Compilation source: Braun, Robert. “Bloodlines: National Border Crossings and Antisemitism in Weimar Germany.” American Sociological Review87.2: 202–236.

2025/05/1401:35:43 psychological 1926

Blood ties: Weimar Germany's border ports and anti-Semitism

Abstract:

This article believes that national border ports are concentrated places of xenophobia. The two mechanisms come together to create this pattern. First, when nation-states are under pressure, border ports make transnational differences prominent, creating a perceived link between international forces and socio-economic problems of socially disadvantaged classes. Second, border ports symbolize international threats and attract active nationalist mobilization from radical movements, who see foreign nations as international demons. In this unique spatial landscape, foreign nations become scapegoats for wider social problems among individuals who have lost their social status. I elaborate on my point of view through my study of the endemic changes in anti-Semitism of Weimar Germany before the Nazi era. Statistical analysis of the scourge of Jewish and in-depth discussion of local anti-Semitism reports reveal how the diversity of Weimar Republic began to erode among the lower and middle class members living on the margins of the country. In the process, I draw attention to the spatial sources of xenophobia and demonstrate that the borders between states activate boundaries within states, bringing new revelations to the complex relationship between pluralism and state formation.

Author profile:

Robert Braun, Department of Sociology, University of California, Berkeley

Compilation source:

Braun, Robert. “Bloodlines: National Border Crossings and Antisemitism in Weimar Germany.” American Sociological Review87.2 (2022): 202–236.

Author of this article: Robert Braun

Introduction

Anti-immigrant mobilization in Western Europe (Koopmans and Olzak 2004), racial relations in the United States (Olzak 1994; Spilerman 1970; Tolnay and Beck 1995), Hindu -Muslim riots in Southeast Asia (Biggs and Dhattiwala 2012; Brass 2011; Varshney 2003; Wilkinson 2006) and anti-Semitism in central Europe (Brustein 2003; Charnysh 2015) all focus on how xenophobia manifests itself in different spaces. Given this empirical regularity globally, it is not surprising that many attempt to explain the spatial heterogeneity of resentment towards outsiders. Most of these academic studies emphasize the importance of political or economic threats in explaining xenophobic changes. In politics, scholars demonstrate how political threats and incitement by movement leaders (Brass 2011; Wilkinson 2006) shape local differences in xenophobic conflict. Instead, economic arguments emphasize the importance of scapegoats (Blalock 1982), through which outsiders are accused of general social chaos or economic crisis (Bendix 1952; Blumer 1958; Olzak 1994), especially among disadvantaged social classes (Lipset 1960).

Most of these studies use "location" as the observation unit, and regard "location" as a container carrying variables for statistical analysis. In contrast, this article emphasizes how “location” itself (Garrido 2019; Gieryn 2000; Logan 2012) shapes xenophobia by coordinating collective emotions (Simmel 1997) and changing perceptions of social problems (Simmel 1994). More precisely, I think that when nation-states are under economic and political pressure, national border ports – the physical spaces where people cross the border – will become the focus of xenophobia, especially for those who are losing their social status.

Two fusion mechanisms link national border ports with fear of foreigners. First, a perceptual mechanism activates the internationalization of social problems. Border ports make the country clear and make people perceive the impact of the international on their lives (Barth 2012; Gellner 1964; Pfaff 2006). Therefore, the border ports create an "international lens" through which local vulnerable groups perceive their social problems. This leads these groups to link their problems to international origins. Second, the attraction mechanism produces external radical nationalist mobilization. Border ports often symbolize international threats and thus attract radical nationalist movements, who see foreign nations as responsible for negative international impacts on social life (Brubaker 1996; Häkli 1998; Radcliffe 1998).The latter mechanism exacerbates the framework for racial aliens as scapegoats for international issues (Snow et al., 1986), while the former mechanism connects social issues with international origins, allowing these frameworks to persist among those who have lost their social status (Koopmans and Olzak, 2004; McDonnell, Bail and Tavory, 2017). It is therefore the convergence of political and economic interactions in a unique spatial environment that creates a breeding ground for xenophobia, revealing that political threats, movement incitement, economic dissatisfaction and the impact of social classes on xenophobia discourse is conditioned on its wider position in the country (Garrido 2019; Schaeffer and Legewie 2016).

