Migrant Political Activism in Vienna and Brussels: How Voting Rights Shape Protest Behaviour

Migrant Political Activism in Vienna and Brussels: How Voting Rights Shape Protest Behaviour | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Migrant Political Activism in Vienna and Brussels: How Voting Rights Shape Protest Behaviour Zeynep Mentesoglu Tardivo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6022305/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract While much research has focused on the electoral participation of voters with migration backgrounds, the political engagement of migrants beyond the ballot box remains significantly underexplored in Western Europe. This article examines migrants’ involvement in public protests in two distinct contexts—at the national and city levels—in Vienna and Brussels. Using an original empirical approach, the analysis draws on data from the European Social Survey (ESS) regional statistics (NUTS) Round 1-11 , exploring protest participation patterns among migrant respondents in these cities. A key question addressed is how different opportunity structures, such as the right to vote at the local level, influence the likelihood of participating in protests. The findings indicate that the presence (or absence) of local voting rights for non-nationals is a strong predictor of minority protest participation. While the right to vote at the local level is shown to impact protest involvement, the comparative analysis reveals divergent patterns in the two cases. In Brussels, where local voting rights are present, and more inclusive, migrants exhibit lower protest participation rates, whereas in Vienna, where such rights are restricted, migrants participate in protests at higher rates. This suggests that formal political avenues, such as voting rights, may reduce the need for protests as a form of political expression. Comparative Political Science migration background political participation protest participation right to vote Vienna Brussels opportunity structures minority rights European Social Survey Introduction Migration has always been a fundamental aspect of human life, with people moving throughout history in search of better opportunities or out of necessity. It has been a constant and influential force across Europe, shaping the continent in countless ways. While its significance cannot be overstated, the so-called migration and refugee crisis of 2015 brought unprecedented attention to the issue. Today, migration has become—and will likely remain—one of the most pressing and salient issues in Europe [1] . The growing migrant populations in Europe are characterized by diverse cultural backgrounds, histories, and migration experiences. These include ‘guest workers’ recruited after World War II, post-colonial migrants from former colonies, European migrants exercising freedom of movement within the EU, and refugees fleeing wars and conflicts in regions such as Africa, the Middle East, and the former Yugoslavia to seek safety and protection (Geddes and Scholten, 2016).) Today, several European countries, especially in Western Europe, are net immigration countries[2], and the presence of diverse ethnic communities marks their urban centres. Cities like Brussels, and to a lesser extent Vienna, have become some of the most ethnically diverse in Europe, with growing populations from the Middle East, South Asia, Africa, the Caribbean, Eastern Europe, and beyond. As a matter of course and the parallel to its salience and prominent role in politics, there is a growing scholarly interest in migration. It represents a major subject of scholarly research, and the field progressively varied in terms of its links across various academic disciplines, including political science, sociology, economics, and anthropology. Within this framework, one key theme within migration studies is integration, which is also a central topic in political debates across Europe and in European Union initiatives. Integration by definition, is ‘the process of becoming an accepted part of society’ (Penninx, 2005) and represents 'a two-way process of adaptation by migrants and host societies and implies consideration of the rights and obligations of migrants and host societies, of access to different kinds of services and the labour market, and of identification and respect for a core set of values that bind migrants and host communities in a common purpose’ (IOM, 2011). Referred as 'different fields' of integration, the process encompasses multiple dimensions, including including socio-economic, cultural, and legal-political dimensions (Entzingerand and Biezeveld, 2003). Importantly, studying the political participation of migrant-origin individuals sheds light on an often-overlooked aspect of their agency. Indeed, in much of the existing the literature, migrants are often predominantly depicted as workers. There is a growing concern among scholars that migrants’ roles in society are often reduced to the labour force, while several other ways they actively shape their social environments are neglected (Smith and Favell, 2006; Schiller and Caglar, 2009). This limited perspective fails to capture the multifaceted roles that migrants play beyond the labour market, thereby underscoring the need for a broader understanding of their contributions to social, civic and political life. By shifting the focus to migrants’ political engagement, this research seeks to reveal and highlight another crucial dimension of their agency. It is worth noting that should While there is a considerable body of literature on migration and political participation separately, research specifically addressing the political involvement of migrant communities remains relatively recent and evolving. This underscores the importance of exploring this intersection to gain a fuller understanding of migrants' roles in society. This article shares the perspective of Ford and Jenning (2020: 302), who underscored the emergence of politically significant ethnic minority groups in Europe, and argued that migrants ‘have distinct ethnic identities and cultural traditions; they tend to cluster geographically and economically in struggling places and lower status, less secure parts of the labour market; and they have unique group political interests, in particular for recognition of their cultural traditions and political representation of their ethnic groups, and for protection from majority hostility and discrimination.’ There is a growing recognition that migrants are not just passive recipients of policies but also active agents who can influence political processes and outcomes. Migrant communities have become increasingly visible in political debates, advocacy efforts, and grassroots organisations, underscoring the importance of studying their political agency and participation. Similarly, other studies acknowledge migrant communities as a potential new electorate. They realise the significant and rising shares of the migrant populations and the diversity of the electorate in European countries (Dancygier and Saunders, 2006; Caramani and Strijbis, 2011). The former authors note that immigrant political behaviour is largely unexplored, and its exploration is limited to the U.S. context. Consequently, this study is also motivated by the fact that the political participation of immigrants in Europe deserves more scholarly attention and various calls for an extensive analysis of immigrant political behaviour from different theoretical and empirical points of view. The political participation of migrants is a fundamental aspect of their integration into new societies, particularly given the growing number of immigrants and their descendants in Europe. The exclusion or abstention of migrant populations from political processes raises significant concerns about the quality of democracy, as their voices and perspectives are essential for truly representative governance. Migrant political participation is especially a prominent issue at the local level and in countries with established immigrant populations. Regarding the former, migrants have a vested interest in decision-making processes that affect housing, public services, and education, directly impacting their daily lives. With regards to the latter, in countries with long-standing immigrant communities, these populations have deep roots and have made substantial contributions to society. The migration experience in such countries has often shaped policies and social perceptions. The exclusion or abstention of migrant populations from political processes raises significant concerns about the quality of democracy, as their voices and perspectives are essential for truly representative governance. Despite this, migrants, whether residents or citizens, often face disparities in political rights and opportunities compared to native citizens. Examining these inequalities and understanding migrant political participation can offer valuable insights into their social inclusion and integration. As the immigrant population grows and the 'participatory gap' between immigrants and natives persists, discussions about their political participation are likely to gain increasing importance in national politics and the broader European agenda. [1] Most recently (by June 2023), the war in Ukraine has resulted in the largest and fastest displacement of people in post-war Europe, with over 6 million refugees leaving Ukraine. [2] Based on the data from UN Desa (2023), Germany, the UK, France, Italy, and Spain are marked with positive net migration balances in 2023 as the number of people entering the country (immigrants) exceeds the number of people leaving the country (emigrants). For further information please see Europe net migration by country 2023 | Statista Migrants’ political participation beyond electoral arenas Political participation is a multidimensional concept that extends beyond the confines of electoral politics. Yet, much of earlier research exclusively focuses on electoral participation, neglecting other forms of political engagement. While electoral participation is prominent, it represents one facet of the broader repertoire of political participation modes. Its conceptualisation has been diversified over time and moved beyond the arenes of voting through the inclusion of several other political activities to its definition. This broader repertoire today includes ‘non-electoral’, ‘unconventional’, and ‘extra-parliamentary’ participation forms through which immigrants engage in the political process and express concerns beyond routine elections (Vintila and Martiniello, 2021). The study of political participation began in the American context during the 1950s and 1960s with an exclusive focus on elections (Lazarsfeld et al. 1948, Campbell et al. 1960). By the 1970s, Verba and Nie (1972) expanded this focus to include activities beyond voting and campaigning. Their seminal work introduced four principal dimensions of political participation: voting, campaign activity, communal activity, and particularized contact. This expansion reflected the era’s growing emphasis on societal groups and direct citizen-politician interactions. Research on political participation has continued to expand in the following years as the domain of the concept extended. It was the inclusion of protest behaviour and civil disobedience into the definition of political participation which shifted an understanding of the concept based on 'conventional' activities towards a broader one. Again, the extension of what counts as political participation was a response to the societal changes in the era and a reflection of the so-called ‘new social movements’. In words of Della Porta and Diani (1999), new social movements refer to ‘the movements which had developed since the late 1960s on issues such as women’s rights, gender relations, environmental protection, ethnicity and migration, peace and international solidarity – with a strong (new) middle-class basis and a clear differentiation from the models of working-class or nationalist collective action that had historically preceded them. While there are surely continuities between those movements and the current wave of global justice campaigns, there are also many suggestions that the overall patterns of collective action they display is significantly different from those we had grown accustomed to’. With