Pi Sigma Alpha Undergraduate Journal of Politics Fall 2019

Vol. XIX No. 2

Fall 2019

PI SIGMA ALPHA

Undergraduate Journal of Politics

Oakland University

Pi Sigma Alpha Undergraduate Journal of Politics

The Pi Sigma Alpha Undergraduate Journal of Politics (ISSN 1556-2034) is published biannually by the Nu Omega Chapter of Pi Sigma Alpha, Oakland University, Department of Political Science, Varner Hall, Room 418, 371 Varner Drive, Rochester, MI 48309-4485.

The Journal is funded by Pi Sigma Alpha, the National Political Science Honor Society, 1527 New Hampshire Avenue, NW, Washington, DC 20036, http://www.pisigmaalpha.org.

The Pi Sigma Alpha Undergraduate Journal of Politics was founded in the Spring of 2001

by Delta Omega Chapter of Pi Sigma Alpha at Purdue University, under the name The American Undergraduate Journal of Politics and Government. With the sponsorship of Pi Sigma Alpha, the National Political Science Honor Society, the name of the Journal was changed to The Pi Sigma Alpha Undergraduate Journal of Politics as of the Fall 2004 edition.

Electronic editions of the Journal are available online at http://www.psajournal.org. For further information, please contact Dr. Terri Towner at Oakland University (towner@ oakland.edu).

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the written permission of the editors and faculty advisors of The Pi Sigma Alpha Undergraduate Journal of Politics.

The Pi Sigma Alpha Undergraduate Journal of Politics and content appearing there-in is copyrighted by Pi Sigma Alpha. While holding these rights, Pi Sigma Alpha does not exert editorial or other control over the content of the Journal or the decisions or actions of its staff in the course of normal business operations. As such, Pi Sigma Alpha neither asserts nor accepts responsibility for the content or actions of staff of the publication in the normal course of business as the customs and usages of the law allow.

All assertions of fact and statements of opinion are solely those of the authors. They do not necessarily represent the views of Pi Sigma Alpha, the National Political Science Honor Society, the Editorial Board, the Advisory Board, the Faculty Advisors, Oakland University, or its faculty and administration.

COPYRIGHT Š 2019 PI SIGMA ALPHA. ALL RIGHTS RESERVED

2

Š Pi Sigma Alpha 2019

Vol. XIX No. 2 • Fall 2019

The Pi Sigma Alpha Undergraduate Journal of Politics Fall 2019 Volume XIX

Number 2 Thirty-Seventh Edition

Christina Pearl Walker Ghazi Ghazi Brooke Hebb Tanir-Vefa Avci Dr. Terri L. Towner

Scheduling/Content Editor Outreach Editor Centennial Editor Cover Designer Faculty Advisor and Editor

Editorial Board Jacob Adams Julia Alexander Tanir-Vefa Avci Ghazi Ghazi Mina Ghobrial AjayPal Gill Brooke Hebb Benjamin Hume

Eric Mehmetaj Jamie Lee Parker Destinee Rule Christina Pearl Walker Johnathan Wertheimer Hunter Willis Emily Zwicker

Advisory Board Dr. Robert Alexander Dr. Nicole Asmussen Mathew Dr. Cristian Cantir Dr. Rosalee Clawson Dr. Erik Cleven Dr. Cody Eldredge Dr. Alan Epstein Dr. Stephen Farnsworth Dr. Megan Hershey Dr. Dwaine Jengelley Dr. Baris Kesgin Dr. Kellee Kirkpatrick Dr. John Klemanski

Dr. Jeanine Kraybill Dr. Paulette Kurzer Dr. Laura Landolt Dr. Anthony Nowns Dr. Daniel O’Neill Dr. Zoe Oxley Dr. Ronald Rapoport Dr. Jo Reger Dr. Jaime Settle Dr. Harry “Neil” Strine Dr. Peter Trumbore Dr. Kali Wright-Smith

© Pi Sigma Alpha 2019

3

Pi Sigma Alpha Undergraduate Journal of Politics

Editor’s Preface to the Fall Edition The Pi Sigma Alpha Journal of Undergraduate Politics would first and foremost like to acknowledge all those individuals and institutions which make the publication of this Journal possible semester after semester and year after year. The Journal has continued to grow in terms of submissions, quality, and prestige. Submissions to the Fall 2019 issue exceeded over 70 manuscripts, representing a diverse array of topics. We greatly appreciate all those who have submitted their work to the Journal in the hope of being published. The articles published herein exemplify a high quality sample of the types of undergraduate research being conducted across the country.

Although the publication is a completely student-run endeavor, the efforts of the student Editorial Board are guided and supported by a number of individuals and institutions which we would like to thank. First, we would like to thank the Pi Sigma Alpha Executive Council and Executive Committee whose vision and financial support has maintained the quality and direction of the Journal. Second, we extend our appreciation to the Oakland University College of Arts and Sciences and the Political Science Department.

Third, we would like to thank the Faculty Advisory board whose constructive reviews ensure the articles published herein meet a consistent standard of quality. Finally, we extend tremendous thanks to Editorial Board Faculty Advisor Terri Towner, who has dedicated her time and energy to ensure the integrity of the Journal continues to exceed the standards of excellence set by the editors of its previous editions.

The Editorial Board at Oakland University is proud to present the Fall issue which contains a well-rounded set of articles with varied methodological approaches and topical matter. The publishing process for the Fall issue followed a relatively smooth path from submission to publication, and the Nu Omega Chapter and Oakland University wish the readers of this issue a similarly enjoyable time.

Best, The Editors

4

Š Pi Sigma Alpha 2019

Vol. XIX No. 2 • Fall 2019

Submission of Manuscripts The Journal accepts manuscripts from undergraduates of any class and major. Members of Pi Sigma Alpha are especially encouraged to enter their work. We strive to publish papers of the highest quality in all areas of political science.

Generally, selected manuscripts have been well-written works with a fully developed thesis and strong argumentation stemming from original analysis. Authors may be asked to revise their work before being accepted for publication.

Submission deadlines are October 1st for the Fall edition and February 1st for the Spring edition.

Manuscripts are accepted on a rolling basis; therefore, early submissions are strongly encouraged.

To submit your work, please email psajournalou@gmail.com with an attached Word document of the manuscript. Please include your name, university and contact details (mailing address, email address, and phone number) in a separate document.

Submitted manuscripts must include a short abstract (approximately 150 words), citations and references that follow the APSA Style Manual for Political Science. Please do not exceed the maximum page length of 35 double-spaced pages, which includes references, tables, figures, and appendices.

The Journal is a student-run enterprise with editors and an Editorial Board that are undergraduate students and Pi Sigma Alpha members at Oakland University.

The Editorial Board relies heavily on the help of our Faculty Advisory Board consisting of political science faculty from across the nation, including members of the Pi Sigma Alpha Executive Council. Due to the time committed to the manuscript review process, we would like to remind students to submit only one manuscript at a time.

Please direct any questions about submissions or the Journal’s upcoming editions to our editors at psajournalou@gmail.com.

© Pi Sigma Alpha 2019

5

Pi Sigma Alpha Undergraduate Journal of Politics

Contents Before Horror Strikes: Economic Disparity, Anti-elite Sentiment, and the Onset of Genocide ....................... 7 Anthony Ghaly, Rutgers University-Newark “Putin Down Protest”: Is Widespread Mobilization Possible in the Shadow of the Oil Curse?....................... 21 Chase LaSpisa, Oklahoma State University Rural Values in Montana ............................................................................................................................. 30 Hailey Oestreicher, Carroll College Hitler’s Hand in the 21st Century: How Holocaust Collaboration in the 1940’s Shapes Modern Anti-Semitism.............................................................................................................................................. 42 Jenna Bisbee, Saint Anselm College

6

© Pi Sigma Alpha 2019

Before Horror Strikes: Economic Disparity, Anti-elite Sentiment, and the Onset of Genocide Box

Before Horror Strikes: Economic Disparity, Anti-elite Sentiment, and the Onset of Genocide Anthony Ghaly, Rutgers University-Newark A central goal of scholarship analyzing genocide has been to understand what “never again” might look like in practice. This paper contributes to this conversation and the normative goal of prevention by employing a comparative analysis of four unique occurrences of genocide: Cambodia, Rwanda, Darfur, and The Holocaust. In this most different case comparison, I find that anti-elite sentiment, inspired and fueled by economic stressors, precipitated genocide. Further, I argue that the direction of such sentiment is not indicative of who will be the victim of genocidal intent or acts: surprisingly, anti-elite sentiment can result in both elites and non-elites becoming the victims of genocide.

INTRODUCTION

T

hroughout history, humanity has demonstrated a proclivity for self-destruction. Moreover, those atrocities which target the weakest members of society are often the most terrible in nature.

Genocide, described by Raphael Lemkin, the term’s originator, as being “a coordinated plan of different actions aiming at the destruction of essential foundations of the life of national groups, with the aim of annihilating the groups themselves,” is thought to exemplify humans’ capacity for inflicting terror and horror on their fellow humans (Lemkin, Power, and Schabas 2008). Apart from understanding what this horror looks like, scholars have sought to understand the primary causes of genocide within the goal of prevention. What causes has this literature pinpointed, and what more can we learn in a small-n analysis of genocides in dramatically different contexts?

This paper will explore the topic of genocide and its perpetration across four unique occurrences. I first analyze the political genocide of Cambodia and ethnic cleansing in Rwanda. The comparative analysis of these two countries focuses on the individual components of the Cambodian and Rwandan political and historical backgrounds, respectively, in order to properly assess the factors which precipitated genocide. Essentially, as each country presents distinct victims, regions, and sociopolitical factors, this paper also seeks to understand why, despite so many differences, did Cambodia and Rwanda converge on an outcome of genocide. The hypothesis generated by the analysis of the Cambodian and Rwandan cases is then tested and refined in two additional cases of genocide: Darfur and the Holocaust. This second comparative analysis yields a more precise understanding of the social, economic, and political dynamics that make countries especially vulnerable to genocide.

CONTRIBUTIONS

Genocide is understood by scholars as the pinnacle of mass violence and has drawn intense study from those who seek to understand the worst outcomes of inter-group conflict (Schabas 2006; Wald 2007). Scholars who study genocide as a phenomenon of human activity have sought to identify the etiology of genocide and, in its most ambitious iterations, have attempted to identify pre-conditions of genocide within the normative project of prevention. Genocide scholars have pointed to various necessary circumstances for the occurrence of genocide which have predominately fallen into three distinct categories: (1) theories of social or ethnic tension, which often note the existence of an elite class that struggles to maintain power within or over a state; (2) ideological explanations, which establish the existence of a nationalistic, purist, or other prevailing ideology that infiltrates the social sphere prior to a period of genocide; and (3) theories of economic distress, which point to the fluctuations of economic conditions as being necessary to a genocide.

Scholars who have pointed to social and ethnic divisions have commonly utilized theories of social mobilization and other similar sociological approaches in their research. In his work, Melson (1996) points to ongoing social tensions as being an important precursor to genocide, arguing that the threat of social mobilization of minorities can inspire genocidal sentiments amongst majority groups. Others have built on this, Midlarsky (2005) specifies that the perpetrators of genocide are most often elite groups acting on fears of social mobilization and the threat of displacement by minorities.1 Campbell’s (2009) research extends Melson’s (1996) foundational work, arguing that genocide is used as a strategic tool to enforce social dominance upon such minorities. Essentially, this scholarship identifies perpetrators and victims of genocide as groups pitted against each other in

© Pi Sigma Alpha 2019

7

Pi Sigma Alpha Undergraduate Journal of Politics

social conflict, with one of these groups often classified as an elite class.

Other scholars, including Mamdani (2001), Palmer (2015), and Harff (2003), have specifically examined ethnicity as the key societal cleavage between elite and non-elite groups.

McDoom (2014) uniquely links this concept of ethnic tension to the role of elite power, positing that ethnic segregation instigates conflict from below while an elite class consolidates power from above, thus building upon both Midlarsky (2005) and Harff (2003) by presenting genocidal acts as elite ethnic groups’ reactions to vulnerability and loss. Williams’ (2016) research also builds on that of Harffs’ (2003), but posits that an upheaval of an authoritarian government or a divisive social ideology can push such vulnerability to become genocidal in nature. Overall, the literature on ethnic tension and its role in genocide operates from a nearly identical perspective as those who use social mobilization and inequality theories to explain the phenomenon: both sets of scholars identify the threat of minority strength and elites’ fear of their loss of power as critical to the onset of genocide.

The second predominant body of literature addressing the question of “why genocide occurs?” analyzes society’s prevailing ideology in the years preceding genocidal conditions.

Scholars examining this tradition highlight the importance of “indoctrination,” “otherness,” or “hateful and incendiary speech” in the instigation of mass violence. The ideology of nationalism has also been specifically explored: using a criminological approach, Alvarez (2001) argues that the common precursor to 21st century genocides is a staunch nationalism that permeates the socio-political sphere of a country. However, most scholars within this literature have written more directly about the role of divisive ideology prior to genocide. Perhaps most prominently, Fein (1984, 1993) and Staub’s (1989) research has been foundational to the discourse on ideology and genocide. Both explore the concept of dehumanization, which they argue creates a moral permissibility to attack victims in the minds of perpetrators.2 Murray (2014) and Straus (2012) have each built on this foundation in their respective works: Murray explicitly analyzes the concept of “otherness” and its role in the dehumanization process, while Strauss instead analyzes the role of dangerous speech in the indoctrination of susceptible societies. Straus’s later scholarship (2015) explains this indoctrination as a “founding narrative” that he argues is “the quintessential element in the causal story that underpins cases of genocide.”

More recent scholarship, such as Maynard and Benesch’s (2016) piece on hate speech and Richter, Markus, and Tait’s (2018) article on indoctrination, has continued the research by Fein (1984, 1993), Staub (1989), and Straus (2012, 2015) in the modern discourse on genocidal ideology.

Although a smaller voice in the scholarship on genocide, those who point to economic conditions, such as stability and equality, have contributed much to the understanding of genocide’s etiology. Most recently, Anderton’s (2014) research 8

has called on economists to address questions of genocide with as much fervency as other social science disciplines, coining the lack of literature on the subject of the “genocide gap.”

Anderton (2014) identifies this literature as not only a subset of the multidisciplinary scholarship on genocide, but as part of the broader literature referred to as conflict economics.

Amongst the earlier literature which examines genocide as a case study of conflict economics, Scully’s (1997) scholarship posits that genocide is an inherently economic issue and, thus, is explainable using theories of economics, such as the law of demand.3 Since then, economic theories of genocide have grown considerably, with genocide scholars using economic indicators to explain the onset of genocide, or lack thereof.

Kisangani and Nafziger (2007), for instance, build on Scully’s (1997) research by analyzing the role of both domestic and international economic indicators in the onset of democide,4 while Anderton’s (2016) most recent work offers a wide-ranging account of the literature on economics and genocide.

Esteban, Morelli, and Rohner (2015) have also built on Scully’s (1997) research, through their examination of the role of natural resources and rent sharing in the occurrence of mass killings. The Rwandan Genocide has been at the center of many such analyses of natural resources, given the country’s notably harsh economic conditions prior to its genocide.5 Percival and Homer-Dixon’s (1996) scholarship was foundational to such scholarship on Rwanda, as they explored how agricultural and natural resource indicators, such as rainfall, might help explain the rise of violent conflict in the country. Similarly, Hendrix and Salehyan (2012) expand on this analysis more generally in their work by studying the relationship between natural resource indicators and social conflict in other African regions, such as Darfur, Sudan.

I make two contributions to the literature on genocide.

First, I challenge the unidirectional thinking about anti-elite sentiment and argue that divisive social or ethnic tension can make both elites and non-elites vulnerable to genocidal attacks. This conception of anti-elite sentiment is a nuanced aggregation of socio-ethnic and economic explanations: for example, while wealthier groups are often ethnically distinct from poorer groups, this is not always the case. My theory creates generalizability between ethnically homogeneous and heterogeneous cases. Second, I bridge the literature about socio-ethnic precipitants to genocide with the economic explanations by arguing that anti-elite sentiment, inspired and fueled by economic stressors, has been a precursor to genocide in four key cases. By identifying anti-elite sentiment as a common precursor to genocide, I take a comparative approach and build primarily on the ideas presented by Midlarsky (2005) and Williams (2016). I argue that this sentiment may arise in states that have either divisive social tensions or historically segregated ethnic groups. However, such sentiment is not indicative of the direction of the genocidal acts; in other words, elites who are victims of such sentiment may become either perpetrators or victims of genocide.

© Pi Sigma Alpha 2019

Before Horror Strikes: Economic Disparity, Anti-elite Sentiment, and the Onset of Genocide Box

Additionally, while Williams (2016) posits that such aggravated environments must be combined with either an ideology of division amongst groups or the upheaval of government, I argue that in place of either additional condition, economic difficulties can act as the catalyst for pushing an already socially or ethnically divided society towards genocidal acts. Similarly, Midlarsky (2005) acknowledges that economic stressors inspire elites to perpetrate genocidal acts against minorities. I add to this theory by indicating that economic stressors inspire explicitly anti-elite sentiment, rather than simply anti-minority sentiment.

METHODOLOGY AND CASE SELECTION

I utilize a most-different comparative case analysis to examine the factors which preceded the Cambodian and Rwandan genocides. By selecting Cambodia and Rwanda, as opposed to other modern-day genocides, I present two nations in which the phenomenon of genocide manifested in fundamentally different contexts and in different historical moments: Cambodia is an ancient, Indochinese kingdom located in Southeast Asia, while Rwanda is a young, small republic landlocked in Central Africa. Through juxtaposing these cases, I generate hypotheses about which pre-genocide indicators may lead to genocidal acts. I generated these six variables by operationalizing the previously-cited literature: 1.

Political Background and Governmental Structure

2. Colonial History 3. Ethnic or Social History

The Darfur conflict presents as an ethnic cleansing somewhat similar to its Rwandan counterpart: both occur in African countries plagued with histories of colonialism and internal ethnic tension. Cambodia and the Holocaust also present somewhat similar circumstances, given their explicit sharing of politically motivated genocidal ideologies. If the same independent variables emerge across and between these very different cases – and also hold true in more similar couplets – we gain a strong sense that the identified explanations (antielite sentiment activated by economic difficulties) may be conceptually salient and important for understanding what precipitates genocide.

The concept of anti-elite sentiment is a critical component in my analysis of Cambodia, Rwanda, Darfur, and the Holocaust, and hinges on elite as a subjective and perceptive, rather than an objectively defined, category. As such, I define anti-elite sentiment as a subjective, collective attitude of resistance and/or resentment exhibited by selfidentified non-elites towards groups who are perceived to be elite. Anti-elite sentiment, therefore, can exist independently of whether its recipients are quantifiably and demonstrably elite – that is, perceived elites may, in theory, be poorer as a group than self-identified non-elites, as was arguably the case in Weimar Germany. This conceptualization of anti-elite sentiment acknowledges that regardless of whether social, ethnic, or religious groups maintain any substantive privileges within a society, the collective perception of their being “elite” has the potential to trigger anti-elite attitudes. Thus, when examining the role of anti-elite sentiment as a motive for violence, the objective accuracy of who is or is not “elite” is inconsequential in cases where such sentiment is already salient.

Case Study #1: Generating Hypotheses

4. Economic Health, Stability, and Equality

Cambodia

5. Genocidal Ideology 6. Modality of Genocide After analyzing each of the variables independently, I assess the degree of convergence, if any, across the variables, and evaluate the extent to which the converging variables played a role in precipitating the onset of genocide. At the conclusion of the first case study, the salient variables are tested in the Darfur genocide and the Holocaust. I selected these cases because they, too, are most different: Darfur is a small region in the west of Sudan which has experienced genocide in the midst of domestic religious and social turmoil, while the Holocaust took place within large European superpowers in the wake of complex international conflicts. In addition to being most different from each other, however, I also gain increased analytical leverage because they provide some withincase reliability. In my discussion, I consider two analytical pairs: Darfur and Rwanda; and Cambodia and the Holocaust.

In order to properly analyze the Cambodian genocide, we should first understand the political background of Cambodia in the years preceding the rise of the Khmer Rouge.

Following 90 years of French colonial subjugation, Cambodia established its independence in 1953, becoming the Kingdom of Cambodia (Alvarez 2001; BBC News 2018). In terms of governmental structure, the Cambodian government is classified as a parliamentary constitutional monarchy, with a monarch serving as head of state and a prime minister serving as the head of government (Central Intelligence Agency 2018; hereafter CIA). As a newly established kingdom, Cambodia was ruled by Norodom Sihanouk from 1941-1970, who first ruled as king, then prime minister, and, finally, as head of state (Alvarez 2001; BBC News 2018).

Sihanouk’s rule was characterized by his explicit oneparty rule and quick consolidation of power, which was accomplished through a national referendum granting him the title of Head of State of Cambodia, an office of his invention with no fixed term (Chandler 1993). Sihanouk’s political

© Pi Sigma Alpha 2019

9

Pi Sigma Alpha Undergraduate Journal of Politics

opposition became increasingly angered with his autocratic regime and subsequently sought a coup d’état to remove him from power. The coup, although ultimately successful, had created anti-western sentiments within the political climate of the country. The Khmer Rouge, a far-left communist party of Cambodia, aligned itself with the fallen regime and fought the United States over control of the newly unstable government.

Soon after, the Khmer Rouge seized power and implemented a new, communist regime, which exercised explicit anti-western practices (United States Holocaust Memorial Museum n.d.; hereafter USHMM). The rule of the Khmer Rouge lasted from 1975-1979, during which time the regime was responsible for over 1.7 million deaths, or 25% of the Cambodian population (End Genocide n.d.). Ultimately, by analyzing Sihanouk’s rise to power, it can be argued that the failure to build democratic institutions, driven by corrupt, tyrannical leadership, gave way to the genocide that followed.

The history of Cambodian culture, as with any society, is deeply intertwined with ethnicity and religion. Cambodian society has long been ethnically homogeneous: the majority of Cambodian citizens are ethnically Khmer, with relatively small minorities of Chinese, Muslim Cham, and Vietnamese immigrants (CIA 2018). At the time of the genocide, these minorities constituted 15% of the population; by 1979, however, the vast majority of Vietnamese and the ethnoreligious Cham had been either exterminated or expelled from the country, while nearly half of the Chinese population was killed off (Kissi 2004). The rhetoric of the Khmer Rouge was explicitly anti-immigrant, as the regime insisted that only 1% of the population was not of Khmer origin, in order to minimize minorities’ place in society (Cultural Survival n.d.).

As part of their victimization, Cambodia’s ethnic minorities became the subjects of xenophobic and racist propaganda, fueling genocidal attitudes in the general Cambodian population through the use of media and radio (Alvarez 2001).

It is clear, therefore, that ethnicity played an active role in the Cambodian genocide, despite the country’s traditionally homogeneous population.

The Cambodian social hierarchy was especially stringent prior to the genocide, as a person’s position on the societal ladder was based upon factors such as “age, gender, familial background, ethnicity, birth order, occupation, political influence, power, education, benevolence, religious piety, and personal character” (Hinton 2005, 186). Additionally, Cambodian culture regarded inequality as natural amongst its people, mandating that each person should pay reverence to those of higher social classes (Kiernan 2008). Upon assessing the objectives of the Cambodian genocide, one finds that the Khmer Rouge sought to purify Cambodia of its classist system. Such a revolutionary goal, according to the Khmer Rouge, necessitated radical change – a change which meant that Cambodians of all different backgrounds were persecuted and victimized (USHMM n.d.). The regime targeted educated professionals, medical personnel, political 10

dissidents, former military officers, the wealthy, and, as previously discussed, ethno-religious minorities; what these victims shared, essentially, was a perception of their elite status and their potential to challenge the Cambodian government.

Of these victims, millions were thrown into labor camps and “killing fields” (Beachler 2009) One scholar coined the term “politicide”, referencing the victimization of any political opposition during the rule of Khmer Rouge (Harff and Gurr 1988; Kiernan 2008; Midlarsky 2005). Given the broad range of targets for this genocide, it is evident that the perpetrators sought to reimagine Cambodian society. This included the removal of social classes, one of the most prominent fixtures of Cambodian society prior to the genocide (USHMM n.d.). The Khmer Rouge sought the creation of a utopia in which social hierarchy ceased to exist, disposing of any group that could present resistance.

The perpetrators of the Cambodian Genocide founded their political ideology on a communist economic agenda.

To what extent did this economic agenda, and the economic conditions of pre-genocide Cambodia, precipitate the rise of the Khmer Rouge? Under the rule of Sihanouk, Cambodia’s foreign policy was marked by political and economic neutrality, which notably spurred domestic economic growth through the influx of sizable aid from international allies. When the Khmer Republic seized control in 1970, cronyism and corruption became rampant in the Cambodian government. The humanitarian aid, which was necessary for the country’s 80% peasantry, was quickly diverted towards funding the lavish lives of the elite (Kamm 2011). By the end of Khmer Republic in 1975, the already large disparity between the rich and poor had grown drastically (Gardere 2010). The Khmer Rouge regime that followed and reigned until 1979 sought to transform the economic landscape of Cambodia and saw communist economic principles as the key to this transformation. While there were not dramatic economic shocks in the years preceding genocide, it is clear that the slow decline of the Cambodian economy in those years—manifested in the gaping inequality and harsh economic conditions under the Khmer Republic— inspired the economic ambitions of the Khmer Rouge as well as the regime’s determination to realize such ambitions.

Rwanda

As with Cambodia, it is important first to understand the genocide of Rwanda in its political context. In the wake of Belgian colonial rule, Rwanda’s independence took the form of a parliamentary democracy. The first administration in the newly formed Republic of Rwanda, of which Grégoire Kayibanda was the first democratically elected president from 1962-1973, was categorized by government-supervised oppression of the Tutsi in all aspects of public life, with the worst of such oppression culminating in the rounding up and killing of thousands of Tutsi people (Golooba-Mutebi 2008). For the 17 years that followed, Rwanda was under the autocratic regime of President Juvénal Habyarimana, who

© Pi Sigma Alpha 2019

Before Horror Strikes: Economic Disparity, Anti-elite Sentiment, and the Onset of Genocide Box

rose to power as the military leader of the coup d’état which overthrew Kayibanda (Gourevitch 2015). The civil war of Rwanda began in 1990 and resulted from heightened tensions between the Tutsi and the Hutu. Over 3 months in 1994, the Tutsi minority of Rwanda faced genocide at the hand of the Hutu majority. The Tutsi were the primary members of the newly formed Rwandan Patriotic Front (RPF), a group that sought justice for the thousands of Tutsi people forced to flee Rwanda over the prior 30 years. The group also sought to challenge the Rwandan government and the one-party, dictatorial rule of Habyarimana (Encyclopedia Britannica 2018). When the President’s plane was shot down in 1994, the government associated the attack with the RPF, and in their public response, framed the RPF as the representative of all Tutsi people in Rwanda. An organized campaign for Hutu citizens to attack their Tutsi neighbors soon followed, resulting in the extermination of over 500,000 Tutsi people in 100 days (Human Rights Watch 1999; hereafter HRW).

The government also targeted moderate Hutu politicians who opposed violence against the Tutsi, such as Prime Minister Agathe Uwilingiyimana (United Nations n.d.). The political propaganda spread by the Hutu government, paired with its utilization of citizen-led militias and military force, indicates that the Rwandan government was desperate to maintain power, utilizing the country’s ethnic conflict as a means to an end (Storey 1999). By provoking ethnic conflict among citizens, the government was able to benefit from national paranoia, thus stabilizing its firm grip on political power.

While European colonialism was vital to the rise of genocidal conflict in Rwanda, the country did have a history of ethnic divide in its precolonial years. Ethnicity played an important role in establishing social rank in their precolonial class system. The system encouraged traditional trade between the Hutu and Tutsi, and it was common for the Tutsi to provide military service in exchange for Hutu land and cattle.

Such a tradeoff was based primarily on traditional Rwandan mythology and religion, which held that the Hutu were natural healers and farmers, while the Tutsi were inherent leaders.

Additionally, according to this system, the monarchy of the Kingdom of Rwanda was Tutsi-controlled, allowing the social system to benefit the Tutsi minority well before the arrival of colonists through the widespread control of land and cattle within the Tutsi aristocracy. Moreover, the disparity between the Hutu and Tutsi became so substantial that both groups became more associated with distinct socio-economic status than with historical, ethnic differences. In short, Hutu and Tutsi became not only markers of ethnic identity, but also came to signify divergent social status.

The ethnic tensions that would eventually lead to genocide were first deepened through Belgian colonial rule.

The Belgian reign favored the Tutsi minority, continuing the systemic disadvantages for the Hutu people. The Belgians mandated the registration of all Rwandans’ ethnicities, a tactic which was used to actively favor the Tutsi and establish

the minority’s dependence on Belgian support. Scholars note this implementation of European-style racism into Rwandan culture as a primary determinant of the eventual genocide (HRW 1999). As soon as Belgium relinquished imperial rule over Rwanda in 1962, the Hutu backlash against the oncefavored Tutsi ensued (End Genocide n.d.), and the Hutu population actively blamed the Tutsi for various political or economic issues (Smeulers and Hoex 2010). These accusations were used to persecute the Tutsi in the years that followed, causing thousands of Tutsi people to die and hundreds of thousands more to flee Rwanda (Gerhart, Prunier, and Destexhe 1996). Given this forced exodus of the Tutsi people, which was fueled by European influence and the long-lasting effects of colonialism, one can point towards outside forces as having laid the foundation for genocide in Rwanda.