I elaborate on this argument through my study of anti-Semitism in Weimar Germany. Out of dissatisfaction with existing measures of anti-Semitism below countries that rely heavily on events of extreme collective violence, I constructed two new data sets to capture the temporal and geographical changes of anti-Semitism. The first dataset, based on data collected by anthropologists, captures anti-Semitism in 19,828 places by observing the universality of Jewish villains in Kinderschreck, a verbal tradition that uses fear to induce children’s obedience. The second dataset contains the encoding of 2283 anti-Semitism events, which came from a local report prepared by Centralverein, the largest secular Jewish organization in the Weimar Republic, dedicated to monitoring and combating the rise of anti-Semitism thought and behavior. The use of two datasets ensures the robustness of my findings, as each has different advantages: the former provides a time dimension and provides an opportunity to compare subtle changes in anti-Semitism before and after the introduction of national border ports; the latter allows us to interpret the key processes and participants in the emergence of resentment against Jews.

empirical analysis was re-produced in accordance with Lipsett's "lower-middle class theory", which argues that small business owners and farmers are more likely to seek scapegoats because they are particularly influenced by Weimar's political and economic issues (Lipsett 1960). Smidged between organized labor and capital, the lower and middle classes see their relative status deteriorating because they are both sellers and buyers in the market (Jensen-Butler 1976), and when large-scale inflation they cannot price themselves (Geiger 1930). Data from

Kinderschreck shows that after the nation-state was established, the border ports in Weimar Germany formed a hotbed of anti-Semitism, especially for places with more small business owners and farmers. Reports from Centralverein show that border ports are magnets for radical nationalists and activate resentment from lower and middle classes on international influence, which were greatly affected by economic turmoil in the 1930s. Over time, this local resentment and external nationalist mobilization brought together to create a fertile soil for the spread of Jewish scapegoats. This finding is of great significance to the study of xenophobia because it shows that the influence of political mobilization, socio-economic issues or social class on xenophobia is conditioned by the spatial location within the state (Garrido 2019; Schaeffer and Legewie 2016), thus clarifying the spatial connection between xenophobia and the rise of nation-states (Wimmer 2002, 2012). This study also reveals how classical xenophobia interacts with contemporary spatial configurations to the point where hatred erupts (Charnysh 2015; Voigtländer and Voth 2012).

Border and xenophobia

Previous studies on racial conflict (Blalock 1982; Olzak 1994), immigration (Koopmans and Olzak 2004), and anti-Semitism (Kopstein and Wittenberg 2018) have identified several explanations of xenophobia that go beyond the direct link between minority size and hostility. Despite the diversity of knowledge, two main themes that emerge in these literatures are the role of economic and political threats. These two aspects of research provide the basis for the boundary-crossing topics elaborated here.

Research on the economic logic of racial bias shows that members of dominant ethnic or ethnic groups tend to blame minorities in times of economic crisis or social chaos (Blumer 1958).Perception is key in this process (Bélanger and Pinard 1991), because “scapegoats” are particularly common among most members, who see themselves as competing with minorities for scarce resources such as work (Olzak 1994), or they see ethnic minorities as the middleman between them and the elite (Blalock 1982). In his lower-middle class theory, Lipset (1960) linked these dynamics to class, believing that scapegoats are a common strategy for disadvantaged members of the lower-middle class, trapped between organized labor and large capital owners.

This approach coincides with historical scholarship on wartime German economic anti-Semitism, which links anti-Semitism to economic modernization and crisis. Capitalism , the rise of industry and liberalism liberated the Jews economically, politically and socially. The social mobility of Jews caused fear among the Gentiles, who developed resentment in their prominent position in the financial industry (Niewyk 2018). Consistent with Lipset's argument, scholars argue that the losers of industrial progress, most prominently among medium-sized farmers and small business owners, harbor the strongest anti-Semitism resentment, as they suffered the most from the economic turmoil of the 1930s (Heberle 1962; Loomis and Beegle 1946).