the rise of ‘new social movements’ and the reorientation of political agenda towards postmaterialist issues, the earlier definitions by Verna and Nie (1972) have been considered as narrow in the sense that their scope of activity was restricted to the government. On this point, Barnes and Kaase (1984) have been critical of excluding protest activity from the domain of political participation and thus incorporated what they call ‘protest potential’ in their influential work Political Action . They expanded the definition of political participation as ‘all voluntary activities by individual citizens intended to influence either directly or indirectly political choices at various levels of the political system’. This paper aligns closer with the latter approach, which recognizes that political participation extends beyond institutional arenas. Beyond voting, a variety of activities are available to express political interests, influence policymaking or voice opinions on public matters. This article argues that migration studies should pay greater attention to the more contemporary forms of participation, such as public protests, through which migrants articulate their concerns and viewpoints in the public arenas in their host countries. Centring its study on the electoral domain, on the other hand, can deliver a biased picture of migrant political participation. Indeed, studies with an excessive focus on voting tend to detect significant gaps in the turnout rates between migrants and the autochthonous population, thus portraying migrants as ‘disengaged’. On the contrary, the study of non-electoral forms of political participation has been conducted to counter such ‘disengagement’ and suggest that migrants are actively engaged in ways comparable to the native population. Electoral abstention isn't always a voluntary decision for everyone (Marien et al., 2010). For many immigrants, in particular, most forms of electoral participation have traditionally been restricted to those who possess the nationality of the host country. As Martiniello (2006) rightly stated, “migrants are not more passive than other citizens, but their involvement should also not be exaggerated by regarding them as the vanguard of the new global proletariat”. Evidently, one-dimensional approaches cannot generate convincing clarifications of migrant political incorporation. Similarly, Hay (2007) points out, ‘those with the most restrictive and conventional conceptions of political participation identify a strong and consistent pattern of declining political participation’. According to Martiniello (1997, 2006), the thesis of the political quiescence of immigrants is related to the absence of electoral rights for migrant workers. For some, they could not play a significant role in the politics of their country of residence, and their exclusion from the electoral process led to a situation of political apathy. Despite this, several studies demonstrate that migrants are actively engaged in other forms of political participation. For example, involvement in trade unions (Marino et al., 2015; Alberti and Pero, 2018) and protest movements (Atac et al., 2016) are clear indicators of their political activity. Migrants have been prominent in movements such as the sans-papier workers' movement (Tapia and Turner, 2013), the Dutch 'Justice for Janitors' strike (Connolly et al., 2017), the Italian Migrants' Strike (Oliveri, 2015), and global protests related to the Israel-Palestine conflict. The lack of formal citizenship rights does not prevent migrants from participating in the political landscape. Instead, it often redirects their efforts towards alternative forms of expression, such as protests. These activities allow migrants to challenge injustices, raise awareness of their issues, and advocate for social and political change. Through participation in protests, migrants without citizenship rights can still make significant contributions to political discourse and advocate for the needs and rights of their communities in both their host and home countries. Theoretical Framework and Hypotheses The theory of political opportunity structures sheds light on the external factors influencing political participation (Kriesi et al. 1997; Meyer, 2004). A significant idea, developed originally for the study of social movement is defined by Tarrow (1996: 54) as ‘consistent but not necessarily formal, permanent, or national signals to social or political actors which either encourage or discourage them to use their internal resources to form social movements’. In the word of Koopmans (2004), opportunities are ‘options for collective action, with chances and risks attached to them, which depend on factors outside the mobilizing group’. Initially considered as a general framework, several studies illustrated the presence of specific opportunities available to different ethnic groups and their role in immigrants’ political activities (Koopmans, 2005; Morales and Giugni, 2011). In this paper, the political opportunity structure refers to the institutional incentives and disincentives relevant to individuals with a migration background, which can influence their choices and strategies in participating in political activities. It does not suggest a uniform set of structures applicable to all immigrants or all forms of political participation. On the contrary, the strength of political opportunity theory lies in its ability to care for variations: uneven grounds between native and immigrant populations, different structures for different political activities, and the varying conditions applied to a diverse category of immigrants. On this point, political opportunity structures are context-sensitive, providing favourable access to some groups while generating adverse conditions for others. Similarly, they can favour certain groups, discourses and policy-claims over other actors, expressions and demands. Drawing on the political opportunity structure (POS) theory, this paper argues that immigrants’ access to political life is pre-determined by certain characteristics of the institutional settings. It suggests that the inclusiveness of political rights is crucial for migrant political integration. In fact, as stated by Fennema and Tillie (2001), the right to vote, one of the most relevant political rights for this study, represents an ‘initial opening of the political opportunity structures’ providing incentives for immigrants to engage in the political process. When immigrants enjoy equal voting rights with the native population, they tend to show greater interest in political debates, feel a stronger connection to their polity, and become familiar with the prevailing political norms (Bauböck et al., 2006). Such a society in which an egalitarian distribution of political rights is achieved would indicate an open political opportunity structure for the framework of this research. Nevertheless, the distribution of political rights in Europe is characterised by significant disparities. As illustrated in Table 1, many Western European countries currently grant non-citizen resident migrants voting rights in municipal elections. Table 1. Right to vote for third-country citizens These varying characterisations of voting rights are expected to indicate the obstacles and opportunities for immigrants' political participation. A similar thought is expressed by Hayduk (2006, 2015), who suggests that granting local voting rights to immigrant residents has the benefit of putting them on a 'pathway to citizenship'. Local voting rights can serve as a catalyst for political socialization and mobilization within migrant communities. As migrants become more politically active through participation in local elections, they are also more likely to organize and engage in collective action to address issues not resolved through formal political channels. However, there is a notable lack of empirical n how voting rights impact protest participation. Based on these considerations, the analysis hypothesizes: H1: The more electoral rights immigrants enjoy, the more likely they are to participate in protest activities, and vice versa. The second block of variables concerns the individual-level characteristics of the respondents. Studies of political participation frequently utilise individual-level variables to explain the phenomenon of political participation. The sample in this paper varies not only in terms of its composition of native and immigrant-origin respondents but also in their individual characteristics (Brady, Verba and Schlozman 1995; Jacobs and Tillie, 2004). Socioeconomic status (SES) has long been accepted as a crucial factor influencing political participation patterns (Verba and Nie, 1972; Quintelier and Hooghe, 2012). Highlighting the ways in which disparities in SES foster unequal representation and participation, factors such as income and education are suggested to display significant impact over individuals' likelihood of taking part in political activities. The rationale behind the relation between SES and political participation comes from numerous theoretical frameworks and empirical results. One prominent theoretical approach is the resource-based model, which posits that that individuals with higher socioeconomic status acquire more advanced resources, such as education, income, and social networks, which facilitate their engagement in political life. Another important theoretical framework for understanding the link between socioeconomic status and participation is the socialization approach. According to this viewpoint, those from higher socioeconomic backgrounds are more likely to grow up in environments where political discussions are common and engagement in political life is encouraged. The explanatory power of SES variables in the specific context of immigrant political participation is less straightforward and multifaced. Immigrants often experience unique challenges and opportunities when taking part in the political process. Several studies have found that immigrants have a complicated relationship to the traditional SES model. As such, they identified a weaker relationship between the SES levels and the political involvement of ethnic minorities (Jones-Correa, 1998; Barreto and Munoz, 2003; Tam Cho, Gimpel and Wu, 2006; Atger, 2009). Nevertheless, these studies were conducted in the Americas, and less is known about the explanatory power of socioeconomic status on protest activity in the European context. The empirical findings aim to shed light on the question of whether socioeconomic status is a powerful factor in explaining migrants’ engagement in protest activity. Therefore, the second hypothesis is: H2: The higher the socioeconomic status (SES) of immigrants, to be more likely they are to engage in political participation compared to those with lower SES. The third hypothesis advances an interaction effect between the presence of local voting rights for non-nationals in Vianna and Brussels, and individual characteristics of socioeconomic status. The interaction hypothesis stems from the fact that the two cities have different provisions for migrant electoral rights. In Vienna, where local voting rights are absent, it may be less apparent whether migrants with higher socioeconomic resources will participate in public protests. Higher socioeconomic status does not always guarantee political participation, as institutional structures can hinder such involvement. The interaction of individual-level characteristics and macro-level factors is thus expected to disentangle this puzzle. Thus, the the third hypothesis the multilevel model aims to address is the following: H3 : The relationship between the socioeconomic status and protest participation is moderated by the presence of (local) political rights, such that the positive effect of education and income on (the log odds) political participation is stronger in Brussels (where non-citizen migrants have local voting rights) compared to Vienna (where local voting rights are not available). Data and Measurement Data sources The data in this paper comes from the European Social Survey (ESS). As acknowledged in the literature, it adopts high standards, particularly ‘in its questionnaire design, the cross-national equivalence of the instruments used and the sampling procedures applied’ (Jowell et al., 2007; Kohler, 2007; 2008). It is a high-quality dataset