While the Cambodian economy experienced a slow decline in economic conditions prior to genocide, the economy of Rwanda enjoyed steady growth through the 1960s and 70s (The World Bank n.d.). Soon after, however, the falling global prices of Rwandan agriculture, a pillar of Rwanda’s economy, coupled with the harsh systemic changes mandated by the International Monetary Fund’s policies, caused the Rwandan economy to suffer severely. In 1990, the government implemented several structural economic changes, including higher fees on market goods and a reworking of the country’s agricultural market. Although new social safety nets were lightly implemented to alleviate the shocks to the poorer social classes, the changes increased economic disparity and soon became an issue that exacerbated socio-ethnic tensions (Storey 1999). By the time the civil war began, market erraticism had already caused severe economic instability. Furthermore, the economic shocks to the Rwandan economy, caused by both domestic and international systemic changes, was a likely cause of the social instability that culminated in genocide in Rwanda.

The Sixth Variable

The final distinction to be made between the cases of genocide in Cambodia and Rwanda is the nature of the genocidal acts themselves. It is crucial to understand the way in which the genocides manifested themselves in either case, in order to determine the ways in which they were similar.

While scholars have categorized the typologies of genocide in various ways, most scholars incorporate some mix of the genocidal ideology, the victims of the atrocity, and the perpetrators of the genocide in order to understand genocide’s core characteristics (Ayvazyan 2012; Chalk and Jonassohn 1990; Meierhenrich 2014; Moses 2008; ).6 The Cambodian genocide was a highly organized, centrally-coordinated effort to restructure society systematically (USHMM n.d.). The Khmer Rouge initiated a system of brainwashing and re-education in order to stifle dissent within the public; all those who refused to be re-educated were sent to the killing fields for execution.

The general public was the primary target of persecution from government-backed military forces (Atkinson 2013). In

© Pi Sigma Alpha 2019

11

Pi Sigma Alpha Undergraduate Journal of Politics

contrast, the Rwandan genocide can be described as retributive, as the perpetrators of the genocide were both political actors as well as members of the general population who sought to cleanse their society ethnically. Thousands of Tutsi died at the hands of their once peaceful Hutu neighbors, and because of this, the genocide is considered to have been perpetrated by the masses (Straus 2004). The Cambodian case, therefore, can be understood as a governmentally enacted and perpetrated genocide. In contrast, the Rwandan case was as a retributive genocide of the masses, supported and carried out by the nongovernmental Hutu population (Smith 1999). Ultimately, this typological divergence in the Cambodian and Rwandan cases is fundamental to understanding how the causes of genocide actually converge amongst the four case studies.

Case Study #1: Analysis

The cases of genocide within Cambodia and Rwanda diverge on all but three of the relevant independent variables.

The Cambodian government at the time of the genocide, for instance, was notable for its socioeconomic utopian ambitions and committed atrocities on political dissidents. Furthermore, the Cambodian genocide was fundamentally ideological, as the Khmer Rouge regime attempted a harsh restructuring of Cambodian civilization. Although the motivation for the Rwandan genocide was also grounded in a desire for political prowess, it can be argued that there was a racist, ethnocentric hatred that fueled the eventual ethnic cleansing. Rwanda’s ethnic cleansing, therefore, may have been singularly caused by decades of ethnic tensions fostered by European influence.

The modalities of both genocides were also quite different, as the Cambodian massacres were perpetrated by a governmental regime while Rwanda’s ethnic cleansing was carried out by nonmilitary Hutu citizens. Although each of these genocides varies significantly on the independent variables, they converge on a

shared outcome of purposeful genocidal acts. As a most different case comparison logic dictates, it is imperative to identify the factors which are shared between these two cases. As presented in Table 1, by analyzing the six variables that were assessed in the Cambodian and Rwandan cases, one finds a certain level of commonality, or convergence, in three distinct areas: 1. Colonial History 2. Economic Health, Stability, and Equality 3. Ethnic and Social History The convergence of these variables, however, does not indicate the actual precursors existing within these variables, nor the degree to which those precursors actively precipitated genocide. Thus, we must drill into these variables to understand the mechanisms and processes associated with them that led to genocidal acts.

Degrees of Convergence

By further analyzing the three converging variables, one finds the existence of three specific precursors which may have precipitated either case of genocide: 1. Socio-economic consequences of colonialism.

2. Economic inequality brought about through consistent or sudden economic instability.

3. Anti-elite sentiment spurred by social or ethnic inequality.

The following analysis, therefore, will explore the involvement and degree to which each precursor precipitated genocide.

In terms of each country’s colonial history, both Cambodia and Rwanda faced subjugation at the hands

Table 1: The Independent Variables Political Background/ Governmental Structure

Colonial History

Ethnic/Social History

Economic Health, Stability, & Equality

Genocidal Ideology

Modality of Genocide

Cambodia

Parliamentary Constitutional Monarchy/ Autocrat preceding genocide

Colonized:

by French

Deep Division: Socially Stringent Hierarchy

Economic Inequality: Long-term decline

Politicide

Systematic/ Centrally Organized

Rwanda

Parliamentary Democracy/ Autocrat during genocide

Colonized:

by Belgium

Deep Division: Ethnic Tension

Economic Inequality: External Shocks

Ethnic Cleansing

Retributive Genocide of the Masses

Note: Converging variables shown in italics.

12

© Pi Sigma Alpha 2019

Before Horror Strikes: Economic Disparity, Anti-elite Sentiment, and the Onset of Genocide Box

of European imperialists: the French and the Belgians, respectively. The 90-year colonial era of Cambodia, in which the country was occupied as a protectorate within French Indochina, is characterized by its relatively peaceful occupation

by France. At first, the French maintained relatively close control over the affairs of the country, while protecting the country from its more dangerous neighbors (Tully 2017).

Moreover, as a protectorate, Cambodia enjoyed certain benefits such as improved agriculture and industrialization. French rule had its negative aspects as well, however, including political suppression, a broken judiciary, and an unforeseen amount of French control over Cambodia’s economy. What had originally been understood as a mutually beneficial relationship between the two countries soon revealed itself to be the slow implementation of colonialism (Chandler n.d.). Still, scholars note that Cambodia’s survival as an independent state could not have been guaranteed if not for France’s protection over the country.

Rwanda’s 30 years as a Belgian colony, however, demonstrated the worst of European imperialism (BBC News 2018). Belgium instituted and exacerbated ethnic divisions within Rwanda, in order to consolidate their political and economic control over the country (Dorsey 1983). Essentially, the Belgians sought to divide the Rwandan people, thus maintaining sufficient control over the country from abroad by way of the Tutsi elite (McDoom 2014). Such ethnic division was among the worst of Belgium’s colonial legacy in Rwanda, as the divisions were systemically codified and implemented into the structure of Rwandan society, lasting well after the country gained its independence. It is evident that Rwanda’s colonial era manifested very differently from that of Cambodia’s; therefore, despite apparent convergence as a precursor to genocide, the degree to which both countries share a similar colonial history is relatively insignificant.

Although manifesting in differing ways, the economic inequality which existed in Cambodia and Rwanda in the years preceding the genocide is a clear point of commonality.

Cambodia suffered from a profoundly corrupt leader who demonstrated explicit cronyism throughout his reign (Gardere 2010). Such corruption caused an already existing disparity between the rich and the poor to grow; even international humanitarian aid, which was channeled to the country as a way of encouraging economic growth, was diverted towards the economic elite (Kamm 2011). Rwanda also experienced large economic disparity prior to the genocide, which contrary to Cambodia, manifested as devastating economic shocks to its economy from external factors. The shocks presented in two primary ways: first, the drastic global fall in prices for Rwandan agriculture and, second, the IMF’s sudden policy changes in humanitarian aid and investment. Rwanda’s economy had become fundamentally unstable, worsening the economic divide between the elite and the poor of the country (Storey 1999). Interestingly, it is apparent that the source of economic inequality was not consequential in the incitement of genocide,

as both countries faced fundamentally different financial backgrounds prior to the onset of economic convergence. Both the Khmer and the Hutu utilized their respective country’s economic inequality to promote their genocidal ideology; in the case of Cambodia, such ideology manifested as the cleansing of social and cultural norms whereas the Hutu sought ethnic purification (Kissi 2004). Therefore, given the role economic inequality played in the culmination of both genocides, it is evident that such inequality, and not the source from which it arose, is a point of clear convergence in precipitating genocide.

It is evident that the economic stress endured by each country, paired with existing, foundational racial or social tensions, fueled explicit anti-elite sentiment, an essential precursor to the genocide in both countries. In Cambodia, the Khmer Rouge sought to eliminate not only the elite class, which included academics, doctors, lawyers, former military, and political dissidents, but also the country’s traditional system of social hierarchy so that such groups could never regain their status (USHMM n.d.). Similarly, the formerly elite Tutsi, who rose to prominence under colonial subjugation by the Belgians, were blamed for the country’s growing economic problems upon their losing their place as the Rwandan elite.

Almost immediately following the Tutsi people’s upheaval from power in 1961, the Hutu elite enacted widespread oppression against the Tutsi, ultimately culminating in genocide (Smeulers and Hoex 2010).

Case Study #1: Results

With regard to the aforementioned variables, this paper has explored six possible precursors to the Cambodian and Rwandan genocides: 1. Political Background and Governmental Structure 2. Colonial History 3. Ethnic or Social History 4. Economic Health, Stability, and Equality 5. Genocidal Ideology 6. Modality of Genocide Of these variables, convergence clearly appears in the countries’ shared history of colonial subjugation, economic inequality, and anti-elite attitudes. As presented in Table 2, the shared history of colonial subjugation proved inconsequential to the convergence of the differing genocides, as colonization had starkly contrasting effects on both countries prior to genocide occurring. Ultimately, it was the economic disparity between the rich and poor, brought about by either long term economic decline or sudden economic shocks, which fueled anti-elite sentiments in both Cambodia and Rwanda.

© Pi Sigma Alpha 2019

13

Pi Sigma Alpha Undergraduate Journal of Politics

Table 2: The Precursors Anti-elite Sentiment: [Ethnic/Racial Tension; or Social Division]

Socio-Economic Consequences of Economic Inequality: Colonialism [Long-term Economic Decline; or Economic Shocks]

Cambodia

Present (social division)

Insignificant

Present (long-term decline)

Rwanda

Present (ethnic tension)

Present

Present (shocks)

Convergence, henceforth, appears most clearly at the point between the economic inequality of a country and the backlash against such inequality’s greatest beneficiaries, the elite class.

Case Study #2: Refining the Hypothesis

The second case study will take the hypothesis derived thus far and apply it across two additional cases of genocide: the ethnic cleansing in the Darfur region of Sudan and the Holocaust in Nazi Germany. In the first case study, it was apparent that economic disparity in both countries resulted in the rise of anti-elite sentiment, an important precursor to the resulting genocide. Therefore, in this case study, I will narrow my analysis to two variables by comparing the sociopolitical/ ethnic histories of Sudan and Germany as well as each country’s economic conditions in the years preceding genocide.

Darfur

The genocide in Darfur, like those of Rwanda and Cambodia, can only be understood in light of its historical context. From 1820-1899, Sudan was under control of the Ottoman-Egyptian Empire; in 1899, power was transferred to British-Egyptian rule for 56 years, until Sudan gained its independence in 1955. Sudan’s newfound independence did not usher in an era of newfound peace, however, as it subsequently suffered two civil wars in its southern region. The first war occurred in 1955, quickly following its independence from British Egyptian rule, and the second in 1983, which culminated in the creation of South Sudan in 2011. The second civil war can be described as motivated by ethnoreligious tension, as the implementation of Sharia Law in 1983 sparked unrest between a predominately Arab-Muslim Sudanese government and their southern, predominately Christian constituents (Sikainga et al. 2019).

Beginning in 2003, the Darfur region of western Sudan saw the onset of rebel uprisings seeking to protest the Sudanese government. Soon after, in reaction to these uprisings, the government sent fleets of soldiers into the region, causing mass violence and the displacement of thousands of Darfuri citizens.

As the violence progressed, hundreds of thousands fled to the neighboring country of Chad, while many more perished at the hands of government soldiers (Hagan and Kaiser 2011).

14

Beginning in 2004, a government funded militia group, called the Janjaweed, began systematic killings of non-Arab Darfuri people (Straus 2005). The crisis, which was first classified as genocide by Secretary of State Colin Powell later that year, is ongoing and has reached death toll estimates of nearly 400,000 and the number of victims totaling 3 million (BBC News 2019).

A military coup in 1989 brought Omar Al-Bashir to power, the eventual facilitator of genocide in Darfur. Al-Bashir quickly began his consolidation of power, finally establishing a new constitution in 1998. One year later, Al-Bashir completely abolished Sudan’s National Assembly, followed by his declaring a State of Emergency in Sudan. Throughout the course of Sudan’s second conflict, the Darfur citizens of West Sudan suffered from systematic oppression at the hands of the central government. These citizens are primarily comprised of three non-Arab tribal groups: the Fur, Masalit, and Zaghawa. This oppression led to the uprisings in 2004, with Darfuri citizens claiming to be victims of apartheid. The central government of Khartoum immediately sent troops to quell the uprisings, soon followed by the state-sponsored Janjaweed’s organized killing and destruction of Darfuri villages, specifically those with non-Arab residents (HRW 2005). By 2004, the crisis had been internationally declared the first genocide of the 21st Century (Copnall 2013).

Darfuri people’s claim of apartheid is particularly important to our analysis of their genocide, as it points to the existence of significant socioeconomic stress endured by those in the region. One should first understand apartheid as being an inherently economic state, in which those who are victims of apartheid experience lesser economic wellbeing compared to their racial counterparts (Hutt 1964; Lowenberg 1989).7 Those non-Arab tribes of Darfur, specifically the Fur, Masalit, and Zaghawa, suffered such economic circumstances at the hands of the Khartoum government, which according to these tribes, favored the predominately Arab population of Sudan, citing economic neglect and marginalization (HRW 2005). Ultimately, the Darfur uprising of 2004 that preceded the violence in the region was fueled by economic stress, and some argue, prompted by anti-Black racism.8 It is important to note that the Fur, Masalit, and Zaghawa tribes almost

© Pi Sigma Alpha 2019

Before Horror Strikes: Economic Disparity, Anti-elite Sentiment, and the Onset of Genocide Box

exclusively practice Islam, thus classifying the Darfur conflict as being a racial one, unlike the ethnoreligious conflict of South Sudan (Straus 2005). Therefore, with regard to ideology and modality, the genocide has been classified as an ethnic cleansing, perpetrated by the proxy-militia of the Janjaweed and facilitated by the central government of Sudan (Hagan and Rymond-Richmond 2008).

The Holocaust

Raphael Lemkin, the founder of modern genocide studies, coined the term genocide in an attempt to describe the systemic massacres carried out by the Nazi Party in Germany and throughout Europe. In doing so, the term genocide became not only a part of the academic vernacular but also a subject of empirical analysis in its own right (Schaller and Zimmerer 2013). It is through this lens that we can understand the Holocaust as the catalyst by which genocide studies were born and, furthermore, as an important tool in understanding the etiology of genocide. The Holocaust began in 1941, 8 years after the start of Adolf Hitler’s rise to power. Over the four years of systemic murder, Hitler and the Nazi Party accomplished much of what they had set out to do: 6 million Jews were exterminated, and 11 million non-Jews were killed for posing threats to the Nazi’s societal ideals (USHMM n.d.). In light of those deaths, the genocide of the Jewish people is of the most commonly cited cases of state-sponsored extermination of an ethnic group, and scholars derived the concept of genocide by studying the Holocaust (Berenbaum and Kramer 2005). As with Darfur, the following analysis will primarily focus on the social and ethnic tensions of Germany prior to the Nazi Party’s rule, as well as the state of its economy following the First World War. Weimar Germany, the state of Germany after the First World War and prior to the Nazi Party’s rule, saw severe external and internal stresses on the German economy. External financial stress on Germany manifested in two ways, with each one having particularly devastating consequences on the economy: first, in the years directly following the war, Germany faced the pressure of reparations, which stipulated the definitive payment of approximately 50 billion German gold marks to the Allied forces as put forward in the Treaty of Versailles; secondly, towards the end of the Weimar Republic, the United States suffered the severe consequences of the Great Depression, thus pressuring them into requesting the war debt owed to them by Britain and France who, in turn, sought out the reparations owed to them by Germany (USHMM n.d.). It is important to note, however, that the time between these two manifestations of external shocks was a period of economic stabilization for Germany, in which the country also experienced vast liberal shifts in culture. Nevertheless, the consequences of these economic shocks directly fueled national disgrace across Germany, and also deepened the financial stress already carried by the general public (King and Brustein 2006). Lastly, the primary internal shock to the German economy was extreme

hyper-inflation, a consequence of the government’s attempts to rapidly repay its debts in response to the stresses of the Great Depression (Feuchtwanger 1993). By the start of the 1930s, the German population had grown tired of the Weimer Republic’s inability to maintain economic stability. Such sentiment, when paired with the ethnic tensions already surging amongst German political and social spheres, resulted in widespread resentment for the government and a desire for legitimate political change.

The economic peak of Weimar Germany produced uniquely progressive contexts for German minorities, specifically those in the homosexual community (USHMM n.d.). While homosexuals experienced newfound liberation, many Jews in German society had found economic or political success. Although such successes do not justify labeling German Jews of the 1920s and 1930s as “elites,” it contributed to a perception of elitism that triggered historical resentment and discrimination amongst much of the non-Jewish German population. Said differently, it was the false imputation of Jews’ elite status, which brought about the relevant antielite sentiment within the German public. As the Nazi Party reminded their followers of the damages done to Germany by the rest of the world, they also harped on the discrepancy between the successes of elites and the economic hardships endured by the working class (King and Brustein 2006). The Nazi Party found success in fueling anti-elite sentiment out of economic inequality, a strategy that would later become the foundation for their genocidal intent (Snyder 2012). By the time genocide had been set into motion, the extermination of Jews, homosexuals, and other minorities was met largely with indifference from the German public, who had instead held onto their desire for the restoration of older hierarchies in the social sphere- a hierarchy in which despised minorities, such as Jews, had not been economically or politically successful (Melson 1996).

Case Study #2: Analysis

In the second paired case study, the Darfur crisis and the Holocaust were presented for the purpose of refining the initial hypothesis. The shared precursor for genocide lies between the economic inequality of a country and the backlash against inequality’s greatest beneficiaries: the elite class. Analysis of the resulting evidence results in similar findings to that of the first case study.

Firstly, economic inequality, whether resulting from sudden shocks to the economy or from slower, long term economic deterioration, acted as a catalyst in all four instances of genocide. In each occurrence, economic inequality gave rise to significant economic stress upon the most vulnerable. In Darfur, the carriers of this stress were the non-Arab Darfuri villagers, who made anti-elite claims of apartheid. In Germany, the non-Jewish public presented indifference at the onset of genocidal acts, allowing for the extermination of their perceived economic oppressors. Existing societal frictions also facilitated

© Pi Sigma Alpha 2019

15

Pi Sigma Alpha Undergraduate Journal of Politics

Table 3: The Convergence Anti-elite Sentiment: [Ethnic/Racial Tension; or Social Division]

Economic Inequality: [Long-term Economic Decline; or Economic Shocks]

Cambodia

Present (social division)

Present (long-term decline)

Rwanda

Present (ethnic tension)

Present (shocks)

Darfur

Present (racial tension)

Present (long-term decline)

Holocaust

Present (social division & ethnic tension)

Present (shocks)

Table 4: Directionality Self-Identified Non-Elites

Perceived Elites

Victims of Genocide

Expression of Anti-Elite Sentiment

Victims: Elites/ Non-Elites

Cambodia

Khmer Rouge

Dissenting Politicians/ Military

Dissenting Politicians/Military

Political Power

Elites

Rwanda

The Tutsi

The Hutu

The Tutsi

Social Mobilization

NonElites

Darfur

Rebel Groups/ Darfuri Villagers

Khartoum Government/ Arab-descended Sudanese

Rebel Groups/ Darfuri Villagers

Social Mobilization

NonElites

Holocaust

Nazi Party

Jewish Population

Jewish Population

Political Power

Elites

Note: Rwanda and Darfur indicated in Red; Cambodia and the Holocaust shown in Blue.

the translation of economic stress into anti-elite sentiment, regardless of whether they manifested as purely social divisions or as ethnic tensions. The Darfur uprisings were an explicit enactment of anti-elite sentiment brought on by anti-black racism. At the same time, the widespread anti-Semitism and homophobia in Germany was a clear response to what was perceived as the elite status of minorities, particularly Jews and homosexuals. Overall, by analyzing the pre-genocide conditions of both Sudan and Germany, a clear convergence emerges. Both cases of genocide involved anti-elite sentiment, which having been fueled by the stresses of economic inequality, gave way to genocidal sentiments and acts. Moreover, Table 3 demonstrates this convergence across and between both paired case studies, indicating that anti-elite sentiment had been a necessary precursor to genocide in all four cases.

Identifying Victim Divergence

Through this analysis, I have shown that the cleavage of elite/non-elite is significant in genocides – but that the target of genocide can be the elites or the non-elites. In Darfur, the elites in the Khartoum government were the perpetrators, while in Germany, the elite-imputed Jewish population were the victims. The first case study also demonstrates this divergence 16

in directionality: anti-elite sentiment in Cambodia preceded the extermination of society’s most privileged. Simultaneously, the Rwandan genocide targeted the Tutsi who, prior to genocide, faced harsh socio-economic conditions under the Hutu government.

The divergence in the victims’ positionality between elite and non-elite suggests that genocidal acts are not unidirectional; that is, social divisions or ethnic tensions make both elites and non-elites to be vulnerable to genocide.

Additionally, when anti-elite sentiment is met with significant social mobilization, the result is retributive in nature, and non-elites are thus made subject to genocidal conditions, as in Darfur and Rwanda. When anti-elite sentiment is paired with an increase in legitimate political power, however, the elites become victims of those once vulnerable, as in Germany or Cambodia. One can understand these different directions as being upwards, where victims are the higher elites, or downwards, where victims are the non-elites. Table 4 demonstrates both this divergence in directionality, indicated as either upwards or downwards, and the corresponding expression of the anti-elite sentiment, indicated as either political power or social mobilization.

© Pi Sigma Alpha 2019

Before Horror Strikes: Economic Disparity, Anti-elite Sentiment, and the Onset of Genocide Box

CONCLUSION AND IMPLICATIONS

By utilizing a most-different comparative case analysis, this paper explored the topic of genocide and its perpetrations across four unique occurrences: Cambodia, Rwanda, Darfur in Sudan, and the Holocaust in Germany. The analysis of these four countries examined the individual components of the respective cases; for the Cambodian and Rwandan genocides, I examined 6 variables: 1. Political Background and Governmental Structure 2. Colonial History

conditions under which genocidal intent arises from economic stress and anti-elite sentiment. In sum, this research suggests the existence of a more nuanced relationship between the social sciences and genocide, perhaps one that can only be discovered through novel interdisciplinary research seeking to understand the most horrible of social phenomena. It is only then, if ever that preventive intervention before horror strikes would be truly feasible. n

ABOUT THE AUTHOR:

Anthony Ghaly is a senior year at Rutgers UniversityNewark, where he is double-majoring in Political Science and Psychology and minoring in Economics. At Rutgers, he also serves as President of the Coptic Society, works as a tutor in the University’s Writing Center, serves on the Student Governing Association, and is a member of The Honors College. Anthony intends to begin law school in the fall of 2020 and hopes to enter legal academia after completing his legal education.

3. Ethnic or Social History 4. Economic Health, Stability, and Equality 5. Genocidal Ideology 6. Modality of Genocide Of these variables, convergence clearly appeared at the countries’ shared history of colonial subjugation, economic inequality, and anti-elite attitudes. The independent variables were then reoriented to measure the degree to which they actually precipitated genocide: 1. Socio-economic consequences of colonialism.

REFERENCES

Alvarez, Alex. 2001. Governments, Citizens, and Genocide: A Comparative and Interdisciplinary Approach. Bloomington: Indiana University Press.

2. Economic inequality brought about through consistent or sudden economic instability.

Anderton, Charles H. 2014. “A Research Agenda for the Economic Study of Genocide: Signposts from the Field of Conflict Economics.” Journal of Genocide Research 16(1): 113-138. doi: 10.1080/14623528.2014.878118.

3. Anti-elite sentiment spurred by social or ethnic inequality.

Anderton, Charles H., and Jurgen Brauer, eds. 2016. Economic Aspects of Genocides, Other Mass Atrocities, and Their Prevention. Oxford University Press.

Having determined that colonial history manifested fundamentally differently in either case, the independent variables essentially converged on economic inequality and anti-elite sentiment. After testing the resulting hypothesis across the genocides of Darfur and the Holocaust, I found that anti-elite sentiment, inspired and fueled by economic stressors, had been a necessary precursor to genocide in all four cases.

Furthermore, a divergence in victims’ positionality also became clear, suggesting that anti-elite sentiment does not indicate the direction of genocidal intent or acts.

While such outcomes can lead to an increased understanding of the etiology of genocide, it is clear that certain factors have yet to be fully explored, such as those mechanisms by which economic stress from inequality results in specifically anti-elitist sentiment and those by which anti-elitist sentiment produces true genocidal intent. While scholarship at the intersection of comparative politics and political psychology has traditionally been scarce, integrative work in the fields can lend valuable insight into the possible

Atkinson, Christopher L. 2013. “Reflections on Administrative Evil, Belief, and Justification in Khmer Rouge Cambodia.” SAGE Open 3(2). doi: 10.1177/2158244013491951.

Ayvazyan, Vahram. 2012. “Genocide: Intent, Motivation and Types.” Contemporary Issues: International Institute for Genocide and Human Rights Studies 5(1).

Beachler, Donald W. 2009. “Arguing About Cambodia: Genocide and Political Interest.” Holocaust and Genocide Studies 23(2): 214–38. doi: 10.1093/hgs/dcp034.

Blomberg, Stephen Brock, and Gregory D. Hess. 2002. “The Temporal Links Between Conflict and Economic Activity.” Journal of Conflict Resolution 46(1): 74–90. doi: 10.1177/0022002702046001005.

BBC News. “Cambodia Profile - Timeline.” 2018. BBC. https://www. bbc.com/news/world-asia-pacific-13006828 (Accessed January 2, 2020).

BBC News. “Rwanda profile - Timeline.” 2018. BBC. https://www. bbc.com/news/world-africa-14093322 BBC News. “Sudan profile - Timeline.” 2019. BBC. https://www.bbc. com/news/world-africa-14095300

© Pi Sigma Alpha 2019

17

Pi Sigma Alpha Undergraduate Journal of Politics Campbell, Bradley. 2009. “Genocide as Social Control.” Sociological Theory 27(2): 150–72. doi: 10.1111/j.1467-9558.2009.01341.x.

Central Intelligence Agency. 2018. “The World Factbook: Cambodia.”

CIA. Retrieved from https://www.cia.gov/library/publications/theworld-factbook/geos/cb.html Chalk, Frank Robert, and Kurt Jonassohn. 1990. The History and Sociology of Genocide: Analyses and Case Studies. Yale University Press.

Chandler, David. “Cambodian History.” Cambodia Tribunal Monitor. http://www.cambodiatribunal.org/history/cambodian-history/ (Accessed January 3, 2020).

Theory of Genocides and Politicides: Identification and Measurement of Cases Since 1945.” International Studies Quarterly 32(3): 359. doi: 10.2307/2600447.

Hagan, John, and Joshua Kaiser. 2011. “The Displaced and Dispossessed of Darfur: Explaining the Sources of a Continuing State-Led Genocide.” The British Journal of Sociology 62(1): 1–25. doi: 10.1111/j.1468-4446.2011.01357.x.

Hagan, John, and Wenona Rymond-Richmond. 2008. “The Collective Dynamics of Racial Dehumanization and Genocidal Victimization in Darfur.” American Sociological Review 73(6): 875–902. doi: 10.1177/000312240807300601.

Chandler, David.1993. “The Tragedy of Cambodian History: Politics, War, and Revolution Since 1945.” The American Historical Review.

New Haven: Yale University Press. doi:10.1086/ahr/98.2.547

Hagan, John, Wenona Rymond-Richmond, and Alberto Palloni.

2009. “Racial Targeting of Sexual Violence in Darfur.” American Journal of Public Health 99(8): 1386–92. doi: 10.2105/ ajph.2008.141119.

Copnall, James. 2013. “Darfur Conflict: Sudan’s Bloody Stalemate.” BBC News. https://www.bbc.com/news/worldafrica-22336600 (Accessed January 3, 2020).

Hendrix, Cullen S, and Idean Salehyan. 2012. “Climate Change, Rainfall, and Social Conflict in Africa.” Journal of Peace Research 49(1): 35–50. doi: 10.1177/0022343311426165.

Cultural Survival. “The Survival of Cambodia’s Ethnic Minorities.”

Cultural Survival. https://www.culturalsurvival.org/publications/ cultural-survival-quarterly/survival-cambodias-ethnic-minorities

Hinton, Alexander Laban. 2005. Why Did They Kill?: Cambodia in the Shadow of Genocide. Berkeley: University of California Press.