’s work on political dynamics and xenophobia underscores the importance of electoral threats and subsequent incitement of racial competition by movement leaders. Again, ideas are essential to understanding this logic. In this view, minorities are only scapegoats for socio-economic issues when they are seen as an electoral threat to political institutions or nation-states as a whole (Kopstein and Wittenberg 2018). In these cases, most members may have xenophobic outbreaks independently or under the influence of the ideological framework, collective identity and mobilization network provided by sports entrepreneurs (Biggs and Dhattiwala 2012; Brass 2011; Wilkinson 2006). Empirical support for this model of political threat has been found in a wide range of cases, including anti-Semitism in twentieth-century Europe (Brustein 2003).

Overall, the evidence on xenophobia and different types of ethnic threats is far from conclusive. Partly because much of the work in this field is so vague about how and when different threats are considered to be (Bélanger and Pinard 1991). More and more work is trying to clarify the finer conditions in which economic and political threats translate into resentment against minorities (Garrido 2019; Schaeffer and Legewie 2016). I join this literature, conceptualizing how space and location constrain the impact of economic and political threats on xenophobia by shaping perceptions of social problems. In this way, I advance spatial social analysis by treating the relative position of places as variables (Logan 2012). Here, local and social processes are deeply intertwined, because local – defined as a fixed, unique, physically established position in the universe – is infused with meaning and value. As I will show, it is through social processes that places like border ports represent unique forms of power, memory, and identity (Gieryn 2000).

Zimmel's work provides a useful starting point for understanding how locations shape behavior (Garrido 2019). According to Zimmel, fixed physical locations, such as bridges, churches or doors, shape social behavior by attracting and shaping perceptions of differences. First, the location can organize collective emotions by providing fixed orientations as magnets for collective action. Zimmer (1997) gave an example that the church’s chapel became the key point in forming religious relations, releasing the power of public rather than isolation, transforming believers into collective church believers. Second, fixed places divide and connect independent spaces, shape perceptions by making the experience of difference more specific and intense (Simmel 1994).

Attraction mechanism: Radical nationalist mobilization

The attraction and perception mechanism provided by Zimmer seems particularly suitable to describe the social impact of national border ports, i.e. fixed physical points such as customs, border defenses or checkpoints, connect and separate different nation-states by transcending originally impermeable boundary lines.As borders symbolize international competition and cross-border influences, already xenophobic nationalists see border ports as places where they can win or lose territory for the state (Häkli 1998; Wilson and Donnan 1998). Therefore, border ports attract mobilization from xenophobics, especially radical nationalist groups, whose aim is to defend the nation-state and oppose outsiders (Brubaker 1996; Elcioglu 2020), and turn border ports into a center of incitement for nationalism (Elcioglu 2020; Wilson and Donnan 1998). These radical nationalist groups carry xenophobic frameworks characterized by international scapegoats, through which they hope to shape the emotions of the locals. I call this process the attraction mechanism. Needless to say, strengthening the use of xenophobic frameworks does not automatically resonate (McDonnell et al., 2017; Snow et al., 1986). To this end, I turn to the second mechanism, which reveals why xenophobic frameworks are more readily accepted among disadvantaged social classes living in border areas.

Perception Mechanism: Internationalization of social problems

border ports not only intensify external agitation and xenophobic framework deployment, but they also influence the views of local residents on social problems. Border ports are fixed in an inherent tension because they make the nation-state both powerful and vulnerable, activate a marginalized process that brings international differences and challenges to the attention (Gellner 1964; Pfaff 2006). On the one hand, border ports physically engrave the power of the nation-state and increase their visibility by demarcating the scope of their powers (Barth 2012). On the other hand, they function as membranes through which peoples, goods, resources and information from other nation-states travel (Wilson and Donnan 1998).