where the sampling design approximates a simple random sample and has a relatively high response rate. By offering information on the context, namely the country the respondent resides in, the ESS enables the merging of individual-level data with contextual data. Crucially for the focus of this study, the ESS collects data at the NUTS (Nomenclature of Territorial Units for Statistics) levels, enabling regional analysis within countries. This granularity is particularly useful for examining urban contexts like Vienna and Brussels, enabling researchers to capture the nuances of local political and social dynamics. As mentioned earlier, the ESS is stated to be representative of the national population. However, it is equally important that the survey is representative of the foreign-born population in the countries under this study. To check if it holds, the percentage of foreign-born individuals in the ESS sample is calculated and compared with external data provided by Eurostat, the statistical office of the European Union. With a correlation coefficient (Pearson’s R) equal to 0.98, a fairly close fit is observed between the two samples of the foreign-born populations. Moreover, for the purpose of this study, relying on electoral surveys would not be sufficient. ‘Politics’ is one of the core modules of the ESS project, and the questionnaire contains a wide repertoire of political participation items, including participating in public protests. his aligns well with the focus of this paper, which is concerned with protest behaviour. Second, it is crucial to test the different sets of working hypotheses and reach empirical findings. The ESS survey provides information on several factors that are highlighted in the theoretical framework. To enhance the robustness and generalizability of the analysis, data from the European Social Survey (ESS) were combined across multiple rounds, from Round 1 to the most recent Round 11. This aggregation of data effectively increased the number of observations, providing a more comprehensive dataset for examining patterns of protest participation across different contexts. Dependent variable Protest participation is measured by asking respondents whether they have participated in the protest activities in the last 12 months. The dependent variable is coded as binary: 1 if the respondent answers affirmatively to the question, "During the last 12 months, have you taken part in a public demonstration?" and 0 if they have not. It should be noted, the ESS questionnaire does not have a direct indicator of the migration status of the respondents. It does not ask the respondents ‘What is your current migration status in this country?’. Instead, it contains information on the respondents’ country of birth, their parents’ country (s) of birth, the time of arrival to the country, citizenship status and religious denominations. These pieces of information are highly important in identifying respondents with a migration background. This study relies on the country of birth indicator available in the ESS, which is generally considered a less biased measure of migration background versus ethnicity. Eventually, the immigrant sample in this study is composed of foreign-born respondents and those who were born in the country with two foreign-born parents (also known as second-generation migrants). Scope The paper focuses on the cities of Vienna and Brussels, which are home to substantial migrant populations. Choosing Vienna and Brussels as case studies for examining migrant protest participation is strategically significant due to their distinct national and local contexts, unique migration histories, and the scarcity of quantitative studies at the city level in this topic. First, the two cities are characterised with distinct national and local contexts presenting two contrasting social and political environments for migrant inhabitants. Vienna, the capital of Austria, operates within a more restrictive national policy context regarding immigration and integration. Austrian policies historically emphasize assimilation, and local voting rights for non-nationals are limited. The process of naturalization has traditionally been stringent, necessitating long periods of residency and demonstrating economic self-sufficiency (Kraler, 2011). This restrictive approach reflects a broader national trend towards conservative citizenship policies that have been criticized for impeding the integration of migrants into Austrian society (Howard, 2013). In contrast, Brussels, the capital of Belgium and the European Union, adopts a more inclusive approach towards migrants. Belgium's citizenship and migration policies are relatively accommodating, with shorter residency requirements and more lenient integration criteria (Martiniello, 2003). This inclusive stance reflects Belgium's broader policy orientation towards facilitating migrant integration and accommodating its diverse population, including significant communities from former Belgian colonies in Africa (Demart, 2013). Brussels’ municipal and regional authorities have adopted progressive measures, such as granting local voting rights to non-national residents, which contrasts with the more restrictive policies observed in Vienna (Arrighi and Bauböck, 2017). Belgium grants local voting rights to non-EU migrants who have resided in the country for at least five years. These differences in citizenship regimes, electoral rights and migration policies between Vienna and Brussels are expected to contribute to diverse patterns of political engagement and integration, including how migrants participate in protests and other non-electoral forms of political expression. Second, Vienna and Brussels have rich, albeit distinct, histories of migration, which significantly shape their contemporary migrant landscapes and political dynamics. Vienna's migration history dates back to the Austro-Hungarian Empire, which fostered a multicultural environment due to its diverse ethnic composition (Steidl, Fischer-Nebmaier and Oberly, 2017). The post-World War II period marked a significant shift with Austria's recruitment of "guest workers" from Southern Europe, particularly Italy, Turkey and Yugoslavia, to address labour shortages (Bischof and Rupnow, 2017). This influx resulted in the establishment of substantial migrant communities that have since faced integration challenges amid evolving political and social landscapes. More recently, Vienna has seen an increase in asylum seekers from the Middle East and Africa, particularly during the 2015 refugee crisis, reflecting a continued evolution in its migration dynamics (Kohlenberger et al., 2017). Meanwhile, Brussels’ migration history is deeply influenced by its colonial past and role as a political and administrative center. After World War II, Brussels attracted a significant number of labour migrants from Southern Europe, similar to other Western European cities. Additionally, the city’s colonial ties to Africa, particularly Congo, Rwanda, and Burundi, have led to a significant presence of migrants from these former colonies, contributing to Brussels' unique demographic profile. In recent decades, Brussels has continued to attract a diverse range of migrants from across the globe, including Eastern Europe, the Middle East, and Asia, driven by its status as the European Union's headquarters and its progressive migration policies (Deboosere, 2009; Goddeeris, 2015; Bousetta, Favell and Martiniello, 2018). These divergent migration histories and experiences are crucial for understanding the political engagement of migrants in these cities. Vienna's integration challenges and Brussels' more inclusive approach reflect different national and local responses to migration, which influene patterns of migrant political participation, including protest activities. Quantitative research focusing on these city-level dynamics remains sparse, underscoring the originality and significance of this study in analysing the impact of local voting rights on migrant protest participation in such varied contexts. All in all, the choice to study Vienna and Brussels is justified by their contrasting migration policies, diverse migrant populations, and the significant yet underexplored role of local voting rights in shaping protest participation. Vienna's restrictive policies and Brussels' inclusive approach offer a compelling comparison that can illuminate the conditions under which migrants are more likely to engage in protests. This comparative analysis not only fills a gap in the existing literature but also provides actionable insights for policymakers aiming to foster political engagement and social integration among migrant communities. Method of analysis The two principal aims of this research are, first, to identify the gaps in participation in public demonstrations between the immigrant and autochthonous populations, and eventually to explain these differences. Therefore, the research is carried out in two stages: descriptive and explanatory. For the first stage, summary statistics are performed to obtain information on the basic statistics of the dependent variable. Frequency tables and visual charts are used to show the frequency distribution of protest activity in the cities of Vienna and Brussels. The second stage, which is at the heart of this study, is explanatory. Logistic regression analysis is performed to assess the effect of independent variables (explanans) on the dependent variable ( explanandum). The choice of logistic regression over the linear regression analysis is due to the fact that the dependent variable in this study are dichotomous (with two possibilities, such as ‘0’ or ‘1’). The logistic regression models the chance of participation in protest based on the predictors. Because chance is a ratio, what is modelled is the logarithm of the chance given by: Analysis and Results A first look at the data reveals that, on average, in Vienna, a similar proportion of migrants (14.60%) and non-migrants (14.98%) participate in protests. Whereas, in Brussels, a smaller proportion of migrants (8.84%) participate in protests compared to non-migrants (16.12%). Table 2 presents the detailed breakdown of protest behaviour among migrants and non-migrants in these two cities. Table 2. Protest Participation Rates of Migrants and Non-Migrants Participation Vienna (AT13) Brussels (BE10) Total Migrants Non-migrants Migrants Non-migrants No Protest 85.40% 85.02% 91.16% 83.88% 1,529 Protest 14.60% 14.98% 8.84% 16.12% 267 Total 541 1,255 430 242 1,796 The following table, Table 3, summarises the characteristics of the sample by type of participation. Table 3. Sample characteristics of migrants participating in protests Characteristics Vienna Brussels % male 43.04 63.16 Mean age 41.21 37.44 % second generation 18.99 23.68 % primary education 12.99 34.21 % secondary education 37.66 15.79 % tertiary education 9.09 7.89 % higher education 40.26 42.11 % with citizenship 48.10 60.53 % born in EU countries 15.53 9.09 Source: Author’s elaborations on ESS data In Vienna, both males and females have similar participation rates in protests, with females participating slightly more than males (56.96% vs. 43.04%). In Brussels, males are more likely to participate in protests compared to females (63.16% vs. 36.84%). In other words, this indicates a gender-related pattern in protest participation in Brussels. The generational characteristics of migrants participating in protests in both Vienna and Brussels closely mirror the overall generational distribution of migrants in these cities. This suggests that the likelihood of protest participation among migrants does not significantly differ between first and second-generation migrants in either city. Moreover, in Vienna, protest participants with higher education (40.26%) are overrepresented compared to their proportion among those who did not participate (29.52%). Those with primary education are underrepresented in protests (12.99%) compared to non-participants (19.60%). Similarly in Brussels, protest participants with higher education (42.11%) are overrepresented compared to their proportion among those who did not participate (26.42%). Those with primary education are underrepresented in protests (34.21%) compared to those who did not participate (43.01%). Overall, in both cities, migrants with higher education constitute a larger share compared