Dorsey, Learthen. 1983. The Rwandan Colonial Economy, 1916-1941.

Michigan State University.

Encyclopedia Britannica. “Juvénal Habyarimana.” 2019.

Britannica. https://www.britannica.com/biography/JuvenalHabyarimana#ref1106821 (Accessed January 11, 2020).

End Genocide. “The Rwandan Genocide.” End Genocide. Retrieved from http://endgenocide.org/learn/past-genocides/the-rwandangenocide/ Esteban, Joan, Massimo Morelli, and Dominic Rohner. 2015.

“Strategic Mass Killings.” Journal of Political Economy 123(5): 1087-1132.

Fein, Helen. 1984. Accounting for Genocide: National Responses and Jewish Victimization During the Holocaust. Chicago: University of Chicago Press.

Fein, Helen. 1993. Genocide: A Sociological Perspective. London: Sage.

Feuchtwanger, Edgar J. 1993. From Weimar to Hitler: Germany, 191833. Springer.

Gardere, Jean-Daniel. 2010. Money and Sovereignty: An Exploration of the Economic, Political and Monetary History of Cambodia. Phnom Penh: Melon Rouge.

Gerhart, Gail M., Gérard Prunier, and Alain Destexhe. 1996. “The Rwanda Crisis: History of a Genocide.” Foreign Affairs 75(3): 156. doi: 10.2307/20047641.

Golooba-Mutebi, Frederick. 2008. Collapse, War and Reconstruction in Rwanda: An Analytical Narrative on State-Making. London: Crisis States Research Centre.

Gourevitch, Philip. 2015. We Wish to Inform You That Tomorrow We Will Be Killed With Our Families. London: Picador.

Harff, Barbara. 2017. “The Comparative Analysis of Mass Atrocities and Genocide.” In R.J. Rummel: An Assessment of His Many Contributions, eds. Nils P. Gleditsch, 116–25. Cham, Switzerland: Springer Open.

Harff, Barbara, and Ted Robert Gurr. 1988. “Toward Empirical 18

Hiebert, Maureen S. 2006. “The Killing Trap: Genocide in the Twentieth Century, Manus I. Midlarsky.” Review of The Killing Trap: Genocide in the Twentieth Century, Manus Midlarsky. Ethics & International Affairs, 20(4): 533-534. doi: 10.1111/j.17477093.2006.00051.x Human Rights Watch. 1999. “Leave None to Tell the Story: Genocide in Rwanda .” HRW Report. https://www.hrw.org/reports/1999/ rwanda/Geno1-3-09.htm (Accessed January 11, 2020).

Human Rights Watch. 2005. “Targeting the Fur: Mass Killings in Darfur.” Human Rights Watch Briefing Paper. https://www.hrw.org/ legacy/backgrounder/africa/darfur0105/darfur0105.pdf Hutt, William. 1964. The Economics of the Colour Bar: a Study of the Economic Origins and Consequences of Racial Segregation in South Africa. London: Andre Deutsch Kamm, Henry. 2011. Cambodia: Report From a Stricken Land. NYC: Arcade Publishing.

Kiernan, Ben. 2008. The Pol Pot Regime: Race, Power, and Genocide in Cambodia Under the Khmer Rouge, 1975-79. New Haven: Yale University Press.

King, Ryan D., and William I. Brustein. 2006. “A Political Threat Model Of Intergroup Violence: Jews In Pre-World War II Germany.” Criminology 44(4): 867–91. doi: 10.1111/j.17459125.2006.00066.x.

Kisangani, Emizet, and E. Wayne Nafziger. 2007. “The Political Economy Of State Terror.” Defence and Peace Economics 18(5): 405–14. doi: 10.1080/10242690701455433.

Kissi, Edward. 2004. “Rwanda, Ethiopia and Cambodia: Links, Faultlines and Complexities in a Comparative Study of Genocide.” Journal of Genocide Research 6(1): 115–33. doi: 10.1080/1462352042000194746.

Lemkin, Raphael, Samantha Power, and William A. Schabas.

2008. Axis Rule in Occupied Europe: Laws of Occupation, Analysis of Government, Proposals for Redress. Clark, NJ: Lawbook Exchange.

Maynard, Jonathan Leader, and Susan Benesch. 2016. “Dangerous Speech and Dangerous Ideology: An Integrated Model for

© Pi Sigma Alpha 2019

Before Horror Strikes: Economic Disparity, Anti-elite Sentiment, and the Onset of Genocide Box Monitoring and Prevention.” Genocide Studies and Prevention 9(3): 70–95. doi: 10.5038/1911-9933.9.3.1317.

Magnarella, Paul J. 2005. “The Background and Causes of the Genocide in Rwanda.” Journal of International Criminal Justice 3(4): 801–22. doi: 10.1093/jicj/mqi059.

Mamdani, Mahmood. 2014. When Victims Become Killers: Colonialism, Nativism, and the Genocide in Rwanda. Princeton: Princeton University Press.

Mcdoom, Omar Shahabudin. 2014. “Predicting Violence within Genocide: A Model of Elite Competition and Ethnic Segregation from Rwanda.” Political Geography 42: 34–45. doi: 10.1016/j. polgeo.2014.05.006.

Meierhenrich, Jens. 2014. Genocide: A Reader. New York: Oxford University Press.

Melson, Robert. 1996. Revolution and Genocide: On the Origins of the Armenian Genocide and the Holocaust. Chicago: University of Chicago Press.

Midlarsky, Manus. I. 2005. The Killing Trap: Genocide in the Twentieth Century. Cambridge: Cambridge University Press.

Moses, A. Dirk. 2008. “Toward a Theory of Critical Genocide Studies.”

Online Encyclopedia of Mass Violence. http://bo-k2s.sciences-po.fr/ mass-violence-war-massacre-resistance/en/document/toward-theorycritical-genocide-studies Palmer, Nicole F. 2015. Courts in Conflict Interpreting the Layers of Justice in Post-Genocide Rwanda. New York: Oxford University Press.

Percival, Val, and Thomas Homer-Dixon. 1996. “Environmental Scarcity and Violent Conflict: The Case of Rwanda.” The Journal of Environment & Development, 5(3): 270-291. doi:10.1177/107049659600500302.

Prunier, Gérard. 2008. Darfur: The Ambiguous Genocide. Ithaca, NY: Cornell University Press.

Richter, Elihu D., Dror Kris Markus, and Casey Tait. 2018.

“Incitement, Genocide, Genocidal Terror, and the Upstream Role of Indoctrination: Can Epidemiologic Models Predict and Prevent?” Public Health Reviews 39(1). doi: 10.1186/s40985-0180106-7.

Schabas, William A. 2006. “Genocide, Crimes Against Humanity, and Darfur: The Commission of Inquiry’s Findings on Genocide.” Cardozo Law Review 27(4): 1703-1722.

Schaller, Dominik J., and Zimmerer Jürgen. 2013. The Origins of Genocide: Raphael Lemkin as a Historian of Mass Violence. London: Routledge.

Snyder, Timothy. 2012. “The Causes of the Holocaust.” Contemporary European History 21(2): 149-168.

Sikainga, Ahmed Alawad, Jay L. Spaulding, Robert O. Collins, Ahmed S. Al-Shahi, and Mohy el Din Sabr. 2019. “Conflict in Darfur.” Encyclopedia Britannica. https://www.britannica.com/place/ Sudan/Conflict-in-Darfur (Accessed January 11, 2020).

Staub, Ervin. 1989. The Roots of Evil: The Origins of Genocide and Other Group Violence. Cambridge: Cambridge University Press.

Storey, Andy. 1999. “Economics and Ethnic Conflict: Structural Adjustment in Rwanda.” Development Policy Review 17(1): 43–63. doi: 10.1111/1467-7679.00076.

Straus, Scott. 2005. “Darfur and the Genocide Debate.” Foreign Affairs 84(1): 123–33. doi: 10.2307/20034212.

Straus, Scott. 2012. “‘Destroy Them to Save Us’: Theories of Genocide and the Logics of Political Violence.” Terrorism and Political Violence 24(4): 544–60. doi: 10.1080/09546553.2012.700611.

Straus, Scott. 2004. “How Many Perpetrators Were There in the Rwandan Genocide? An Estimate.” Journal of Genocide Research 6(1): 85–98. doi: 10.1080/1462352042000194728.

Straus, Scott. 2015. Making and Unmaking Nations: War, Leadership, and Genocide in Modern Africa. Ithaca, NY: Cornell University Press.

The World Bank. “GDP of Rwanda.” World Bank. https://data. worldbank.org/indicator/NY.GDP.MKTP.CD Tully, John. 2017. “Modern Cambodia Since 1863.” Oxford Research Encyclopedia of Asian History. doi: 10.1093/ acrefore/9780190277727.013.241.

United Nations. “Rwanda: A Brief History of the Country.” UN. http://www.un.org/en/preventgenocide/rwanda/education/ rwandagenocide.shtml United States Holocaust Memorial Museum. “Cambodia 1975– 1979.” USHMM. https://www.ushmm.org/confront-genocide/cases/ cambodia/introduction/cambodia-1975 (Accessed January 3, 2020).

United States Holocaust Memorial Museum. “Documenting Numbers of Victims of the Holocaust and Nazi Persecution.” USHMM. https://encyclopedia.ushmm.org/content/en/article/documentingnumbers-of-victims-of-the-holocaust-and-nazi-persecution (Accessed January 3, 2020).

United States Holocaust Memorial Museum. “The Weimar Republic.”

USHMM. https://encyclopedia.ushmm.org/content/en/article/theweimar-republic

Scully, Gerald W. 1997. Democide and Genocide as Rent-Seeking Activities. Public Choice, 93(1/2): 77-97. http://www.jstor.org/ stable/30024282

United States Holocaust Memorial Museum. “World War I: Treaties And Reparations.” USHMM. https://encyclopedia.ushmm.org/ content/en/article/the-weimar-republic

Sikainga, Ahmad. 2009. “Understanding the Darfur Conflict.” Origins. https://origins.osu.edu/article/worlds-worst-humanitarian-crisisunderstanding-darfur-conflict

United to End Genocide. “The Cambodian Genocide.” End Genocide. http://endgenocide.org/learn/past-genocides/the-cambodiangenocide/ (Accessed January 11, 2020).

Smeulers, Alette, and Lotte Hoex. 2010. “Studying the Microdynamics of the Rwandan Genocide.” British Journal of Criminology 50(3): 435–54. doi: 10.1093/bjc/azq004.

Wald, Patricia M. 2007. Genocide and Crimes AgainstHumanity.

Washington University Global Studies Law Review 6(3): 621-634.

Smith, Roger W. 1999. “State Power and Genocidal Intent: On the Uses of Genocide in the Twentieth Century.” Studies in Comparative Genocide: 3–14. doi: 10.1007/978-1-349-27348-5_1.

Williams, Timothy. 2016 “More Lessons Learned from the Holocaust - Towards a Complexity-Embracing Approach to Why Genocide Occurs.” Genocide Studies and Prevention: An International Journal 9(3): 137-153.

© Pi Sigma Alpha 2019

19

Pi Sigma Alpha Undergraduate Journal of Politics

NOTES

1. This analysis of Midlarsky’s work is drawn from this book review: Hiebert, Maureen S. 2006. “The Killing Trap: Genocide in the Twentieth Century, Manus I. Midlarsky.” Review of The Killing Trap: Genocide in the Twentieth Century, Manus Midlarsky. Ethics & International Affairs, 20(4), 533-534. doi: 10.1111/j.17477093.2006.00051.x 2. While Fein’s (1984, 1993) work is primarily concerned with the role of dehumanization in the incitement of genocidal acts, her work is referenced and supported in Staub’s (1989) later work, Staub, Ervin.

1989. The Roots of Evil: The Origins of Genocide and Other Group Violence. Cambridge: Cambridge University Press.

3. For another early work on the connections between economics and conflict studies, see Blomberg, Stephen Brock, and Gregory D. Hess. 2002. “The Temporal Links Between Conflict and Economic Activity.” Journal of Conflict Resolution 46(1): 74–90.doi: 10.1177/0022002702046001005.

4. For a comprehensive understanding of “democide,” see the following chapter: Harff, Barbara. 2017. “The Comparative Analysis of Mass Atrocities and Genocide.” In R.J. Rummel: An Assessment of His Many Contributions, eds. Nils P. Gleditsch, 116–25. Cham, Switzerland: Springer Open.

5. For more on the role of economic stress in the Rwandan Genocide, see Magnarella, Paul J. 2005. “The Background and Causes of the Genocide in Rwanda.” Journal of International Criminal Justice 3(4): 801–22. doi: 10.1093/jicj/mqi059.

6. Given the lack of consensus among genocide scholars, understanding the typologies of genocide is as complicated as it is understudied. In his (2008) analysis of the field, “Toward a Theory of Critical Genocide Studies,” A. Dirk Moses briefly explains the differing schemata established by genocide scholars to determine modalities. I base my categorizations primarily on Vahram Ayvazyan’s (2012) work, “Genocide: Intent, Motivation and Types,” and Frank Chalk and Kurt Jonassohn’s (1990) book, “The History and Sociology of Genocide: Analyses and Case Studies.” For a comprehensive overview of the several classifications of genocide, see: Meierhenrich, Jens.

2014. Genocide: A Reader. New York: Oxford University Press.

7. The concept of apartheid has previously been studied through the lens of economic inequality. Anton Lowenberg’s (1989) work “An Economic Theory of Apartheid,” for example, argues that economic principles and goals undergird apartheid states. Lowenberg explains race discrimination as “possess[ing] a distinctly ‘economic’ rational,” referencing the previous work of William Hutt (1964). By framing apartheid as a state of economic subjugation, my analysis of the Darfur crisis builds on the perspective offered by Lowenberg (1989).

8. The notion that anti-Black racism explains the genocide in Darfur is controversial. Straus (2005) and Hagan and Rymond-Richmond (2008) highlight the importance of tribal claims of “African” ancestry and “Arab” ancestry – and therefore race – in the conflict.

Supporting this racialized understanding of the conflict, the actors in the Darfur conflict have employed racial epithets and anti-Black justifications for their participation in genocidal acts (Hagan, Rymond-Richmond, and Palloni 2009). Sikainga (2009) and Prunier (2008), on the other hand, disentangle the complicated and intertwined history of the warring tribes in Darfur and argue that, despite claims of competing ancestry, ethnic boundaries between tribes in Sudan are not as salient as previous scholarship has suggested.

20

© Pi Sigma Alpha 2019

“Putin Down Protest”: Is Widespread Mobilization Possible in the Shadow of the Oil Curse?

“Putin Down Protest”: Is Widespread Mobilization Possible in the Shadow of the Oil Curse?

Chase LaSpisa, Oklahoma State University Do regional variations in oil production also lead to regional variations in protest activities? In understanding social movements, the literature has traditionally been dominated by three frameworks: grievances, resource mobilization, and political opportunity structures. Combining this social movement framework and drawing analogies to past work on civil conflict and natural resources, I argue that in non-democracies, local oil production increases public frustrations with the regime and provide a loot able source of income that movements can use to enhance and sustain themselves. Due to these two factors increasing, regions with oil production should experience increased levels of protest. I also develop a nuanced argument using the Russian context that regime capacity may override increased grievances and resources. I test these arguments using Lankina and Voznayas’ (2015) data on geographic variation in protest events and attendance in the Russian Federation and combine this with demographic, economic, and geographic variables from the PRIO-Grid’s spatial data set. I find no relationship between local oil production and protest occurrence, but I do find that oil-producing regions have significantly lower attendance when protests do occur.

INTRODUCTION

I

n the spring of 2017, tens of thousands of Russian protesters filled the streets across the country in response to Alexei Navalny’s, an opposition leader and legitimate threat to Putin, call for corruption investigations against Prime Minister Dmitry Medvedev (Robertson 2017). This string of large protests demonstrating against the Kremlin has continued into the summer of 2019 with over 60,000 protesters seeking justice for election rigging and widespread corruption allegations, and these summer protests were the largest since 2012 (Roth 2019).1 Despite increased efforts by the Kremlin to discourage political opposition, Russia has experienced a consistent increase in the number of mass protests over the past decade. The protests in December 2011 in response to the Russian Duma elections were particularly disruptive due to the large turnout and caught both foreign and internal spectators off-guard (Reiter and Osborn 2017).

Collective action is a significant concern for the Putin regime as widespread protests were a significant factor in the fall of the Soviet Union as well as other regional non-democratic regimes (Robertson 2009). Both this substantial increase in protest movements and the reaction from the Kremlin suggest that the Putin regime feels threatened, especially if these social movements continue to grow (Robertson 2012).

While the recent boom in Russian protest incidents is an interesting trend in and of itself, it is also of note that the distribution of these protests geographically varies (Lankina and Voznaya 2015). I am analyzing why different regions of Russia

have more protests than others could provide important insight into understanding protest behavior in non-democratic regimes and the sustainability of these regimes. I argue that regional variations in the presence of petroleum deposits and petroleum development help to explain these divergent trends. Using past research on the political effects of oil wealth, I test comparative resource curse logic generally and, more specifically, using the Russian context. By analyzing Russian protest trends, this paper seeks to explore a gap in the literature concerning the subnational dynamics of protests in oil-rich autocratic societies as well as exploring the link between oil and nonviolence conflict expression. Whereas most past research on oil and collective action has focused on oil’s impact on violent conflict, I argue that oil has substantial effects on non-violent collective action like protests as well.

The “Big Three” of the Protest Literature

In the social movements literature, there are three main theories relevant to predicting the frequency, location, and magnitude of political action: grievances, resource mobilization, and political opportunity structures (POS). Grievances generally operate as the essential initial motive for social movements (Simmons 2014), while resource mobilization and POS often shape the form protest takes (Tarrow 2011). One common theme uniting recent work in all three approaches; however, is the realization that these trends vary within states as subnational variations lead to regional and group differences in protest dynamics.

© Pi Sigma Alpha 2019

21

Pi Sigma Alpha Undergraduate Journal of Politics

At the core of protest motivation is a set of grievances (Dalton et al. 2009). Grievances are commonly experienced in the form of political, social, and economic inequalities and deprivations relative to the rest of the society (Gurr 1993).

In terms of protest behavior, past scholarly work posits that participation in collective action generally begins as a response to an objective state of disadvantage, which could include individual dissatisfaction with their current physical, economic, political, or social conditions (Opp 2000). This objective disadvantage realization is a strong motivator for individual dissent, but perceived, or imagined, injustice and inequality may be more important than real material conditions, especially when considering the point at which an individual decides to join social movements (Zomeren et al. 2008). Realization of an objective state of disadvantage is rarely enough to trigger full-on participation of individuals in collective action, but this objective state of disadvantage is particularly motivating when tied to group identity (Foster and Matheson 1999; Zomeren et al. 2008). Once individual grievances are tied to a group identity, comparisons with other groups in society are made, which increases motivation to protest (Foster and Matheson 1999).

A vast array of earlier work in the protest literature finds that individual grievances have little impact on the likelihood of social conflict (Collier and Hoeffler 2004; Fearson and Laitin 2003). In a rebuttal to many of these large-N studies that conclude inequality does not substantially increase the probability of civil conflict, Østby (2008) argues that instead of examining the individual aspect of inequality, researchers should focus on inequalities between groups. She argues that “horizontal inequalities,” or inequalities that align with group identity divisions, facilitate conflict by increasing grievances and group unity, and she also argues that this is a better test of grievance logic (2008). In recent years, this trend of group inequalities and grievances explaining conflict likelihood has reemerged and become a fundamental mobilization factor for civil conflict (Cederman et al. 2013; Deiwiks et al. 2012).

These studies argue that collective action must be analyzed in terms of horizontal inequality, or systematic features that reinforce inequalities between different groups, as civil conflict is group conflict, not conflict between individuals (Cederman et al. 2013; Deiwiks et al. 2012; Østby 2008).

However, an aggrieved group is only able to mobilize if they have the resources to sustain collective action (McCarthy and Zald 1977). Resources necessary to sustain collective action include financial and physical capital, human labor and skills, some form of communicative system like social media, and moral support and legitimacy (Edwards and McCarthy 2004).2 When populations have low levels of useful resources, social movements lack the capacity to form any substantial collective action making this behavior significantly less appealing and causing those social movements that do emerge to be vulnerable to state suppression (Dalton et al. 2009). Another important component of the resource mobilization approach maintains that resources are spread unequally throughout societies, and the 22

control of the resources needed for the continuation of collective action is distributed unequally among social groups (Edwards and McCarthy 2004).

A distinction must be made here between how social groups are geographically distributed. Some group distinctions are fundamentally geographic, such as urban and rural groups, whereas other groups are not necessarily geographically limited, such as an economic middle class. Edwards and McCarthy (2004) hold that middle-class groups are the group most suited to protest behavior as they have access to substantial resources necessary for social movements. Beyond that, groups in more urbanized areas might be more likely to protest, since urbanization generally brings with it a variety of resources like social connectivity and economic support (Jenkins 1983).

Thus, geographic protest variation could be driven by the distribution of resources among these geographically varied portions of the population.

The resource mobilization approach has primarily debated the availability of resources in democracies, and the approach suggests that democratic regimes should provide ample resources for protest movements to sustain themselves. Democratic societies generally have higher levels of development, which provides higher levels of resources necessary for collective action. The third major social movement approach – political opportunity structures – shows that social movements in democratic regimes have access to other forms of political action (e.g., lobbying). The latter approach reduces the necessity and efficacy of protest, thereby making the protest option less attractive (Dalton et al. 2009).

In this sense, democratic states and democratic opportunity structures become a resource for social movements that drives down the need for protest. In the context of non-democracies, populations have significantly fewer resources conducive to sustainable collective action as the state restricts the public’s access to them. Following this logic, non-democratic regimes attempt to appear democratic by allowing opposing parties and elections, but without providing democratic resources, like Russia, could be a breeding ground for protest movements.

While resource mobilization often determines the efficacy of collective action and grievances provide the mobilization factor, POS open, or close, opportunities in which social movements can expect to make the most impact. POS are “compromised of specific configurations of resources, institutional arrangements, and historical precedents for social mobilization” (Kitschelt 1986). Under political opportunity theory, the polity of a state directly impacts the grievances, such as exclusion, that social movements mobilize around, and the organization of the polity makes certain forms of collective action more appealing, and sometimes more effective than other forms (Meyer 2004). Some work postulates the relatively open opportunity structures may experience increased levels of peaceful protest because individuals and groups can make political demands without fear of retribution (Tarrow 2011).

Generally, however, open systems decrease protests due to

© Pi Sigma Alpha 2019

“Putin Down Protest”: Is Widespread Mobilization Possible in the Shadow of the Oil Curse?

the availability of other conventional channels, while closed regimes do not permit their public to protest at all. The social movement literature indicates that there is something about the middle ground, which makes protests the most appealing and efficient form of collective action.

As a result, POS theory predicts that as political institutions become more democratic, the viability and safety of protests will rise, but overall levels may not increase due to other viable revenues of public expression. In contrast, more closed systems are characterized by fewer conduits for public influence in the political process and restricted civil liberties which forces social movements outside of conventional forms of political demonstrations and sometimes escalating social mobilization past protest and into the realm of conflict (Asal et al. 2016; Kitschelt 1986). However, POS that have a mix of closed and open features have consistently been the most likely to experience protest (Kitschelt 1986).

Elections are one particular feature that provide openings for collective action in both open and mixed systems, and elections provide a particularly volatile opening in mixed POS systems. Elections in the Russian context have been shown to increase the likelihood of protests, especially when the public perceives the election results as fraudulent (Lankina and Skovoroda 2017). Saleyhan and Linebarger (2015), analyzing the relationship between elections and the magnitude of social conflict in Africa, find that elections caused increased levels of protest and other forms of collective action in electoral autocracies.3 Often, these autocratic regimes allow fraudulent elections to satisfy a variety of democratic demands. However, this institutional inconsistency is dangerous in that rival parties and oppositions can more easily organize and mobilize in times of elections (Salehyan and Linebarger 2015). This further reinforces the idea that the middle ground of POS provides a breeding ground for protest movements. In the next section, I present my theory for how the presence of petroleum fundamentally changes the social movement frameworks and how oil wealth impacts protest dynamics.

The Role of the Resource Curse in Regional Protest Variability

Less studied in the protest literature is the influence the resource curse has on collective action, specifically protests. The resource curse is defined as the “adverse effects of a country’s national resource wealth on its economic, social, or political well-being” (Ross 2015). While there is little literature on the resource curse-protest link, the conflict literature does contain a vast amount of research linking natural resources like alluvial diamonds, petroleum, and nonfuel materials to the advent of civil war and armed conflict (Asal et al. 2016; Fearon 2004; Lujala et al. 2005). Although the resource curse is a broad term that encompasses a variety of non-renewable natural resources, the most persuasive evidence indicates that one type of resource wealth has the most important effects: petroleum (Basedau and Lay 2009; Ross 2015).

As comparative conflict studies have shown, there are several ways petroleum extraction in a country may impact the grievances, collective action resources, and POS in such a way as to increase the likelihood of group conflict. The resource curse exacerbates grievances through the application of the rentier state theory, which claims that regimes who extensively rely on external revenue, such as oil income, rather than taxation, are less likely to address claims of grievances put forth by its populace (Gervasoni 2010). These regimes also tend to provide benefits to individual citizens and populations, thereby reinforcing group inequalities (Wright et al. 2014).

Furthermore, natural resources damage political institutions and reinforce non-democratic regimes, which in turn leads to more corruption (Andersen et al. 2013). Consistently, corruption has been shown to be a strong motivator for protests, especially in non-democracies (Brancati 2016).

The presence of petroleum also makes collective action more viable by shifting the availability of resources within a society, including societies not generally conducive to opposition movements. Research in this area has found that oil leads to more armed and violent conflict partly because it makes central governments prime targets for insurgents to loot and to take over petroleum production for themselves (Asal et al. 2016; Collier and Hoeffler 2004). These insurgencies then use petroleum production to finance conflict activities and enhance the sustainability of their social movements (Collier and Hoeffler 2004; Lujala et al. 2005; Ross 2004). In the case of protest movements, the resource rents gained from looting petroleum production could allow for a variety of movement sustaining and enhancing activities such as funding more staff, buying equipment, better advertisement and publicity, and offsetting legal costs. While oil can improve the sustainability of collective action, it also increases the sustainability and capacity of regimes (Morrison 2009).

Non-democratic regimes with petroleum generally use oil wealth to consolidate their political control and close POS to discourage opposition (DeMeritt and Young 2013; Gervasoni 2010). The regime is incentivized to institute regime-preserving activities and utilize repression to maintain its control, and it especially seeks to maintain control of the major revenue producing oil industry (Caselli and Cunningham 2009; Conrad and DeMeritt 2013; DeMeritt and Young 2013). Mixed regimes, like electoral autocracies, though face additional challenges in maintaining this control as the elections, rigged or otherwise, provide opposition opportunities to organize and incite collective action (Lankina and Skovoroda 2017; Salehyan and Linebarger 2015). This would indicate that populations in mixed POS regimes experiencing the exacerbated grievances from oil-induced rentier states could use elections as openings in the POS to express public dissent without escalating to conflict. Following this comparative logic, elections could contribute to an outbreak in protests in oil rich regions by producing openings in the POS that would typically not be available. In conjunction with oil driven grievances and

© Pi Sigma Alpha 2019

23

Pi Sigma Alpha Undergraduate Journal of Politics

resource mobilization, this should make regions with oil production in mixed regimes hot spots for protest likelihood.

While oil production shifts national-level grievances, resource mobilization, and political opportunities, considerable research suggests that the specific physical location of the resource in the country is just as important. Only onshore oil deposits have been found to have a robust impact on a state’s risk of conflict, as they are more easily accessed, and thereby more easily looted, than off-shore deposits (Lujala 2010).

Conflict may also be especially likely when oil wealth aligns with other forms of grievances, as the likelihood of civil war and other armed conflict is higher when an area contains both oil and politically excluded ethnic groups (Asal et al. 2016; Cotet and Tsui 2013), and onshore oil deposits also appear to instigate conflict more often in regions that are poor in relation to their state’s national average (Østby et al. 2009).

Utilizing the comparative literature on the impact petroleum has on other types of contentious politics, this would suggest that regions with more oil production should be more likely to experience protest. The discussion of general resource curse trends on collective action leads to the first part of my first hypothesis that oil production increases grievances and resource availability and creates openings that increase the likelihood of protest: Hypothesis 1a: Regions with more oil production are more likely to experience protests.

The theory thus far has only focused on broad comparative trends without taking the Russian context into account. While Hypothesis 1a will test broad comparative resource curse logic applied to protest likelihood, I develop a sub hypothesis that accounts for additional nuance specific to Russia. It can also be argued that oil production may have the opposite effect on protest likelihood in Russia if the regime can successfully use the oil to undermine collective action.

The Putin regime is a relatively capable regime when it comes to repressing its population, and co-optation and selective repression, in particular, have allowed the regime to maintain control, particularly in regions of strategic interest (Gel’man 2015b). Russian protests have recently come under scrutiny after the mass electoral protests of 2011 with studies finding that the Russian citizenry are increasingly engaging in social mobilization after a period of less mobilization during the 2000s (Gel’man 2015a; Lankina 2015). These protests seem to vary geographically, with some regions in Russia overly inundated with protests while others much less so (Lankina 2015). Lankina (2015) posits that Russian regions vary substantially in the way their POS are structured, with some regions being much more open compared to others.