Therefore, people living near border ports not only have excessive contact with the authorities, markets and citizens of their own countries, but also those across the border. Depending on the local situation, border ports can mark the concept of opposition to ethnic and racial identity (Brubaker 1996); the negative effects of cross-border currency differences, smuggling, invasion, immigration, tourism and other forms of foreign competition (Radcliffe 1998; Wilson and Donnan 1998); and the contempt of state categories by groups such as racial mixing, stateless person or regionalists (Elcioglu 2020; Sahlins 1989).

, individually, each of these intermittent processes makes border ports a “lens” of international disagreements caused by major geopolitical, social and economic events such as wars or economic crises (Wilson and Donnan 1998). During times of crisis, border crossings have expanded perceptions of international inequality, threats and negative cross-border impacts (Brubaker 1996). In this social environment, economically vulnerable locals will be more likely to blame their increased social problems on forces located outside the country and become susceptible to xenophobic sentiment. I call this process a perception mechanism. The two mechanisms of

are combined to create a xenophobic space involving international scapegoats. Radical nationalist mobilization activated by attraction mechanisms strengthens the supply of top-down xenophobic frameworks involving international scapegoats, but it does not explain why these frameworks resonate among locals who have lost their social status. Framework is more likely to resonate if it is linked to the way people envision actual challenges in everyday life (McDonnell et al., 2017). This is where the perception mechanism comes into play. By highlighting the international origins of local social problems, it makes vulnerable groups more likely to accept xenophobic frameworks involving international scapegoats. Figure 1 summarizes the process of this convergence. A social group has lost its status. Proximity to border crossings allows these groups to link their losses to negative international impacts. Furthermore, border ports attracted radical nationalist groups, which exacerbated the framework for national outsiders as international demons. These frameworks resonate among the lost social groups living near border areas (Koopmans and Olzak 2004; Snow et al., 1986), because they have linked their social losses to negative international impacts.

Figure 1. A descriptive overview of the arguments in this paper

economic and political threat approach highlighted by several dynamics intersecting at border ports. One common point in the two literatures is that xenophobia is most likely to emerge when disadvantaged social classes (Lipset 1960) view outsiders as political (Kopstein and Wittenberg 2018) or economic (Olzak 1994) threats during times of social and economic turmoil (Bendix 1952). The leap of state boundaries makes this more likely because they shape perceptions by connecting social problems with transnational differences and forces beyond the state. In line with the concept of movement incitement proposed in the political threat approach (Biggs and Dhattiwala 2012; Brass 2011; Wilkinson 2006), xenophobia emerges further reinforced by the attraction of radical nationalist entrepreneurs near border areas who deploy frameworks, identities and networks to mobilize resentment against xenophobia scapegoats to "protect the state."

This argument is based on the assumption of Michael Mann (2005), but unlike Michael Mann’s assumption, Mann’s assumption is that areas near threatened borders are more likely to cultivate aggressive forms of nationalism, while Brubeck (1996)’s notion is that the presence of ethnic compatriots outside the state in the vicinity makes the borders of nations harder. The arguments across boundaries proposed in this paper are both more universal and more specific. It is more specific because it focuses on small clusters located near border ports, rather than entire provinces or regions. It is more common because it identifies border crossings in all countries as the focus of xenophobia, not just those that are controversial. Historians criticize Michael Mann and Brubeck for being too general (Applegate 1990), but I think their arguments about the boundary effect are not general enough.

data

Is there a spatial relationship between the resonance of xenophobia and the emergence of border lines? Existing local analyses of pre-cleaning European anti-Semitism often rely on cleaning data (Johnson and Koyama 2019; Voigtländer and Voth 2012). However, there are three disadvantages to cleaning data. First, purge is an extreme form of anti-Semitism, and anti-Semitism may exist even without purge. Second, no cleaning occurs without Jewish goals. Therefore, the assumption that the presence of local Jews is a prerequisite for the emergence of anti-Semitism remains an open empirical question (Charnysh 2015). Third, purges are not merely measuring local sentiments towards Jews, as they also utilize mobilization capabilities and, in some cases, the incitement of sports entrepreneurs. Therefore, the purge tells us about organized forms of anti-Semitic violence, but does not adequately capture potential and non-violent sentiments.