to those with lower educational levels. This trend is more pronounced in Brussels, where a significant portion of protest participants have higher education, whereas in Vienna, the distribution is somewhat more balanced but still favours those with higher education. Sample characteristics by citizenship show that in Vienna, protest participants are almost equally divided between citizens with migration backgrounds (48.10%) and non-citizens (51.90%), with a slightly higher representation of non-citizens among protest participants. On the other hand, in Brussels, protest participants are predominantly citizen migrants (60.53%), while non-citizens (39.47%) are underrepresented among protest participants compared to their share among those who did not participate (49.23%). Finally, in Vienna, 15.53% of migrants who protested were born in an EU member state, while 56.96% were non-EU migrants. In comparison, in Brussels, 9.09% of protesting migrants have an EU background, and 28.95% were non-EU migrants. These findings highlight varying levels of protest participation among EU and non-EU migrants in Vienna and Brussels, underscoring potential differences in civic engagement and political mobilization across these two European cities. Multivariate Analysis The analysis requires to combine data collected at the individual level with data at the country level indicating the multilevel nature of the data (one level, the individual, is nested within the other, the country). The test of the multilevel model fit against the unconditional mean model (Wang, Xie and Fisher, 2011) suggests that it would be a mistake to disregard the multilevel nature of the data (i.e. assuming individuals were uncorrelated within counties). This supports the hypothesis on the significant role of the institutional context in shaping protest participation. The results of the multi-level logistic regression model are presented in Table 4. Table 4. Odds ratios for protest participation for migrants living in Austria and Belgium Model 1 (Austria) Model 2 (Belgium) Model 3 Model 4 Individual-level variables Gender (female) .86 .56* .73* .75* Age .97*** .99 .98*** .98*** Education 1.26** 1.25** 1.27** 1.26** Income .95 1.03 .97 .97 Citizens of country 1.22 1.85* 1.42 1.14 Born in EU country 1.45 1.11 1.36 1.34 Country-level variables Local voting rights for non-nationals .68** .41 Cross-level interactions Education*voting rights for non-nationals 1.01 Citizenship*voting rights for non-nationals 1.71 Intercept .34* .11** .27*** .31** Wald X 2 (df) 22.56** 12.24** 33.18*** 5.62* N 614 529 1,143 1,143 Note: * p < 0.05, ** p < 0.01, *** p < 0.001 Model 1 and Model 2 focus on Vienna and Brussels separately, while Model 3 and Model 4 analyse the combined sample from both cities. By examining both context-specific and combined models, we gain insights into how various factors interact to affect protest behaviour. In Austria, the analysis reveals a complex interplay of factors influencing protest participation. Gender is a conventional predictor; although the odds ratio for females is 0.86, indicating lower participation compared to males, this result is not statistically significant (p > 0.05). Age is a significant negative predictor (OR = 0.97, p < 0.001), suggesting that older migrants are less likely to engage in protests. This result resonates with the literature that portrays younger individuals as more inclined towards alternative forms of political engagement, such as protests, rather than traditional methods like voting. Marsh, O’Toole, and Jones (2007) highlight that young people often show less interest in traditional forms of politics, preferring alternative, less institutionalized methods of engagement. Similarly, Henn, Weinstein, and Wring (2002) argue that the lower turnout among youth is less about political apathy and more about a critical engagement or ‘engaged skepticism’ toward formal politics. Conversely, higher education levels are strongly associated with increased protest participation (OR = 1.26, p < 0.01), emphasizing the role of educational attainment in fostering political activism. Citizenship status shows an odds ratio of 1.22, which is not statistically significant, indicating that being a citizen does not significantly impact the likelihood of protest participation. However, being born in an EU country has a positive, though not statistically significant, effect on protest participation (OR = 1.45). In Belgium, the results differ in several key aspects. Gender appears to be a significant predictor, with females exhibiting significantly lower odds of protest participation (OR = 0.56, p < 0.05). Age does not significantly predict protest likelihood (OR = 0.99), while the effect of education on protest participation is positive and significant (OR = 1.25, p < 0.01). The odds ratio for citizenship status (OR = 1.85) is significant, highlighting that Belgian citizenship is associated with higher protest participation. However, being born in an EU country does not significantly affect protest behaviour (OR = 1.11). The Wald chi-squared tests for both models confirm the models’ significance in predicting protest participation in Vienna and Brussels. When combining data from both Vienna and Brussels, it is observed that gender continues to influence protest behaviour, with an odds ratio of 0.73 (p < 0.05), suggesting lower participation rates for females across both cities. Age remains a strong negative predictor (OR = 0.98, p < 0.001), while education significantly increases the likelihood of participation (OR = 1.27, p < 0.01). The impact of citizenship is positive but not significant in the combined sample (OR = 1.42), and being born in an EU country also does not significantly affect protest participation (OR = 1.36). Local voting rights for non-nationals emerge as a significant predictor (OR = 0.68, p < 0.01), indicating that greater voting rights correlate with decreased protest participation. Earlier, the hypothesis posited that an the presence of electoral rights for immigrants would lead to greater protest participation. The reasoning was that with more formal avenues for political expression—such as voting rights—immigrants might feel empowered and thus less likely to resort to protest as a means of voicing their grievances. However, the observed negative association suggests the opposite. Lastly, Model 4 introduces interaction terms to explore how the effects of education and citizenship on protest participation vary with local voting rights for non-nationals. The interaction between education and voting rights (OR = 1.01) and between citizenship and voting rights (OR = 1.71) are not statistically significant, suggesting that the presence of voting rights does not substantially alter the relationship between education or citizenship and protest participation. Higher levels of education do not have a markedly different impact on protest participation depending on whether immigrants have local voting rights. This finding implies that education's influence on protest behaviour is independent of the local electoral rights immigrants possess. Similarly, the symbolic and practical value of citizenship in protest participation is not strongly affected by the availability of local voting rights. Other factors, such as the effectiveness of political representation or the specific political context, might be more influential in shaping the protest behaviour of citizens. Concluding Remarks This article has aimed to explain the differences in protest participation patterns between migrants in two Western European contexts: Vienna and Brussels. By leveraging the theory of Political Opportunity Structures (POS) and analysing multilevel logistic regression models, the research has unravelled how institutional contexts and personal attributes influence political activism. The POS theory posits that political opportunities, such as voting rights, shape the engagement of minority groups in political activities. Contrary to the initial hypothesis that greater electoral rights would lead to increased protest participation, the analysis revealed a negative association between local voting rights for non-nationals and protest participation. Specifically, in the presence of local voting rights (Brussels), migrants demonstrated lower rates of protest participation compared to non-migrants, while in Vienna (with no local voting rights), protest participation rates were relatively higher among migrants. This unexpected result suggests that the presence of formal political avenues, such as voting rights, may reduce the perceived need for protest as a method of political expression. This interesting finding should caution us against adopting a simplistic understanding of political engagement that conflates electoral participation with overall political activism, particularly non-institutional forms like protest. While the presence of voting rights for non-nationals seems to be crucial for enabling and enhancing electoral participation, its impact on non-institutional forms of engagement, such as protests, can be markedly different. As illustrated by the findings, formal political opportunities might not always lead to increased protest participation. Instead, they may offer alternative means of engagement that reduce the need for protests. For instance, the presence of local voting rights in Brussels offers migrants a legitimate and structured avenue to express their political preferences and influence decisions through institutional means. This formal inclusion may lead to a decreased reliance on protest as a mode of political expression. When migrants perceive that they have adequate channels to address their grievances through voting and other institutional mechanisms, they may be less likely to resort to protest, which is often seen as a more confrontational and less formal method of political engagement. Conversely, in Vienna, where local voting rights for non-nationals are limited, migrants may face barriers to formal political participation. The lack of electoral rights can heighten their sense of political marginalization and restrict their avenues for institutional political engagement. As a result, protest may become a more prominent and accessible way for migrants to express their dissatisfaction and seek change. This higher protest participation among migrants in Vienna reflects their limited opportunities within the formal political system and underscores their reliance on non-institutional forms of political action. This highlights the importance of considering how different forms of political engagement interact with one another and how formal political rights can alter the dynamics of non-institutional activism. Moving on to the individual-level determinants of protest participation amongst migrants, the analysis revealed nuanced insights that both support and challenge existing literature. They suggest that while traditional SES factors like income might play a role in broader political engagement, education emerges as a more salient factor in the context of protest participation in this study. This points to the complexity of socio-economic influences on political behaviour, as outlined by Jones-Correa (1998) and others, who have noted the multifaceted relationship between SES and political involvement among ethnic minorities. The lack of a significant relationship between income and protest participation in this study aligns with findings from Atger (2009), suggesting that SES factors might interact differently within various socio-political contexts. It underscores the importance of distinguishing between different dimensions of SES when analysing political engagement and suggests that educational attainment may be a more critical factor in understanding migrant protest participation. In conclusion, this study contributes to the understanding of protest behaviour by highlighting the complex interplay between institutional contexts and individual characteristics. By shedding light on the factors that influence protest participation among migrants, the research offers valuable insights for policymakers and scholars interested in fostering more inclusive and effective political engagement. Future research should explore the underlying mechanisms behind the negative relationship between voting rights and protest participation. Qualitative studies could provide deeper insights into how migrants perceive and utilize different political opportunities. References Alberti, G., & Però, D. (2018). Migrating industrial relations: migrant workers’ initiative within and outside trade unions. British Journal of Industrial Relations , 56 (4), 693-715. Alberti, G., Holgate, J., & Tapia, M. (2013). Organising migrants as workers or as migrant workers? 