Oil production may be a critical factor in explaining this variation in regional POS due to oil increasing the capacity of the state to deal with potential dissent (Girod, Stewart, and Walters 2018). The Putin regime routinely incentivizes regional governments to maintain control of its populace, and 24

regions with comparatively closer ties to the federal government are those considered to be the most politically closed regions (Lankina 2015). Russian regions with oil production could face higher levels of supervision as well as assistance from regional governments in order to secure the loyalty, or obedience, of the citizenry and maintain good relations with the national regime (Gel’man 2015b; Lankina 2015). Due to the regime’s financial dependence on oil production, regions with oil production are considered strategically important and have closer ties to the national regime. As a result of this increased control, populations in these oil regions should be less likely to protest, leading to a nuanced version of the general resource curse protest hypothesis: Hypothesis 1b: Regions in Russia with more oil production are less likely to experience protests.

Based on the nature of the Russian context, the presence of natural resources in a region may also shift political opportunities in a way that decreases turnout, no matter the impact on protest likelihood. Regarding political opportunities, regimes that extensively rely on oil income rather than taxation are more willing to repress opposition (DeMerritt and Young 2013; Wright et al. 2013). High levels of natural resources allow non-democratic regimes to weaken better or crush any substantial social movements that rise against them (DeMeritt and Young 2013; Girod, Stewart, and Walters 2018; Ross 2001), and the availability of resource rents supports the development of a rentier state which stresses more investment in regime-preserving activities (Caselli and Cunningham 2009; Ross 2004). Applying rentier theory to POS, national governments are highly motivated to keep their primary revenue source flowing and are thus more likely to use repression techniques to keep oil extraction in operation (DeMeritt and Young 2013; Jensen and Wantchekon 2004). They will use their fiscal power to institute regime preserving activities – including surveillance on the population, fiscal pressure on political opposition, and labor control in oil producing industries (Gervasoni 2010)– in regions with more natural resource presence. Due to these activities, the costs of collective action rise significantly in regions with oil production. As a result, areas with oil will experience much higher levels of supervision and suppression to stop protests from emerging, especially if the presence of these resources coincides with excluded social or ethnic groups (Asal et al. 2016; Salehyan and Linebarger 2015).

Thus, I hypothesize: Hypothesis 2: If protests do occur, regions in Russia with more oil production will see fewer protesters attend protests.

Methodology

To test my hypotheses, I utilize the PRIO-Grid Database (Tollefsen et al. 2012) as the basis of my dataset. The PRIOGrid is a spatial data set that divides the globe into roughly

© Pi Sigma Alpha 2019

“Putin Down Protest”: Is Widespread Mobilization Possible in the Shadow of the Oil Curse?

55km x 55km hexagons, splitting geographic territories around the world into 64,818 distinct units or “cells.” As I am only examining the variation in Russian protest events in this study, I only include cells located within the Russian Federation. Due to data availability in my dependent variable, my timeframe is limited to the years between 2007 and 2012. However, I argue that this small-time frame still offers interesting insight, as doing so means that I am able to focus my analyses on protests that a) occur after Russia has achieved a solid recovery from their late 1990s financial crisis and b) are limited to the leadership of Vladimir Putin. This helps control for additional explanations that may drive protest dynamics in Russia. Even with this short time frame, the geographic size of Russia provides ample regional variation in protests and the presence of oil. The unit of analysis for this project is cell-year, meaning that each data point represents events occurring in each Russian PRIO-GRID cell for a year within the five-year time frame.

Dependent Variables

In order to code for the number of protest events, I use a dataset compiled by Lankina and Voznaya (2015). They constructed their dataset using the information found on namarsh.ru, which is a Russian media website run by an opposition group that reports protest events with web links to the “original press coverage of a given event.”4 The group that operates the website is invested in providing accurate and extensive reporting on protest events for use by opposition efforts. The baseline data record protests beginning in March of 2007 through December 2012, providing the timeframe for this study. The location of the protests is the most relevant aspect of the protests in the context of this project, and each data point contains the city and oblast location of reported protests. I then coded the latitude and longitude of these protest locations and matched them to their coinciding PRIOGrid cell. This variable is a count of the number of protest events per cell per year.

To test hypothesis 2, I utilized the number of people per protest as a second dependent variable, also available through the Lankina and Voznaya (2015) study.5 To assess the robustness of my results, I use both the maximum and minimum estimates of the average number of protesters at these events. Given that both my dependent variables are continuous nature, I analyzed my data using a linear regression model. I robust clustered on cell, which acts as a control for any cell-specific explanations not included in the empirical model.

Independent Variable

To code my main variable of interest, I use the PRIOGrid’s petroleum variable regional petroleum dependency, originally from Lujala, Rød, and Thieme (2007). Lujala et al.

(2010) identify every petroleum deposit on the planet that has ever been publicly found, with the PRIO-GRID matching these locations to a specific cell. The resulting measure is a static dummy variable of on-land oil reserves found within

each individual grid cell. It is important to narrow down the analysis only to on-land oil reserves as only on-land oil deposits have been found to have an impact on the advent of collective action (Lujala 2010). This static petroleum variable is only updated to 2003. While this means there may be considerably more oil producing regions than my model estimates, it is the best that can be done with the available data. Other recent studies, such as Asal et al.’s (2016) work, follow a similar practice, providing some continuity with the literature.

Control Variables

As a proxy for political exclusion, I utilize the Georeferencing Ethnic Power Relations (EPR) 2014 dataset (Vogt et al. 2015). In the social movement literature, exclusion generally exacerbates or causes other grievances, and politically excluded groups have no outlet to remedy these other grievances. In fact, Asal et al.’s 2016 study found that oil only increased conflict likelihood when it was located in areas where an ethnic group was politically excluded. As a result, I use ethnic political exclusion as a proxy for intercommunal grievances to better control for an alternative grievance motivator. The GeoEPR exclusion variable is a count of the number of discriminated or powerless ethnic in each grid cell per year.

The second control variable I include is population density per cell found on the PRIO-Grid, which is based on the Gridded Population of the World Dataset (CIESIN 2005). Population was chosen as a control variable because the population density can serve as a proxy for whether a cell has a significant urban center (Hansen et al. 2018; Nemeth et al. 2014). More urban areas may be more likely to experience protests independent from factors like oil production (Lankina and Voznaya 2015).

As for my third control variable, I control for economic development using the PRIO-Grid’s data on nighttime light emission (Elvidge et al. 2014). The PRIO-Grid contains an economic measure called gross cell product (GCP), a measure which is analogous to a country’s gross domestic product (GDP) in that it reports the overall economic output per individual cell, I chose not to use this measure though because the presence of oil could over predict regional wealth.

In reality, an oil-producing region can have a high GCP per capita, but still have an overwhelming majority of the population lives in abject poverty with wealth concentrated in the hands of a few elites. Nighttime light emission is a more accurate measure of the population’s overall wealth, as richer and more developed areas will be more able to maintain steady nighttime light emission over a larger area. Furthermore, this economic proxy has been used by some economic geographers (see, for instance, Sutton et al. 2007).

Beyond socioeconomic factors, I control for the cell’s distance from the capital and distance from the state’s border.

I included these measures as prior work in the sub-national conflict literature has shown that distance from the capital

© Pi Sigma Alpha 2019

25

Pi Sigma Alpha Undergraduate Journal of Politics

and proximity to borders directly impacts the duration of civil conflict and the ability of a state to exercise its power (Buhaug et al. 2009). State power is concentrated in capitals, and so cells further from a capital are likely to have more POS openings given that it will be more difficult for the central government to deploy their coercive force (Cederman et al.

2009). In that same line, past research shows that rebel groups may prefer border regions as they give access to co-ethnics in neighboring states, offer places to hide and avenues of escape, and the potential for international support (Buhaug et al. 2009; Cederman et al. 2009). For the distance from the capital variable, I use the PRIO-Grid variable capdist, which is originally from Weidmann et al. (2010). As for the distance from the border variable, I again utilize a variable from the PRIO-Grid, bdist1, which is also from Weidmann et al. (2010).

The data gives the spherical distance from the cell centroid to the national capital city and the border of the nearest landcontiguous country.

RESULTS

The results of my analysis are presented in Table 1. Regarding Hypothesis 1a and Hypothesis 1b, which held opposite expectations of regional oil production on protest likelihood, the analysis indicated that the presence of oil production had no significant effect on the likelihood of protests occurring in the region. The lack of oil’s impact on protest likelihood

could be attributed to additional factors specific to the Russian context not accounted for in the data. The Russian population in these regions trails behind other regions and still perceives the regime’s repressive capacity as making protest in general counter-productive. The regime’s ability historically to co-opt opposition, reinforce loyalty, and control the dissemination of news to the people in these regions may also decrease the viability of any form of collective action. These regions may trail significantly in terms of economic development, and the citizenry are simply more invested in maintaining their livelihood than expressing discontent publicly.

Regarding my second hypothesis, that protests in oilrich regions will experience less protest turnout, I do find a statistically significant and negative coefficient for both the minimum number and the maximum number of protesters.

The results do suggest that regional oil production significantly decreases the number of people who show out to protest.

Since both the maximum and minimum number of protestors were negatively affected, this provides some robustness to the results as it shows that any reporting bias does not drive the results. Tying this result back to my theory, I predicted that the state would institute regime preserving activities such as a coercive apparatus and financial and legal pressure on political opposition and organizations, thereby increasing the costs of protesting for those living in oil-producing regions.

This finding reinforces the idea that regions with oil may be experiencing more governmental repression and co-optation

Table 1: Protest incidents and number of protesters; Russia 2007-2012 (linear regression with robust standard errors clustered on cell).

Number of Protests

Number of Protesters (Min. est.)

Number of Protesters (Max. est.)

Regional Petroleum Dependency

0.0002 (0.0054)

-0.1723** (0.0560)

-0.1698* (0.0560)

Ethnic Political Exclusion

0.0040* (0.0022)

0.1563 (0.0984)

0.1543 (0.0972)

Population Density

0.0001 (0.0001)

0.0031 (0.0025)

0.0031 (0.0024)

Economic Development

-0.0681** (0.0341)

-2.558* (1.350)

-2.534* (1.330)

Distance from Capital

-4.24*** (0.0000)

-0.0002*** (0.00003)

-0.0002*** (0.00003)

Distance from Border

-0.00002*** (0.0000)

-0.0006*** (0.0002)

-0.0006*** (0.0002)

Constant

0.0312*** (0.0069)

1.070*** (0.2397)

1.058*** (0.2369)

Observations F R-Squared Adjusted R-Squared

8717 4.94*** 0.007 0.0063

8717 5.12*** 0.0063 0.0056

8717 5.12*** 0.0063 0.0056

Note: Robust standard error clustered on cell. * p < .10, ** p < .05, *** p < .01

26

© Pi Sigma Alpha 2019

“Putin Down Protest”: Is Widespread Mobilization Possible in the Shadow of the Oil Curse?

compared to regions without oil production. These costs could include loss of employment in the oil industry, the threat of violence against the protester and the protester’s family, and incarceration.

Predictably, the majority of my control variables were found to be statistically significant, which is consistent with other research done on protest trends. The presence of an excluded social group in a cell had a slight positive effect on the likelihood of protest, meaning that the number of protests were higher in regions with more politically excluded ethnic groups. However, this variable had no measurable effect on protest turnout. Consistent with conflict scholars and social movements predictions (Fearon and Laitin 2004; Gurr 1993; Østby et al. 2009), poorer regions were more prone to protest and experienced higher protest turnout.

Additionally, protests were more likely to occur, and turnout was much higher the closer the cell was to Moscow, even when I controlled for regional population density.

On the same note, there were more protest incidents with larger turnouts the farther from Russia’s borders. This could be attributed to the fact that Russia’s border regions are traditionally sparsely populated. Finally, population density, my proxy for urbanization, had no discernable statistical significance in the likelihood of protest or protest turnout.

Another obstacle to obtaining protest data for some areas of the world is the lack of incentive non-democratic regimes have to report protests. Most protest data sets utilize media coverage (Lankina and Vozanaya 2015) to constitute their data, which can be problematic. Formulating other methods of obtaining reliable protest data will be vital to further research on this topic. n

CONCLUSIONS AND FUTURE RESEARCH

REFERENCES

The results of this research are preliminary in many ways. I faced considerable problems collecting data, and it is possible that there were errors in the geographic coding of the protest events. With that being said, the results are encouraging, even if they only supported one of my main hypotheses. By analyzing past Russian protests, insight can be gleaned on what is motivating more recent protests and what factors might be driving these social movements. There also seems to be an interesting repression angle that warrants further investigation.

While there is cross-national work on the relationship between oil-rich governments’ use of repression (DeMeritt and Young 2013; Ross 2001), there seems to be little tangible, quantitative research on the sub-national level of the interaction between the resource curse, oil specifically, and governmental repression of protest. I believe continuing with this research would be a valuable contribution to the social movement, conflict, and resource curse literature.

Moving forward, I would like to acquire more cases to further analyze sub-national variations in repress. More importantly, utilizing more sophisticated geographic information system software, such as ArcGIS, to code geographical coordinates for protest events will be essential for the continuation of this research. The time frame of the data was limited due to the original protest data from Lankina and Voznaya (2015), so finding a more complete data set for global protest events might be necessary to yield more accurate results.

ABOUT THE AUTHOR:

Chase LaSpisa is a senior Political Science major with minors in Economics and Russian at Oklahoma State University.

He is involved in multiple honor societies as well as working as a residential assistant. He is a research assistant for the Department of Political Science, assisting faculty on quantitative research projects. He has presented his research at conferences across the country, and this past summer he participated in the National Science Foundation’s Research Experience for Undergraduates (NSF-REU) in Conflict Management and Peace Science hosted by the University of North Texas. He hopes to attend graduate school in the fall, pursuing a doctorate in Political Science.

Andersen, Jørgen Juel , Niels Johannesen, David DreyerLassen , and Elena Paltseva. 2013. Petro rents and hidden wealth: evidence from bank deposits in tax havens. Econ. Policy Res. Unit Work. Pap. No. 2013-03, Copenhagen, Denmark.

Asal, Victor, Michael Findley, James A. Piazza, and James Igoe Walsh.

2016. Political Exclusion, Oil, and Ethnic Armed Conflict. Journal of Conflict Resolution 60 (8): 1343-1367.

Basedau, Matthias, and Jann Lay. 2009. “Resource curse or rentier peace? The ambiguous effects of oil wealth and oil dependence on violent conflict.” Journal of Peace Research 46 (6): 757-776.

Besley, Timothy, and Torsten Persson. 2009. “Repression or Civil War?”. The American Economic Review 99 (2): 292-297.

Brancati, Dawn. 2016. Democracy Protests: Origins, Features, and Significance. New York: Cambridge University Press.

Buhaug, Halvard, Scott Gates, and Päivi Lujala. 2009. “Geography, Rebel Capability, and the Duration of Civil Conflict.” Journal of Conflict Resolution 53 (4): 544-569.

Caselli Franceso, and Tom Cunningham. 2009. “Leader behaviour and the natural resource curse.” Oxford Economic Papers 61: 628–50 Cederman, Lars-Erik, Halvard Buhaug, and Jan Ketil Rød. 2009.

“Ethno-Nationalist Dyads and Civil War: A GIS-Based Analysis.”

Journal of Conflict Resolution 53 (4): 496-525.

Cederman, Lars-Erik, Kristian Skrede Gleditsch, and Halvard Buhaug.

2013. Inequality, Grievances, and Civil War. New York, NY: Cambridge University Press.

Center for International Earth Science Information Network (CIESIN) and Centro Internacional de Agricultura Tropical

© Pi Sigma Alpha 2019

27

Pi Sigma Alpha Undergraduate Journal of Politics (CIAT) (2005). Gridded Population of the World, Version 3 (GPWv3): Population Count Grid. Palisades, NY. doi:10.7927/ H4639MPP. Accessed 11.06.2018.

Lankina, Tomila. 2015. “The Dynamics of Regional and National Contentious Politics in Russia: Evidence from a New Dataset.”

Post-Communism 62 (1): 26-44.

Collier, Paul, and Anke Hoeffler. 2004. “Greed and grievance in civil war.” Oxford Economic Papers 56: 563-595.

Lankina, Tomila, and Alisa Voznaya. 2015. “New Data On Protest Trends In Russia’s Regions.” Europe-Asia Studies 67 (2): 327-342.

Cotet Anca M., and Kevin K. Tsui. 2013. “Oil and conflict: What does the cross-country evidence really show?” American Economic Journal of Macroeconomics 5 (1): 49–80.

Lankina, Tomila, and Rodion Skovoroda. 2017. “Regional protest and electoral fraud: evidence from analysis of new data on Russian protest.” East European Politics 33 (2): 253-274.

Dalton, Russell, Alix Van Sickle, and Steven Weldon. 2009. “The Individual-Institutional Nexus of Protest Behavior.” British Journal of Political Science 40 (1): 51-73.

Lujala, Päivi. 2010. “The spoils of nature: armed civil conflict and rebel access to natural resources.” Journal of Peace Research 47 (1):15–28.

Davenport, Christian, and John D. McCarthy. 2005. “Protest Mobilization, Protest Repression, and Their Interaction.” In Repression and Mobilization, ed. Christian Davenport, Hank Johnston, Carol Mueller, University of Minnesota Press.

Lujala, Päivi, Nils Petter Gleditsch, and Elisabeth Gilmore. 2005.

“A diamond curse? Civil war and a lootable resource.” Journal of Conflict Resolution 49 (4): 538–62.

Deiwiks, Christa, Lars-Erik Cederman, and Kristian Skrede Gleditsch.

2012. “Inequality and Conflict in Federations.” Journal of Peace Research 49(2): 289–304.

Lujala, Päivi, Jan Ketil Rød, and Nadia Thieme, 2007. “Fighting over Oil: Introducing A New Dataset.” Conflict Management and Peace Science 24 (3), 239-256.

DeMeritt, Jacqueline H. R., and Joseph K. Young. 2013. “A political economy of human rights: Oil, natural gas, and state incentives to repress.” Conflict Management and Peace Science 30 (2): 99-120.

McAdam, Doug, John D. McCarthy, and Mayer N. Zald.

1996. Comparative Perspectives on Social Movements: Political Opportunities, Mobilizing Structures, and Cultural Framings.

Cambridge: Cambridge University Press.

Edwards, Bob, and John D. McCarthy. 2004. “Resources and Social Movement Mobilization.” In The Blackwell Companion to Social Movements, ed. David A. Snow, Sarah A. Soule, Hanspeter Kriesi, Wiley: Blackwell Publishing Ltd.

McCarthy, John, and Mayer Zald. 1977. “Resource Mobilization and Social Movements: A Partial Theory.” American Journal of Sociology 82 (6): 1212-1241.

Fearon James D. 2004. “Why do some civil wars last so much longer than others?” Journal of Peace Research 41 (3): 275–303.

Fearon, James D., and David D. Laitin. 2003. “Ethnicity, Insurgency, and Civil War.” American Political Science Review 97 (1): 75-90.

Foster, Mindi, and Kimberly Matheson. 1999. “Perceiving and Responding to the Personal/Group Discrimination Discrepancy.”

Personality and Social Psychology Bulletin 25 (10): 1319-1329.

Gel’man, Vladimir. 2015a. “Political Opposition in Russia: A Troubled Transformation.” Europe-Asia Studies 67 (2): 177-191.

Gel’man, Vladimir. 2015b. “The Politics of Fear: How the Russian Regime Confronts Its Opponents.” Russian Politics and Law 53 (5-6): 6-26.

Gervasoni, Carlos. 2010. “A rentier theory of subnational regimes: Fiscal federalism, democracy, and authoritarianism in the Argentine provinces.” World Politics 62 (2): 302-340.

Gurr, Ted Robert. 1993. “Why Minorities Rebel: A Global Analysis of Communal Mobilization and Conflict Since 1945.” International Political Science Review 14 (2): 161-201.

Meyer, David. 2004. “Protest and Political Opportunities.” Annual Review of Sociology 30: 125-145.

Morrison, Kevin M. 2009. “Oil, Nontax Revenue, and the Redistributional Foundations of Regime Stability.” International Organizations 63 (1): 107-138.

Nemeth, Stephen, Jacob Mauslein, and Craig Stapley. 2014. “The Primacy of the Local: Identifying Terrorist Hot Spots Using Geographic Information Systems.” The Journal of Politics 76 (2): 304-317.

Opp, Karl-Dieter. 2000. “Adverse Living Conditions, Grievances, and Political Protest after Communism: The Example of East Germany.” Social Forces 79 (1): 29-65. Østby, Gudrun. 2008. “Polarization, horizontal inequalities, and violent civil conflict.” Journal of Peace Research 45 (2): 143-62. Østby Gudrun, Ragnhild Nordås, and Jan Ketil Rød. 2009. “Regional inequalities and civil conflict in sub-Saharan Africa.” International Studies Quarterly 53 (2): 301–24.

Hansen, Holley, Stephen Nemeth, and Jacob Mauslein. “Ethnic political exclusion and terrorism: Analyzing the local conditions for violence.” Conflict Management and Peace Science 00 (0): 1-21.

Reiter, Svetlana, and Andrew Osborn. 2017. “Anti-Kremlin protesters fill Russian streets, Putin critic Navalny jailed.” Reuters, June 11. https://www.reuters.com/article/us-russia-opposition-protests/antikremlin-protesters-fill-russian-streets-putin-critic-navalny-jailedidUSKBN192167 (December 6, 2018).

Jenkins, Craig. 1983. “Resource Mobilization Theory and the Study of Social Movements.” Annual Review of Sociology 9: 527-533.

Robertson, Graeme. 2009. “Managing Society: Protest, Civil Society, and Regime in Putin’s Russia.” Slavic Review 68 (3): 528-547.

Jensen, Nathan, and Leonard Wantchekon. 2004. “Resource wealth and political regimes in Africa.” Comparative Political Studies 37 (7): 816-841.

Robertson, Graeme. 2012. “Protesting Putinism: The Election Protests of 2011-2012 in Broader Perspective.” Problems of Post-Communism 60 (2): 11-23.

Kitschelt, Herbert. 1986. “Political Opportunity Structures and Political Protest: Anti-Nuclear Movements in Four Democracies.”

British Journal of Political Science 16 (1): 57-85.

Robertson, Graeme. 2017. “Russians are protesting! Why? Part 1: Putin’s vulnerable.” Washington Post, March 31. https://www. washingtonpost.com/news/monkey-cage/wp/2017/03/31/russians-

28

© Pi Sigma Alpha 2019

“Putin Down Protest”: Is Widespread Mobilization Possible in the Shadow of the Oil Curse? are-protesting-why-part-1-putins-vulnerable/ (September 17, 2019).

Ross, Michael L. 2001. “Does Oil Hinder Democracy?” World Politics 53(3):325–361.

Ross, Michael L. 2004. “How does natural resource wealth influence civil war? Evidence from thirteen cases.” International Organization 58 (1): 35-67.

Ross, Michael L.. 2015. “What Have We Learned about the Resource Curse.” Annual Review of Political Science 18: 239-259.

Roth, Andrew. 2019 “Russian protesters demand end to political crackdown.” The Guardian, September 29. https://www. theguardian.com/world/2019/sep/29/russia-protesters-demandend-to-political-crackdown (September 30, 2019).

Salehyan, Idean and Christopher Linebarger. 2015. “Elections and Social Conflict in Africa: 1990-2009.” Studies in Comparative and International Development 50 (1): 23-29.

NOTES

1 Over a thousand protesters were detained during the height of the protests during the summer of 2019, and a bevy of “criminal investigations” have been opened against prominent protesters (Roth 2019).

2 Edwards and McCarthy (2004) detail many more resources and identify five broad types of resources: moral, cultural, socioorganizational, material, and human.

3 Electoral autocracies are regimes that “conduct regular multiparty elections at all levels of governments yet violate basic democratic standards in serious and systematic ways” (Schedler 2010).

4 A Rentier state is a state who “dominates society because of its easy access to significant economic resources that are independent of broad domestic taxation” (Gervasoni 2010).

5 Each data entry has numerous details, including protester turnout, the underlying inspiration of the protest, and whether suppression occurred (Lankina and Voznaya 2015, 331).

Simmons, Erica. 2014. “Grievances do matter in mobilization.” Theory and Society 43 (5): 513-546.

Sutton, Paul C., Christopher D. Elvidge, and Tilottama Ghosh.

2007. “Estimation of Gross Domestic Product at Sub-Naional Scales using Nighttime Satellite Imagery.” International Journal of Ecological Economics & Statistics 8 (7): 5-21.

Tarrow, Sidney. 2011. Power in movement: Social movements and contentious politics. Cambridge University Press.

Tollefsen, Andreas Forø, Håvard Strand, and Halvard Buhaug. 2012.

“PRIO-GRID: A unified spatial data structure.” Journal of Peace Research 49 (2): 363-374. doi: 10.1177/0022343311431287.

Vogt, Manuel, Nils-Christian Bormann, Seraina Rüegger, LarsErik Cederman, Philipp Hunziker, and Luc Girardin. 2015.

“Integrating Data on Ethnicity, Geography, and Conflict: The Ethnic Power Relations Dataset Family.” Journal of Conflict Resolution 59 (7): 1327-1342.

Weidmann, Nils B., Doreen Kuse, and Kristian Skrede Gleditsch.

2010. “The geography of the international system: The CShapes Dataset.” International Interactions 36 (1): 86-106.

Wright, Joseph, Erica Frantz, and Barbara Geddes. 2013. “Oil and Autocratic Regime Survival.” British Journal of Political Science 45: 287-306.

Zomeren, Martijn van, Tom Postmes, and Russell Spears. 2008.

“Toward an Integrative Social Identity Model of Collective Action: A Quantitative Research Synthesis of Three Socio-Psychological Perspectives.” Psychological Bulletin 134 (4): 504-535.

© Pi Sigma Alpha 2019

29

Pi Sigma Alpha Undergraduate Journal of Politics

Rural Values in Montana Hailey Oestreicher, Carroll College Montana communities are difficult to classify as rural or urban. However, we often hear that rural values influence how Montanans vote. In this study, I seek to determine whether it is possible to define the rural values of Montanans. I ask questions such as, “Are there specific words or phrases that people associate with the term ‘rural’?” and, “Are rural residents generally more or less confident in state or federal government than urban residents?” In response to these questions, I present two hypotheses: first, I posit that living in rural Montana leads to the development of rural values characterized by a feeling of resentment towards urban communities. Second, I hypothesize that Montanans, regardless of where they live, will express feelings of resentment towards the federal government more than the Montana state government. In this article, I present the results of my study, derived from traveling to communities across the state of Montana and interviewing nearly fifty Montana residents.

INTRODUCTION

O

ne way to study the politics of place is to separate voters into two categories: rural and urban. This split, also known as the “rural-urban divide,” has become increasingly prevalent in American politics. However, few researchers have tried to understand politics from the rural perspective (McKee and Springer 2015, 592). In their article “The Rural Side of the Urban-Rural Gap,” Gimpel and Karnes (2006, 467) write: “For all the research on urban politics, there is no remotely comparable body of accumulated wisdom on rural populations.” One recent study of rural values was conducted by Katherine J. Cramer, who believes an identity as a rural person includes “much more than an attachment to place” (Cramer 2016, 5).

For Cramer, a rural identity includes feeling fundamentally different from urbanites and systematically ignored by decision makers (Cramer 2016, 10).

The purpose of this study is to discern whether a distinguishable set of rural values exists in Montana and, if rural values do exist, how they influence a person’s perception of politics and their feelings of resentment towards federal and state governments. I do so by replicating some aspects of Cramer’s (2016) research. The comparison with Cramer’s research in Wisconsin illuminates some of the differences between rural voters in a state with large, metropolitan areas and rural voters in a state with very few urban areas.

I aim to answer the following questions: What are rural values? Are there specific words or phrases that people associate with the term “rural”? Are residents of rural areas generally more confident or less confident in state or federal government than urban residents? Why? In response to these questions, I present two hypotheses: first, I posit that living in rural Montana leads to the development of a set of rural values characterized by a feeling of resentment towards urban communities. Second, I hypothesize that residents of Montana, regardless of where they live, will express negative

30

sentiment (or resentment) towards the federal government and more positive sentiment towards the Montana state government.

Community Identity and Place Politics Identities and Politics

The significance of how communities influence our daily lives is important for both psychological and political reasons.

As Winston Churchill (1943) once stated: “We shape our buildings, and afterwards, our buildings shape us.” Churchill’s statement is corroborated by studies suggesting a relationship between community identity and politics. A social identity may influence how one perceives politics and how politically active one is likely to be within a given community. With two distinct approaches, Conover (1984) and Miller, Gurin and Malanchuk (1981) study the relationship between group identification (among groups of similar race, gender, age, and class), political perception, and political participation. Conover (1984, 761) defines group identification as a “self-awareness of one’s objective membership in the group and a psychological sense of attachment to the group.” To measure psychological attachment, Conover (1984) conducts interviews in which respondents are given a list of groups and are asked to rate the groups in terms of “closeness” to their interests, ideas, and feelings. Respondents are then told to choose to which group they feel “closest.” The “close to” and “closest to” ratings, when analyzed together, provide a way of measuring an individual’s group identity (Conover 1984, 766). The author concludes that a group identity, combined with a sense of “psychological attachment” to that group produces identifiable patterns of issue positions in politics (Conover 1984, 782).

