workers during the golden age of Ahmedabad’s cotton industry was more idealized than a fact of workers’ day-to-day life. Indeed, given that Muslims were occupied in segregated sectors of production, they set up their own Union, outside the realm of the
Hindu-dominated TLA. Accordingly, they voted for the Muslim League instead of for
Congress, even when the candidate for the latter was a mill worker (Breman 2004). There is also evidence that caste and religious loyalties never truly gave way to class-based political mobilization in Ahmedabad. As Breman (2004) argued, at times the TLA was more engaged in ‘taming the work force’ than in defending the workers’ interests vis-à- vis the very wealthy textile-mill owners.
While the link between the collapse of Ahmedabad’s mill industry and the demise of networks of inter-religious engagement seems elusive, there is little doubt that the
Sangh Parivar has managed to fill the vacuum created by the gradual decline of Congress and the TLA (Berenschot 2011). The problem seems to lie on explaining how this replacement took place. I contend that the argument advanced here accomplishes precisely this. By showing that recurrent and large communal riots since the mid-1980s increased Hindu-Muslim segregation in Ahmedabad, I suggest how the BJP might have benefited from the informalization of the laboring poor. Specifically, with the demise of
94 Whereas the self-employed increased only marginally from 34.6 in 1987-88 to 35.6 per cent in 1993-94, the regularly employed increased from 45.4 in 1987-88 to 51.3 per cent in 1993-94 (Mahadevia 2002).
180 mill-based networks, industrial workers increasingly turned to neighborhood-based networks to defend their interests. As riots increasingly gave localities a religious coloration, this favored the BJP’s attempts at communal mobilization. This fits with
Desai’s (2011, p. 111) description:
The breaking up of the Congress’s KHAM alliance was, in fact, poignantly reflected in these reconfigurations of working-class localities and neighborhoods through communal violence that prised apart Dalits and Muslims.
5.5.2 Rise of the Neo-Middle Class
A second alternative explanation emphasizes the BJP’s success in capturing the votes of upwardly mobile urban dwellers (Ilaiah 2002; Shah 1998; Jani 2009; Jaffrelot
2013). This group, described in the party’s 2007 electoral manifesto in Gujarat as the
‘neo-middle class,’ is dominated by OBCs who have recently migrated to urban areas and joined the informal sector (Jaffrelot 2013). According to Jaffrelot, though their socio- economic status remains vulnerable, they are relatively better off than their rural counterparts (underscoring a growing urban/rural divide in the state) and they have high expectations about the future. They are thus more receptive to the BJP’s pro-development agenda as well as Modi’s personal trajectory as an OBC himself (from the Hindu Ganchi community). This view is supported by CSDS data collected following the 2012 Gujarat state elections showing that the BJP’s share of support among semi-urban and urban
OBCs came only third to the party’s share of support among Upper Caste and Patels
(Jaffrelot 2013).
181 Yet, while the BJP’s success in wooing members of this neo-middle class seems indisputable, its traction as an explanation for the BJP’s rise remains questionable. First, there is a temporal mismatch between the rise of the neo-middle classes in Ahmedabad and the BJP’s rise. According to this argument, there are two fundamental structural transformations driving this process: urbanization and education (Jaffrelot 2013). Yet, these transformations do not coincide with the BJP’s rise: based on data from the Census of India, the rate of urban growth in Ahmedabad has declined since the 1970s and the literacy rate in the city has increased steadily by around 10 per cent from each round of census to the next.95 This discrepancy does not improve if we define urbanization to refer solely to OBC migration to Gujarat’s urban centers. Indeed, the growth of the neo-middle classes, as the name already evidences, is a relatively recent process and thus likely to be posterior to the BJP’s rise to power.96
Second, this argument has difficulty in explaining why the OBCs threw their weight behind the BJP when Congress had already began to expand reservations for
OBCs in government jobs, schools and elected offices. In contrast, since coming to power, the BJP has not advanced the status of OBCs, instead preferring to project Modi as a successful OBC who succeed without positive discrimination (Jaffrelot 2014).
Explanations for the OBCs’ contradictory support for the BJP in Gujarat fall into two categories. The first strand of arguments claism that the experience of upward social
95 Literacy Rate Gujarat: 52.2 (1981); 61.3 (1991); 69.1 (2001); 79.3 (2011) Population Change in Ahmedabad District: 37.15 (1961- 71); 34.01 (1971-81); 24.95 (1981-91); 27.25 (1991-01); 22.31 (2001-11). Literacy Rate Change in Ahmedabad District: 42.81 (1961); 73.6 (1991) 79.5 (2001); 86.65 (2011) (Census of India). 96 This is because the overwhelming majority of OBCs in Ahmedabad is employed in the new industrial sectors that came up in the city following the decline of the textile mills (Hirway et al. 2014).
182 mobility has imbued this group with intense Hindu religiosity (Jaffrelot 2014). Yet, to be valid, this argument must engage with the thorny issue of explaining how cultural identity came to trump material and social advancement in the voting calculus of OBCs. The second version contends that the BJP invited the OBCs to provide muscle power in its campaigns against Muslims in exchange for offering some leadership roles to the OBCs
(Ilaiah 2002; Spodek 2010). According to Kancha Ilaiah (2002), the rise of Kalyan Singh and Vinay Katiyar in Uttar Pradesh, Uma Bharti in Madhya Pradesh and Narendra Modi in Gujarat provide evidence of the party’s reliance on social engineering.
However, this argument goes against the BJP’s reluctance to adopt such an electoral strategy (in fact, Modi’s rise drew an angry reaction from the BJP’s high caste leadership in the state, from Keshubhai Patel to L.K. Advani) as well as the fact that, as pointed out before, the Congress was already pursuing it. In fact, the Congress’s Chief
Minister between 1980-85 and 1989 and 1990, Madhavsinh Solanki, was himself an
OBC. This suggests that if a party was expected to benefit from social engineering in the period between 1985 and 1995 then this would Congress, rather than the BJP.
The argument advanced here complements these arguments by showing that recurrent and severe Hindu-Muslims riots between the mid-1980s and early 2000 helped the BJP woo OBC voters in Ahmedabad. It provides a better explanation for the sharp upswing in the BJP’s popular support between 1985 and 1990 and it also illuminates the strategic incentives behind OBC electoral support for the BJP in Ahmedabad. Ultimately, by showing that ethnic unmixing reduced (Hindu) voters’ uncertainty about access to
183 crucial public goods, this project provides a novel account of the link between the neo- middle class and the BJP’s electoral success.