Given these shortcomings, I used anti-Semitism-themed data from children's stories collected by anthropologists and reports from local Centralverein to investigate the discussion of the border. These sources tap into potential and less extreme forms of anti-Semitism and do not require Jewish presence to emerge. These two datasets have different advantages. Folk data are fine-grained and have dimensions that change over time, allowing us to explore anti-Semitism through time and space, while Centralverein’s report allows us to unravel the processes and participants that produce anti-Semitism.

To test the transit discussion, I paired the anti-Semitism data outlined above with geocoded information at national border ports. As shown in the first three panels in the figure below, I compiled these data in three steps. First, I got information on all paved roads based on the postal map (panel a). Second, I made a georeference to the road (panel b). Third, based on this newly created road network, I then marked the location of a paved road across the borders of Weimar and then calculated the distances of the roads from these intersections to places experiencing varying degrees of anti-Semitism (the triangle in panel c). Panel d shows all the boundaries of Germany. In the analysis presented here, the Rhineland boundary (marked in bold) is also considered a national boundary.

This analysis includes only land boundaries and therefore does not include international ports. There are three reasons for this.First, at the methodological level, ports are unique places with different history of tolerance and hatred (Jha 2013), introducing high levels of omission variable bias. Second, more importantly, I want to pay close attention to the spatial dynamics of land ports, which have received little attention compared to port cities (Jha 2013). Third, in theory, international ports are often big cities, and focus effect is more scattered. Nevertheless, I re-analyze the international port as a border crossing point. The boundary effect becomes somewhat weak, but remains robust in this specification. In the current analysis, I control the existence of international ports to study the impact of border ports separately. The results of the port effect are discussed in the Conclusion section.

Results

The central argument proposed in this article will guide us to expect that anti-Semitism demons will gather around border ports. As a first cut of the data, I plotted all the locations in the dataset and marked them with Jewish monsters. The a panel in the figure below shows that Jewish demons tend to gather near the border with Denmark, France, Belgium, Switzerland, parts of Austria, the Netherlands and Czechoslovakia. Panel b shows the geographical distribution of Jewish citizens living in Weimar, Germany in 1925. Of the 1,114 towns reporting Jewish demons, 71% are within 50 kilometers of the border port. There does not seem to be a strong overlap between the existence of anti-Semitism in children’s stories and the density of Jews, suggesting that anti-Semitism without Jews is very prominent (Charnysh 2015).

Jewish and Jewish “devil” in Weimar, Germany, usually have different histories of tolerance and conflict and have experienced unique demographic, economic, political and military transformations that may be related to the outbreak of anti-Semitism (Segal 2016). Therefore, I analyzed the relationship between the “devil” and the near-boundary ports, and included a range of controls involving (1) population composition, (2) legacy of hatred and tolerance, (3) economic issues, (4) political threats, and (5) partial issues exposed to World War I. Control variables and their descriptions are shown in the appendix. Sources are described in Section B, supplemented online. The analysis is based on 19,828 regions nested in 946 counties and uses county-level clustering standard errors. To further isolate the effects of transboundary neighborhoods, rather than being more widely located in the border area, I ran the model where I kept my distance from the border line the same. These models provide a fine test of the discussion of border ports as they compare places equidistant to the border but vary in proximity to border ports. Therefore, these models compare places where there is no transit road near the border with places where there is a border crossing road near the border.

Traditional statistical analysis assumes that observations are independent. The “devil” data used in this article may violate this assumption, as verbal traditions tend to spread throughout space (Grober-Glück 1974). Spatial dependencies create autocorrelations and often introduce biases in standard errors and coefficients. To explain spatial autocorrelation, I used spatial filtering (Murakami and Griffith 2019). This method absorbs autocorrelation in the residual by including the Moran eigenvector on the right side of the statistical model as a synthesis control. Because the existence of the "devil" is a binary result, I use the logical link function. Finally, I utilize the generalized additive model (GAM), which allows any functional relationship between the popularity of anti-Semitism and the distance to the road to the nearest crossing (Wood 2017). The results are shown in the figure below. The complete model results are reported in Section C, Tables 4 and Tables 5, supplemented online.