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It has been a constant and influential force across Europe, shaping the continent in countless ways. While its significance cannot be overstated, the so-called migration and refugee crisis of 2015 brought unprecedented attention to the issue. Today, migration has become\u0026mdash;and will likely remain\u0026mdash;one of the most pressing and salient issues in Europe\u003csup\u003e\u003csup\u003e[1]\u003c/sup\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe growing migrant populations in Europe are characterized by diverse cultural backgrounds, histories, and migration experiences. These include \u0026lsquo;guest workers\u0026rsquo; recruited after World War II, post-colonial migrants from former colonies, European migrants exercising freedom of movement within the EU, and refugees fleeing wars and conflicts in regions such as Africa, the Middle East, and the former Yugoslavia to seek safety and protection (Geddes and Scholten, 2016).) Today, several European countries, especially in Western Europe, are net immigration countries[2], and the presence of diverse ethnic communities marks their urban centres. Cities like Brussels, and to a lesser extent Vienna, have become some of the most ethnically diverse in Europe, with growing populations from the Middle East, South Asia, Africa, the Caribbean, Eastern Europe, and beyond.\u003c/p\u003e\n\u003cp\u003eAs a matter of course and the parallel to its salience and prominent role in politics, there is a growing scholarly interest in migration. It represents a major subject of scholarly research, and the field progressively varied in terms of its links across various academic disciplines, including political science, sociology, economics, and anthropology. Within this framework, one key theme within migration studies is integration, which is also a central topic in political debates across Europe and in European Union initiatives. Integration by definition, is \u0026lsquo;the process of becoming an accepted part of society\u0026rsquo; (Penninx, 2005) and represents \u0026apos;a two-way process of adaptation by migrants and host societies and implies consideration of the rights and obligations of migrants and host societies, of access to different kinds of services and the labour market, and of identification and respect for a core set of values that bind migrants and host communities in a common purpose\u0026rsquo; (IOM, 2011). Referred as \u0026apos;different fields\u0026apos; of integration, the process encompasses multiple dimensions, including including socio-economic, cultural, and legal-political dimensions (Entzingerand and Biezeveld, 2003).\u003c/p\u003e\n\u003cp\u003eImportantly, studying the political participation of migrant-origin individuals sheds light on an often-overlooked aspect of their agency. Indeed, in much of the existing the literature, migrants are often predominantly depicted as workers. There is a growing concern among scholars that migrants\u0026rsquo; roles in society are often reduced to the labour force, while several other ways they actively shape their social environments are neglected (Smith and Favell, 2006; Schiller and Caglar, 2009). This limited perspective fails to capture the multifaceted roles that migrants play beyond the labour market, thereby underscoring the need for a broader understanding of their contributions to social, civic and political life. By shifting the focus to migrants\u0026rsquo; political engagement, this research seeks to reveal and highlight another crucial dimension of their agency. It is worth noting that should While there is a considerable body of literature on migration and political participation separately, research specifically addressing the political involvement of migrant communities remains relatively recent and evolving. This underscores the importance of exploring this intersection to gain a fuller understanding of migrants\u0026apos; roles in society.\u003c/p\u003e\n\u003cp\u003eThis article shares the perspective of Ford and Jenning (2020: 302), who underscored the emergence of politically significant ethnic minority groups in Europe, and argued that migrants \u0026lsquo;have distinct ethnic identities and cultural traditions; they tend to cluster geographically and economically in struggling places and lower status, less secure parts of the labour market; and they have unique group political interests, in particular for recognition of their cultural traditions and political representation of their ethnic groups, and for protection from majority hostility and discrimination.\u0026rsquo; There is a growing recognition that migrants are not just passive recipients of policies but also active agents who can influence political processes and outcomes. Migrant communities have become increasingly visible in political debates, advocacy efforts, and grassroots organisations, underscoring the importance of studying their political agency and participation. Similarly, other studies acknowledge migrant communities as a potential new electorate. They realise the significant and rising shares of the migrant populations and the diversity of the electorate in European countries (Dancygier and Saunders, 2006; Caramani and Strijbis, 2011). The former authors note that immigrant political behaviour is largely unexplored, and its exploration is limited to the U.S. context. Consequently, this study is also motivated by the fact that the political participation of immigrants in Europe deserves more scholarly attention and various calls for an extensive analysis of immigrant political behaviour from different theoretical and empirical points of view. \u003c/p\u003e\n\u003cp\u003eThe political participation of migrants is a fundamental aspect of their integration into new societies, particularly given the growing number of immigrants and their descendants in Europe. The exclusion or abstention of migrant populations from political processes raises significant concerns about the quality of democracy, as their voices and perspectives are essential for truly representative governance. Migrant political participation is especially a prominent issue at the local level and in countries with established immigrant populations. Regarding the former, migrants have a vested interest in decision-making processes that affect housing, public services, and education, directly impacting their daily lives. With regards to the latter, in countries with long-standing immigrant communities, these populations have deep roots and have made substantial contributions to society. The migration experience in such countries has often shaped policies and social perceptions. The exclusion or abstention of migrant populations from political processes raises significant concerns about the quality of democracy, as their voices and perspectives are essential for truly representative governance. Despite this, migrants, whether residents or citizens, often face disparities in political rights and opportunities compared to native citizens. Examining these inequalities and understanding migrant political participation can offer valuable insights into their social inclusion and integration. As the immigrant population grows and the \u0026apos;participatory gap\u0026apos; between immigrants and natives persists, discussions about their political participation are likely to gain increasing importance in national politics and the broader European agenda.\u003c/p\u003e\n\u003cp\u003e[1] Most recently (by June 2023), the war in Ukraine has resulted in the largest and fastest displacement of people in post-war Europe, with over 6 million refugees leaving Ukraine.\u003c/p\u003e\n\u003cp\u003e[2] Based on the data from UN Desa (2023), Germany, the UK, France, Italy, and Spain are marked with positive net migration balances in 2023 as the number of people entering the country (immigrants) exceeds the number of people leaving the country (emigrants). For further information please see Europe net migration by country 2023 | Statista\u003c/p\u003e"},{"header":"Migrants’ political participation beyond electoral arenas","content":"\u003cp\u003ePolitical participation is a multidimensional concept that extends beyond the confines of electoral politics. Yet,\u0026nbsp;much of earlier research exclusively focuses on electoral participation, neglecting other forms of political engagement.\u0026nbsp;While electoral participation is prominent, it represents one facet of the broader repertoire of political participation modes. Its conceptualisation has been diversified over time and moved beyond the arenes of voting through the inclusion of several other political activities to its definition. This broader repertoire today includes ‘non-electoral’, ‘unconventional’, and ‘extra-parliamentary’ participation forms through which immigrants engage in the political process and express concerns beyond routine elections (Vintila and Martiniello, 2021).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study of political participation began in the American context during the 1950s and 1960s with an exclusive focus on elections (Lazarsfeld et al. 1948, Campbell et al. 1960). By the 1970s, Verba and Nie (1972) expanded this focus to include activities beyond voting and campaigning. Their seminal work introduced four principal dimensions of political participation: voting, campaign activity, communal activity, and particularized contact. This expansion reflected the era’s growing emphasis on societal groups and direct citizen-politician interactions.\u003c/p\u003e\n\u003cp\u003eResearch on political participation has continued to expand in the following years as the domain of the concept extended. It was the inclusion of protest behaviour and civil disobedience into the definition of political participation which shifted an understanding of the concept based on 'conventional' activities towards a broader one. Again, the extension of what counts as political participation was a response to the societal changes in the era and a reflection of the so-called ‘new social movements’. In words of Della Porta and Diani (1999), new social movements refer to ‘the movements which had developed since the late 1960s on issues such as women’s rights, gender relations, environmental protection, ethnicity and migration, peace and international solidarity – with a strong (new) middle-class basis and a clear differentiation from the models of working-class or nationalist collective action that had historically preceded them. While there are surely continuities between those movements and the current wave of global justice campaigns, there are also many suggestions that the overall patterns of collective action they display is significantly different from those we had grown accustomed to’.\u003c/p\u003e\n\u003cp\u003eWith the rise of ‘new social movements’ and the reorientation of political agenda towards postmaterialist issues, the earlier definitions by Verna and Nie (1972) have been considered as narrow in the sense that their scope of activity was restricted to the government. On this point, Barnes and Kaase (1984) have been critical of excluding protest activity from the domain of political participation and thus incorporated what they call ‘protest potential’ in their influential work \u003cem\u003ePolitical Action\u003c/em\u003e. They expanded the definition of political participation as ‘all voluntary activities by individual citizens intended to influence either directly or indirectly political choices at various levels of the political system’.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis paper aligns closer with the latter approach,\u0026nbsp;which recognizes that political participation extends beyond institutional arenas. Beyond voting, a variety of activities are available to express political interests, influence policymaking or voice opinions on \u003cem\u003epublic matters.