5.6 Conclusion
By drawing on the case of Ahmedabad, the capital of the Indian state of Gujarat, this chapter has sought to illustrate the causal mechanisms linking ethnic riots, unmixing and the enduring rise of an ethnic party. In the previous sections, I have showed how the
BJP turned to ethnic unmixing as an electoral strategy due to its limited means to expand its popular base without antagonizing its core elite base as well as the city’s incompatibility with a welfare-based strategy. I have then provided empirical evidence of the causal link between riots, unmixing and the BJP’s enduring success in Ahmedabad since the late 1980s. In the next section, I outlined the system of interacting parts that transforms ethnic unmixing into long-term ethnic party success. Specifically, I highlighted three electoral effects of religious unmixing: (1) increased the visibility of the
Hindu-Muslim divide vis-à-vis other social categories; (2) consolidation of the link between religious identities and access to public goods; and (3) advantages in the deployment of other electoral strategies. Finally, I have examined the dominant alternative explanations for the success of the BJP in Ahmedabad and I have showed how my argument complements these accounts.
The conclusions of this chapter have important implications for the theory and policy on ethnic conflict. First, while Ahmedabad constitutes an extreme case in all the relevant variables for this study, its trajectory provides us an insight into what may lie
184 ahead for other riot-affected cities in India. This fits with the Sangh Parivar’s description of Gujarat as the ‘Laboratory of Hindutva,’ a favorable political environment for carrying out political experiments that then can be replicated in other parts of India. Indeed, in the wake of the 2002 anti-Muslim pogrom, the VHP’s International Working President
Pravin Togadia – himself an Ahmedabad native – said: “In Gujarat, for the first time there has been a Hindu awakening and Muslims have been turned into refugees. This is a welcome sign and Gujarat has shown the way to the country” (Concerned Citizens
Tribunal 2002, p. 261). Togadia’s inflammatory remark was later turned into a VHP resolution which warned Muslims throughout could all be driven into refugee camps
(Varadarajan 2002).97
Second, while ethnic riots may assume the characteristics of holocaustian politics
(Baxi 2002), this chapter suggests that, from the politicians’ point of view, the goal of the violence is not to make the ethnic Other disappear. In fact, the obliteration of the ethnic difference risks draining an ethnic party from its ability to raise the salience of ethnic issues that favor it in electoral competition. Therefore, this research indicates that violence provides ethnic parties with an efficient means of pushing the Other towards ghettos, enclosed by clearly defined ‘borders,’ where the differences between groups can be permanently highlighted and the Other can be further marginalized. As Renu Desai
(2011, p. 115) says the border “not only separates but also becomes a zone of engagement through violence, a zone where communal hostility is displayed to reinforce separateness, antagonism, and irreconcilability.”
97 The Sangh Parivar’s description of Gujarat as the ‘Laboratory of Hindutva’ implies that it considers favorable political environment for testing electoral strategies to be replicated in other parts of India.
185 Finally, as a culmination of the empirical sections of this dissertation, this examination of Ahmedabad has showed that political parties may have both short- and long-term incentives for the production of ethnic riots. Riots enable a party raise a salient ethnic category in the run-up to a competitive election but they also enable them to inscribe an ethnic divide in the spatial tissue of a city and, in this way, to turn it into a device of enduring power. In the following section, then, I conclude this dissertation with some thoughts about the broader implications of this finding, the application of these insights to contexts beyond India and, finally, what we might anticipate for the country’s future.
186 Chapter 6
Conclusion
The violent outburst may change the course of the system altogether or simply accelerate earlier trends. (...) One thing it will not do is to leave conflict where it was. -- Donald L. Horowitz, The Deadly Ethnic Riot, 2001
But as an American negro, I am deeply concerned with the racial ghettos of our cities – for the ghetto exists at the very core of, and is both a part and a cause of our cities’ sickness. -- Dr. Martin Luther King Jr., Washington D.C., 1966
6.1 Re-visiting the argument
What explains the rise and enduring success of ethnic parties? From the repeated success of the Movement for Socialism (MAS) in Bolivia to the emergent triumph of
Sinn Fein in Ireland, Prawo i Sprawiedliwość (PiS, lit., Law and Order) in Poland, and the Orange Democratic Movement (ODM) in Kenya, ethnic parties are today prospering across the globe (Ishiyama 2011). Scholars have highlighted a number of factors to explain this phenomenon, but they have so far overlooked the relationship between violence and the enduring rise of ethnic parties. This is surprising given that ethnic violence is known to promote a perpetuation or escalation of ethnic conflict (Fearon and
Laitin 2000). Moreover, previous research has already pointed out that riots reverberate through the political system long after the debris has settled (Horowitz 2001; Kasara
2017).
187 Drawing on a study of variation in Hindu-Muslim riots in India, this study proposes a novel theory linking recurrent and severe ethnic riots to the enduring success of an ethnic party. The central puzzle animating this dissertation was the enduring rise of the Hindu right – specifically, the Bharatiya Janata Party (BJP) and the Shiv Sena – in recent decades in India. Briefly, I argue that neither conventional accounts for the rise of ethnic parties nor existing explanations for the Hindu right’s success in India (the ‘saffron wave’) fully account for its electoral performance. Instead, I argue that the Hindu right’s enduring success has been the product of spatial strategies, which included violently refashioning India’s social geography in ways that fix and enduringly highlight the
Hindu-Muslim divide (Deshpande 1995; Appadurai 2000; Oza 2007; Desai 2011). Such violent strategies reached a peak between the mid-1980s and early 1990s, when the
Sangh Parivar (the family of Hindu nationalist organization) revitalized a long-standing dispute over a religious site in Ayodhya, Uttar Pradesh.
To support this argument, this dissertation outlines a two-part analytic framework conceptualizing the link between ethnic riots and long-term political outcomes. The first part of the argument contends that recurrent and severe riots shift the ethnic composition of electoral constituencies, constructing homogeneous constituencies where relative heterogeneity had been the norm. Following Brubaker’s seminal work (Brubaker 1995;
1998), I name this wholesale restructuring of peoples ‘ethnic unmixing.’
The second part argues that greater ethnic homogeneity at the constituency level promotes lasting electoral support for ethnic parties. Underlying this argument is a simple
188 assumption: benefit-seeking voters will support the social category that makes them part of a winning coalition (Riker 1962; Bates 1974). The most effective way of doing so is by comparing the size of the identity categories in the electoral context (‘counting heads’) and then selecting the ethnic category that offers the most usefully sized coalition
(Chandra 2004). By increasing residential segregation along ethnic lines, riots can thus enduringly raise the status of one ethnic category, consolidate the link between ethnic majoritarianism and public good provision and to deploy other electoral strategies more efficiently. In this way, I argue, ethnic riots contribute to the rise and enduring success of parties seeking to mobilize a matching ethnic category.