generalized additive model: anti-Semitism and distance from border ports, confidence interval is 95%

Panel a on the figure above shows the results of the baseline model. Initially, there was a strong negative relationship between distance from border crossings and anti-Semitism. Almost one in ten of all towns adjacent to the border port reported anti-Semitism, but if moved inward by 60 km, that ratio quickly dropped to less than 2%.Once we reach the 100km point, the strong negative correlation between the distance from the border crossing and anti-Semitism will stabilize and smooth out. This suggests that the border effect becomes weaker once we move inward, and if xenophobia does gather around the border crossing, that's exactly what we expect. Panels b to f in Figure 5 show that this pattern has not fundamentally changed when we control for population differences, the legacy of hatred and tolerance, economic recession, political threats, the exposure of World War I, and distance from the border. Although the initial negative effects were slightly weakened, the gathering around the border crossing remains evident.

tool variables and double-differential

Another major method problem stems from endogenous or reverse causal bias. Historically, Jewish immigrants played an important role in the construction of trade routes, often including roads across the Weimar border (Welford and Bossak 2010). We also know that in the centuries after the plague, Jewish immigration was sometimes driven by outbreaks of anti-Semitic violence (Johnson and Koyama 2019). As road construction and anti-Semitism persist in space (Voigtländer and Voth 2012), it seems reasonable that historical borders and the roads forming Weimar border ports are produced by anti-Semitism at the local level rather than in the opposite way. To solve this problem, I used two strategies: the instrumental variable method and the double difference.

Before introducing these methods, I would like to publish a technical discussion. Both tool variables and differential designs are difficult to integrate into the flexible generalized additive framework used in the previous section. Because the above analysis shows that there is a curved relationship between anti-Semitism, distance and border ports, I used the reciprocal record distance to the border port to capture this form of function in my next analysis. Furthermore, I allow correlation errors in observations within the same county by deploying agglomeration standard errors.

To eliminate the concerns about the legacy of forced long-distance migration that occurred after the plague of anti-Semitism, I used Epidemiology pre-road data (Welford and Bossak 2010) collected by Epidemiology to construct an instrumental variable. Based on a wide range of sources, scholars interested in the social transmission of the Black Death have constructed fine-grained data on medieval road networks from before the initial outbreak of the Black Death to before the first major wave of anti-Semitism. I use this data to capture the location of the pre-plague roads cross the Weimar borders. I then used these pre-plague crossings as tools for Weimar border crossings. Mapping data shows that road information in Poland is sparse compared to other parts of Europe; examination of original source materials suggests that epidemiologists cannot identify any original Polish sources on medieval roads. Therefore, I excluded the closest area to the Polish border from the dataset. This results in a reduction of more than 3,000 observations.

In order to make the pre-plague crossing point an effective tool, I need to make two assumptions. First, the location of Weimar border ports needs to be strongly influenced by the location of medieval road networks. This is often referred to as the correlation hypothesis. I tested this hypothesis in the first phase regression, which uses the OLS model to predict the proximity to the Weimar border crossing and uses a variable to measure the proximity to the pre-plague crossing (see Table 1). As we see from the F statistics, whether we control the distance to the boundary line or not (Model 2) (Model 1), the border crossings in Weimar are highly correlated with pre-plague crossings.

Secondly, the exclusion restrictions need to be met. This requires that the pre-plague border crossing itself does not directly affect anti-Semitism at the local level unless it is created by the creation of later national border ports. This assumption is more likely to be valid if the pre-plague crossing did not affect the rise of anti-Semitism before the establishment of the state border port in 1871. Therefore, I confirm this hypothesis by returning to the pre-plague crossing points and the massacres that occurred during the Holocaust. The first wave of anti-Semitism after the plague, and the resonance of the Jewish demons in 1865, was six years ahead of the establishment of the German nation-state in 1871.

cleaning data were compiled by Voigtländer and Voth (2012).I obtained data on Jewish demons in 1,609 regions from the expert survey conducted by Wilhelm Mannhardt (1884). The survey was digitized based on original materials held by Preussischer Kulturbesitz, the National Library of Berlin. 284 of the 1,608 locations surveyed by Mann-hardt were not used for this analysis because they were closest to the Polish border crossing (for this purpose, we lack complete data, as previously described).