\u0026nbsp;\u003c/em\u003eThis article argues that migration studies should pay greater attention to the more contemporary forms of participation, such as public protests, through which migrants articulate their concerns and viewpoints in the public arenas in their host countries.\u003c/p\u003e\n\u003cp\u003eCentring its study on the electoral domain, on the other hand, can deliver a biased picture of migrant political participation. Indeed, studies with an excessive focus on voting tend to detect significant gaps in the turnout rates between migrants and the autochthonous population, thus portraying migrants as ‘disengaged’. On the contrary, the study of non-electoral forms of political participation has been conducted to counter such ‘disengagement’ and suggest that migrants are actively engaged in ways comparable to the native population.\u0026nbsp;Electoral abstention isn't always a voluntary decision for everyone (Marien et al., 2010). For many immigrants, in particular, most forms of electoral participation have traditionally been restricted to those who possess the nationality of the host country.\u0026nbsp;As Martiniello (2006) rightly stated, “migrants are not more passive than other citizens, but their involvement should also not be exaggerated by regarding them as the vanguard of the new global proletariat”. Evidently, one-dimensional approaches cannot generate convincing clarifications of migrant political incorporation.\u003c/p\u003e\n\u003cp\u003eSimilarly, Hay (2007) points out, ‘those with the most restrictive and conventional conceptions of political participation identify a strong and consistent pattern of declining political participation’. According to Martiniello (1997, 2006), the thesis of the political quiescence of immigrants is related to the absence of electoral rights for migrant workers. For some, they could not play a significant role in the politics of their country of residence, and their exclusion from the electoral process led to a situation of political apathy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDespite this, several studies demonstrate that migrants are actively engaged in other forms of political participation. For example, involvement in trade unions (Marino et al., 2015; Alberti and Pero, 2018) and protest movements (Atac et al., 2016) are clear indicators of their political activity. Migrants have been prominent in movements such as the sans-papier workers' movement (Tapia and Turner, 2013), the Dutch 'Justice for Janitors' strike (Connolly et al., 2017), the Italian Migrants' Strike (Oliveri, 2015), and global protests related to the Israel-Palestine conflict.\u003c/p\u003e\n\u003cp\u003eThe lack of formal citizenship rights does not prevent migrants from participating in the political landscape. Instead, it often redirects their efforts towards alternative forms of expression, such as protests. These activities allow migrants to challenge injustices, raise awareness of their issues, and advocate for social and political change. Through participation in protests, migrants without citizenship rights can still make significant contributions to political discourse and advocate for the needs and rights of their communities in both their host and home countries.\u003c/p\u003e"},{"header":"Theoretical Framework and Hypotheses","content":"\u003cp\u003eThe theory of political opportunity structures sheds light on the external factors influencing political participation (Kriesi et al. 1997; Meyer, 2004). A significant idea, developed originally for the study of social movement is defined by Tarrow (1996: 54) as \u0026lsquo;consistent but not necessarily formal, permanent, or national signals to social or political actors which either encourage or discourage them to use their internal resources to form social movements\u0026rsquo;. In the word of Koopmans (2004), opportunities are \u0026lsquo;options for collective action, with chances and risks attached to them, which depend on factors outside the mobilizing group\u0026rsquo;.\u003c/p\u003e\n\u003cp\u003eInitially considered as a general framework, several studies illustrated the presence of specific opportunities available to different ethnic groups and their role in immigrants\u0026rsquo; political activities (Koopmans, 2005; Morales and Giugni, 2011). In this paper, the political opportunity structure refers to the institutional incentives and disincentives relevant to individuals with a migration background, which can influence their choices and strategies in participating in political activities. It does not suggest a uniform set of structures applicable to all immigrants or all forms of political participation. On the contrary, the strength of political opportunity theory lies in its ability to care for variations: uneven grounds between native and immigrant populations, different structures for different political activities, and the varying conditions applied to a diverse category of immigrants. On this point, political opportunity structures are context-sensitive, providing favourable access to some groups while generating adverse conditions for others. Similarly, they can favour certain groups, discourses and policy-claims over other actors, expressions and demands.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDrawing on the political opportunity structure (POS) theory, this paper argues that immigrants\u0026rsquo; access to political life is pre-determined by certain characteristics of the institutional settings. It suggests that the inclusiveness of political rights is crucial for migrant political integration. In fact, as stated by Fennema and Tillie (2001), the right to vote, one of the most relevant political rights for this study, represents an \u0026lsquo;initial opening of the political opportunity structures\u0026rsquo; providing incentives for immigrants to engage in the political process. When immigrants enjoy equal voting rights with the native population, they tend to show greater interest in political debates, feel a stronger connection to their polity, and become familiar with the prevailing political norms (Baub\u0026ouml;ck et al., 2006). Such a society in which an egalitarian distribution of political rights is achieved would indicate an open political opportunity structure for the framework of this research. Nevertheless, the distribution of political rights in Europe is characterised by significant disparities. As illustrated in Table 1, many Western European countries currently grant non-citizen resident migrants voting rights in municipal elections.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Right to vote for third-country citizens\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003eThese varying characterisations of voting rights are expected to indicate the obstacles and opportunities for immigrants\u0026apos; political participation. A similar thought is expressed by Hayduk (2006, 2015), who suggests that granting local voting rights to immigrant residents has the benefit of putting them on a \u0026apos;pathway to citizenship\u0026apos;. Local voting rights can serve as a catalyst for political socialization and mobilization within migrant communities. As migrants become more politically active through participation in local elections, they are also more likely to organize and engage in collective action to address issues not resolved through formal political channels.\u0026nbsp;However, there is a notable lack of empirical n how voting rights impact protest participation. Based on these considerations, the analysis hypothesizes:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH1:\u003c/strong\u003e The more electoral rights immigrants enjoy, the more likely they are to participate in protest activities, and vice versa.\u003c/p\u003e\n\u003cp\u003eThe second block of variables concerns the individual-level characteristics of the respondents. Studies of political participation frequently utilise individual-level variables to explain the phenomenon of political participation. The sample in this paper varies not only in terms of its composition of native and immigrant-origin respondents but also in their individual characteristics (Brady, Verba and Schlozman 1995; Jacobs and Tillie, 2004).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSocioeconomic status (SES) has long been accepted as a crucial factor influencing political participation patterns (Verba and Nie, 1972; Quintelier and Hooghe, 2012). Highlighting the ways in which disparities in SES foster unequal representation and participation, factors such as income and education are suggested to display significant impact over individuals\u0026apos; likelihood of taking part in political activities. The rationale behind the relation between SES and political participation comes from numerous theoretical frameworks and empirical results. One prominent theoretical approach is the resource-based model, which posits that that individuals with higher socioeconomic status acquire more advanced resources, such as education, income, and social networks, which facilitate their engagement in political life. Another important theoretical framework for understanding the link between socioeconomic status and participation is the socialization approach. According to this viewpoint, those from higher socioeconomic backgrounds are more likely to grow up in environments where political discussions are common and engagement in political life is encouraged.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe explanatory power of SES variables in the specific context of immigrant political participation is less straightforward and multifaced. Immigrants often experience unique challenges and opportunities when taking part in the political process. Several studies have found that immigrants have a complicated relationship to the traditional SES model. As such, they identified a weaker relationship between the SES levels and the political involvement of ethnic minorities (Jones-Correa, 1998; Barreto and Munoz, 2003; Tam Cho, Gimpel and Wu, 2006; Atger, 2009). Nevertheless, these studies were conducted in the Americas, and less is known about the explanatory power of socioeconomic status on protest activity in the European context. The empirical findings aim to shed light on the question of whether socioeconomic status is a powerful factor in explaining migrants\u0026rsquo; engagement in protest activity. Therefore,\u0026nbsp;the second hypothesis is:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eH2:\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;The higher the socioeconomic status (SES) of immigrants, to be more likely they are to engage in political participation compared to those with lower SES.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe third hypothesis advances an interaction effect between the presence of local voting rights for non-nationals in Vianna and Brussels, and individual characteristics of socioeconomic status. The interaction hypothesis stems from the fact that the two cities have different provisions for migrant electoral rights. In Vienna, where local voting rights are absent, it may be less apparent whether migrants with higher socioeconomic resources will participate in public protests. Higher socioeconomic status does not always guarantee political participation, as institutional structures can hinder such involvement. The interaction of individual-level characteristics and macro-level factors is thus expected to disentangle this puzzle. Thus, the the third hypothesis the multilevel model aims to address is the following:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH3\u003c/strong\u003e: The relationship between the socioeconomic status and protest participation is moderated by the presence of (local) political rights, such that the positive effect of education and income on (the log odds) political participation is stronger in Brussels (where non-citizen migrants have local voting rights) compared to Vienna (where local voting rights are not available).