To empirically examine the argument, I employed a mixed methods research design that combines large-N statistical analysis with in-depth case study research. The empirical chapters of the dissertation are structured into two sections corresponding to each of the steps of my causal claim. Each section is composed by a quantitative and a qualitative chapter that explores a typical case study. This structure follows the most conventional template for mixed methods research: a quantitative analysis examines the direction and significance of the relationship between variables and the qualitative explorations sheds light on the causal mechanisms as well as the robustness of the findings (King, Keohane and Verba 1994; Mahoney 2010).
The first part of the dissertation examines the link between communal riots and spatial segregation by religion. In chapter 2, I employ original data to conduct two statistical tests on the impact of communal riots on the degree of Hindu-Muslim
189 segregation. The analysis shows that not only is the evolution of segregation by religion consistent with the intensification of Hindu-Muslim between the late 1980s and early
2000s but also that there is a positive and significant effect of communal riots on the level of residential segregation by religion in some of India’s largest cities.
Chapter 3 then examined why and how the Shiv Sena promoted ethnic unmixing during and after the 1992-93 riots in Mumbai for its own electoral benefit. This chapter enabled me to illustrate two main points: first, politicians find it useful to promote favorable ethnic demographies when they contemplate electoral marginalization; second, intense and frequent ethnic riots trigger two types of migratory flows: (1) an initial movement of people forced to flee their homes as a direct consequence of the violence; and (2) an unmixing cascade in search for ‘safety in numbers’ that trickles over many years after the violence.
Part two of the dissertation examines the relationship between ethnic demography and the performance of ethnic parties. Chapter 4 draws on an original dataset of demographic variables and electoral results in India’s seven largest cities: Mumbai,
Delhi, Kolkata, Bangalore, Chennai, Hyderabad and Ahmedabad. The analysis lends strong support to the existence of a positive link between growing Hindu-Muslim segregation and the Hindu right’s success. The analysis shows that not only are Hindu- majority constituencies more likely to vote for the Hindu right but also that this likelihood increases with the size of the Hindu majority in a constituency.
190 Chapter 5 then examines the relationship between communal riots, Hindu-Muslim unmixing and resilient support for the BJP in Ahmedabad, the capital of the western
Indian state of Gujarat. Drawing on extensive qualitative evidence collected during two stints of fieldwork in Ahmedabad (between June-July 2014 and November-December
2015), I show how these three phenomena – communal riots, religious unmixing and BJP success – have evolved alongside each other each since the mid-1980s in Ahmedabad.
Building on this analysis, I then highlight three electoral effects of religious unmixing:
(1) increased the visibility of the Hindu-Muslim divide vis-à-vis other social categories;
(2) consolidation of the link between religious identities and access to public goods; and
(3) advantages in the deployment of other electoral strategies.
6.2 Implications for scholarly and policy debates
The findings of this dissertation have far-reaching implications for debates on ethnic conflict and Indian politics. Here, I outline how they contribute to three crucial areas of research: the rise of ethnic parties; the electoral incentives behind ethnic riots; and India’s political development of India. Finally, I conclude with some thoughts about what these results tell us about the future of India.
6.2.1 Literature on the rise of ethnic parties
First, many authors have argued that the rise of ethnic parties, and the politicization of ethnic categories more generally, threaten the stability of democratic regimes (see for example Rustow 1970, Dahl 1971, Lijphart 1977, Horowitz 1985,
Chandra 2005). Ethnic parties do not seek national unity; rather, they limit their appeal to
191 a particular ethnic constituency, and “explicitly seek to draw boundaries between ethnic
‘friends’ and ‘foes’” (Kitschelt 2001, p. 305). Given the irreducible nature of ethnic demands, the flourishing of ethnic parties is said to pose greater challenges for democracies than socio-economic demands. As Rustow (1970, p. 359-360) aptly puts it,
‘there is no middle position between Flemish and French as official languages.’
However, while there has been an increase in the number of parties that serve an ethnic constituency across the globe since the end of the Cold War, the processes by which such parties become enduring electoral players remain little understood (Ishiyama
2011). This dissertation sought to contribute to this literature by shedding light on the role of ethnic violence on the rise and enduring success of an ethnic party.
Chiefly, this research suggests that riots shape not only the outcome of the first elections after the violence but also have the power to transform the nature of electoral competition in a state. This finding informs social scientific and policy debates on ethnic politics in two specific ways. First, this dissertation highlights the fact that ethnic demography cannot always be treated as exogenous to political phenomena. This raises new questions about the link between demography and electoral competition.
Specifically, how should governments (both foreign and domestic) and voters respond to political parties that seek to alter ethnic demography to tilt electoral outcomes in their favor?
192 Second, this study addresses ongoing policy debates about the relationship between ethnic demography and ethnic peace, namely between the idea that greater heterogeneity increases the chances for positive intergroup contacts (the ‘contact’ hypothesis) and the counter claim that greater heterogeneity is likely to promote inter- ethnic prejudice (the ‘threat’ hypothesis).98 While much of this literature focuses on the
United States and Western Europe, this project provides a first systematic analysis of the impact of demography on the voting behavior of an ethnic majority in a non-Western, developing democracy: India. The findings presented in the previous chapters come down on the side of the contact hypothesis: greater ethnic heterogeneity at the constituency level diminishes ethnic party support. Ultimately, these results provide policy-makers committed to democratic stability across the world with strong evidence in favor of the promoting inter-ethnic propinquity as a means to alleviating ethnic conflict in divided societies.
6.2.2 Electoral Incentives Behind Riots
This research also contributes to the growing literature on the electoral incentives behind ethnic riots. While strategic political considerations are said to play a key role in the production of riots, works illuminate only how riots shape electoral competition in the short-term (Brass 1997; Wilkinson 2004; Dhattiwala and Biggs 2012; Blakeslee 2013;
Arcand and Chakraborty 2013; Iyer and Shrivastava 2015). Theorizing the political logic of ethnic riots, Wilkinson (2004, p. 23) highlights that politicians “use ethnic wedge
98 For examples of work offering for the 'threat' hypothesis see Blalock 1957; Fossett and Kiecolt 1989; Huckfeldt and Kohfeld 1989. For examples of evidence to support the 'contact' hypothesis see Allport 1954; Pettigrew 1998; Oliver and Wong 2003; Tropp and Pettigrew 2005; Kasara 2017.
193 issues to increase – albeit in a short-term – the salience of the ethnic issues that will favor their party.”99 Yet, there are good reasons to believe that ethnic riots can also shape long- term electoral outcomes. As Horowitz (2001) tells us, homogeneity is valued because the capacities and dangers posed by target groups are exaggerated and their negative impact on the fulfillment of the aggressors is emphasized. This suggests that ethnic riots can have far more serious consequences for electoral competition than previously thought.