As shown in Model 3 and Model 4 in Table 1 , the distance to the pre-plague crossing point was not significantly correlated with the incidence of post-plague Holocaust or the prevalence of anti-Semitism “devils” before the emergence of German nation-states, providing suggestive evidence that the border crossing point was not related to anti-Semitism before the rise of nation-states, which makes it more reasonable to satisfy exclusion restrictions.

Table 2 The simplified form analysis presented in Models 5 and 6 shows that there is a positive correlation between the existence of Jewish monsters and the proximity of the pre-plague border crossing points. Models 7 and 8 show the second phase of the two-stage probability model. The second phase uses boundary proximity (based on proximity to pre-plague road networks) to predict whether Jewish “devils” are reported locally. In instrumental variable norms, the impact of state boundary proximity is robust. The size of the influence is summarized in the upper half of Figure 6. Adding a standard deviation tool increases the likelihood of Jewish monsters by more than 8%, even if we keep our distance from the boundary line the same.

Estimates using dual-differential design and instrumental variable method

's impact on the existence of anti-Semitist "devils": Based on results from the frontier border ports

combines Weimar data from ADV with Mannhardt's 1865 investigation, and also allows us to explore the aggregation of Jewish demons before and after the introduction of border crossings. The figure below shows the percentage of places with Jewish “devils” divided by region from 1865 and 1930 to 1932. When we look at panels a, b, and c, two phenomena stand out. First, we see an overall increase in Jewish “devils” between 1865 and 1930 and 1932. This pattern may be related to two factors: the overall growth of anti-Semitism and the rise of nationalist myths. Second, no matter the distance threshold, the upward trend of anti-Semitism is much stronger in areas near the Weimar border port. When we use a 10km buffer to mark transit proximity, the Jewish “devil” is almost twice as likely to be in the border area (panel a). Likewise, when using a wider radius to calculate the boundary area, the effect leveles up (panel d). In summary, this supports the view that proximity to newly established borders has an independent and positive impact on the production of anti-Semitism.

In the 95% confidence interval, the percentage of villages with Jewish "devils" divided by region before and after Germany's unification

's in-depth case study of the northwest border reveals two mechanisms that turn border crossings into xenophobic breeding grounds. First, border transit is the main cause of national differences, forming a perceived link (perception mechanism) between social problems and international factors in groups that are losing their social status. According to existing work (Heberle 1962; Lipset 1960; Loomis and Beegle 1946), Centralverein data suggest that this is especially true for farmers and small business owners who are most likely to face the consequences of price regulation and hyperinflation. Secondly, border ports attract radical political mobilization (attraction mechanism). In this section, I use quantitative data to evaluate the rationality of the different components of the argument.

Let us start with the important role played by the lower middle class in the emergence of anti-Semitism. If farmers and small business owners believe that the internationalization of social problems is the cause of anti-Semitism, the cross-border effect should be stronger in places with large-scale farm communities and a large number of small business owners. To study these empirical implications, I used nuclear density interactions (Hainmueller, Mummolo and Xu 2019) to examine the heterogeneity of cross-border effects across regions, with or without a vulnerable economic class experiencing recession. The figure below shows the marginal effect of the recession.An anti-Semitism standard deviation will be changed based on the percentage of the population employed as a farmer or small business owner. The latter captured the existence of the losing middle class in the Weimar Republic (Heberle 1962; Lipset 1960; Loomis and Beegle 1946).