\u003c/p\u003e"},{"header":"Data and Measurement","content":"\u003cp\u003e\u003cem\u003eData sources\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe data in this paper comes from the European Social Survey (ESS). As acknowledged in the literature, it adopts high standards, particularly \u0026lsquo;in its questionnaire design, the cross-national equivalence of the instruments used and the sampling procedures applied\u0026rsquo; (Jowell et al., 2007; Kohler, 2007; 2008). It is a high-quality dataset where the sampling design approximates a simple random sample and has a relatively high response rate. By offering information on the context, namely the country the respondent resides in, the ESS enables the merging of individual-level data with contextual data. Crucially for the focus of this study, the ESS collects data at the NUTS (Nomenclature of Territorial Units for Statistics) levels, enabling regional analysis within countries. This granularity is particularly useful for examining urban contexts like Vienna and Brussels, enabling researchers to capture the nuances of local political and social dynamics.\u003c/p\u003e\n\u003cp\u003eAs mentioned earlier, the ESS is stated to be representative of the national population. However, it is equally important that the survey is representative of the foreign-born population in the countries under this study. To check if it holds, the percentage of foreign-born individuals in the ESS sample is calculated and compared with external data provided by Eurostat, the statistical office of the European Union. With a correlation coefficient (Pearson\u0026rsquo;s R) equal to 0.98, a fairly close fit is observed between the two samples of the foreign-born populations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMoreover, for the purpose of this study, relying on electoral surveys would not be sufficient. \u0026lsquo;Politics\u0026rsquo; is one of the core modules of the ESS project, and the questionnaire contains a wide repertoire of political participation items, including participating in public protests. his aligns well with the focus of this paper, which is concerned with protest behaviour. Second, it is crucial to test the different sets of working hypotheses and reach empirical findings. The ESS survey provides information on several factors that are highlighted in the theoretical framework. To enhance the robustness and generalizability of the analysis, data from the European Social Survey (ESS) were combined across multiple rounds, from Round 1 to the most recent Round 11. This aggregation of data effectively increased the number of observations, providing a more comprehensive dataset for examining patterns of protest participation across different contexts.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDependent variable\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eProtest participation is measured by asking respondents whether they have participated in the protest activities in the last 12 months. The dependent variable is coded as binary: 1 if the respondent answers affirmatively to the question, \u0026quot;During the last 12 months, have you taken part in a public demonstration?\u0026quot; and 0 if they have not.\u003c/p\u003e\n\u003cp\u003eIt should be noted, the ESS questionnaire does not have a direct indicator of the migration status of the respondents. It does not ask the respondents \u0026lsquo;What is your current migration status in this country?\u0026rsquo;. Instead, it contains information on the respondents\u0026rsquo; country of birth, their parents\u0026rsquo; country (s) of birth, the time of arrival to the country, citizenship status and religious denominations. These pieces of information are highly important in identifying respondents with a migration background. This study relies on the country of birth indicator available in the ESS, which is generally considered a less biased measure of migration background versus ethnicity. Eventually, the immigrant sample in this study is composed of foreign-born respondents and those who were born in the country with two foreign-born parents (also known as second-generation migrants).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eScope\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe paper focuses on the cities of Vienna and Brussels, which are home to substantial migrant populations. Choosing Vienna and Brussels as case studies for examining migrant protest participation is strategically significant due to their distinct national and local contexts, unique migration histories, and the scarcity of quantitative studies at the city level in this topic.\u003c/p\u003e\n\u003cp\u003eFirst, the two cities are characterised with distinct national and local contexts presenting two contrasting social and political environments for migrant inhabitants. Vienna, the capital of Austria, operates within a more restrictive national policy context regarding immigration and integration. Austrian policies historically emphasize assimilation, and local voting rights for non-nationals are limited. The process of naturalization has traditionally been stringent, necessitating long periods of residency and demonstrating economic self-sufficiency (Kraler, 2011). This restrictive approach reflects a broader national trend towards conservative citizenship policies that have been criticized for impeding the integration of migrants into Austrian society (Howard, 2013).\u003c/p\u003e\n\u003cp\u003eIn contrast, Brussels, the capital of Belgium and the European Union, adopts a more inclusive approach towards migrants. Belgium\u0026apos;s citizenship and migration policies are relatively accommodating, with shorter residency requirements and more lenient integration criteria (Martiniello, 2003). This inclusive stance reflects Belgium\u0026apos;s broader policy orientation towards facilitating migrant integration and accommodating its diverse population, including significant communities from former Belgian colonies in Africa (Demart, 2013). Brussels\u0026rsquo; municipal and regional authorities have adopted progressive measures, such as granting local voting rights to non-national residents, which contrasts with the more restrictive policies observed in Vienna (Arrighi and Baub\u0026ouml;ck, 2017). Belgium grants local voting rights to non-EU migrants who have resided in the country for at least five years. These differences in citizenship regimes, electoral rights and migration policies between Vienna and Brussels are expected to contribute to diverse patterns of political engagement and integration, including how migrants participate in protests and other non-electoral forms of political expression.\u003c/p\u003e\n\u003cp\u003eSecond, Vienna and Brussels have rich, albeit distinct, histories of migration, which significantly shape their contemporary migrant landscapes and political dynamics. Vienna\u0026apos;s migration history dates back to the Austro-Hungarian Empire, which fostered a multicultural environment due to its diverse ethnic composition (Steidl, Fischer-Nebmaier and Oberly, 2017). The post-World War II period marked a significant shift with Austria\u0026apos;s recruitment of \u0026quot;guest workers\u0026quot; from Southern Europe, particularly Italy, Turkey and Yugoslavia, to address labour shortages (Bischof and Rupnow, 2017). This influx resulted in the establishment of substantial migrant communities that have since faced integration challenges amid evolving political and social landscapes. More recently, Vienna has seen an increase in asylum seekers from the Middle East and Africa, particularly during the 2015 refugee crisis, reflecting a continued evolution in its migration dynamics (Kohlenberger et al., 2017).\u003c/p\u003e\n\u003cp\u003eMeanwhile, Brussels\u0026rsquo; migration history is deeply influenced by its colonial past and \u0026nbsp;role as a political and administrative center. After World War II, Brussels attracted a significant number of labour migrants from Southern Europe, similar to other Western European cities. Additionally, the city\u0026rsquo;s colonial ties to Africa, particularly Congo, Rwanda, and Burundi, have led to a significant presence of migrants from these former colonies, contributing to Brussels\u0026apos; unique demographic profile. In recent decades, Brussels has continued to attract a diverse range of migrants from across the globe, including Eastern Europe, the Middle East, and Asia, driven by its status as the European Union\u0026apos;s headquarters and its progressive migration policies (Deboosere, 2009; Goddeeris, 2015; Bousetta, Favell and Martiniello, 2018).\u003c/p\u003e\n\u003cp\u003eThese divergent migration histories and experiences are crucial for understanding the political engagement of migrants in these cities. Vienna\u0026apos;s integration challenges and Brussels\u0026apos; more inclusive approach reflect different national and local responses to migration, which influene patterns of migrant political participation, including protest activities. Quantitative research focusing on these city-level dynamics remains sparse, underscoring the originality and significance of this study in analysing the impact of local voting rights on migrant protest participation in such varied contexts. All in all, the choice to study Vienna and Brussels is justified by their contrasting migration policies, diverse migrant populations, and the significant yet underexplored role of local voting rights in shaping protest participation. Vienna\u0026apos;s restrictive policies and Brussels\u0026apos; inclusive approach offer a compelling comparison that can illuminate the conditions under which migrants are more likely to engage in protests. This comparative analysis not only fills a gap in the existing literature but also provides actionable insights for policymakers aiming to foster political engagement and social integration among migrant communities.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMethod of analysis\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe two principal aims of this research are, first, to identify the gaps in participation in public demonstrations between the immigrant and autochthonous populations, and eventually to explain these differences. Therefore, the research is carried out in two stages: descriptive and explanatory.\u003c/p\u003e\n\u003cp\u003eFor the first stage, summary statistics are performed to obtain information on the basic statistics of the dependent variable. Frequency tables and visual charts are used to show the frequency distribution of protest activity in the cities of Vienna and Brussels.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe second stage, which is at the heart of this study, is explanatory. Logistic regression analysis is performed to assess the effect of independent variables \u003cem\u003e(explanans)\u003c/em\u003e on the dependent variable (\u003cem\u003eexplanandum).\u003c/em\u003e The choice of logistic regression over the linear regression analysis is due to the fact that the dependent variable in this study are dichotomous (with two possibilities, such as \u0026lsquo;0\u0026rsquo; or \u0026lsquo;1\u0026rsquo;).\u003c/p\u003e\n\u003cp\u003eThe logistic regression models the chance of participation in protest based on the predictors. Because chance is a ratio, what is modelled is the logarithm of the chance given by:\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis and Results\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA first look at the data reveals that, on average, in Vienna, a similar proportion of migrants (14.60%) and non-migrants (14.98%) participate in protests. Whereas, in Brussels, a smaller proportion of migrants (8.84%) participate in protests compared to non-migrants (16.12%).\u0026nbsp;Table 2 presents the detailed breakdown of protest behaviour among migrants and non-migrants in these two cities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Protest Participation Rates of Migrants and Non-Migrants\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParticipation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 32.7815%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVienna\u003c/strong\u003e \u003cem\u003e(AT13)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 31.2914%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBrussels\u003c/strong\u003e \u003cem\u003e(BE10)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9272%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eMigrants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7086%;\"\u003e\n \u003cp\u003eNon-migrants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eMigrants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eNon-migrants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9272%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eNo Protest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003e85.