Along this vein, the argument advanced by this dissertation suggests that ethnic unmixing is not merely a by-product of ethnic riots. Instead – as illustrated in the chapters
3 and 5 – the patterns of the violence, slogans of rioters and public statements of politicians denounce an explicit intention to create or accentuate the spatial segregation between ethnic groups. In this way, riots can be thought of as a spatial device designed by ethnic parties to promote their long-term success. They are part of a large repertoire of spatial tactics, that in the case of the Hindu right included: a campaign for the ‘liberation’ of a sacred site; the collection and consecration of bricks from villages across India; the organization of religious marches; the distribution of maps marking the areas dominated by each community; the use of a spatialized discourse that refers to Hindu-majority areas as ‘Hindustan’ and Muslim-majority areas as ‘Pakistan’; and the fixation of boards claiming certain urban localities to be part of the Hindu Rashtra (‘nation’). All this suggests, as Deshpande (1995) argues, that the essentialization of space provides the ideological context for the production and reproduction of world views as well as properly indoctrinated workers for the cause of an ethnic party.
99 Emphasis is mine.
194 6.2.3 Debates on Indian Politics
Finally, the results of this study have important implications for the political development of India, the world’s largest democracy. They provide a theoretically- informed, yet empirically-rich novel account of the rise of the Hindu right in India – arguably, the defining transformation of Indian politics over the past three decades.
Though previous scholars have already highlighted the link between the Ayodhya campaign and the enduring rise of the BJP and the Shiv Sena, no work to date amounts to a general testable theory that might have some predictive power about the relationship between this wave of violence and long-term electoral patterns. In the year that India’s marks the twenty-fifth anniversary of the Babri Masjid’s demolition, this study draws on systematic empirical evidence to show that the intensification of Hindu-Muslim during this period contributed to the Hindu right’s rise and enduring success.
My claim is not that riots and unmixing explain all variation in electoral support for the Hindu right. Given the complexity of party politics and electoral competition, putting forward such a unicausal explanation of why the BJP and the Shiv Sena have become major, long-lived players in the Indian electoral landscape would be unrealistic. I also do not claim that the discourse of communalism has been the only, or even the most salient, element of the Hindu right’s electoral platform since the 1990s. Certainly, after the electoral setbacks of the 1993 Assembly election, the BJP has placed more emphasis on socio-economic than on ethno-religious issues (Jaffrelot 1996). Modi’s historic victory in the 2014 general elections has been widely interpreted by academics and observers as
195 owing more to popular economic aspirations than communal animosities (see for example Chhibber and Verma 2014; Sridharan 2014; Varshney 2014).
But I think this does not undermine the conclusions of this dissertation. First, showing that greater Hindu-Muslim segregation in urban India contributes to the Hindu right’s enduring success does not necessarily imply that the BJP and the Shiv Sena have continuously emphasized religious cleavages in their canvassing efforts. Rather, the argument put forward by this dissertation is that religious homogeneity at the constituency levels contributes to the Hindu right success even when its candidates highlight other campaign issues.
Second, while this is not comparable to the parties’ aggressiveness during the
Ayodhya campaign, both the BJP and the Shiv Sena continue to espouse policies that aim to bring state institutions in line with the politics of Hindutva, such as efforts to
‘saffronize’ the bureaucracy, the educational institutions and the media (Hasan 2002).
Even in its 2004 national parliamentary campaign, when the BJP was headed by the moderate Vajpayee, the party’s manifesto explicitly stated its support for the construction of a temple to Ram in Ayodhya, its support for banning religious conversions and an emphasis on returning Kashmiri Hindus to their place of residence (Thachil 2014). In its
2009 and 2014 electoral manifestos, the BJP continued to support policies traditionally associated with the Hindu majority.100 The BJP’s commitment to Hindutva is even more
100 Even while announcing a commitment to improving the socio-economic condition of religious minorities, in 2014, the party restated support for the construction of the Ram Temple in Ayodhya, as well as opposition to the 'Sethusamudram Shipping Canal Project', the adoption of an Uniform Civil Code, the promotion of 'Indian languages,' the protection and promotion of cow and its progeny and the return of Kashmir Pandits to their ancestral land (BJP Election Manifesto 2014).
196 apparent if we shift the focus from the national sphere to the actions of a BJP government at the state or municipal level. For example, the BJP has recently introduced stringent penalties for cattle slaughter in states where it has ruled such as Madhya Pradesh,
Gujarat, Rajasthan and Maharashtra.
6.2.4 Looking ahead
The results of this investigation offer a mixed outlook for communal peace and democratic stability in India. On the one hand, they suggest that the Hindu right is likely to benefit greatly from India’s rapid urbanization. The country’s urban population is projected to nearly double from 377 million today to over 600 million over the next three decades, thus surpassing its rural population (and making it the largest urban population in the world). This is thus a far cry from Gandhi’s adage that ‘India lives in its villages.’
Previous scholars have already provided evidence for the existence of a strong link between urbanization and the BJP’s success (Sridharan 2014; Jaffrelot and Kumar 2015;
Auerbach 2015). By showing that ethnic unmixing following riots contributes to the
Hindu right’s enduring success, this study offers a novel account of this relationship.
Specifically, it suggests that as individuals move from relatively mixed rural environments to settle in cities sharply divided along communal lines, they will also become more receptive to the Hindu right’s mobilization. One corollary of this is that the
Hindu right is not only likely to remain a major player in Indian politics but also to increase its vote share in future decades. Given the previously noted threat posed by ethnic parties to peace and stability, this might indeed spell dark times ahead for India’s democracy.
197 On the other hand, the results of this dissertation provide us two reasons for
(measured) optimism. The first is that this study suggests that urbanization, per se, does not translate into the Hindu right’s success. More important than how fast cities and how big cities are growing is the type of urbanization taking place. In particular, the findings indicate that urbanization contributes to Hindu right support only when a city is acutely segregated along communal lines. The best example of this relationship is Bangalore –
India’s third largest city and fastest growing metropolis between 1991 and 2011. While the city has grown at unprecedented rates during this period, the BJP has been less successful electorally than in other major cities in India. Crucially, Bangalore has remained relatively peaceful during this period and, as we saw in Chapter 2, also has moderate levels of Hindu-Muslim segregation. Overall, then, this indicates that policy- makers should dedicate greater efforts to safeguarding Hindu-Muslim propinquity throughout India’s urban transition.