Change the inverse distance of an SD condition for the marginal effect of farmers and percentages of small business owners

is consistent with the perception mechanism that believes that the lower and middle classes blame social problems on international forces, and in areas with a higher proportion of economically disadvantaged social classes, the overall impact is indeed stronger. While close to border crossings has little effect in areas where farmers are few and small business owners have little recession, an increase in the prevalence of anti-Semitism “devils” in areas with considerable vulnerable groups facing worsening economic conditions. This confirms the importance of the lower middle class in the creation of anti-Semitism resentment.

's analysis of different forms of political mobilization provides quantitative evidence consistent with attractiveness and perceived mechanisms. However, fine-grained data on different forms of political mobilization cannot be found for each of Germany’s 19,829 places. However, second-hand literature and books allow me to retrieve county-level information about several radical nationalist groups and the different forms of lower and lower mobilization introduced in the previous section.

If border areas become the focus of radical nationalist movements, as the attraction mechanism assumes, we expect to find more far-right mobilization near border ports. I compiled county-level information about the existence of local chapters of the Pan-German Union and the Free Legion, the campaigns held by Hitler’s NSDAP and the protests held by Landvolk Bewegung. Based on this information, I created a binary outcome variable to mark whether the county is affected by at least one form of mobilization.

To capture the perception mechanism, I created three variables that mine the mobilization of the lower and middle classes around the perceived internationalization of social problems. If the borders do activate the internationalization of social problems, we expect this form of political mobilization to be more intense near border ports. As mentioned in the previous section, between 1924 and 1928, farmers held a series of protests, demanding that the government protect it from international competition and price differences (Bergmann and Megerle 1989). Small business owners often participate in these demonstrations, and they also rallied by supporting the Business Party (BP) in the 1924 and 1928 elections to prevent international competition (Schumacher 1972; Winkler 1976). So, I tagged counties where farmers participated in the protests of protectionism between 1924 and 1928. I also marked the counties in which small business owners participated in the protectionist protests, and I set the average percentage of votes for BP between 1924 and 1928 as a measure of the international roots of small businesses mobilizing to deal with social problems. Record the latter variable to handle its deviation.

The figure below shows the results of a generalized additive model containing all control variables described in the appendix. According to the attraction mechanism, panel a shows that radical mobilization is most common near border ports and rapidly declines when moving inward. However, this decline is curved and tends to level up with the increase of distance. Panels b and c show that all three forms of mobilization that support protectionism against international threats in the lower middle class follow a similar pattern. In summary, this provides preliminary support for the attraction mechanism, which assumes that border ports are the basis for radical nationalist mobilization; perceived mechanisms that assume that lower and middle classes living near border ports are more likely to perceive the international roots of social problems; and the concept of the convergence of these two mechanisms at border ports.

radical nationalist mobilization, protests supporting protectionism, voting of the business party and distance to border ports, with a confidence interval of 95%

Conclusion

A large amount of work on xenophobia has identified the political and economic sources of resentment. The former emphasizes the importance of electoral threats and incitement by movement leaders, while the latter focuses on how vulnerable social classes who have lost their status during times of socio-economic turmoil become scapegoats for outsiders.This article combines these two branches to provide a spatially contextualized explanation of xenophobia by indicating whether economic recession, the existence of vulnerable social groups, or the political incitement of social movements converges to generate fear of outsiders, depending on the relative position within the country.

This article reveals the national border port, connecting the spatial location of two nation-states, activates the top-down and bottom-up process, and jointly provides a fertile breeding ground for the emergence of racial fear. First, when nearby border crossings make national differences prominent, groups that lose social status are more likely to attribute their decline to international factors. Second, disproportionately in border areas attracted radical xenophobia, who wanted to protect the country from external threats. The first process creates bottom-up demands for international scapegoats among disadvantaged social groups, which meet these needs from the top down by viewing international actors as the source of all evil.

Before discussing the potential strengths and contributions of the project, I would like to briefly emphasize one of its main weaknesses. While this article convincingly suggests that anti-Semitism demons and events gather near border ports and begin to reveal the socio-economic dynamics behind these clusters, it does not really explain how the latter dynamic can shape the content of children’s stories in the first place. Research is currently underway to track this process.

compile｜Zhiyuanxing

review｜Cha Hao

final review｜Li Zhixian