Miller, Gurin and Malanchuk (1981) analyze data from the 1976 presidential election collected by the Center for Political Studies (CPS) based on race, class, age, and gender. They find an association to politicized groups leads to

© Pi Sigma Alpha 2019

Rural Values in Montana

an increase in political participation, where politicization is defined as “identification with a group and a political awareness or ideology” aimed at a collective action to “realize” the group’s political goals (Miller, Gurin and Malanchuk 1981, 495).

Whereas Tajfel, Billig, Bundy, and Flament (1971) study the perception of group identity over time, Conover (1984) and Miller, Gurin and Malanchuk (1981) establish links between politics, people’s perception of community, and participation within that community, therefore expanding upon Tajfel et al.’s (1971) research on group identities. These researchers demonstrate that a community becomes more politically active when people within that community mobilize to support a common cause.

Place Politics and Rural Values

McKee and Springer (2015) study voting behaviors of voters in the southern United States, whereas Gimpel and Karnes (2006) research rural voters nationally. McKee and Springer (2015, 605) find that rural voters in the “Deep South” vote differently than those in the “Peripheral South.”

They also discover voters in the North vote differently than those in the Deep or Peripheral South and that these distinctions between communities are politically significant (McKee and Springer 2015, 605). Their research is based on the politics of place, but also on racial divisions between the northern and southern states, especially how race structures southern politics more than northern politics (McKee and Springer 2015, 590). The authors define the Deep South as “more rural” than northern states or the Peripheral South.

However, they fail to address what makes rural voters truly distinctive from urban voters.

Similar to McKee and Springer (2015), Gimpel and Karnes (2006) categorize voters by location (rural and urban); however, their research is performed across the United States. They cite a recent migration of Republicans to rural areas as the cause of counties in rural America being more morally conservative (Gimpel and Karnes 2006, 467). They contribute to the research of group identities in politics by adding literature specific to rural voters; they attribute the voting behavior of rural residents to a unique self-image of independence adopted by rural residents. Gimpel and Karnes (2006, 469) refer to this self-image as containing “core values” of residents. They are among the first to relate place and politics, specifically rural voting behavior, to voters’ values.

Cramer (2016) expanded on the relationship between place politics and rural values. She performed a four-year study of rural values amidst the rise of Governor Scott Walker.

Governor Walker’s support for Act 10, also known as the “Wisconsin Budget Repair Bill,” a controversial bill against a union’s ability to collectively bargain, divided the state between urban residents (the majority of which benefit from unionizing and collective bargaining) and rural residents (Cramer 2016, 193). Cramer visited and conversed with groups of residents in urban and rural communities across the state of Wisconsin. She 31

aimed to determine why rural residents are resentful of state government, regardless of party affiliation (Cramer 2016, 55).

During her field study, Cramer analyzed patterns in people’s speech as they talked about government, politicians, their community, and other communities. Cramer concluded that a specific set of rural values might act independently as a lens through which people interpret politics (Cramer 2016, 175).

She defined “rural consciousness” as a: “Strong sense of identity as a rural person combined with a strong sense that rural areas are the victims of injustice” (Cramer 2016, 89). The “injustice” Cramer described is more precisely defined as “distributive injustice,” meaning rural residents feel as though they do not get their fair share of “power, respect, or resources” when compared to urbanites (Cramer 2016, 89). Cramer’s interviews distinguish her work as one of the most relevant and recent qualitative studies of politics in relation to place and rural values.

Comparing States: Montana and Wisconsin

Similar to Cramer’s (2016) study of rural values in Wisconsin, I researched the prevalence of rural values in Montana. Montana differs from Wisconsin in three substantial ways, which may add to our understanding of the rural-urban divide. First, Montana does not have any large urban centers comparable to Milwaukee or Madison, Wisconsin. Second, Montana has a higher percentage of American Indian and Alaska Native residents per capita. Third, Montana, unlike Wisconsin, has a part-time, non-professional legislature.

In 2010, Montana’s population was just under one million people. In the same year, Wisconsin’s population (5.6 million people) was over five times that of Montana’s, with many Wisconsin residents living in the densely populated urban centers of Madison and Milwaukee, Wisconsin (United States Census Bureau 2010). Oliver (2000) studies the connection between the population of communities and political activity.

The author compares the political participation rates of people in rural and metropolitan areas. Using data from the 1990 American Citizen Participation Study (CPS) and the 1990 Census, participation rates are categorized among rural and metropolitan residents into five political activities and concluding that, in general, the average rate of political participation declines in larger cities. Oliver (2000, 366) claims that city size alone is “a powerful predictor of local civic activity,” and attributes the heightened political participation of residents in rural communities to the character of social relations in smaller places. He claims that people from rural areas are more likely mobilized to act politically by friends, neighbors, or acquaintances than their urban counterparts (Oliver 2000, 369).

Oliver (2000) suggests that voter turnout is influenced by how people view and evaluate their place within a community, as well as the size of their community.

While population figures are important for distinguishing among rural, suburban, and urban communities, population density is equally essential. McGranahan and Beale (2002) note that population density offers a scale to complement

© Pi Sigma Alpha 2019

31

Pi Sigma Alpha Undergraduate Journal of Politics

population figures, not replace them when studying rural versus urban populations (Oliver 2000, 5). The majority of counties in Wisconsin have a high population density. In contrast, most counties in Montana are low-density and are subject to “rural sprawl” (McGranahan and Beale 2002, 4) The researchers suggest that communities experiencing rural sprawl are more likely to contain residents who work in urban areas and live in rural or suburban areas. Living and working in two communities can influence a person’s perception of their identity, as earlier posited by Conover (1984). However, cultural differences may also lead to fluid community identities.

The American Indian populations in Montana and Wisconsin add to the diversity of each state. Montana has a higher percentage of American Indian residents than Wisconsin (6.7 percent to 1.2 percent, respectively) (United States Census Bureau 2010). Dewees and Marks (2017) offer an explanation as to why Montana may have a higher percentage of American Indians per capita than Wisconsin.

Their research suggests that approximately 54 percent of the United States’ American Indian population lives in rural zones, rather than urban (Dewees and Marks 2017, 1). Dewees and Marks cite a misunderstanding of the term “rural” at the federal level as the reason many American Indian, rural residents are not accounted for in large-scale studies (Dewees and Marks 2017, 3). They, like McGranahan and Beale (2002), believe population density was not adequately taken into consideration when the United States Census Bureau (USCB) defined the terms “urban,” “suburban,” and “rural,” leading to an overrepresentation of suburban communities and an underrepresentation of rural communities on American Indian reservations. Compounded identities of indigenous and rural residents of Montana complicate the study of rural values more so than in Wisconsin. According to Warry (2007, 99), “individual identity can be seen as personalized culture.” The choice between which culture one identifies with varies and is a matter of self-reflection.

Finally, Montana’s state legislature convenes for ninety days every two years (Montana Legislature 2018).

In Wisconsin, the legislature is in session an average of ten months a year and state legislators are not confined by term limits (Wisconsin State Legislature 2018). The absence of term limits is one characteristic of a “professionalized legislature,” which are sometimes viewed unfavorably by people in less populated areas (Squire 1993, 489). By analyzing public opinion polls from five Midwestern states (including Wisconsin), Squire (1993) finds an overwhelmingly poor opinion of permanent, professionalized legislatures. Apollonio, Glantz, and Bero (2014) suggest that biennial legislatures are often perceived as less professionalized, sometimes being referred to as citizen legislatures. Proponents of term limits and less professionalization argue that citizen legislatures have more in common with constituents and are therefore unlikely to be swayed by party politics or corporate influence.

32

The aforementioned research (Apollonio, Glantz, and Bero 2014; Cramer 2016; Squire 1993) provide a basis for considering that feelings of “injustice” towards the state legislature in Wisconsin may be more noticeable than in Montana. In Montana, state legislators may be less readily identified as political elites because they are subject to term limits and the state legislature is not professionalized (National Conference of State Legislatures 2015). With this interpretation of the literature, it is reasonable to think Montanans may hold a relatively more unfavorable view of the federal government than Wisconsinites, due to its highly professionalized nature. Similarly, Montanans may have a more positive view of their state government than Wisconsinites because the Montana state government is less professionalized.

For these reasons, Montana presents an alternative setting in which to study rural values that can add to a greater understanding of group identities and the politics of place.

RESEARCH DESIGN AND METHODOLOGY Convenience sampling was used to select the respondents in the sample, and then respondents were interviewed from urban (population of 50,000 or more), urban cluster (population of at least 2,500 and less than 50,000), and rural (population of 2,500 or less) communities in Montana (Geographic Products Branch 2012). In total, I selected 48 respondents from 27 communities across Montana. Respondents were residents of Montana and over 18 years old. I interviewed respondents from each community, recruiting respondents mainly in cafes, bars, gas stations, supermarket parking lots, and public buildings (such as county courthouses or public schools). In each community, I spent anywhere from a half-hour to four hours actively seeking out participants from public spaces.1 As a part of the recruitment process, I introduced myself and my research. Then, I asked each respondent to sign a consent form. Respondents were presented with a list of 15 questions and proceeded to conduct a semi-structured interview, allowing approximately 25 minutes for the completion of each interview. Most respondents preferred having the list of interview questions in front of them as they were answering questions, which I allowed (although this was not part of my original design) because it neither noticeably affected the flow of conversation nor my ability to ask followup questions. The respondents were not limited in their time to respond or what they could say in response to the questions, so long as the topic of conversation pertained to the original question. The respondents were informed that they could optout of any question or stop the interview at any time. I took handwritten notes of each response. I did not digitally record the interviews in an attempt to eliminate any potential bias from the respondent. This design was consistent with Cramer’s (2016) interpretivist approach, although I did not record and transcribe the interviews. Instead, I listened to respondents and then compared their responses with others’ while looking

© Pi Sigma Alpha 2019

32

Rural Values in Montana

for patterns in their speech and/or opinions. For more specific details and the survey questions, see the Appendix.

After each interview, I carefully reviewed and expanded my notes while omitting any personally identifiable information the respondent intentionally or unintentionally provided. Then, I examined my notes and looked for patterns and repeated terms, phrases, or answers to questions. To assess whether public opinion of some residents in Montana differed from those interviewed in Wisconsin by Cramer (2016), I first had to determine the sentiment of the responses I received while conducting interviews. I created a spreadsheet wherein I listed each respondent, the community in which I conducted the interview, the time, and short, categorical words to signify the respondent’s answers to each question. I developed a frequency chart of repeated responses, thus allowing for a visual representation of the patterns of words and phrases used to answer each question.

Although Cramer (2016) relies primarily on her intuition when determining patterns in responses and the meaning behind word sentiments, I chose to implement the use of the 2016 SentiWord 5 Lexicon, a lexicon developed by HLT, a company specializing in machine learning to advance natural language processing (Gatti, Guerini and Turchi 2016, 420).

The SentiWord 5 Lexicon categorizes words on a scale from -1 to 1, with -1 being the most negative sentiment value assigned to a word, 0 as neutral, and 1 as having the most positive sentiment value. I compared the keywords provided by respondents in four interview questions to the sentiment word list in the Lexicon. Then, I created a frequency chart of repeated words and phrases organized by population categories, which I color-coded to reflect the sentiment values of each word or phrase. After I determined the sentiment values of the most frequently used words and phrases, I calculated the average sentiment of respondents in each city to an array of topics, including their opinion of rural areas, and federal and state governments.

Throughout her research, Cramer (2016) equates negativity with resentment. I utilized the 2018 Carroll College exit poll to make the same equivalence (Street 2018). Cramer (2016, 12) defines rural resentment as “a sense that rural folks don’t get their fair share” and concludes that residents of rural Wisconsin have strong feelings of resentment towards the state government. On the 2018 Carroll College exit poll, two questions pertain to this feeling of resentment as defined

by Cramer (2016): “How fairly are resources to urban areas distributed by the state and federal governments?” and “How fairly are resources to rural areas distributed by the state and federal governments?” (Street 2018). I used the data collected from the exit poll responses, in addition to data regarding where the exit poll was conducted (in an urban or rural setting), as a check against my interpretations of public opinion.

DATA Collection

In the rural communities included in my study, participants refused an interview more than fifty percent of the time, on average. In contrast, I experienced an average rejection rate of less than six percent in urban communities and approximately twenty percent in suburban communities (except for Hardin, where the rate of rejection was seventy-five percent). These non-response rates align with Reyes (2016).

After analyzing over 600,000 opinion surveys from around the world, Reyes (2016, 17) found that “Urban areas have, on average, higher response rates” than rural or suburban communities. Reyes (2016) attributes the high non-response rates of less-populated areas to the population’s likelihood of being less educated, single, poorer, and therefore more skeptical of answering questionnaires.

Interpretation What are Rural Values?

Before asking respondents to describe rural values, I first asked each respondent if they thought rural values exist. 87.5 percent of participants in this study agreed that a distinguishable set of rural values exist in Montana. An American Indian living on the Crow Agency reservation who was among this majority said, “We all have values, but the community—the small community—really is unique in forming good values.” Other respondents gave clear, concise answers to this question such as, “Most definitely” or “Of course!”, followed by puzzled looks as to why I would ask a question with such an obvious answer. One elderly female respondent from an urban community explained why she disagreed with the overwhelming majority of responses, saying: “Rural values existed, but not anymore. People were different.

More of them lived on family farms. Now everyone lives in the city and it’s hard to put a label on people’s values when they come from so many different backgrounds.”

Having established that most respondents thought rural values exist, I then asked each person to describe rural values.

“In rural Montana, a deal is a handshake,” claimed one middleaged man. He explained that he had lived in rural Montana until moving to Los Angeles, California for a job opportunity.

“People there [in LA] just didn’t have the same understanding of what it means to be neighborly,” he said, “I moved back [to rural Montana] quick because I wanted to feel [like] a part of a family again—a family that helps in times of need.” A young, male, self-identified urban resident said that rural values were related to being “peaceful,” “family-oriented,” and “welcoming.”

Most respondents, regardless of whether they identified as a rural resident or not, described rural values positively.

I analyzed the frequently repeated words and phrases respondents used in the interviews using WordStat, a word mining software, to better understand how respondents defined

© Pi Sigma Alpha 2019

33

Pi Sigma Alpha Undergraduate Journal of Politics

rural values and if rural values were viewed positively. After developing a list of frequently repeated keywords used in each open-ended question, I assigned each keyword a sentiment value using the SentiWord 5 Lexicon. Figure 1 displays a frequency chart of the ten most repeated words and phrases used per interview in response to the question: “How would you describe ‘rural values’?” The bars are colored to reflect positive sentiment value, with the darkest green being the most positive.

The ten most frequently used words and phrases to define rural values were: neighborly, community-based, strong work ethic, traditionalist, family-oriented, humble, wholesome, caring, ethical, and prideful. These words and phrases are assigned positive sentiment values, meaning respondents, regardless of location, viewed rural values positively. A business owner from suburban Montana defined the term “value” in his interview. He said values reflect “the way that you treat others.”

Most respondents seemed to describe rural values in similar ways, especially given that the most frequently used word, neighborly, is associated with the treatment of people.

By assigning an overall sentiment value to every respondent’s answer to open-ended interview questions, I was able to calculate an average sentiment value for each question and then an average sentiment value for each community.

I re-scaled sentiment values, with 1 being the most positive sentiment value and 0 being the most negative. Table 1 displays the average sentiment value to two questions, categorized by community size. On the right is the rural sentiment value for each community. The cells in this table are colored to reflect sentiment value, with dark green representing a more positive

sentiment and red representing a more negative sentiment value. Average sentiment values, displayed in the “Rural Sentiment Value” column, show that urban communities, in general, express a slightly more negative sentiment towards rural communities.

I asked respondents to self-identify whether or not they lived in a “rural” community. Then, throughout the interview process, all respondents were asked to describe the major issues facing the community in which they lived. In doing so, all respondents self-identified the community in which they primarily resided, at the time. I was able to compare the community size of each respondents’ primary residence with data from the U.S. Census Bureau to categorize the size of communities into “urban,” “suburban” and “rural” (United States Census Bureau 2010). Interestingly, most respondents claimed to be rural residents of Montana, although they were not from “rural” communities. Of the 48 people I interviewed, 42 (87.5 percent) self-identified as a rural resident of Montana.

In actuality, only 14 respondents (29 percent) were indeed residents of a rural community, as defined by the U.S. Census Bureau (United States Census Bureau 2010). Since I have shown that rural values are viewed as mostly positive across the state, I believe these results show that people tend to want to associate with groups they view positively. This theory of positive group association, as suggested by Tajfel et al. (1971) in their study on group identity, appears to be prevalent for respondents across Montana because of their desire to associate with the same positive values they listed when asked about rural values (Tajfel et al. 1971).

Figure 1: Most Frequently Used Words and Phrases Overall

How Would You Describe “Rural Values”?

Neighborly Community Based

Keywords

Strong Work Ethic Traditionalist Family-Oriented Humble Wholesome Caring Ethical Prideful 0 2 4 6 8 Frequency (Times Repeated per Interview)

34

© Pi Sigma Alpha 2019

Rural Values in Montana

Table 1: Average Sentiment Values by U.S. Census Bureau Community Categorization Community Size

RURAL

SUBURBAN

URBAN

Question 5: What Does “Rural” Mean?

Question 7: Describe “Rural Values”

Rural Sentiment Value

0.89

0.89

0.94

0.35

0.61

0.74

0.49

0.46

0.74

0.89

0.12

0.75

0.06

0.83

0.72

0.89

0.19

0.77

0.94

0.90

0.96

0.47

0.34

0.70

0.03

-0.06

0.49

0.15

0.71

0.72

0.47

0.49

0.74

0.11

0.39

0.62

0.89

0.19

0.77

0.63

0.49

0.78

0.07

0.79

0.71

0.03

0.81

0.71

0.89

0.86

0.94

-0.09

0.54

0.61

-0.06

-0.79

0.29

-0.41

-0.02

0.39

0.47

-0.06

0.60

0.89

-0.89

0.50

-0.54

0.30

0.44

Note: The dark green represents a more positive sentiment value, while the dark red represents a more negative sentiment value.

Are Rural Montanans Resentful Towards Urbanites?

Cramer (2016, 193) associates rural values with resentment, writing: rural values make rural resentment toward urbanites and public employees “commonsense knowledge.”

I did not, however, gather the same feelings of resentment towards urbanites from self-identified rural respondents in Montana. Although many respondents claimed rural residents of Montana are more likely to know their neighbors and help one another than urban residents, none of the respondents spoke of urbanites in hostile terms. One woman from one of the smallest towns in Montana said, “Just because city people don’t understand what it’s like to live out here [in rural Montana] doesn’t mean they don’t have their own problems.

They’re still plenty busy!”

Cramer (2016, 12) describes resentment as “a sense

that rural folks don’t get their fair share.” Yet, an exit poll conducted in Montana, independent of this study, also suggests that rural residents of Montana are not resentful of urbanites. On November 6, 2018, undergraduate students from Carroll College surveyed over 500 voters and asked each respondent to self-identify as a rural, suburban, or urban resident of Montana (Street, 2018). Table 2 displays the proportions of responses to two questions asked on the exit poll, categorized by community size. This table shows that rural residents of Montana are not significantly different from urban or suburban residents in feeling as though they receive their fair share of resources. Considering the latter finding, one may conclude that rural residents’ feelings of resentment towards urbanites are not as prevalent in Montana as Cramer (2016) found in Wisconsin.

© Pi Sigma Alpha 2019

35

Pi Sigma Alpha Undergraduate Journal of Politics

Table 2: Exit Poll Data by Self-Identified Community Categorization

Do rural areas receive more or less than their fair share of resources?

Do urban areas receive more or less than their fair share of resources?

Rural communities get less than their fair share of resources and urban communities get more than their fair share of resources.

Rural communities get their fair share of resources and urban communities get their fair share of resources.

Rural communities get more than their fair share of resources and urban communities get less than their fair share of resources.

Does the U.S. Federal Government Represent Rural Values?

Interview respondents had much to say about the U.S. federal government. One self-identified rural resident of Montana told me about his experience in banking before he moved to rural Montana and started a small business. He said, “When I was working for [the bank], I started to realize that the federal government was slowly killing rural America.

They treat us like we are stupid when most of these [rural] people are wiser than some stock brokers I knew… The federal government does very little where it counts and too much where it shouldn’t.” Another older woman who self-identified as a rural resident said, “The federal government only cares

Overall

Rural

Suburban

Urban

0.15

0.14

0.12

0.18

0.66

0.68

0.68

0.62

0.19

0.18

0.20

0.20

about their agenda. Very rarely does that agenda match ours [in Montana].” Even urban residents complained about what they perceived as the federal government’s ignorance of issues in Montana. A younger Hispanic man who self-identified as an urbanite listed reasons as to why he thought the federal government pays little attention to Montana, saying: “[Montana] is too much ground with too few people for the [federal] government to bother with.”

Figure 2 displays overall sentiment values of words used when I asked respondents to answer the following two questions: “How much attention do you feel the state government pays to what the people in (community) want?”

Figure 2: State and Federal Government Sentiment by Self-Identified Community Categorization Positive Sentiment Value of Government 1 = Most Positive

Sentiment Values of State and Federal Government by Community 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

State Federal State Federal State Federal

Rural Suburban Urban

Communities by Size

36

© Pi Sigma Alpha 2019

Rural Values in Montana

Table 3: Exit Poll Government Data by Self-Identified Community Categorization

How well does the state government in Helena, MT represent your community’s values?

How well does the federal government in Washington, D.C. represent your community’s values?

The U.S. federal government represents my community’s values better than the MT state government.

The MT state government represents my community’s values as well as the U.S. federal government.

The MT state government represents my community’s values better than the U.S. federal government.

and “How much attention do you feel the federal government pay to what the people in (community) want?”

Table 3 shows that, in each community, respondents viewed the federal government far less favorably than the state government. Similarly, the survey data from the 2018 Carroll College exit poll displayed in Table 3 also illustrates that residents of Montana, regardless of their community’s size based off of each respondent’s self-identification as a rural, suburban, or urban resident, have a generally unfavorable opinion of the federal government as compared to the Montana state government.

Why is the Montana State Government Viewed More Positively?

Contrary to the resentment towards the state government described in Wisconsin (Cramer 2016), I have found that some residents of Montana not only dislike the federal government but generally prefer the Montana state government. Many of the respondents I interviewed claimed to have a friendly relationship with their district’s representative or senator in the Montana state legislature. One woman from suburban Montana said, “I can talk to the politicians that go to Helena [and serve in the legislature]. One of the guys that will serve next term is actually my neighbor... Montana does a good job at keeping that ‘one of us’ feeling in politics.” A self-identified rural resident answered questions about the Montana state government as he filled his pickup truck with diesel, saying: “Those guys and gals up there [in Helena] making the laws, they’re farmers, ranchers… they’re not exactly your career politician… most are trustworthy, too.” These statements are consistent with Squire (1993) and Apollonio et al.’s (2014) research suggesting that biennial legislatures, often referred to as citizen legislatures, are less professionalized and, therefore, viewed more favorably than professionalized legislatures.

Figure 3 visually summarizes information drawn from

Overall

Rural

Suburban

Urban

0.07

0.08

0.07

0.03

0.46

0.49

0.40

0.46

0.48

0.42

0.53

0.50

this research. This graphic compares the overall positive sentiment of state government to the rural sentiment value calculated for each community, categorized by interviewees’ self-identification as a rural, suburban, or urban resident.

On the graph, the communities are grouped by size. Similar to Figure 2, there is a difference in the range of sentiment values with regard to each community’s overall opinion of the Montana state government. However, each community still views the Montana state government positively.

The points in Figure 3 represent cities in which I conducted interviews. Since these points are clustered in the mid-range of the graph (from a 0.5 to 0.8 positive sentiment value), one can conclude that respondents in my survey, despite having self-identified as a resident of urban, suburban, or rural Montana, generally share a positive sentiment of the Montana state government as compared to the U.S. federal government.

Figure 3 also shows that respondents who self-identified as urban residents had a slightly more negative rural sentiment than respondents who self-identified as residents of suburban or rural communities.

Significance and Limitations

This study adds to the understanding of what “rural values” are in Montana. Not only does it allow for a clearer interpretation of the 2018 Carroll College exit poll (which includes questions about community values without defining those values), but it provides a better understanding of why some Montanans have more resentment towards the federal government and less resentment towards the Montana state government than do Wisconsinites. Further research on the topic of rural values in Montana may include a longitudinal study with a larger sample of respondents, more diversity among respondents, and a more even distribution of communities surveyed. Another opportunity for further research could include a comparison of Montana to its neighboring states in

© Pi Sigma Alpha 2019

37

Pi Sigma Alpha Undergraduate Journal of Politics

Figure 3: Rural to Government Sentiment by Self-Identified Community Categorization MT State Government and Rural Sentiment by Location 1

Opinion of MT State Government 1 = Most Positive

0.9 0.8 0.7 0.6 0.5 0.4 0.4 0.2 .2 .3 .4 .5 .6 .7 .8 .9 1

Average Rural Sentiment 1 = Most Positive the Northwest to determine if Montana residents are unique in holding positive views of rural residents while favoring the state government over the federal government.

This study is limited by the method of convenience sampling, which does not include any systematic randomization and, therefore, cannot produce a representative sample of Montanaâ&#x20AC;&#x2122;s demographics. Unlike Cramerâ&#x20AC;&#x2122;s (2016) study, this research is not longitudinal because second or third interviews with the respondents were not conducted over an extended time frame. In addition, there may be some inaccuracies in respondent quotations, as taking handwritten notes likely decreased the accuracy of quoting respondents directly as compared to recording the interviews and then transcribing the audio. Finally, since it is unknown if the interview respondents voted in the 2018 midterm election, the exit poll is only used as a comparative tool rather than evidence to support the claims of the interview respondents or vice versa.

CONCLUSION

In this article, two hypotheses were proposed: 1) that living in rural Montana leads to the development of a set of rural values characterized by a feeling of resentment towards urban communities; and 2) that residents of Montana, regardless of 38

where they live, will express negative sentiment (or resentment) towards the federal government and more positive sentiment towards the Montana state government. I also provided evidence to suggest that Montana offers an alternative setting in which to study rural values, thus adding to a greater understanding of group identities and the politics of place.

Based on the results, I can conclude that there is a distinguishable set of rural values that participants in my research were able to define. Unlike the results promulgated

by Cramer (2016) in Wisconsin, my results suggest that selfidentified rural residents of Montana do not express a significant amount of resentment towards urban communities or the state government. Therefore, the rural values present in Montana do not seem to be characterized by resentment. My second hypothesis is supported by responses to my interview questions as well as an independent exit poll. Residents of Montana, regardless of where they live, express negative sentiment towards the federal government and more positive sentiment towards the Montana state government. I have also found that an overwhelmingly positive sentiment towards rural areas leads to a disproportionate number of Montanans self-identifying as rural residents, even if they live in the largest cities of Montana.

The values of rural residents in Montana seem to be different from rural values in Wisconsin. Montana has

Š Pi Sigma Alpha 2019

Rural Values in Montana

less diversity, less urban population density, and a lessprofessionalized state government. Cramer’s (2016) study was situated not only in a state with different demographics, but also a different political climate than Montana. In Montana, there is not currently such a divisive issue as Walker’s Act 10 (Cramer 2016, 193) that negatively influences rural opinions of urban residents or the Montana state government. (See also Wisconsin 2011). Rather, I have found that, overall, Montanans express negative sentiment towards the U.S. federal government and positive sentiment towards rural residents and the Montana state government while maintaining a sense of what it means to have rural values. n

ABOUT THE AUTHOR

Hailey Oestreicher is a recent graduate of Carroll College, with a Bachelor of Arts in Political Science and minors in International Relations and Constitutional Studies. Her interest in studying politics in rural America stems from her childhood, as she was raised in a small ranching community located in south-central Montana. Hailey loves to travel and has spent time studying abroad in Siena and Rome, Italy as both a Lex Fellow and a recipient of the Benjamin A. Gilman International Scholarship. In the summer of 2019, Hailey participated in a think-tank on Poverty and Welfare in the 21st Century, as part of the American Enterprise Institute Summer Honors Program.

Hailey is currently employed at a law firm in Helena, Montana as a Legal Assistant and HIPAA Compliance Manager, and she intends to pursue a career in law.

REFERENCES

Apollonio, Dorie E., Stanton A. Glantz, and Lisa A. Bero. 2014.

“Term Limits and the Tobacco Industry.” Social Science & Medicine 113.

Conover, Pamela Johnston. 1984. “The Influence of Group Identifications on Political Perception and Evaluation.” Journal of Politics 46: 760-785.

Cramer Walsh, Katherine J. 2016. The Politics of Resentment: Rural Consciousness in Wisconsin and the Rise of Scott Walker. The University of Chicago Pres. Chicago, IL. Dewees, Sarah and Benjamin Marks. 2017. “Twice Invisible: Understanding Rural Native America.” First Nations Development Research Notes 1-10.

Dowling, Robyn. 2009. “Geographies of Identity: Landscapes of Class.” Progress in Human Geography 33 (6): 833-839.