Lastly, this dissertation suggests that the marginal benefits for politicians seeking to promote ethnic violence as an electoral strategy may sharply decrease once Hindu-
Muslim segregation reaches acute levels. This is so because one of the main goals of riots
– i.e., the accentuation of segregation along ethnic lines – becomes exhausted. Moreover, at such high levels of segregation, politicians may be better off by putting their efforts on other electoral strategies that benefit from it, such as welfare-provision or selective distribution of public goods. In this way, high levels of Hindu-Muslim segregation in some of India’s largest cities may translate into fewer communal riots. This does not mean, however, that the conflict is over. Rather, the communalization of space mutates
198 riots into everyday forms of abuses against Muslims. Still, this is a less terrifying prospect than the grotesque violence that usually takes place during communal riots.
6.3 Generalizability
One obvious question of any study that focuses exclusively on one country is whether its principal findings are applicable beyond the case in point. However, a full comparative test of the framework that I have developed in the previous chapters for the enduring success of the Hindu right in India would require extensive research, including time-series and cross-sectional demographic data, as well as detailed qualitative information on the history, electoral competition, patterns of ethnic violence of many countries. Segregation is particularly difficult to capture because its measurement requires fine-grained data on the distribution of ethnic groups within small areas (Kasara
2017). Such difficulties would thus preclude efforts to test the external validity of the argument.
Still, existing research suggests that the findings of this dissertation can be generalizable to other regions. First, there is abundant evidence from across the world that ethnic riots produce an accentuation of segregation along ethnic lines. According to one estimate, the number of riot-produced refugees and internally displaced persons
(IDPs) surpasses the number of officially reported deaths on average in a ratio of at least
100 to one (Horowitz 2001; Kasara 2017).101 Previous works also show that politicians use a variety of strategies to shape the demographic composition of electoral
101 For example, in 2010, clashes between ethnic Kyrgyz and Uzbeks in southern Kyrgyzstan killed more than 420 people and produced 300,000 internally displaced and over 111,000 refugees across the border in Uzbekistan (International Crisis Group 2012).
199 constituencies to their lasting electoral advantage. The most well-known example is perhaps that of James Michael Curley, a four-time mayor of Boston, who used targeted redistributive policies to encourage non-target groups to leave the city, thereby shaping the electorate in his favor – the so-called ‘Curley effect’ (Glaeser and Shleifer 2005).
Along this vein, Chandra (2004) points out that politicians courting strategic voters use a variety of strategies, including proposing favoring ethnic demographies, inflating the proportions and turnout rates of their target ethnic categories, to reduce voters’ uncertainty about the ethnic category most likely to form a winning coalition.
To further support the external validity of the argument, next, I briefly discuss two cases that seem to confirm the link between ethnic riots and the enduring rise of an ethnic party.
6.3.1 The ODM in Kenya
One case study is Kenya, another populous, multi-ethnic, federal democracy.
Between December 2007 and February 2008, Kenya experienced ethnic violence triggered by a disputed presidential election. In the run-up to elections, the two coalitions vying for power – the ruling Party for National Unity (PNU) and the Orange Democratic
Movement (ODM) – were strongly represented by ethnically-rooted political constituencies. The PNU was supported by the Kikuyu ethnic group, based in the Central and Eastern Provinces and strongly represented in Nairobi, the Coast Province and Rift
Valley; whereas the ODM, founded in 2007, was backed by the Luo, Luhya and Kalenjin ethnic groups, represented in the Nyanza, Western Provinces and Rift Valley. On 30
200 December 2007, the announcement of the PNU’s victory triggered a wave of violence by
ODM-affiliated individuals across the country.
The clashes were characterized by ethnically-targeted killings against Kikuyus living outside their traditional settlements areas, particularly in the Rift Valley Province
(Elhawary 2008). There is evidence that in some parts of the Rift Valley, violence was planned before the election but, crucially, it only took place after it (Kasara 2017).
Moreover, as in earlier periods of ethnic violence, perpetrators of violence openly expressed a desire to send members of the Kikuyu and Kisii ethnic groups “home”
(Kenya National Commission on Human Rights 2008). According to different sources, roughly 1300 people were killed and up to 600,000 people were displaced during the violence (Khazan 2013). Kasara (2016; 2017) shows that those who migrated following the violence moved to homogeneous areas in search for safety in numbers and that these flows persist long after the violence subsided.
Since then, the ODM has remained a major player in Kenyan politics. In the 2013 general elections, the ODM again came second with 43.7 per cent of the vote but won the largest number of counties (26 against the winning Jubilee alliance’s 20).102 Crucially, the electoral map reflects the demography weight of the the two ethnic blocs (Lewis 2013).
In general, Jubilee won handily in Kikuyu and Kalenjin areas, whereas the ODM won by similar margins in Luo and Kamba areas. While a more detailed study of the electoral
102 In October 2012, the PNU’s National Executive Committee entered a tentative election pact with The National Alliance (TNA), where it would surrender the right to field individual candidates in the 2013 in exchange for supporting Uhuru Kenyatta's presidential bid. This marked the beginning of the end of the party, as without any candidates in any office in Kenyan politics, lack of funds and multiple overdue debts, the party was de-registered in October 2014. In turn, The Jubilee Alliance is a multi-party coalition established to support the joint presidential elections ticket of Uhuru Kenyatta and William Ruto in the 2013 Kenya general elections.
201 impact of ethnic unmixing in the Rift Valley would be necessary to confirm whether the
2007-08 violence contributed to the ODM’s performance in 2013, this brief elaboration seems to confirm the link between ethnic riots, ethnic unmixing and lasting electoral outcomes.
6.3.2 The Sinn Fein in Northern Ireland
Between 1968 and 1998, Northern Ireland experienced a period of unprecedented violent conflict along ethnic lines. During the euphemistically-called ‘Troubles,’ more than 3,500 people were killed, of whom 52 per cent were civilians, 32 per cent were members of the British security forces, and 16 per cent were members of paramilitary forces (Sutton 2017). The city of Belfast, accounting for 54.5 per cent of the fatal incidents during the ‘Troubles,’ was the worst affected by the violence (Doherty and
Poole 1997). The violence peaked in 1972, when nearly 500 people, the majority of them civilians, lost their lives. The core protagonists of the confrontation were the
Republicans, mostly Catholics, who espouse an all-Ireland nationalist ideology that favors political unification of the island in the long term; and the Unionists, overwhelmingly Protestants, who supported continued union with Great Britain.
The extent of Catholic-Protest segregation grew very rapidly with the outbreak of the ‘Troubles.’ In 1969, 69 per cent of Protestants and 56 per cent of Catholics lived in streets where they were in their own majority; as the result of large-scale flight from mixed areas between 1969 and 1971 following outbreaks of violence, the respective proportions had by 1972 increased to 99 per cent of Protestants and 75 per cent of
202 Catholics (Wright 1988). A report published soon after these events noted that “mixed areas are increasingly becoming under threat. Protestants are tending to move out of the newer housing areas on the city’s margins and Catholics are crowding into the
Falls/Andersonstown sector of the city and the older housing in north Belfast” (Black,
Pinter and Ovary 1971, p. 9). A subsequent and more detailed report on intimidation in housing argued that “the most significant trend observed in the movements of August
1971was the re-sorting of mixed areas into segregated areas, the continuation of the patterns of 1969 and 1970” (Darby and Morris 1974, p. 2).