Gatti, L., Guerini, M., and Turchi, M. 2016. “SentiWords: Deriving a High Precision and High Coverage Lexicon for Sentiment Analysis.” IEEE Transactions on Affective Computing 420.

Geographic Products Branch. 2012. “Urban and Rural.” Census Bureau QuickFacts, September 1. https://www.census.gov/geo/ reference/urban-rural.html.

Gimpel, James G., and Kimberly A. Karnes. 2006. “The Rural Side of the Urban-Rural Gap.” PS: Political Science and Politics 39 (3): 458-467.

Halpin, John, and Karl Agne. 2009. “State of American Political Ideology: A National Study of Political Values and Beliefs.” Center for American Progress 17-29.

Jokela, Markus, Bleidorn, Wiebke, Lamb, Michael E., Gosling, Samuel D, and Peter J. Rentfrow. 2015. “Geographically Varying Associations Between Personality and Life Satisfaction in the London Metropolitan Area.” PNAS 112 (3): 728-756.

Karp, Jeffrey A, Banducci, Susan A, and Shaun Bowler. 2008.

“Getting out the Vote: Party Mobilization in a Comparative Perspective.” British Journal of Political Science 38 (1): 89-102.

McGranahan, David and Calvin Beale. 2002. “Understanding Rural Population Loss.” Rural America 14 (4): 1-11.

McKee, Seth C., and Melanie J. Springer. 2015. “A Tale of ‘Two Souths’: White Voting Behavior in Contemporary Southern Elections.” Social Science Quarterly 96 (2): 588-607.

Miller, Arthur H., Patricia Gurin, Gerald Gurin, and Oksana Malanchuk. 1981. “Group Consciousness and Political Participation.” American Journal of Political Science 25: 494-511.

Montana Legislature. 2018. “Session Information.” October 1. https://leg.mt.gov/session/.

Nagel, Joane. 1995. “American Indian Ethnic Renewal: Politics and the Resurgence of Identity.” American Sociological Review 60 (6): 945-957.

National Conference of State Legislatures. 2015. “The Term-Limited States.” http://www.ncsl.org/research/about-state-legislatures/ chart-of-term-limits-states.aspx.

Oliver, Eric J. 2000. “City Size and Civic Involvement in Metropolitan America.” The American Political Science Review 94 (2): 350-365.

© Pi Sigma Alpha 2019

39

Pi Sigma Alpha Undergraduate Journal of Politics Reyes, German. 2016. “Non-Response Rates: Insights from 600,000 Opinion Surveys.” n.p. 17. http://pubdocs.worldbank.org/ en/708511466183857404/paper-reyes.pdf.

Rubin, Gretchen. 2011. “We Shape Our Buildings, and Afterwards Our Buildings Shape Us.” Forbes.com. https://www.forbes.com/ sites/gretchenrubin/2011/10/04/we-shape-our-buildings-andafterwards-our-buildings-shape-us/#51e4770f549d.

Street, Alexander. 2018. Helena, MT: Carroll College. 2018 Exit Poll. .https://scholars.carroll.edu/exit-polls/4.

Squire, Peverill. 1993. “Professionalization and Public Opinion of State Legislatures.” The Journal of Politics 55 (2): 476-489.

Tajfel, Henri, M.G. Billig, R.P. Bundy, and Claude Flament. 1971.

“Social Categorization and Intergroup Behavior.” European Journal of Social Psychology 1: 149-178.

United States Census Bureau. 2010. “QuickFacts: Wisconsin; Montana.” https://www.census.gov/quickfacts/fact/table/wi,mt/ PST045217.

Urban Indian Health Institute. 2013. “U.S. Census Marks Increase in Urban American Indians and Alaska Natives.” http://www.uihi. org/wp-content/uploads/2013/09/Broadcast_Census-Number_ FINAL_v2.pdf.

Warry, Wayne. 2007. Ending Denial: Understanding Aboriginal Issue.

99. The University of Toronto Press: Toronto.

Wisconsin State Legislature. 2018. “Session Calendar.” https://docs. legis.wisconsin.gov/2017/related/session_calendar/calendar.

Wisconsin, State of. 2011. “2011 Wisconsin Act 10: An act relating to: state finances, collective bargaining for public employees, compensation and fringe benefits of public employees, the state civil service system, the Medical Assistance program.” http://docs. legis.wisconsin.gov/2011/related/acts/10.

NOTES 1. This research was reviewed, expedited, and accepted by the Institutional Review Board at Carroll College. An approval letter was received from Carroll College dated October 12, 2018.

40

© Pi Sigma Alpha 2019

Rural Values in Montana

APPENDIX Participants:

5. What does the term “rural” mean to you?

• 48 respondents, ages 18 and above

6. Do “rural values” exist?

• At least 5 respondents from each of the following age categories: 18-25; 26-35; 36-55; 56+

7. How would you describe rural values?

Communities:

8. What do you think are the major issues facing people in (name of community)?

9. What do you think should be done to remedy these issues?

• Day 1: South-Central Montana

10. How much attention do you feel the state government pays to what the people in (community) want? What about the federal government?

• Day 2: Central Montana • Day 3: Central Montana • Day 4: North-Central Montana • Day 5: Northern Montana

a. A Lot

• Day 6: Northwest Montana

b. Some

• Day 7: Northwest Montana

c. Not Much

Interview Questions:

d. None

1. What is your age?

11. Agree or Disagree: People like me have a say in what the government does.

a. 18-25

12. Agree or Disagree: Public officials do not care much about what people like me think.

b. 26-35 c. 36-45

13. How would you describe a typical person from rural Montana?

d. 46-55 e. 56+

14. When evaluating a candidate running for any political office, what contributes most to the formation of your opinion?

2. Please state your ethnicity. a. White

a. Their policies (past, present, or proposed)

b. Hispanic or Latino

b. Their ability to represent and reflect your values

c. Black or African American d. Native American or American Indian e. Asian/Pacific Islander

c. Their understanding of the current political situation and the economy

f. Other (please specify)

d. Other (explain)

3. Please state your gender.

15. How important is it for you that politicians reflect the values of rural America?

a. Male b. Female

a. Very important

c. Other (please specify)

b. Somewhat important

4. Do you consider yourself to live in a rural area of Montana?

© Pi Sigma Alpha 2019

c. Not so important d. Not at all important

41

Pi Sigma Alpha Undergraduate Journal of Politics

Hitler’s Hand in the 21st Century: How Holocaust Collaboration in the 1940’s Shapes Modern Anti-Semitism Jenna Bisbee, Saint Anselm College What role do historical factors play in explaining the variation in present-day levels of anti-Semitism in Europe? Existing scholarship debates whether greater visibility of minority groups, economic factors such as unemployment rates, or historical factors (relationships between Jewish and non-Jewish communities) explain current levels of anti-Semitism. I hypothesize that anti-Semitism is inherited through culture and that countries that collaborated with the Nazis in the Holocaust are more likely to have higher levels of modern anti-Semitism than countries that did not collaborate. I also investigate alternative hypotheses such as the effects of unemployment rates and Jewish population size on levels of anti-Semitism. I answer my research question through a statistical analysis of data on modern levels of anti-Semitism and degrees of Holocaust collaboration. I supplement this analysis with a comparative case study of Bulgaria and the Netherlands, two countries with similar levels of Holocaust collaboration but differing levels of present-day anti-Semitism. My research establishes a positive relationship between Holocaust collaboration during World War II and present-day levels of anti-Semitism. My comparative case study suggests that although anti-Semitism is a cultural trait that can be passed down across generations, Holocaust education can aid in reducing modern European anti-Semitism.

INTRODUCTION

D

espite receiving minimal media attention, nearly all scholars agree that anti-Semitism is once again on the rise on a global scale. Europe is of particular interest due to its long history of anti-Semitism and, for some countries, participation in the Holocaust. The re-emergence of European anti-Semitism is evident in tragedies such as the Paris kosher market attack in 2015 (Witte 2015) and in recent political movements such as legislation prohibiting accusations of Poland’s participation in the Holocaust (Mackey 2018). What factors predict higher levels of anti-Semitism in some European countries and lower levels in others? I hypothesize that, as a result of the continuation of cultural norms, countries that collaborated with the Nazis in the Holocaust are more likely to have higher levels of modern anti-Semitism than countries that did not collaborate. Using OLS regression, I compare the Anti-Defamation League’s 2014 survey results on countries’ levels of anti-Semitism to my own scale of Holocaust collaboration ranging from 0 – 7. I found that Holocaust collaboration has a strong, positive influence on modern levels of anti-Semitism, and the relationship is statistically significant. I also found that unemployment rates from 2013 and the change in unemployment between 2009 2013 both have a positive impact on anti-Semitism; however, Jewish population size has no relationship to modern levels of anti-Semitism. After analyzing these four variables, I conducted a small-N case study based on Lieberman’s (2005) method of

42

nested analysis using Bulgaria and the Netherlands to evaluate the impact on Holocaust education as a way to hinder the spread of anti-Semitism across generations. As Lieberman suggests, I chose these two countries since they have the same level of collaboration (4) but different levels of anti-Semitism. Through this small-N analysis, I found that the Netherlands, which has extremely low levels of anti-Semitism (5%), actively promotes Holocaust education while Bulgaria, which has a higher level of anti-Semitism (44%) does not implement well-organized Holocaust education and does not take responsibility for its role in collaborating with the Nazis. Therefore, I conclude that although anti-Semitism is a cultural trait that can be passed down across generations, Holocaust education and awareness programs can aid in reducing post-Holocaust anti-Semitism in Europe.

Literature Review

At a basic level, most scholars agree that anti-Semitism, like other forms of anti-minority sentiment, is formed around the notion of perceived social categorization. These social categories arise when people with a common history, race, religion, or other perceived shared characteristics group together and see themselves as a superior homogeneous “in-group” while categorizing those who do not share these common traits into subordinate “out-groups” (Blumer 1958, 4). Anyone who does not qualify as part of the in-group is considered an alien outsider – a perception that the in-group uses to justify excluding, belittling, and marginalizing the out-

© Pi Sigma Alpha 2019

Hitler’s Hand in the 21st Century: How Holocaust Collaboration in the 1940’s Shapes Modern Anti-Semitism

group (Blumer 1958, 4). Prejudice against the out-group will arise if the in-group feels the outsiders threaten the perceived social order or have too much influence in society (Blumer 1958, 4; Valentine and McDonald 2004, 17).

Because of their perceived superiority, the in-group often feels that they deserve certain privileges or advantages in society which they believe the rest of the population is less entitled to (Blumer 1958, 4). The in-group may respond with prejudice if they feel that the outsiders have intruded upon these privileges (Blumer 1958, 4) or if the in-group believes the outsiders unfairly compete against them over limited resources, particularly economic opportunities, which the in-group feel they deserve (Allport 1979, 229; 371). In regards to the economy, Allport (1979) argues that groups will feel increasingly frustrated as they become more and more discontent about this perceived threatening economic competition. As frustration increases, the in-group will target the out-group they believe is responsible for their economic misfortune, resulting in prejudice against the targeted out-group (Allport 1979, 229; 350). Mocan and Raschke (2016) demonstrate evidence for this theory by analyzing German attitudes towards the economy in relation to their attitudes towards the German Jewish population. They discovered that survey respondents who viewed their individual financial situation negatively also held negative views about the Jewish population in Germany (Mocan and Raschke 2016, 16).

Bilewicz and Krzeminski (2010) conducted a similar study in Poland and the Ukraine and found the same positive correlation between perceptions about economic standing and anti-Semitic sentiments. In addition, they discovered in Poland that the more economically deprived citizens felt, the more they accepted negative stereotypes about the Jewish population (Bilewicz and Krzeminski 2010). These findings suggest that modern economic grievances could reinforce long-existing European stereotypes, such as that Jews use financial exploitation and their thirst for power for personal gain at the expense of the economy (Bergmann 2008, 346; 349). If this is the case, countries with weak economies, or other unfavorable conditions, may be more susceptible to anti-Semitism and the adoption of anti-Semitic stereotypes. This explanation, however, does not account for the presence of anti-Semitism in more stable nations.

In addition, many scholars agree that European Jews are often used as scapegoats. This means that when outside circumstances are unfavorable, the majority collectively blames the minority for the unfavorable conditions even if the minority had no direct involvement in the problem (Chesler 2003, 26-28). Unlike economic frustration, scapegoating does not assume that the out-group is infringing upon the in-group’s privileges nor does it assume that the out-group threatens ingroup superiority. Instead it merely seeks a party to blame for any inconveniences. From a psychological standpoint, blaming a minority relieves the majority from any responsibility for a problem and unites them against the perceived common enemy (Chesler 2003, 26-28). In many European countries, Jews make a convenient target for scapegoating since they are widespread 43

and well-integrated while still unique in their culture and therefore easily categorized as an out-group (Chesler 2003, 28).

Additionally, since Europe has an extensive history of using the Jewish population as a scapegoat, some authors theorize that Europeans default to scapegoating Jews in times of hardship when no other explanation is available (Goldstein 2012, 349).

Although the literature up to this point has focused on the nature of European anti-Semitism and anti-minority sentiments in general, it is vital to consider the reemergence of European anti-Semitism in the context of the Holocaust as well. Unlike other minorities, Jews are often well-integrated into European societies and are therefore not marginalized based on culture, religion, race, language, ethics, and other factors that normally categorize minorities (Bergmann 2008, 346-47; Valentine and McDonald 2004, 17). Instead, Jews are more often alienated due to their historical position in European society (Bergmann 2008, 346-47). For instance, due to their persecution throughout European history, many Jews feel victimized by European society and, as a result, have requested apologies from countries who participated in the Holocaust. While this could be considered a step towards healing, some believe that the Jews have over-victimized themselves and are using their victimhood to continue to make ongoing demands of restitution or to cast a negative image of the perpetrating countries (Bergmann 2008, 4; Imhoff and Banse 2009). This has caused continued resentment against Holocaust perpetrators from the international community as well as a growing irritation with the Jews for continuously seeking recognition as victims and portraying some countries as aggressors (Krondorfer 2008). Therefore, although it was originally believed that Holocaust recognition would create more empathy and compassion for the European Jewish population, some scholars believe this recognition has instead produced hostility and ultimately resulted in the rise of antiSemitism (Imhoff and Banse 2009; Porat 2013, 472). These findings suggest that variation in modern levels of European anti-Semitism may be determined by the extent to which Jews have been portrayed as Holocaust victims within each individual state. If this is the case, then countries where the Jews have been extensively portrayed as victims would be more likely to have higher levels of anti-Semitism as a result of the frustration against the Jewish community for their desire for post-Holocaust recognition.

Some literature suggests that the differences in postHolocaust politics between Eastern and Western Europe have also had an impact on levels of anti-Semitism. For instance, although the Soviets strongly opposed Nazi anti-Semitism, many Jews still endured discrimination and prejudice under Soviet rule (Gross 2006). Therefore, due to the lack of religious education and the continuation of anti-Jewish discrimination during the era of Eastern-European communism, some scholars argue that anti-Semitism never actually diminished in Eastern Europe but instead was temporarily masked, refined, and later unveiled with the fall of communism in the 1980’s and 1990’s (Ambrosewicz-

© Pi Sigma Alpha 2019

43

Pi Sigma Alpha Undergraduate Journal of Politics

Jacobs 2000, 569-70, 576-77; Gross 2006; Zuroff 2005). Unlike Western Europe, which underwent trials and restitution fairly soon after the war, Eastern Europe did not begin to address such matters until after the fall of communism (Zuroff 2005). At the time, in order to gain acceptance in the international sphere during the rise of democracy, Eastern European countries were suddenly pressured to reconcile and repent of national crimes related to the Holocaust long after these events had taken place (Zuroff 2005). However, many eastern nations felt that the Jews were demanding excessive recognition which furthered the pre-existing doctrine of anti-Semitism in Eastern Europe (Zuroff 2005). As a result, one could argue that post-communist countries are more likely to harbor more radical and widespread anti-Semitic sentiments today than Western European countries.

However, this explanation does not account for high levels of anti-Semitism in Western European countries that were not influenced by communist regimes.

Finally, in regards to the role of the Holocaust in modern anti-Semitism, several studies suggest that societies which supported the Nazi party during World War II are prone to have higher levels of anti-Semitism today (Bergmann 2008, 345-346; Mocan and Raschke 2016, 6; Voigtländer and Voth 2012, 17). This is because cultural traits, such as antiSemitism, can be passed down over time and persist in society (Mocan and Raschke 2016, 6). In addition, stereotypes and negative beliefs against Jews can be spread not only through familial relationships, but also through peers (Voigtländer and Voth 2012, 2). However, the proposed correlation between Holocaust collaboration and modern levels of anti-Semitism has thus far only been observed on a community level, not on a national level. Mocan and Rasche’s (2016) and Voigtländer and Voth’s (2012) studies were conducted exclusively within German society, looking at varying levels of anti-Semitism within certain German communities in light of whether or not the same community voted for the Nazi party in the 1920’s.

One scholar, Bergmann (2008), did argue that national levels of Nazi support and collaboration with the Holocaust could predict modern levels of anti-Semitism in Europe; however, his claims lacked any empirical evidence.

Overall, scholars have been unable to agree on a single theory to explain the variation of the degree of anti-Semitism in European countries. Furthermore, most literature regarding this subject relies solely on theory rather than tests of empirical data. As a result, research on why some European countries are more anti-Semitic than others is inconclusive.

Research Question and Hypothesis

Despite the various theories regarding the general existence of anti-Semitism in Europe, the lack of agreement among scholars leaves the main question unanswered. What factors predict higher levels of anti-Semitism in some European countries and lower levels of anti-Semitism in others? This study seeks to determine whether or not there is a relationship between Holocaust collaboration and the extent of anti44

Semitism in European countries today. I hypothesize that countries with high levels of Holocaust collaboration will have higher levels of modern anti-Semitism than countries with little or no collaboration. I hypothesize that this correlation is the result of the continuation of culture, norms, and beliefs over time (Mocan and Raschke 2016, 6). Although the Holocaust ended and the Allies liberated the concentration camps, the prejudice which fueled the Holocaust could not have suddenly disappeared at a social or political level after the war. Although some leading architects of the Holocaust from Nazi Germany were tried and brought to justice, many collaborators, at both state and local levels, were never accused. Average citizens who collaborated to exterminate the Jewish population during the Holocaust had families and businesses and continued to rebuild their lives after World War II ended. If society embodied antiJewish attitudes during the Holocaust, these prejudices would most likely have been accepted in institutions, adopted by children and students, and passed down across generations.

Finnemore and Sikkink (1998) identify a “lifecycle of norms” that helps explain how norms, such as cultural antiSemitism, might be transmitted as well as how they can be changed. In the lifecycle, norms first emerge as ideas in society promoted by norm entrepreneurs, then become increasingly accepted on a wide scale, before finally becoming an internalized, habitual part of society (Finnemore and Sikkink 1998, 895-896).

This cycle is not perfectly linear, but instead can vary or fail at any stage (Finnemore and Sikkink 1998, 895). Once a societal norm has taken root, these ideas are reinforced across generations not only through families and peers, but also through institutions such as churches, schools, and other organizations (Acharya, Blackwell, and Sen 2016, 637-638). After these norms are internalized in a culture, actors no longer think rationally or intentionally about these attitudes but instead accept them as ordinary (Finnemore and Sikkink 1998, 913). According to norm theorists, internalized norms will not just fade away over time, but instead they continue to be passed down over time unless new norms replace them or if social conditions no longer allow them to persist in society (Cubitt 2007, 180-181).

The strength of these norms can vary across time, societies, and cultures; however, once these norms are institutionalized, it can be radical to introduce new, competing ideas (Finnemore and Sikkink 1998, 897; Gelfand 2012, 423). Applying this theory to European anti-Semitism, I argue that prejudice, negative stereotypes about Jews, and an “us” versus “them” mentality have existed in various capacities for hundreds of years and were embodied during the Holocaust in countries that willingly collaborated against the Jewish population. Therefore antiSemitism has become an institutionalized, ordinary part of these European societies. Negative stereotypes and anti-Jewish prejudice have continued for so long because societies have not intentionally combatted these patterns of thinking with new norms (Cubitt 2007, 180-181). If not combatted, anti-Semitism could be passed down from the Holocaust era and continue to persist in former collaborating countries today.

© Pi Sigma Alpha 2019

44

Hitler’s Hand in the 21st Century: How Holocaust Collaboration in the 1940’s Shapes Modern Anti-Semitism

DATA, CONCEPTUALIZATION, AND OPERATIONALIZATION Main Hypothesis

In this study, the independent variable, Holocaust Collaboration, measures the extent to which an individual European country collaborated with Nazi Germany in the Holocaust. The dependent variable, Anti-Semitism, measures the level of anti-Semitism within that European country today.

For the purpose of this study, Holocaust collaboration can be defined as willing participation in Nazi agendas in working towards exterminating the Jewish race through genocide.

Holocaust Collaboration was measured using a sum of four different components. Data for each component span from 1939 to 1945 and were taken from a large variety of sources including publications by Holocaust museums, academic journals, and historical studies on individual countries. (See Appendix 1).

The first component of Holocaust Collaboration is the presence of the involvement of a state’s police forces in the eviction, deportation, or execution of Jews during the Holocaust. I collected data for police involvement from the United States Holocaust Memorial Museum (USHMM) and a compilation of sources for individual countries. Countries were coded as “1” if there was evidence of police involvement and “0” if there was no evidence of involvement. This factor is important since many sources argue that successful implementation of the Final Solution would not have been possible without the help of local authorities (Dean 2004, 121-122). However, I argue that police involvement alone is insufficient for measuring collaboration since police forces may have had other incentives to collaborate. Therefore, it must be combined with the following components.

The second component of Holocaust Collaboration is the presence of a Nazi-established puppet regime during the period of deportation of Jews from each country. If there was no puppet regime, it would be more likely that the nation’s own government is responsible for the state’s actions during the Holocaust. On the other hand, if there was a puppet regime, Jewish deportations were more likely the responsibility of Nazi occupiers rather than the state itself. These data were compiled from a variety of sources for each country, including academic journals, scholarly books published by various universities, and the USHMM website. Countries with no puppet regime were coded as “1” and countries with a puppet regime were coded as “0”. Neutral countries are an exception to this since although their own governments were in power during the Holocaust, they were not responsible for any collaboration because they chose to avoid direct involvement in World War II and the Holocaust. Therefore, neutral countries were coded as “0”.

The third component of Holocaust Collaboration is the presence of state-implemented systems of Jewish persecution in each country. For the purposes of this study, a state was coded as having a system of persecution if they willingly implemented one or more of the following: ghettos, forced

labor camps, deportations, death camps, or pogroms against the Jewish population. The presence of a nation’s own system of persecution, as opposed to systems implemented by Nazi occupiers, indicates the presence of anti-Semitism and a willingness to collaborate in the Holocaust. These data were compiled from a variety of sources for each country, including scholarly books, journals, and the USHMM website. Countries with their own persecution system were coded as “1”; countries without a persecution system were coded as “0”.

The fourth component of Holocaust Collaboration looks at what percentage of Jews were killed from each country during the Holocaust using a compilation of statistics from the USHMM, the Jewish Virtual Library, and other sources on individual countries. This measurement is relevant because it is less likely that the Germans would have been able to murder a high percentage of the Jewish population without the collaboration of the state or locals. Countries with death rates ranging from 1% - 25% were coded as “1”, from 26% - 50% were coded as “2”, from 51% - 75% were coded as “3”, and from 76% - 100% were coded as “4”.

After compiling data from various sources and coding each country accordingly, I added the scores from each of these coded factors for each country to create a single number on a scale of zero to seven that measures the extent of each state’s collaboration in the Holocaust. The higher the number, the greater extent a state has collaborated in the Holocaust.

In this study, the dependent variable Anti-Semitism is operationalized as an index score of anti-Semitism in each country produced from a 2014 survey conducted by the AntiDefamation League (ADL). Anti-Semitism is defined by the Anti-Defamation League as “The belief or behavior hostile toward Jews just because they are Jewish. It may take the form of religious teachings that proclaim the inferiority of Jews, for instance, or political efforts to isolate, oppress, or otherwise injure them. It may also include prejudiced or stereotyped views about Jews” (Anti-Defamation League 2018). The survey offered a series of statements to participants and asked respondents to indicate “probably true”, “probably false”, or “don’t recognize” as their response (Anti-Defamation League, 2015). The survey includes statements such as: • “Jews have too much power in international financial markets.”

• “Jews still talk too much about what happened to them in the Holocaust.”

• “Jews don’t care what happens to anyone but their own kind.”

• “Jews have too much control over global affairs.”

• “Jews think they are better than other people.”

• “Jews are responsible for most of the world’s wars.”

(Anti-Defamation League, 2015)

© Pi Sigma Alpha 2019

45

Pi Sigma Alpha Undergraduate Journal of Politics

The ADL calculated percentages of adults in each country who answered “probably true” to fifty percent or more of the statements (Anti-Defamation League, 2014). These percentages constitute the index scores of Anti-Semitism.

Alternative Hypotheses

In addition to evaluating the main hypothesis, current literature on anti-Semitism suggests two possible alternative hypotheses. First, if prejudice results from the formation of “in-groups” and “out-groups” (Blumer 1958, 4; Valentine and McDonald 2004, 17), it is possible that anti-Semitism would be greater in countries with larger Jewish populations since greater visibility of the Jewish “out-group” would cause the majority to feel more threatened. Second, some argue that when social and economic conditions are unfavorable the majority collectively blames minorities for these circumstances (Bilewicz and Krzeminski 2010, 242). If this is the case, countries with higher unemployment rates would be more likely to harbor anti-Semitic attitudes.

The first alternative hypothesis is that as the number of Jews in a country increases, the level of anti-Semitism also increases. The variable Jewish Population measures Jewish population estimates published by Berman Jewish Databank in 2013 for each of the countries in my analysis.

The second alternative hypothesis is that as a country’s unemployment rate increases, so does a country’s level of antiSemitism. The independent variable Unemployment 2013 was measured using 2013 unemployment rates published by the International Labor Organization. In addition to analyzing the correlation between Unemployment 2013 and Anti-Semitism, I was able to evaluate whether or not having an increase in unemployment resulted in higher levels of anti-Semitism.

The variable Unemployment Change was calculated using unemployment rates from 2009 from the International Labor

Organization to find the difference in unemployment between 2013 and 2009.

Sample, Data Limitations, and Missing Data

The sample for this analysis is comprised of twentysix of the Eastern and Western European countries involved in World War II as well as the neutral countries of Sweden, Spain, and Portugal. This sample is somewhat limited based on which countries existed during the 1940’s. It is possible to code some regions, such as the former Czechoslovakia, in terms of modern geography since the geographic regions of modern Slovakia and the Czech Republic acted somewhat independently from one another during the Holocaust (Fox 2004, 428). As a result, data are available to code these regions individually.

However, countries such as Bosnia and Herzegovina and North Macedonia, which were strongly imbedded in Yugoslavia during World War II, are not included in this study since they were impossible to code separately from other Yugoslavian countries.

Data were also limited depending on which countries were surveyed by the Anti-Defamation League in their analysis of modern anti-Semitism. Slovakia, for example, was excluded from the ADL survey and therefore data regarding their modern levels of anti-Semitism were unavailable.

In addition to limitations regarding case sampling, there were a few data limitations within the twenty-six countries analyzed as well. Due to the historical nature of the data, I was unable to collect certain collaboration variables in Austria and Portugal. These are the only two cases of missing data.

DATA ANALYSIS OLS Regression Analysis

Table 1 below details the descriptive statistics of the data I collected for each of the variables. It includes the average level

Table 1: Descriptive Statistics Variable

Mean

Standard Deviation

Minimum

Maximum

N

Anti-Semitism

28.9

14.4

4

69

26

Holocaust Collaboration

3.3

1.8

0

6

26

Jewish Population

0.1

0.2

0.005

0.8

26

Unemployment 2013

11.2

6.3

3.5

27.6

26

Unemployment Change

2.2

4.9

-6.2

18.1

26

All variables shown above are measured in percentages except for Holocaust Collaboration Jewish Population and Unemployment 2013 data were taken from 2013 Unemployment Change data were taken from 2009 and 2013 Anti-Semitism data were taken from 2014

46

© Pi Sigma Alpha 2019

Hitler’s Hand in the 21st Century: How Holocaust Collaboration in the 1940’s Shapes Modern Anti-Semitism

Table 2: OLS Regression Analysis Anti-Semitism

Model 1

Holocaust Collaboration

4.72*** (1.31)

Model 2

Model 3

Model 4

5.45 (17.45)

Jewish Population

1.21*** (0.40)

Unemployment 2013

1.31**

Unemployment Change

(0.53) 13.27**

28.17***

15.33***

26.03***

(4.91)

(3.67)

(5.06)

(2.82)

R²

0.35

0.004

0.28

0.20

N

26

26

26

26

Constant

Standard errors in parentheses; *p<0.10; **p<0.05; ***p<0.01 All variables shown above are measured in percentages except for Holocaust Collaboration Jewish Population and Unemployment 2013 data were taken from 2013 Unemployment Change data were taken from 2009 and 2013 Anti-Semitism data were taken from 2014

of Holocaust Collaboration, the average level of Anti-Semitism, the average Jewish Population, the average Unemployment 2013, and the average Unemployment Change for each of the twenty-six countries studied. The average of Anti-Semitism was approximately 29%. The standard deviation is approximately 14.4, indicating that Greece (69%) and Sweden (4%) are extreme outliers. In regards to Holocaust Collaboration, the average is approximately 3.3 on a scale that ranges from 0 – 7. The standard deviation is approximately 1.8. The highest collaborators were Hungary and Poland with a score of 6. The lowest on the collaboration scale included the neutral countries of Sweden, Spain, and Portugal with a score of 0. Among the non-neutral countries, the lowest collaborators included Denmark and Estonia with a score of 1.

All 26 countries studied had Jewish populations that made up less than 1% of the population. Slovenia had the lowest Jewish Population with 0.005% and France had the highest Jewish Population with 0.8%. On average, Jewish Population was 0.1%. The standard deviation is approximately 0.2. Overall, all of the countries studied had an extremely small Jewish Population which is interesting considering many of these countries are very anti-Semitic.

For this study, I analyzed unemployment rates in two different ways. Unemployment 2013 was measured using unemployment rates from the year 2013. The country

with the highest Unemployment 2013 was Greece with 27.6% unemployment. This was interesting considering that Greece also has the highest level of anti-Semitism as discussed previously. However, 2013 marks the beginning of the recession in Greece, so this unemployment rate might abnormally high. Norway had the lowest Unemployment 2013 with only 3.5% unemployment. The average Unemployment 2013 was 11.2% with a standard deviation of 6.3. In regards to Unemployment Change, which measures the difference in unemployment between 2013 and 2009, the average was 2.2% with a standard deviation of about 4.9. Latvia had the most favorable Unemployment Change at -6.2. This means that their unemployment rates were reduced by 6.2% between 2009 and 2013. Greece had the maximum Unemployment Change with their rates increasing by 18.1%.

After compiling the data for each of my variables, I analyzed them using OLS regression. These results are shown in Table 2 above. Model 1 shows a bivariate regression between Holocaust Collaboration and Anti-Semitism as the variables in my main hypothesis. The coefficient on Holocaust Collaboration is 4.72 and is statistically significant at the p<0.01 level. This means for every 1 unit increase in my collaboration variable, modern anti-Semitism is predicted to rise approximately 5%. This suggests a fairly strong correlation between the two variables. The R2 value is a measure of goodness of fit and

© Pi Sigma Alpha 2019

47

Pi Sigma Alpha Undergraduate Journal of Politics

can be interpreted as the extent to which the independent variable accounts for variation in the dependent variable. As shown in Model I, the R2 value is fairly high and indicates that Holocaust Collaboration accounts for 35% of the variation in Anti-Semitism. This indicates that Holocaust Collaboration is a good fit for predicting Anti-Semitism. Overall these results suggest that there is a strong correlation between Holocaust Collaboration and Anti-Semitism since there is a high coefficient and high statistical significance. This relationship is depicted in Figure 1.

Model 2 shows the results of a bivariate regression between Jewish Population and Anti-Semitism as described in my first alternative hypothesis. Based on these results, I find no relationship between Jewish Population and Anti-Semitism. The coefficient is positive (5.45), but not statistically significant.

Model 3 examines my second alternative hypothesis and shows a bivariate regression of Unemployment 2013

and Anti-Semitism. Here, the coefficient on unemployment is 1.21 which is statistically significant at the p<0.01 level.

This indicates that for every 1% increase in unemployment, anti-Semitism will increase by about 1%. The R2 shows that unemployment accounts for 28% of the variation in modern anti-Semitism, indicating that unemployment rates are a good fit for this data. Similarly, Model 4 shows the bivariate regression between Unemployment Change and Anti-Semitism.

Here, the coefficient is 1.31 and is statistically significant at the p<0.05 level. The R2 shows that Unemployment Change accounts for 20% of the change in Anti-Semitism, which indicates that Unemployment Change is a good fit for this data, but not as good of a fit as Unemployment 2013 as shown in Model 3. Overall, these results suggest that unemployment does affect modern levels of anti-Semitism.

Because data were only available for twenty-six countries, I did not have a large enough sample size to test for control

Figure 1: Anti-Semitism 2014 vs Holocaust Collaboration

Greece

Anti-Semitism 2014

60

Bulgaria

40 Russia

Portugal

Estonia

20

Hungary Belarus France Romania Lithuania

Latvia

Austria Italy

Denmark

Belgium

Croatia

Slovenia Finland Norway

Czech Republic Netherlands

Sweden

R 2 Linear = 0.351

0 1 2 3 4 5 6

Holocaust Collaboration

48

Poland

Ukraine Spain

0

Serbia

Š Pi Sigma Alpha 2019

Hitler’s Hand in the 21st Century: How Holocaust Collaboration in the 1940’s Shapes Modern Anti-Semitism

variables. Therefore, my regression alone is not entirely conclusive since Holocaust Collaboration, Unemployment 2013, and Unemployment Change are all statistically significant and could not be subjected to further quantitative analysis. As a result, in order to further analyze the relationship between Holocaust Collaboration and Anti-Semitism, I used Lieberman’s (2005) method of nested analysis which combines a large-N analysis with a small-N analysis to analyze variables through process tracing. His method suggests choosing cases that do not conform to the regression line, but instead are either above or below the expected outcome while having the same value on the independent variable (Lieberman 2005, 446). Lieberman’s method allows me to further analyze the cultural continuation of post-Holocaust anti-Semitism and what factors might hinder the spread of anti-Semitic sentiments in European cultures.

For this analysis, I have selected Bulgaria and the Netherlands as my sample countries since, as seen in Figure 1, they have the same level of Holocaust Collaboration but different levels of Anti-Semitism. Although they both have a Holocaust Collaboration score of 4, Bulgaria is above the regression line at 44% anti-Semitic while the Netherlands is far below the regression line at only 5% anti-Semitic. According to my theory of cultural continuation, since these countries have the same level of Holocaust Collaboration they should also have similar levels of Anti-Semitism. What factors cause variation in Anti-Semitism between countries with identical Holocaust Collaboration scores?

According to Finnemore and Sikkink’s (1998) theory of the lifecycle of norms, the successful introduction of new ideas, such as tolerance, that challenge pre-existing antiSemitism and hinder its continuation could explain how countries with the same level of Holocaust Collaboration could have varying levels of modern anti-Semitism. In other words, are institutions and norm entrepreneurs able to introduce education in ways that would create new norms to reduce anti-Semitism and prejudice? In order to analyze this question, I used process tracing to evaluate the different approaches that Bulgaria and the Netherlands have taken to prevent post-Holocaust generations from inheriting cultural traditions of anti-Semitism from older generations. I analyzed factors such as the framing of national Holocaust narratives, the effectiveness and implementation of Holocaust education, the role of Holocaust remembrance organizations, and the role of the nation’s government in promoting Holocaust awareness to combat anti-Semitism. Overall, I found that the Netherlands more actively promotes Holocaust education, more transparently acknowledges Dutch involvement in the Holocaust, and frames Holocaust education in ways to promote tolerance and responsibility. Bulgaria, on the other hand, has less Holocaust education and promotes a very controversial Holocaust narrative contrary to what historical records show.

Based on these findings, I argue that the implementation of Holocaust education hinders the spread of anti-Semitism across generations and that different approaches to Holocaust

education and recognition can result in varying levels of AntiSemitism between countries with similar levels of Holocaust Collaboration.

Bulgaria

During World War II, Bulgaria was an ally to Nazi Germany and an official member of the Axis alliance (USHMM, “Bulgaria”). They assisted the Nazis in the invasion of Yugoslavia and as a result were permitted to occupy parts of Greece and Yugoslavia, including modern day North Macedonia (USHMM, “Bulgaria”). Although they did not deport Jewish Bulgarian citizens to concentration camps, Bulgarian officials in annexed parts of Yugoslavia and Greece willingly deported over 11,000 Jews to killing centers where nearly all of them perished (USHMM, “Bulgaria”). As time went on, the Bulgarian government made plans with Nazi officials to deport Jews from Bulgaria proper as well; however, these plans were delayed and later abandoned after facing great resistance from Bulgarian intellectuals, opposition politicians, and church leaders (USHMM, “Bulgaria”). Although Bulgarian resistance fought to save the majority of Jews from deportation to killing centers, many Jews were murdered by the Bulgarian government in Yugoslavia and some Jewish Bulgarian citizens were expulsed from the capital city and interned in forced labor camps within Bulgaria itself (USHMM, “Bulgaria”).

When discussions about the incidents of the Holocaust first appeared in Bulgaria in the 1950’s and 1960’s, it was under the framework of political discourse rather than a desire to educate or for sympathy for persecuted Jews (Ragaru 2017; Chary 1994, 45-46). Since this time, both anti-communists and socialists (ex-communists) claimed that their political party was responsible for saving the Bulgarian Jews and both parties blamed either their political opponents or the German Nazis for the deportations of Jews in Greece and Yugoslavia (Ragaru 2017; Chary 1994, 45-46). In the early 2000’s, Bulgaria began to accept a more bi-partisan narrative regarding the rescue of the Bulgarian Jews as more historical records began to emerge; however, this newly-accepted narrative of Holocaust involvement focuses almost exclusively on the rescuing of the Bulgarian Jews and fails to recognize their role in the death of non-Bulgarian Jews (Ragaru 2017; Chary 1994, 46; USHMM and Salzburg Global Seminar, 2013).

Still today the image of the Bulgarians acting courageously as saviors to the Jewish population frames every aspect of Bulgarian remembrance. In fact, Bulgaria has recently taken extraordinary measures to outright ignore their involvement in the death of the Yugoslavian Jews to the point of placing excessive emphasis on their goodness during the Holocaust. For example, instead of joining the international community in recognizing January 27th as the official International Holocaust Remembrance Day, Bulgaria has instituted their own day of remembrance on March 10th called “The Day of the Holocaust and the Saving of Bulgarian Jews” (USHMM and Salzburg Global Seminar, 2013). Furthermore,

© Pi Sigma Alpha 2019

49

Pi Sigma Alpha Undergraduate Journal of Politics

to commemorate the 70th anniversary of the rescue of Bulgaria’s Jews, the Bulgarian Parliament published a declaration to “pay our respects to the victims of the Holocaust” (Novinite. com 2013). In the declaration, the parliament does recognize that there were Jews deported in their territories in Yugoslavia and Greece; however, they fail to take responsibility for these deportations and instead blame the German Nazis. They wrote: “An objective evaluation of the historic events today could not ignore the fact of the 11,343 Jews deported from North Greece and the Kingdom of Yugoslavia, which were at that time under German jurisdiction. We denounce this criminal act, undertaken by the Hitler’s commandment and express our regrets for the fact that the local Bulgarian administration had not been in a position to stop this act” (Novinite.com 2013).

Bulgaria’s failure to recognize their role in collaboration has also affected their relations with modern-day North Macedonia, which was under Bulgarian annexation during World War II. In 2011, the North Macedonian government sponsored the making of a film portraying a love story under the context of the Holocaust in North Macedonia (Risteska 2011). Since this film portrays the Holocaust in North Macedonia under Bulgarian occupation, Bulgarians accused North Macedonia of rewriting history and spreading hatred towards Bulgaria (Risteska 2011). This issue was brought under evaluation by the European Commission in Brussels to attempt to resolve the matter (Risteska 2011).

This incomplete Bulgarian narrative of the Holocaust is also present in the nation’s education system. Although Holocaust education is included in standard curriculum, the role of Bulgaria in the Holocaust is taught once again through the lens of Bulgarians as saviors to the Jewish people and the Germans as aggressors and perpetrators of prejudice (USHMM and Salzburg Global Seminar, 2013). Bulgarian schools do not teach about the murder of the Yugoslav and Greek Jews under Bulgarian authority, but they do teach about the Bulgarian Jews that were saved (Owen-Jones n.d.). Furthermore, there is no training for educators in Bulgaria on how to teach Holocaust education and the subject is usually not addressed until students reach 10th, 11th, or 12th grade (USHMM and Salzburg Global Seminar, 2013).

In addition, there was no mention of Bulgaria using historical monuments, Holocaust sites, or guest speakers as ways of teaching students about the Holocaust. Scholars agree that Holocaust memorials and museums are mechanisms for shaping public thought and memory about the Holocaust (Davis and Rubinstein-Avila 2013, 158). While some countries have used memorials to educate the public, there are very few Holocaust memorials in Bulgaria, and those that do exist represent the saving of the Bulgarian Jews rather than the memory of the victims (Owen-Jones n.d.). Furthermore, while some Jewish synagogues have temporary displays, there are no 50

official Holocaust museums in Bulgaria (Owen-Jones n.d.). A small display is located within the Central Sofia Synagogue, which says their collection focuses on “the salvation of the Jews in Bulgaria during the years of the Second World War, striking a bright contrast with the six million Jews, who tragically lost their lives across Europe during the times of Nazism” (Shalom n.d.). Therefore, although Bulgaria does acknowledge the Jews as victims of the Holocaust, they only acknowledge and mourn Jewish suffering as the tragedy of other nations rather than recognizing the blood on their own hands. Unlike some countries that resent Jews for “over-victimizing themselves” (Bergmann 2008; Imhoff and Banse 2009), Bulgaria gives the Jews plenty of recognition as victims as long as Bulgarians are not portrayed as the aggressors.

In 2012, Bulgaria started expressing an interest in joining the International Holocaust Remembrance Alliance (IHRA), a sub-organization of the United Nations dedicated to combatting anti-Semitism through the promotion of Holocaust education; however, Bulgaria initially joined only as an observer country and refused full membership status until 2018(Sofia Globe Staff 2017; IHRA 2018, “About Us”; Sofia Globe Staff 2018). When they finally adopted full membership, the ministry declared, “Bulgaria’s membership will provide a platform for an even wider global popularization of the act of saving Bulgarian Jews during World War 2…” (Sofia Globe Staff 2018).

Overall, Bulgaria has a rather weak Holocaust education system both inside and outside of the classroom setting. Their refusal to recognize Bulgarian collaboration in the Holocaust has prohibited them from teaching future generations the truth about anti-Semitism and prejudice. Although it is beneficial for Bulgarians to recognize the goodness of those who stood up for Jews during the Holocaust, it is necessary to accept their nation’s past mistakes in order to prevent similar incidents from reoccurring. Due to continual ignorance regarding their role in the Holocaust and refraining from implementing thorough educational programs, Bulgarians have allowed past traditions of anti-Semitism to continue through recent generations. Holocaust recognition and education is necessary in order to allow future generations to heal and learn from past mistakes.

The Netherlands

After Germany invaded the Netherlands in May, 1940, the Dutch royal family fled the country and the Nazis immediately set up a civil administration run by the SS (Braber 2014, 76; USHMM, “Netherlands”). Unlike Bulgaria, the Netherlands had remained neutral in the war until occupied

by Germany (Braber 2014, 76). Once occupied, anti-Jewish measures were gradually implemented with the help of the Dutch National Socialist party, a pre-existing Dutch anti-Semitic party that gained more power under the Nazi occupation, and local police collaboration (Braber 2014, 83,100; Blom, Fuks-Mansfeld, and Schoffer 2001, 320). In

© Pi Sigma Alpha 2019

Hitler’s Hand in the 21st Century: How Holocaust Collaboration in the 1940’s Shapes Modern Anti-Semitism

addition to demoting Jews and segregating them in society, Dutch collaborators worked with the Nazis to burn synagogues, punish resisters, and eventually deport Jews to concentration camps (Blom, Fuks-Mansfeld, and Schoffer 2001, 311). While there were some resistance movements, including an anti-Nazi strike organized by Jews in 1941, these efforts were quickly smothered by the Nazi occupiers, and the public refrained from organizing further collective action (Blom, Fuks-Mansfeld, and Schoffer 2001, 306). Although most anti-Semitic measures were carried out by a radical minority of the Dutch population, the majority of the Dutch accepted new implementations and generally responded passively to Jewish suffering (Blom, FuksMansfeld, and Schoffer 2001, 301). As anti-Semitic policies increased, the Dutch natives began to accept the view that the Jews were inferior and not a part of civil society (Blom,FuksMansfeld, and Schoffer 2001, 310). Instead of resisting, the Dutch knew that if they kept quiet and did not protest, they themselves would be safe from Nazi persecution (Blom, FuksMansfeld, and Schoffer 2001, 310).

Unlike Bulgaria, the Netherlands has successfully implemented various methods of education and commemoration in order to combat anti-Semitism and preserve Holocaust education for future generations. For instance, the Netherlands joined the International Holocaust Remembrance Alliance in 1999, just one year after the founding of the organization (IHRA 2018, “Netherlands”). Since joining the IHRA, the Netherlands has served as the rotating chair of the organization for two separate terms and has played a vital role in designing and implementing Holocaust education materials aimed at recognizing the past and preventing anti-Semitism in the future (IHRA 2018, “Netherlands”; Government of the Netherlands 2011). In addition, they have partnered with the IHRA to host international Holocaust education and remembrance meetings, to organize international research institutions, to form relationships between Dutch Holocaust museums and other international foundations, and to update and preserve former concentration camps (IHRA 2018, “Netherlands”; Government of the Netherlands 2011).

Dutch involvement in international Holocaust remembrance organizations, such as the IHRA, demonstrates a willingness not only to recognize the past but also to promote Holocaust awareness in order to combat anti-Semitism.

In addition to promoting and supporting international Holocaust programs, the Netherlands has also instituted strong domestic educational programs in hopes of preventing homegrown Dutch anti-Semitism. The Dutch government enforces standards for Holocaust education which indicate that students must be able to identify “certain consequences of the German occupation during the Second World War and the process of Nazification and the persecution of the Jews” (Boersema and Schimmel 2001). In addition, students must be able to comprehend the different “reactions of the Dutch population to German occupation”, which includes understanding the various roles the Dutch played not only as victims, but also

bystanders and perpetrators in the Holocaust (Boersema and Schimmel 2001). Unlike Bulgarian education, Dutch Holocaust educational programs are implemented at a relatively young age, starting with a basic overview of the Holocaust in primary school and going more in-depth through literature, films, and guest speakers in secondary school (Zwaan 2005). In order to further implement the reality of the Holocaust in the Netherlands, many Dutch schools organize field trips to local commemorative sites including memorials and museums, such as the Anne Frank House (Zwaan 2005). In primary schools, the government has also recently implemented a program encouraging schools to adopt a local WWII or Holocaust monument as a way for students to familiarize themselves with Holocaust history on a local level (Government of the Netherlands, “Public education”). Furthermore, politicians such as the State Secretary for Health, Welfare and Sport have partnered with the National Youth Council in the Netherlands to encourage young individuals to embrace Holocaust remembrance (Government of the Netherlands, 2012).

Initiatives by the Dutch government to support and implement Holocaust education on both a domestic and international level show that the Netherlands is truly committed to recognizing the past and using the tragedies of the Holocaust as a tool for preventing anti-Semitism through education.

After comparing Bulgaria and the Netherlands, these findings suggest that although anti-Semitism has a strong correlation to Holocaust collaboration, certain initiatives can be put into place in order to inhibit the spread of anti-Semitism in future generations. Based on Finnemore and Sikkink’s (1998) norm theory, these results indicate that institutions aimed at promoting Holocaust education, such as schools and museums, can serve as norm entrepreneurs and can combat the spread of cultural anti-Semitism by challenging existing anti-Semitic attitudes. As described above, the Netherlands strives to promote Holocaust education on various levels and has worked hard to preserve all aspects of Holocaust history – both the positive aspects and the shameful aspects – as a lesson for future generations about the consequences of prejudice. By teaching these lessons to Dutch children at a young age and reinforcing Holocaust education with hands-on field trip experiences, the Netherlands has been able to promote a highly tolerant society and have impressively low levels of anti-Semitism. Bulgaria, on the other hand, has refused to accept their role as collaborators in the genocide and has fed their society a false narrative about Bulgarian history. Moreover, although Bulgaria does have Holocaust curriculum, it is less organized and students are not exposed to it until very late in their academic career. By the time a student reaches high school, he or she has already been exposed to many different ideas both in society and in their homes. Although Holocaust education is important at any age, I believe Holocaust education in Bulgaria would be more effective aimed at younger students in order to expose them to the dangers of prejudice before they reach adolescence.

© Pi Sigma Alpha 2019

51

Pi Sigma Alpha Undergraduate Journal of Politics

Furthermore, the first step in combating cultural antiSemitic norms is to recognize their existence and to accept the need for change. Although Bulgaria does have some Holocaust education, their skewed historical accounts have prevented future generations from identifying the problem of anti-Semitism in Bulgaria because the institutions teach them that Bulgarians saved the Jews, while society continues to spread prejudice and negative stereotypes. This incomplete narrative implies that Bulgaria does not have a problem with anti-Semitism and, as a result, norm entrepreneurs do not feel the need to create new norms of tolerance. In addition, although norm entrepreneurs and Holocaust remembrance organizations have tried to reach Bulgaria, norm theorists argue that norms typically require the support of the state to embrace new norms and to shape institutions to make these changes (Finnemore and Sikkink 1998, 900). The Bulgarian government refuses to accept responsibility for their Holocaust collaboration and have not identified norms of prejudice that need to change through education programs and involvement in international organizations. As a result, new norms of tolerance and unity have not taken root in Bulgaria. Bulgaria cannot combat its norm of cultural anti-Semitism if they ignore and deny it ever existed.

In conclusion, an in-depth analysis of these two cases shows that countries that take decisive action to promote Holocaust education are more likely to reduce levels of antiSemitism despite previous collaboration in the Holocaust.

Likewise, countries that fail to recognize past collaboration and as a result do not educate their citizens efficiently are more likely to have higher levels of anti-Semitism.

DISCUSSION AND CONCLUSION

My research makes several contributions to the field of Holocaust studies as well as studies on prejudice and modern anti-Semitism. This study adds to the idea that anti-Semitism is cultural and can be passed down through generations. As seen in my OLS regression, Holocaust collaboration has a strong positive correlation to modern levels of anti-Semitism and is statistically significant. Several authors argue that Nazi support in pre-war elections would predict anti-Semitism (Bergmann 2008, 345-346; Mocan and Raschke 2016, 6; Voigtländer and Voth 2012, 17), however, previous studies had only been conducted within German towns and not on an international scale. Overall, my results were consistent with the conclusions of the authors who had previously studied the correlation between small-town Nazi supporters and modern anti-Semitism within those same locations today. As my study indicates, this positive relationship between historical events and current anti-Jewish prejudice stays consistent when applied to an international level as well as a community level.

In order to expand on this relationship between historical events and modern prejudice, I would be interested in analyzing the difference between citizen collaboration 52

versus state collaboration and their different impacts on anti-Semitism. In my analysis, I code collaboration based on four factors: police cooperation, the presence of a puppet regime, the presence of a system of state-implemented Jewish persecution, and the percentage of Jewish fatalities in the Holocaust. The first three variables measure state collaboration in the Holocaust while the last variable is intended to measure how strong resistance was against Jewish persecution. In theory, if local resistance was very high they would have resisted against Jewish deportations, such as the case in Denmark, and would have generally low fatality rates. On the other hand, if citizens passively or actively allowed persecution to take place, the fatality rates would be higher. In this way, my analysis combined state collaboration variables with local collaboration variables to evaluate to what extent a nation collaborated in the Holocaust. Future research should evaluate citizen versus state collaboration variables separately to analyze whether one has a greater impact on modern anti-Semitism. Do norms of antiSemitism become more institutionalized in societies that had more local collaboration than state collaboration?

In addition to coding police collaboration, regime type, state-implemented persecution systems, and the percentage of Jewish fatalities, future research should consider evaluating Holocaust collaboration using additional criteria if possible.

For the purposes of this study, I was unable to collect data for additional criteria of Holocaust collaboration due to a lack of access to resources. These resources are composed of historical records which are often incomplete, inaccessible, or require translating from their original languages. However, with the proper access to resources, adding more criteria to the operationalization of Holocaust collaboration would provide a more extensive evaluation of how different methods of collaboration affect modern anti-Semitism.

This research is also innovative in analyzing individual case studies in addition to a large-N analysis when evaluating anti-Semitism. Although it is important to recognize that historical events can affect modern prejudice, it is perhaps more important to understand what factors can minimize the continuation of prejudice across generations. Based on the results of my small-N analysis, it appears that Holocaust education is an important tool for combatting the spread of anti-Semitism in European countries. However, because I only evaluated two cases, it is difficult to know the strength of this relationship. It is possible that other factors, such as Bulgariaâ&#x20AC;&#x2122;s history of communism, played a role in the variation of antiSemitism. Future research should conduct similar analyses using wider sample sizes to see whether using Holocaust education to combat anti-Semitism is effective across a variety of countries.

Scholars agree that other types of education, such as multicultural education, can work towards reducing prejudice in general (Camicia 2007, 225). Although multicultural education likely reduces prejudice, if combatting anti-Semitism is the goal then Holocaust education most intensely identifies

Š Pi Sigma Alpha 2019

Hitler’s Hand in the 21st Century: How Holocaust Collaboration in the 1940’s Shapes Modern Anti-Semitism

the problem and consequences of anti-Semitism specifically.

Multicultural education combats prejudice very broadly and does not associate its lessons to address any specific type of prejudice. Through Holocaust education, students identify concrete examples of the severity of hatred, how it can have numerous victims, and how it can affect any society. Does the generality of multicultural education effectively combat antiSemitism or are the concrete examples in Holocaust education necessary to combat this prejudice?

This study also contributed new evidence regarding the correlation between a country’s Jewish population size and the level of anti-Semitism within that country. Current scholarship argues that prejudice is formed based on the perceived social categories of “in-groups” and “out-groups” (Blumer 1958, 4; Valentine and McDonald 2004, 17), which suggests that greater visibility of the “out-group” might cause the “in-group” to feel threatened and prejudiced against the “out-group”. My results did not find support for this hypothesis. Therefore, although prejudice may be founded upon the notion of “ingroups” and “out-groups” (Blumer 1958, 4; Valentine and McDonald 2004, 17), a greater visibility of the “out-group” in this case does not affect the level of prejudice.

Regarding unemployment rates, my study shows that unemployment, whether it is a fixed unemployment rate or the change in unemployment, does significantly affect that nation’s level of anti-Semitism. This conclusion supports previous research showing that individuals who are not content with their financial situation are more likely to be anti-Semitic (Allport 1979, 229; 350; Bilewicz and Krzeminski 2010; Mocan and Raschke 2016, 16). These findings demonstrate that this correlation previously analyzed on a community or individual level remains positive and statistically significant when applied to an international level. Future research should analyze whether this relationship between unemployment and anti-Semitism stays consistent across different regions of the world or whether it most significantly applies to European countries. Future research should also evaluate whether antiSemitism appears during prolonged periods of economic hardship or if it can spike after a sudden economic downfall.

Overall, this study shows that prejudice can run deep in societies and can be passed down across generations. This finding has significant implications not only in the study of anti-Semitism but also regarding other post-conflict societies around the world. This study indicates that while passing legislation, implementing human rights policies, and ending oppressive conditions are necessary steps to overcoming identity-based conflict, it is necessary to combat hatred in the hearts and minds of people in order to prevent prejudice from being passed down to future generations. In the context of anti-Semitism, Holocaust education serves as a mechanism to promote empathy, intercultural understanding, and citizenship on a societal level. This type of education can dispel stereotypes and prevent future generations from resorting back to stereotyping and blaming the “other” when problems, such

as economic hardship, arise. These results suggest that other societies that have experienced identity-based conflict, such as Hutus and Tutsis in Rwanda, may also benefit from instituting educational programs aimed at reducing prejudice in younger generations and preventing hatred from passing down to future generations. n

ABOUT THE AUTHOR:

Jenna Bisbee is a graduate of the Saint Anselm College Class of 2019. She majored in International Relations with minors in History and French Language and Literature. During her senior year, she presented her research at multiple academic conferences, including the Pi Sigma Alpha Undergraduate Conference (Washington, DC), the Midwestern Political Science Association conference (Chicago), and at Saint Anselm College’s Mind Over Major conference (Manchester, NH).

After graduation, she spent a month as a research intern for an international peacemaking organization in the Middle East.

Since returning from the Middle East, Jenna now works as an Educational Outreach Coordinator for a Holocaust survivor in New Hampshire. In the latter role, she has promoted Holocaust education in schools, drafted state legislation to create Holocaust education standards, and worked with the state governor to improve genocide education in her state.

In the future, she hopes to continue her education and her research in a graduate program.

REFERENCES

Acharya, Avidit, Matthew Blackwell, and Maya Sen. 2016. “The Political Legacy of American Slavery.” The Journal of Politics 78 (3): 621-641.

Allport, Gordon W. n.d. The Nature of Prejudice. Reading, MA: Addison-Wesley Publishing Company.

Ambrosewicz-Jacobs, Jolanta. 2000. “Attitudes of Young Poles toward Jews in Post-1989 Poland.” East European Politics and Societies 14 (3): 565-596.

Anti-Defamation League. 2014. “ADL Poll of Over 100 Countries Finds More Than One-Quarter of Those Surveyed Infected with Anti-Semitic Attitudes.” https://www.adl.org/news/press-releases/ adl-global-100-poll (Accessed May 2, 2018).

Anti-Defamation League. 2015. “ADL Global 100.” http://global100. adl.org/#map/weurope (Accessed April 6, 2018).

Anti-Defamation League. 2018. “Anti-Semitism.” https://www.adl. org/anti-semitism (Accessed October 28, 2018).