Using data from the Northern Ireland Censuses of Population Small Area
Statistics, Doherty and Poole (1997), show that the Dissimilarity Index and the Isolation
Index for Catholics increases markedly during the most intense period of the ‘Troubles,’ namely between 1971 and 1991 (from 49.6 to 60.2 per cent, and 53 to 61 per cent, respectively). In 2004, it was estimated that 98 per cent of public housing in Belfast was divided along religious lines (O’Hara 2004). Moreover, there is evidence that self- segregation continues today despite the Northern Ireland peace process. According to
Jarman (2005), an estimated 1,500 people a year are being forced to move as a consequence of intimidation.
Crucially, this period coincides with the rise of the Sinn Fein (‘We Ourselves’) the Irish Republican political party. In 1983 Alex Maskey was elected to Belfast City
Council, the first Sinn Fein member to sit on that body. Sinn Fein polled over 100,000 votes in the Westminster election that year, with its leader Gerry Adams, winning the
203 West Belfast seat previously held by the Social Democratic and Labour Party (SDLP). In the 1985 local it won fifty-nine seats on seventeen of the twenty-six Northern Ireland councils, including seven on Belfast City Council. Since then, the Sinn Fein has enjoyed continued electoral success, overtaking the SDLP to become the largest nationalist party in Northern Ireland in the early 2000s. Unsurprisingly, the party draws its largest margins of support from Catholic-dominated areas in Belfast (Tonge 2006).
6.4 Limitations and areas for further research
To conclude this dissertation, I outline two areas where further research is warranted. One first question that this dissertation has left unresolved is what explains ethnic party failure in contexts with high levels of segregation on the relevant ethnic category? In other words, are there deviant cases? And, if yes, do they challenge the conclusions of this dissertation? It is possible that the crucial variable for explaining such cases is the provision of patronage. Thus, in contexts where other parties have already built deep patronage linkages with voters, it is more difficult for ethnic parties to mobilize an ethnic majority. Future research should thus examine such deviant cases to shed light on the mechanisms that explain the failure of spatial strategies.
Finally, another question that I have not considered very much in this dissertation is whether I expect the theory to apply to other ethnic parties in India. Specifically, can riots also benefit other political parties in India? In the first place, it would be important to examine whether Hindu-Muslim riots have a similar effect for parties seeking to mobilize the Muslim minority in India. The most obvious case for exploring this question
204 would be that of the All India Majlis-e-Ittehad-ul Muslimeen (AIMM), which has a strong presence in the city of Hyderabad. The AIMM has held the Lok Sabha seat for the
Hyderabad constituency since 1984 and, in the 2014 Telangana Legislative Assembly elections, it won seven seats and received recognition by the ECI as a ‘state party.’ The party has also expanded to other states, winning two seats in the 2014 Maharashtra
Legislative Assembly election and emerging as the second largest party in the
Aurangabad (Maharashtra) municipal elections. It would thus be pertinent to explore whether the AIMM also benefits from the post-riot dynamics described in this project.
Moreover, there is no other reason why the framework for the rise of ethnic parties developed in this dissertation could not be applied to other, non-religious, ethnic parties in India. The most pertinent example for examining this question would be that of caste-based parties. Much like communal riots, caste riots happen with periodic regularity across India. For example, in February 2016, sixteen people were killed and hundreds hurt in three days of violence led by Jat community protestors. Moreover, as I described in the previous chapters, the 1980s saw also intense violence between castes in some of
India’s largest cities, namely in Ahmedabad. Research on Indian electoral competition could thus benefit from a study that explores the relationship between caste-related violence and the rise of parties seeking to mobilize specific caste categories.
The exploration of these questions can help to consolidate the link between violence and the rise of political parties. It is particularly important to understand whether the effects identified in this dissertation are specific to certain forms of violence (i.e.,
205 riots) and/or to certain ascriptive identities (i.e., religion). Such research has also the potential to yield important insights for policy-making on conflict resolution and peace- building in sharply polarized societies. Ultimately, this dissertation hopes to inspire subsequent research into the nexus between violence and electoral competition that contributes for democratic peace and stability across the world.
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231
APPENDIX
232 Appendix 1
List of Names Extracted from the National Voter’s Service Portal for Mumbai
Religion Total
Abdul Muslim 151224
Ibrahim Muslim 26481
Desai Hindu 70111
Sharma Hindu 78801
Souza Christian 18087
Anthony Christian 18270
Harprit Sikh 303
Anand Hindu 82200
Kamble Buddhist 73656
Kumar Hindu 184256
Mahadeo Hindu 116442
Jai Hindu 31512
Jain Jain 99299
Rai Hindu 59168
Shetty Hindu 130802
Fernandes Christian 29256
Mohammed Muslim 197263
233 Miranda Christian 1886
Rao Hindu 59168
Manohar Hindu 56545
Joshi Hindu 57020
Das Hindu 16069
Ram Hindu 71340
Krishna Hindu 71882
Gaikwad Hindu 42384
Kaur Sikh 12689
Grewal Sikh 81
Pushpa Hindu 19622
Bhosle Hindu 18368
Shirke Hindu 10309
Ravi Hindu 17323
234 Appendix 2
Index of Isolation for India’s Seven Metro Cities in the Last Seven General Elections for the State
Legislative Assembly:
Election Mumbai Bangalore Chennai Ahmedabad Kolkata Hyderabad Delhi
1 30.86175 24.55960 22.26134 25.92593 41.47388 47.63692 49.11484
2 43.18873 30.28319 21.61345 35.22470 32.44949 43.27625 37.792156
3 35.54119 25.89643 15.23671 45.63839 38.51002 43.33782 39.21441
4 41.54157 28.58201 17.04135 43.58466 35.14013 43.68660 43.75040
5 36.24910 19.11503 18.40545 36.11111 37.14593 43.34030 44.40942
6 41.41984 24.77750 22.61905 46.23067 38.93128 41.73945 30.98057
7 38.02841 27.59251 18.91557 48.82738 33.40442 34.95632 37.01242
Change 7.16666 3.03291 -3.34577 22.90146 -8.06946 -12.68060 49.11484
235 Appendix 3
Index of Dissimilarity (D) for India’s Largest Cities + Municipal Corporations in UP and Gujarat (AC Level Analysis) City D Size-Adjusted D
Delhi 35.29 20.66
Mumbai 37.18 38.84
Bangalore 36.53 30.36
Hyderabad 42.37 40.95
Chennai 20.53 14.80
Kolkata 43.11 31.97
Ahmedabad 50.20 39.02
Kanpur 37.19 41.06
Lucknow 25.70 31.56
Ghaziabad 3.53 4.46
Agra 16.42 21.48
Varanasi 7.85 9.93
Meerut 25.55 31.24
Allahabad 21.40 26.74
Bareilly 1.84 2.11
Aligarh 21.32 22.83
Moradabad 11.01 13.95
Saharanpur 4.72 5.39
Gorakhpur 8.27 10.52
Surat 34.28 24.58
Vadodara 17.08 14.50
Rajkot 11.31 8.99
Bhavnagar 1.49 1.13
Jamnagar 5.54 3.71
236 Appendix 4
Index of Dissimilarity (D) for India’s Largest Cities + Cities in UP and Gujarat (Part Level Analysis)
City D Size-Adjusted D
Delhi 57.57 86.63
Bangalore 61.27 60.26
Hyderabad 67.4 73.81
Chennai 40.19 51.34
Kolkata 80.14 69.26
Ahmedabad 81.14 89.00
Kanpur 57.91 61.73
Lucknow 46.72 47.23
Ghaziabad 48.15 56.16
Agra 50.55 49.10
Varanasi 54.87 57.17
Meerut 69.31 69.92
Allahabad 50.82 52.68
Bareilly 58.68 58.10
Aligarh 70.54 67.46
Moradabad 68.88 71.62
Saharanpur 61.55 68.28
Gorakhpur 48.11 42.58
Faizabad 38.81 39.21
Firozabad 76.95 77.22
Jhansi 37.31 38.35
Surat 67.67 73.45
Vadodara 66.65 81.23
Rajkot 48.43 58.54
237 Bhavnagar 68.59 79.43
Jamnagar 67.23 78.33
Junagadh 69.88 70.27
Gandhinagar 40.61 43.32
Muzaffarnagar 68.60 69.83
Mathura 44.59 45.82
Budaun 58.56 54.70
Rampur 60.36 59.56
Shahjahanpur 41.66 41.37 Farrakhabad-cum- 40.01 42.40 Fategarh Maunath Bhajan 63.32 54.86
Hapur 62.38 63.25
Noida 28.14 28.44
Etawah 49.47 44.45 Mirzapur-cum- 38.33 39.76 Vindhyachal Bulandshahr 55.76 56.45
Sambhal 61.04 58.78
Amroha 55.73 57.67
Hardoi 35.65 34.15
Fatehpur 46.05 44.30
Raebareli 39.76 39.55
Orai 41.95 39.32
Sitapur 49.61 47.64
Bahraich 46.54 43.97
Modinagar 50.23 50.57
Unnao 41.87 40.64
Jaunpur 45.41 44.46
238
Lakhimpur 40.45 42.76
Hathras 32.49 30.03
Banda 32.94 34.56
Pilibhit 58.66 58.49
Mughalsarai 35.13 33.82
Barabanki 42.36 40.86
Khurja 53.57 50.17
Gonda 50.14 51.49
Mainpuri 43.20 37.77
Lalitpur 25.19 23.95
Etah 40.58 36.41
Deoria 32.02 31.29
Ujhani 45.64 41.82
Ghazipur 36.60 38.24
Sultanpur 41.27 41.37
Azamgarh 43.23 43.01
Bijnor 55.03 53.21
Sahaswan 61.14 59.75
Basti 39.82 36.61
Chandausi 57.89 58.04
Akbarpur 34.27 32.86
Ballia 36.50 37.49
Tanda 54.79 54.79
Shikohabad 64.24 58.69
Shamli 52.29 54.71
Khair 37.57 32.44
Kasganj 50.82 47.38
239 Gandhidham 50.64 51.55
Nadiad 70.67 74.44
Anand 77.79 83.20
Morbi 61.99 61.19
Surendranagar 57.04 64.14
Bharuch 64.52 68.81
Vapi 59.45 57.65
Navsari 63.87 57.79
Veraval 75.76 77.23
Porbandar 45.36 49.20
Godhra 85.60 78.62
Bhuj 64.62 62.35
Ankleshwar 69.92 67.15
Botad 53.67 51.29
Palanpur 66.92 66.98
Patan 70.63 70.63
Dahod 75.35 74.33
Jetpur 52.26 51.14
Valsad 62.83 62.08
Kalol 72.45 76.62
Amreli 58.87 55.08
Mahesana 71.15 81.97
240 Appendix 5
Figure 1: Mumbai – Hindu Population and Hindu Right Vote
241 Figure 2: Kolkata - Hindu Population and Hindu Right Vote
242 Figure 3: Ahmedabad - Hindu Population and Hindu Right Vote
243 Figure 4: Bangalore - Hindu Population and Hindu Right Vote
244
Figure 5: Chennai - Hindu Population and Hindu Right Vote
245 Figure 6: Delhi - Hindu Population and Hindu Right Vote
246 Figure 7: Hyderabad - Hindu Population and Hindu Right Vote
247 Appendix 6
Figure 1:Marginal Effects of Hindu population on BJP success (Logit), Municipal Constituencies
Predictive Margins with 95% CIs .6 .4 .2 Pr(Dummy1Win0Loose) 0
.0907 .2513144 .4119288 .5725432 .7331576 .893772 pHindu
Figure 2: Marginal Effects of Hindu population on BJP success, (Logit), city-wide, Municipal Constituencies
Predictive Margins of city with 95% CIs 1 .8 .6 .4 Pr(Dummy1Win0Loose) .2 0
Ahmedabad Bangalore Delhi Kolkata City Name
248 Figure 3: Marginal Effects of Hindu population on BJP success (OLS), State Assembly Constituencies
Predictive Margins with 95% CIs .4 .3 .2 Linear Prediction .1 0
.1894 .3338003 .4782006 .6226009 .7670012 .9114015 pHindu
Figure 4: Marginal Effects of Hindu population on BJP success (OLS), city-wide, State Assembly Constituencies
Predictive Margins of cid with 95% CIs .8 .6 .4 .2 Linear Prediction 0 -.2 Ahmedabad Bangalore Chennai Kolkata City Name
249 Appendix 7
Image 5.3: A typical Juhapura street. The buildings in the background belong to a nearby Hindu-dominated neighborhood (Source: author’s own photograph)
250
Image 5.4: Card Playing on Election Day. Picture taken in Ahmedabad on 22nd November 2015, during the Gujarat Local Civic Elections 2015 (Source: author’s own photograph).
251
Image 5.5: Muslim and Hindu areas in Juhapura, Ahmedabad. The brick wall on the left side is routinely described by residents of the area as ‘the border’ that separates the Hindu-majority buildings in the background (Source: author’s own photograph).