Bergmann, Werner. 2008. “Anti-Semitic Attitudes in Europe: A Comparative Perspective.” Journal of Social Issues 64 (2): 343-362.

Berman Jewish Databank. 2013. “World Jewish Population 2013.”

American Jewish Yearbook. http://www.jewishdatabank.org/studies/ downloadFile.cfm?fileid=3113 (Accessed September 13, 2018).

Bilewicz, Michal, and Ireneusz Krzeminski. 2010. “Anti-Semitism in Poland and Ukraine: The Belief in Jewish Control as a Mechanism of Scapegoating.” International Journal of Conflict and Violence 4 (2): 235-243.

© Pi Sigma Alpha 2019

53

Pi Sigma Alpha Undergraduate Journal of Politics Blom, J.C.H., R.G. Fuks-Mansfeld, and I. Schoffer, eds. 2001. The History of the Jews in the Netherlands. London: The Littman Library of Jewish Civilization.

Blumer, Herbert. 1958. “Race Prejudice as a Sense of Group Position.”

The Pacific Sociological Review 1 (1): 3-7.

Boersema, Jacob and Noam Schimmel. 2001. “Challenging Dutch holocaust Education: Towards A Curriculum Based On Moral Choices And Empathetic Capacity.” Humanity in Action. https:// www.humanityinaction.org/knowledgebase/8-challenging-dutchholocaust-education-towards-a-curriculum-based-on-moralchoices-and-empathetic-capacity (Accessed November 1, 2018).

Braber, Ben. 2014. This Cannot Happen Here: Integration and Jewish Resistance in the Netherlands, 1940-1945. Amsterdam: Amsterdam University Press.

Camicia, Steven P. 2007. “Prejudice Reduction through Multicultural Education: Connecting Multiple Literatures.” Social Studies Research and Practice 2 (2): 219-227.

Chary, Frederick B. 1994. “Anti-Semitism and the Treatment of the Holocaust in Postcommunist Bulgaria.” In Anti-Semitism and the Treatment of the Holocaust in Postcommunist Eastern Europe, edited by Randolph L. Braham. New York, NY: Columbia University Press.

Chesler, Phyllis. 2003. The New Anti-Semitism: The Current Crisis and What We Must Do About It. San Francisco, CA: Jossey-Bass.

Cubitt, Geoffrey. 2007. History and Memory. Manchester, UK: Manchester University Press.

Gross, Jan. 2006. Fear: Anti-Semitism in Poland after Auschwitz. New York: Random House.

Imhoff, Roland, and Rainer Banse. 2009. “Ongoing Victim Suffering Increases Prejudice: The Case of Secondary Anti-Semitism.”

Psychological Science 20 (12): 1443-1447.

International Holocaust Remembrance Alliance. 2018. “About Us: Promoting Holocaust education, research and remembrance since 1998.” https://www.holocaustremembrance.com/about-us (Accessed November 1, 2018).

International Holocaust Remembrance Alliance. 2018. “Netherlands.” https://www.holocaustremembrance.com/member-countries/ netherlands (Accessed November 1, 2018).

International Labor Organization. 2014. “Where is the unemployment rate the highest in 2014?” http://www.ilo.org/global/about-the-ilo/ multimedia/maps-and-charts/WCMS_233936/lang--en/index. htm (Accessed September 13, 2018).Krondorfer, Björn. 2008. “Is Forgetting Reprehensible? Holocaust Remembrance and the Task of Oblivion.” Journal of Religious Ethics 36 (2): 233–267.

Lieberman, Evan S. 2005. “Nested Analysis as a Mixed-Method Strategy for Comparative Research.” American Political Science Review 99 (3): 435-452.

Mackey, Robert. 2018. “Polish Law on Holocaust Draws New Attention to Anti-Semitism in Poland’s Past and Present.” The Intercept. March 3. https://theintercept.com/2018/03/03/evenpoland-never-enforces-new-holocaust-law-lot-damage-alreadydone/ (Accessed March 27, 2018).

Davis, Bryan L., and Eliane Rubinstein-Avila. 2013. “Holocaust Education: global Forces Shaping Curricula Integration and Implementation.” Intercultural Education 24 (1-2): 149-166.

Dean, Martin. 2004. “Local Collaboration in the Holocaust in Eastern Europe.” In The Historiography of the Holocaust, edited

by Dan Stone. New York, NY: Palgrave Macmillan, 120-140.

Finnemore, Martha, and Kathryn Sikkink. 1998. “International Norm Dynamics and Political Change.” International Organization 52 (4): 887-917.

Mocan, Naci, and Christian Raschke. 2016. “Economic Well-Being and Anti-Semitic, Xenophobic, and Racist Attitudes in Germany.”

European Journal of Law and Economics 41 (1): 1-63.

Fox, Thomas C. 2004. “The Holocaust Under Communism.” In The Historiography of the Holocaust, edited by Dan Stone. New York, NY: Palgrave Macmillan, 420-439.

Owen-Jones, Caderyn. n.d. “Bulgaria." Holocaust Remembrance Project. https://www.holocaustremembranceproject.com/ Countries/Bulgaria (Accessed January 13, 2020).

Gelfand, Michele J. 2012. “Culture’s Constraints: International Differences in the Strength of Social Norms.” Current Directions in Psychological Science 21 (6): 420-424.

Porat, Dina. 2013. “Holocaust Denial and the Image of the Jew, or: ‘They Boycott Auschwitz as an Israeli Product’.” In Resurgent Antisemitism, edited by Alvin H. Rosenfeld. Bloomington: Indiana University Press, 467-481.

Goldstein, Phyllis. 2012. A Convenient Hatred: The History of Antisemitism. Brookline, MA: Facing History and Ourselves.

Government of the Netherlands. 2011. “The Netherlands chairs the Holocaust Task Force.” August 3. https://www.government.nl/ latest/news/2011/03/08/the-netherlands-chairs-the-holocaust-taskforce (Accessed November 1, 2018).

Government of the Netherlands. 2012. “State Secretary for health, Welfare and Sport announces support for International Holocaust Memorial Day.” June 2. https://www.government.nl/latest/ news/2012/02/06/state-secretary-for-health-welfare-and-sportannounces-support-for-international-holocaust-memorial-day (Accessed November 1, 2018).

Government of the Netherlands. n.d. “Public education about the Second World War.” https://www.government.nl/topics/secondworld-war/public-education-about-the-second-world-war (Accessed November 1, 2018).

54

Novinite.com. 2013. “Bulgarian Parliament’s Declaration on the 70th Anniversary of Rescue of Jews.” Sofia News Agency. March 10. https://www.novinite.com/articles/148552/Bulgarian+Parliament%27s+Declaration+on+70th+Anniversary+of+Rescue+of+Jews (Accessed November 1, 2018).

Ragaru, Nadege. 2017. “Contrasting Destinies: The Plight of Bulgarian Jews and the Jews in Bulgarian-occupied Greek and Yugoslav Territories during World War Two.” March 15. https:// www.sciencespo.fr/mass-violence-war-massacre-resistance/en/ document/contrasting-destinies-plight-bulgarian-jews-and-jewsbulgarian-occupied-greek-and-yugoslav- (Accessed November 1, 2018).

Risteska, Aneta. 2011. “Macedonian Wartime Love Story Angers Bulgarians.” Balkan Insight. http://www.balkaninsight.com/sr/ article/macedonian-wartime-love-story-angers-bulgarians (Accessed November 1, 2018).

Shalom: Organization of the Jews in Bulgaria. n.d. “Museum.” https:// www.shalom.bg/en/museum/ (Accessed January 13, 2020).

Sofia Globe Staff. 2017. “Bulgaria is a step closer to full membership of the International Holocaust Remembrance Alliance.” The Sofia

© Pi Sigma Alpha 2019

Hitler’s Hand in the 21st Century: How Holocaust Collaboration in the 1940’s Shapes Modern Anti-Semitism Globe. July 1. https://sofiaglobe.com/2017/07/01/bulgaria-is-astep-closer-to-full-membership-of-the-international-holocaustremembrance-alliance/ (Accessed November 1, 2018).

Sofia Globe Staff. 2018. “Bulgaria Joins the International Holocaust Remembrance Alliance as Full Member.” The Sofia Globe. https:// sofiaglobe.com/2018/11/29/bulgaria-joins-the-internationalholocaust-remembrance-alliance-as-full-member/ (Accessed January 13, 2020).

United States Holocaust Memorial Museum. n.d. “Bulgaria.”

Holocaust Encyclopedia. https://encyclopedia.ushmm.org/content/ en/article/bulgaria (Accessed October 11, 2018).

United States Holocaust Memorial Museum. n.d. “Collaboration.”

Holocaust Encyclopedia. https://www.ushmm.org/wlc/en/article. php?ModuleId=10005466 (Accessed April 6, 2018).

United States Holocaust Memorial Museum. n.d. “The Netherlands.”

Holocaust Encyclopedia. https://encyclopedia.ushmm.org/content/ en/article/the-netherlands (Accessed January 12, 2020).

United States Holocaust Memorial Museum and Salzburg Global Seminar. 2013. “Global Perspectives on Holocaust Education: Trends, Patterns, and Practices.” https://holocaust.salzburgglobal. org/fileadmin/ushm/documents/Overview/May2013_ GlobalPerspectives_final.pdf (Accessed November 1, 2018).

Valentine, Gill, and Ian McDonald. 2004. Understanding Prejudice: Attitudes Towards Minorities. London, UK: Stonewall.

Voigtländer, Nico and Hans-Joachim Voth. 2012. “(Re-) Shaping Hatred: Anti-Semitic Attitudes in Germany, 1890-2006.” CEPR Discussion Paper No. DP8935. Available at SSRN: https://ssrn. com/abstract=2066308 Witte, Griff. 2015. “In a Kosher Grocery Store in Paris, Terror Takes a Deadly Toll.” The Washington Post. January 9. https:// www.washingtonpost.com/world/europe/paris-kosher-marketseized-in-second-hostage-drama-in-nervous-france/2015/01/09/ f171b97e-97ff-11e4-8005-1924ede3e54a_story.html?utm_ term=.8374d3a94c5c (Accessed March 27, 2018).

Zuroff, Efraim. 2005. “Eastern Europe: Anti-Semitism in the Wake of Holocaust-Related Issues.” Jewish Political Studies Review 17 (1-2). http://www.jcpa.org/phas/phas-zuroff-s05.htm (Accessed March 27, 2018).

Zwaan, Ton. 2010. “Teaching and Learning About WWII, Holocaust and Genocide in the Netherlands.” Learning From History. January 28. http://learning-from-history.de/International/content/7497 (Accessed November 1, 2018).

© Pi Sigma Alpha 2019

55

Pi Sigma Alpha Undergraduate Journal of Politics

APPENDIX 1: HOLOCAUST COLLABORATION SOURCES Austria

ushmm.org/wlc/en/article.php?ModuleId=10005466 (Accessed April 6, 2018).

Police: CODE MISSING Puppet Regime: YES (Code 0)

Puppet Regime: YES (Code 0)

United States Holocaust Memorial Museum. n.d.

“Austria.” Holocaust Encyclopedia. https://encyclopedia. ushmm.org/content/en/article/austria (Accessed October 21, 2018).

United States Holocaust Memorial Museum. n.d.

“Belgium.” Holocaust Encyclopedia. https://encyclopedia.ushmm.org/content/en/article/belgium (Accessed October 11, 2018).

Bukey, Evan Burr. 2000. Hitler’s Austria: Popular Sentiment in the Nazi Era, 1938-1945. Chapel Hill, NC: The University of North Carolina Press.

Extermination System: NO (Code 0) Death Rates: 60% (Code 3)

Pauley, Bruce F. 1992. From Prejudice to Persecution: A History of Austrian Anti-Semitism. Chapel Hill, NC: The University of North Carolina Press.

Bulgaria

Extermination System: NO (Code 0)

Police: YES (Code 1)

(Bukey 2000, 131)

(USHMM, “Collaboration”)

Death Rates: 35% (Code 2)

Puppet Regime: NO (Code 1)

United States Holocaust Memorial Museum. n.d. “Jewish Losses During the Holocaust: By Country.” Holocaust Encyclopedia. https://encyclopedia.ushmm.org/ content/en/article/jewish-losses-during-the-holocaustby-country (Accessed October 5, 2018).

United States Holocaust Memorial Museum. n.d.

“Bulgaria.” Holocaust Encyclopedia. https://encyclopedia.ushmm.org/content/en/article/bulgaria (Accessed October 11, 2018).

Belarus

Chary, Frederick B. 1972. The Bulgarian Jews and the Final Solution 1940-1944. Pittsburgh, PA: University of Pittsburgh Press.

Police: YES (Code 1) Dean, Martin. 2000. Collaboration in the Holocaust: Crimes of Local Police in Belorussia and Ukraine, 194144. New York, NY: Saint Martin’s Press.

Puppet Regime: YES (Code 0) Beorn, Waitman Wade. 2014. Marching Into Darkness: The Wehrmacht and the Holocaust in Belarus. Cambridge, MA: Harvard University Press.

Extermination System: NO (Code 0) (Beorn 2014, 27-28) Death Rates: 65% (Code 3) Jewish Virtual Library. n.d. “The ‘Final Solution’: Estimated Number of Jews Killed.” https://www. jewishvirtuallibrary.org/estimated-number-of-jewskilled-in-the-final-solution (Accessed October 8, 2018).

Belgium

56

(USHMM, “Belgium”) (Jewish Virtual Library, “The ‘Final Solution’”)

Extermination System: YES (Code 1)

Death Rates: 22% (Code 1) (Jewish Virtual Library, “The ‘Final Solution’”)

Croatia Police: YES (Code 1) (USHMM, “Collaboration”) Puppet Regime: YES (Code 0) Mojzes, Paul. 2011. Balkan Genocides: Holocaust and Ethnic Cleansing in the Twentieth Century. Plymouth, United Kingdom: Rowman & Littlefield Publishers, Inc. United States Holocaust Memorial Museum. n.d. “Axis Invasion of Yugoslavia.” Holocaust Encyclopedia. https://encyclopedia.ushmm.org/content/en/article/ axis-invasion-of-yugoslavia (Accessed October 23, 2018).

Police: YES (Code 1)

Extermination System: NO (Code 0)

United States Holocaust Memorial Museum. n.d.

“Collaboration.” Holocaust Encyclopedia. https://www.

Death Rates: 95% (Code 4)

(Mojzes 2011, 52-53)

© Pi Sigma Alpha 2019

Hitler’s Hand in the 21st Century: How Holocaust Collaboration in the 1940’s Shapes Modern Anti-Semitism

Subotic, Jelena. 2018. “Political memory, ontological security, and Holocaust remembrance in post-communist Europe.” European Security 27 (3): 296-313.

Czech Republic (Bohemia and Moravia)

(Misiunas and Taagepera 1993, 62) Death Rates: 21% (Code 1) (USHMM, “Jewish Losses During the Holocaust”)

Finland

Police: YES (Code 1) Rothkirchen, Livia. 1984. “The Jews of Bohemia and Moravia: 1938-1945.” In The Jews of Czechoslovakia, edited by Avigdor Dagan, Gertrude Hirschler, and Lewis Weiner. Philadelphia, PA: The Jewish Publication Society of America, 3-74.

Puppet Regime: YES (Code 0)

Police: YES (Code 1) Cohen, William B. and Jörgen Svensson. 1995. “Finland and the Holocaust.” Holocaust and Genocide Studies 9 (1): 70-92.

Puppet Regime: NO (Code 1)

(Rothkirchen, Livia 1984, 15)

Upton, Anthony F. 1965. Finland in Crisis 1940-1941.

Ithaca, NY: Cornell University Press.

Extermination System: NO (Code 0)

Extermination System: NO (Code 0)

(Rothkirchen, Livia 1984, 9)

(Cohen 1995)

Death Rates: 65% (Code 3)

Death Rates: 0.38% (Code 1)

(USHMM, “Jewish Losses During the Holocaust”)

Pre-war population:

Denmark Kirchhoff, Hans. 1995. “Denmark: A Light in the Darkness of the Holocaust? A Reply to Gunnar S. Paulsson.” Journal of Contemporary History 30 (3): 465-479.

United States Holocaust Memorial Museum. n.d.

“Jewish Population of Europe in 1933: Population Data by Country.” Holocaust Encyclopedia. https:// encyclopedia.ushmm.org/content/en/article/ jewish-population-of-europe-in-1933-population-data-by-country?parent=en%2F7294 (Accessed October 20, 2018).

Puppet Regime: YES (Code 0)

Number of Jews Killed:

Petrow, Richard. 1974. The Bitter Years: The Invasion and Occupation of Denmark and Norway April 1940-May 1945. New York, NY: William Morrow & Company, Inc.

Hogan, David J., and David Aretha, eds. 2003. “Jews Killed During the Holocaust by Country.” In The Holocaust Chronicle, eds. David J. Hogan and David Aretha. Lincoln, IL: Publications International, 702.

Extermination System: NO (CODE 0)

France

Abrahamsen, Samuel. 1987. “The Rescue of Denmark’s Jews.” In The Rescue of the Danish Jews, edited by Leo Goldberger. New York: New York University Press, 3-11.

Police: YES (Code 1)

Death Rates: 0.69% - 1.54% (CODE 1)

Puppet Regime: NO (Code 1)

Police: NO (CODE 0)

(USHMM, “Jewish Losses During the Holocaust”)

Benbassa, Esther. 1999. The Jews of France: A History from Antiquity to the Present. Princeton, NJ: Princeton University Press.

Laub, Thomas J. 2010. After the Fall: German Policy in Occupied France, 1940-1944. New York, NY: Oxford University Press.

Estonia Police: NO (Code 0)

(Benbassa 1999, 178)

(USHMM, “Collaboration”) Misiunas, Romauld J., and Rein Taagepera. 1993. “The War Years, 1940-1945.” In The Baltic States: Years of Dependence 1940-1990. Berkeley and Los Angeles: University of California Press, 15-75.

Boissoneault, Lorraine. 2017. “Was Vichy France a Puppet Government or a Willing Nazi Collaborator?”

Smithsonian.com. https://www.smithsonianmag.com/ history/vichy-government-france-world-war-ii-willingly-collaborated-nazis-180967160/ (Accessed October 11, 2018).

Extermination System: NO (Code 0)

Yad Vashem. 2018. “Concentration Camps in France.”

Puppet Regime: YES (Code 0)

© Pi Sigma Alpha 2019

57

Pi Sigma Alpha Undergraduate Journal of Politics

Yad Vashem. https://www.yadvashem.org/yv/en/holocaust/france/camps.asp (Accessed October 9, 2018).

Extermination System: YES (Code 1) (Yad Vashem 2018, “Concentration Camps in France”) Death Rates: 26% (Code 2)

(Reguer 2013, 129-144) (USHMM, “Collaboration”) Zuccotti, Susan. 2000. Under His Very Windows: The Vatican and the Holocaust in Italy. New Haven, CT: Yale University Press.

Death Rates: 20% (Code 1)

(Jewish Virtual Library, “The ‘Final Solution’”)

(Jewish Virtual Library, “The ‘Final Solution’”)

Greece Police: YES (Code 1)

Latvia

Bowman, Steven B. 2009. Agony of Greek Jews, 1940-1945.

Stanford, CA: Stanford University Press.

Police: NO (Code 0) (USHMM, “Collaboration”)

Puppet Regime: YES (Code 0)

Puppet Regime: YES (Code 0)

(Bowman 2009, 10)

(Misiunas and Taagepera 1993)

Extermination System: NO (Code 0)

Extermination System: NO (Code 0)

(Bowman 2009, 10)

(Misiunas and Taagepera 1993, 62)

Death Rates: 77% (Code 4)

Death Rates: 75% (Code 3)

(Jewish Virtual Library, “The ‘Final Solution’”)

(USHMM, “Jewish Losses During the Holocaust”)

Hungary

Lithuania

Police: YES (Code 1)

Police: NO (Code 0)

(USHMM, “Collaboration”)

(USHMM, “Collaboration”)

Puppet Regime: NO (Code 1)

Puppet Regime: YES (Code 0)

Braham, Randolph L. 2000. The Politics of Genocide: The Holocaust in Hungary. Detroit, MI: Wayne State University Press.

(Misiunas and Taagepera 1993)

History.com Editors. 2009. “Hungary Declares War on Germany.” History. https://www.history.com/this-dayin-history/hungary-declares-war-on-germany (Accessed October 17, 2018).

Extermination System: YES (Code 1)

Extermination System: NO (Code 0) (Misiunas and Taagepera 1993) Death Rates: 85% (Code 4) (USHMM, “Jewish Losses During the Holocaust”)

Netherlands Police: YES (Code 1)

(Braham 2000, 31-32)

(USHMM, “Collaboration”)

Death Rates: 70% (Code 3)

Puppet Regime: YES (Code 0)

(Jewish Virtual Library, “The ‘Final Solution’”)

Warmbrunn, Werner. 1963. The Dutch under German Occupation 1940-1945. Stanford, CA: Stanford University Press.

Italy Police: NO (Code 0) Reguer, Sara. 2013. “World War II.” In The Most Tenacious of Minorities: The Jews of Italy. Brighton: Academic Studies Press, 129-144.

Extermination System: NO (Code 0)

Puppet Regime: NO (Code 1)

(Jewish Virtual Library, “The ‘Final Solution’”)

Marchione, Margerita. 1997. Yours Is a Precious Witness: Memoirs of Jews and Catholics in Wartime Italy. Mahwah, NJ: Paulist Press.

Extermination System: NO (Code 0)

58

(Warmbrunn 1963, 166) Death Rates: 75% (Code 3)

Norway: Police: YES (CODE 1) Abrahamsen, Samuel. 1991. Norway’s Response to the

© Pi Sigma Alpha 2019

Hitler’s Hand in the 21st Century: How Holocaust Collaboration in the 1940’s Shapes Modern Anti-Semitism

Romania

Holocaust: A Historical Perspective. New York, NY: Holocaust Library.

Police: YES (Code 1)

Puppet Regime: YES (CODE 0) (Abrahamsen 1991, 10) Bruland, Bjarte, and Mats Tanestuen. 2011. “The Norwegian Holocaust: changing views and representations.”

Scandinavian Journal of History 36 (5): 587-604.

Extermination System: NO (CODE 0) (Abrahamsen 1991, 10) Wennström, Johan. 2017. “Anarchy, State, and Utopia: Timothy Snyder’s Interpretive Framework for the Holocaust Applied to Norway Under the Nazi Occupation, 1940-45.” IFN Working Paper No. 1151. Available at SSRN: https://ssrn.com/abstract=3112225

Ioanid, Radu. 2000. The Holocaust in Romania: The Destruction of Jews and Gypsies under the Antonescu Regime, 1940-1944. Chicago, IL: Ivan R Dee, Inc. Puppet Regime: NO (Code 1) United States Holocaust Memorial Museum. n.d. “Romania.” Holocaust Encyclopedia. https://encyclopedia. ushmm.org/content/en/article/romania (Accessed October 9, 2018).

Extermination System: YES (Code 1) – pogroms and had own camp (Ioanid 2000, 62-63; 67)

Poland

Brustein, William I., and Ryan D. King. 2004. “Anti-Semitism as a Reponse to Perceived Jewish Power: The Cases of Bulgaria and Romania before the Holocaust.” Social Forces 83 (2): 691-708.

Police: YES (Code 1)

Death Rates: 50% (Code 2)

Piotrowski, Tadeusz. 1998. Poland’s Holocaust: Ethnic Strife, Collaboration with Occupying Fores and Genocide in the Second Republic, 1918 – 1947. Jefferson, NC: McFarland & Company, Inc., Publishers.

(Jewish Virtual Library, “The ‘Final Solution’”)

Russia (non-occupied Soviet Union)

Puppet Regime: YES (Code 0)

(USHMM, “Collaboration”)

(Longerich 2010, 143; 147)

Puppet Regime: NO (Code 1)

Extermination System: YES (Code 1)

Arad, Yitzhak. 2009. The Holocaust in the Soviet Union.

Lincoln, NE: University of Nebraska Press.

Death Rates: 50% (CODE 2) (Jewish Virtual Library, “The ‘Final Solution’”)

(Piotrowski 1998, 40)

Police: NO (Code 0)

Death Rates: 90% (Code 4)

Extermination System: NO (Code 0)

(Jewish Virtual Library, “The ‘Final Solution’”)

(Arad 2009)

Portugal

Death Rates: 11% (Code 1)

Police: NO (Code 0)

(Jewish Virtual Library, “The ‘Final Solution’”)

Schulze, Rainer. 2012. “The Heimschaffungsaktion of 1942-43: Turkey, Spain and Portugal and their Responses to the German Offer of Repatriation of their Jewish Citizens.” Holocaust Studies 18 (2-3): 49-72.

Serbia Police: YES (Code 1) (Mojzes 2011, 76)

(USHMM, “Collaboration”)

Puppet Regime: YES (Code 0)

Puppet Regime: NEUTRAL (Code 0)

(Mojzes 2011, 74)

Schulze, Rainer. 2012. “The Heimschaffungsaktion of 1942-43: Turkey, Spain and Portugal and their Responses to the German Offer of Repatriation of their Jewish Citizens.” Holocaust Studies 18 (2-3): 49-72.

Extermination System: NO (Code 0)

Extermination System: NO (Code 0)

Shoah Resource Center. n.d. “Yugoslavia.” Yad Vashem. https://www.yadvashem.org/odot_pdf/Microsoft%20 Word%20-%206379.pdf (Accessed October 23, 2018).

(Schulze 2012, 60-63)

Death Rates: 88% (Code 4)

Death Rates: MISSING

(USHMM, “Jewish Losses During the Holocaust”)

© Pi Sigma Alpha 2019

59

Pi Sigma Alpha Undergraduate Journal of Politics

Slovenia

Ukraine

Police: NO (Code 0)

Police: YES (Code 1)

(Mojzes 2011, 68-69)

Weinryb, Bernard D. 1970. “Antisemitism in Soviet Russia.” In The Jews in Soviet Russia Since 1917, edited

by Lionel Kochan. London: Oxford University Press, 288-320.

(USHMM, “Collaboration”) Puppet Regime: YES (Code 0) (USHMM, “Axis Invasion of Yugoslavia”) Extermination System: NO (Code 0)

Gilboa, Yeoshua A. 1971. The Black Years of Soviet Jewry 1939-1953. Boston, MA: Little, Brown and Company.

(Shoah Resource Center,“Yugoslavia”)

Puppet Regime: YES (Code 0)

Death Rates: 87% (Code 4)

Lower, Wendy. 2005. Nazi Empire-Building and the Holocaust in Ukraine. Chapel Hill, NC: University of North Carolina Press.

(USHMM, “Jewish Losses During the Holocaust”)

Spain

Extermination System: NO (Code 0)

Police: NO (Code 0)

(Lower 2005, 69-78)

Leitz, Christian. 2015. “Spain and the Holocaust.” Holocaust Studies 11 (3): 70-83.

Death Rates: 60% (Code 3)

Puppet Regime: NEUTRAL (Code 0)

(Jewish Virtual Library, “The ‘Final Solution’”)

(Leitz 2005, 70) Extermination System: NO (Code 0) (Leitz 2005) (Schulze 2012, 56-60) Death Rates: 0% (Code 0) Pre-war population: (USHMM, “Jewish Population of Europe in 1933”) Number of Jews Killed: (Hogan and Aretha, 2003)

Sweden Police: NO (Code 0) Levine, Paul A. 1996. From Indifference to Activism: Swedish Diplomacy and the Holocaust 1938-44. Uppsala, Sweden: Uppsala University.

Puppet Regime: NEUTRAL (Code 0) Shoah Resource Center. n.d. “Sweden.” Yad Vashem. https:// www.yadvashem.org/odot_pdf/Microsoft%20Word%20 -%206061.pdf (Accessed November 13, 2018).

Extermination System: NO (Code 0) (Levine 1996, 13) Death Rates: 0% (Code 0) Pre-war population: (USHMM, “Jewish Population of Europe in 1933”) Number of Jews Killed: (Hogan and Aretha, 2003)

60

© Pi Sigma Alpha 2019

Hitler’s Hand in the 21st Century: How Holocaust Collaboration in the 1940’s Shapes Modern Anti-Semitism

APPENDIX 2: HOLOCAUST COLLABORATION CODES Appendix 2: Holocaust Collaboration Codes Countries

Police

Austria

Puppet Regime

System of Persecution

Percentage Killed

Total Collaboration

0

0

2

2

Belarus

1

0

0

3

4

Belgium

1

0

0

3

4

Bulgaria

1

1

1

1

4

Croatia

1

0

0

4

5

Czech Republic

1

0

0

3

4

Denmark

0

0

0

1

1

Estonia

0

0

0

1

1

Finland

1

1

0

1

3

France

1

1

1

2

5

Greece

1

0

0

4

5

Hungary

1

1

1

3

6

Italy

0

1

0

1

2

Latvia

0

0

0

3

3

Lithuania

0

0

0

4

4

Netherlands

1

0

0

3

4

Norway

1

0

0

2

3

Poland

1

0

1

4

6

Portugal

0

0

0

Romania

1

1

1

2

5

Russia

0

1

0

1

2

Serbia

1

0

0

4

5

Slovenia

0

0

0

4

4

Spain

0

0

0

0

0

Sweden

0

0

0

0

0

Ukraine

1

0

0

3

4

© Pi Sigma Alpha 2019

0

61