252 Appendix 8
Interview Procedures
I completed interviews with thirty-eight individuals in a cross-section of Indian cities covered in this study. To ensure the collection of a diversified sample of opinions within the limited timeframe of my field research, I selected respondents that fit into the following categories: politicians, political consultants, activists, riot survivors, journalists and academics. At the end of each interview session, I asked respondents to suggest other individuals who might possess valuable information for this project. This snowball strategy helped me to select interview subjects more effectively as well as to reach a larger pool of potential interviewees.
All interviews were conducted in person, either in the interviewee’s home, office or in a private, quiet space kindly provided to me by an NGO (i.e., in the cases of interviews with riot survivors in Mumbai and Ahmedabad). Most interviews were conducted in English, except for interviews conducted with riot survivors in Mumbai and
Ahmedabad. In these two cases, I made use of both my basic knowledge of Hindi as well as the services of a translator, who mediated the interviews in either Marathi/Hindi and
Gujarati, respectively. Given the sensitivity of the topic discussed in this dissertation, I did not use a voice or video recorder during the interviews. Instead, I took detailed longhand notes, sometimes asking the interviewee to repeat a point or pause while I finished taking notes, and I immediately typed them up after returning home.
253 I employed semi-structured interviews following the standards set out by the
Rand Corporation for the U.S. Government (Harrell and Bradley 2009). For the most part, I adhered to the basic questionnaire listed below but I did leave the space open to follow explanations with additional questions based on the information brought up by the respondents and/or ask specific questions based on the respondent’s profile. My interview protocol consisted mainly of descriptive questions, but I also included structural, example and experience questions. I began the interviews by presenting myself (i.e., My name is
Diogo Lemos, I am a Ph.D. candidate in political science at the George Washington
University focusing on Indian politics) and providing basic information about the purpose of the interview, avoiding revealing information that might bias replies.
Despite the topic’s sensitivity, most interview subjects were rather candid and forthcoming in replying to my questions. Respondents who expressively asked me to remain anonymous in this dissertation are labeled as such. To ensure the safety and privacy of riot survivors, I also decided to maintain their identity confidential. Other respondents, mainly journalists and activists, were identified by their names. A list of complete interviews is also provided below.
Basic Questionnaire:
I. General Questions:
1. What is your name, occupation and age?
2. How long have you lived in this house/ward?
3. How would you describe the population living in this ward?
254 a. By Caste
b. By Religion
c. By Class
4. Has this ward/assembly constituency suffered significant changes in the religious
composition over the last thirty years? How so?
5. Overall do you think that Hindu-Muslim relations in this ward have:
a. Improved
b. Worsened
c. Remained the Same
. Can you please explain why?
II. Riots and Unmixing Questions:
6. Has this ward been affected by Hindu-Muslim riots in the last thirty years?
a. How many riots?
b. Were there fatal victims?
7. What about during the Ayodhya agitation? What was the atmosphere then?
8. Overall, do you think that Hindu-Muslim segregation has increased since
Ayodhya? Why?
9. Can you please give me an example of a way in which the riots promoted greater
Hindu-Muslim segregation?
10. Would you be willing to move to a larger/better house in a neighborhood
dominated by another religious community?
255 11. Do you think that politicians were directly involved in increasing segregation
between Hindus and Muslims?
III. Unmixing and Elections Questions:
12. How would you describe electoral competition in this ward/assembly
constituency?
13. How has electoral competition in this ward/assembly constituency evolved over
the past thirty years?
14. Do you think that the religious composition of the electorate shapes the electoral
outcomes in this ward/assembly constituency?
15. (If respondent agrees with unmixing hypothesis) Do you think that the BJP/SS has
deliberately promoted greater Hindu-Muslim segregation to its electoral
advantage?
256 List of Interviews:
. Interview with Father Cedric Prakash, Ahmedabad, November 2015
. Interview with Riot Survivor 1, Ahmedabad, November 2015
. Interview with Riot Survivor 2, Ahmedabad, November 2015
. Interview with Riot Survivor 3, Ahmedabad, November 2015
. Interview with Riot Survivor 4, Ahmedabad, November 2015
. Interview with Riot Survivor 5, Ahmedabad, November 2015
. Interview with Riot Survivor 6, Ahmedabad, November 2015
. Interview with Riot Survivor 7, Ahmedabad, November 2015
. Interview with Riot Survivor 8, Ahmedabad, November 2015
. Interview with Riot Survivor 9, Ahmedabad, November 2015
. Interview with Dr. Kiran Desai, Surat, November 2015
. Interview with Activist, Surat, November 2015
. Interview with Victim of Segregation, Surat, November 2015
. Interview with Dr Bandukwala, Vadodara, November 2015
. Interview with Abdul Rakhib Zakir, Corporator, Ward 78 (Pulakeshi Nagar),
Bangalore, November 2015
. Interview with Sampath Raj, Corporator, Ward 47 (Devara Jeevanahalli),
Bangalore, December 2015
. Interview with Samar Halarnkar, Journalist, Bangalore, December 2015
. Interview with Aakar Patel, Executive Director of Amnesty International,
Bangalore, December 2015
. Interview with Avinash Gowda, Takshashila, BPAC, Bangalore, December 2015
257 . Interview with Academic, Bangalore, December 2015
. Interview with A. Sivasankaran, Advisor, Jago Federation, Bangalore, December
2015
. Interview with Asif Ahmed Zakaria, Corporator, Ward 95 (Bandra West),
Mumbai, November 2015
. Interview with Tanveer Patel, Corporator, Ward 97 (Lilavati Hospital – Bandra
Bus Terminal), Mumbai, November 2015
. Interview with Ram Punyiani, Activist, Mumbai, November 2015
. Interview with Shyama Kulkarni, Activist, Mumbai, November 2015
. Interview with Riot Survivor 1, Mumbai, October 2015
. Interview with Riot Survivor 2, Mumbai, October 2015
. Interview with Riot Survivor 3, Mumbai, October 2015
. Interview with Riot Survivor 4, Mumbai, November 2015
. Interview with Riot Survivor 5, Mumbai, November 2015
. Interview with Riot Survivor 6, Mumbai, November 2015
. Interview with Riot Survivor 7, Mumbai, November 2015
. Interview with Riot Survivor 8, Mumbai, November 2015
. Interview with Naresh Fernandes, Journalist, Mumbai, November 2015
. Interview Prof. P.K. Jahan, TISS, Mumbai, November 2015
. Interview with Prof. Ranu Jain, Mumbai, November 2015
. Interview with S.Y. Quraishi, New Delhi, December 2015
258 Appendix 9
Map of Ahmedabad
259