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7086%;\"\u003e\n \u003cp\u003e85.02%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003e91.16%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e83.88%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9272%;\"\u003e\n \u003cp\u003e1,529\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eProtest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003e14.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7086%;\"\u003e\n \u003cp\u003e14.98%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003e8.84%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e16.12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9272%;\"\u003e\n \u003cp\u003e267\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003e541\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7086%;\"\u003e\n \u003cp\u003e1,255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003e430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9272%;\"\u003e\n \u003cp\u003e1,796\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe following table, Table 3, summarises the characteristics of the sample by type of participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Sample characteristics of migrants participating in protests \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.5985%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2714%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVienna\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.1301%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBrussels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.5985%;\"\u003e\n \u003cp\u003e% male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2714%;\"\u003e\n \u003cp\u003e43.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.1301%;\"\u003e\n \u003cp\u003e63.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.5985%;\"\u003e\n \u003cp\u003eMean age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2714%;\"\u003e\n \u003cp\u003e41.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.1301%;\"\u003e\n \u003cp\u003e37.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.5985%;\"\u003e\n \u003cp\u003e% second generation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2714%;\"\u003e\n \u003cp\u003e18.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.1301%;\"\u003e\n \u003cp\u003e23.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.5985%;\"\u003e\n \u003cp\u003e% primary education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2714%;\"\u003e\n \u003cp\u003e12.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.1301%;\"\u003e\n \u003cp\u003e34.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.5985%;\"\u003e\n \u003cp\u003e% secondary education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2714%;\"\u003e\n \u003cp\u003e37.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.1301%;\"\u003e\n \u003cp\u003e15.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.5985%;\"\u003e\n \u003cp\u003e% tertiary education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2714%;\"\u003e\n \u003cp\u003e9.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.1301%;\"\u003e\n \u003cp\u003e7.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.5985%;\"\u003e\n \u003cp\u003e% higher education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2714%;\"\u003e\n \u003cp\u003e40.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.1301%;\"\u003e\n \u003cp\u003e42.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.5985%;\"\u003e\n \u003cp\u003e% with citizenship\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2714%;\"\u003e\n \u003cp\u003e48.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.1301%;\"\u003e\n \u003cp\u003e60.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.5985%;\"\u003e\n \u003cp\u003e% born in EU countries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2714%;\"\u003e\n \u003cp\u003e15.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.1301%;\"\u003e\n \u003cp\u003e9.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: Author\u0026rsquo;s elaborations on ESS data\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn Vienna, both males and females have similar participation rates in protests, with females participating slightly more than males (56.96% vs. 43.04%). In Brussels, males are more likely to participate in protests compared to females (63.16% vs. 36.84%). In other words, this indicates a gender-related pattern in protest participation in Brussels. The generational characteristics of migrants participating in protests in both Vienna and Brussels closely mirror the overall generational distribution of migrants in these cities. This suggests that the likelihood of protest participation among migrants does not significantly differ between first and second-generation migrants in either city.\u003c/p\u003e\n\u003cp\u003eMoreover, in Vienna, protest participants with higher education (40.26%) are overrepresented compared to their proportion among those who did not participate (29.52%). Those with primary education are underrepresented in protests (12.99%) compared to non-participants (19.60%). Similarly in Brussels, protest participants with higher education (42.11%) are overrepresented compared to their proportion among those who did not participate (26.42%). Those with primary education are underrepresented in protests (34.21%) compared to those who did not participate (43.01%). Overall, in both cities, migrants with higher education constitute a larger share compared to those with lower educational levels. This trend is more pronounced in Brussels, where a significant portion of protest participants have higher education, whereas in Vienna, the distribution is somewhat more balanced but still favours those with higher education.\u003c/p\u003e\n\u003cp\u003eSample characteristics by citizenship show that in Vienna, protest participants are almost equally divided between citizens with migration backgrounds (48.10%) and non-citizens (51.90%), with a slightly higher representation of non-citizens among protest participants. On the other hand, in Brussels, protest participants are predominantly citizen migrants (60.53%), while non-citizens (39.47%) are underrepresented among protest participants compared to their share among those who did not participate (49.23%). Finally, in Vienna, 15.53% of migrants who protested were born in an EU member state, while 56.96% were non-EU migrants. In comparison, in Brussels, 9.09% of protesting migrants have an EU background, and 28.95% were non-EU migrants.\u0026nbsp;These findings highlight varying levels of protest participation among EU and non-EU migrants in Vienna and Brussels, underscoring potential differences in civic engagement and political mobilization across these two European cities.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMultivariate Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis requires to combine data collected at the individual level with data at the country level indicating the multilevel nature of the data (one level, the individual, is nested within the other, the country). The test of the multilevel model fit against the unconditional mean model (Wang, Xie and Fisher, 2011) suggests that it would be a mistake to disregard the multilevel nature of the data (i.e. assuming individuals were uncorrelated within counties). This supports the hypothesis on the significant role of the institutional context in shaping protest participation. The results of the multi-level logistic regression model are presented in Table 4.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Odds ratios for protest participation for migrants living in Austria and Belgium\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1 (Austria)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2 (Belgium)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003eIndividual-level variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003eGender (female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e.56*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e.73*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e.75*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003eAge\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e.97***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e.98***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e.98***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e1.26**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e1.25**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e1.27**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e1.26**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003eIncome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003eCitizens of country\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e1.85*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003eBorn in EU country\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003eCountry-level variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003eLocal voting rights for non-nationals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e.68**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003eCross-level interactions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003eEducation*voting rights for non-nationals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003eCitizenship*voting rights for non-nationals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e.34*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e.11**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e.27***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e.31**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003eWald X\u003csup\u003e2\u003c/sup\u003e (df)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e22.56**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e12.24**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e33.18***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e5.62*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.9867%;\"\u003e\n \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7396%;\"\u003e\n \u003cp\u003e614\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.5887%;\"\u003e\n \u003cp\u003e1,143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e1,143\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote:\u003c/em\u003e * p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001\u003c/p\u003e\n\u003cp\u003eModel 1 and Model 2 focus on Vienna and Brussels separately, while Model 3 and Model 4 analyse the combined sample from both cities.\u0026nbsp;By examining both context-specific and combined models, we gain insights into how various factors interact to affect protest behaviour.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn Austria, the analysis reveals a complex interplay of factors influencing protest participation. Gender is a conventional predictor; although the odds ratio for females is 0.86, indicating lower participation compared to males, this result is not statistically significant (p \u0026gt; 0.05). Age is a significant negative predictor (OR = 0.97, p \u0026lt; 0.001), suggesting that older migrants are less likely to engage in protests. This result resonates with the literature that portrays younger individuals as more inclined towards alternative forms of political engagement, such as protests, rather than traditional methods like voting. Marsh, O\u0026rsquo;Toole, and Jones (2007) highlight that young people often show less interest in traditional forms of politics, preferring alternative, less institutionalized methods of engagement. Similarly, Henn, Weinstein, and Wring (2002) argue that the lower turnout among youth is less about political apathy and more about a critical engagement or \u0026lsquo;engaged skepticism\u0026rsquo; toward formal politics.\u003c/p\u003e\n\u003cp\u003eConversely, higher education levels are strongly associated with increased protest participation (OR = 1.26, p \u0026lt; 0.01), emphasizing the role of educational attainment in fostering political activism. Citizenship status shows an odds ratio of 1.22, which is not statistically significant, indicating that being a citizen does not significantly impact the likelihood of protest participation. However, being born in an EU country has a positive, though not statistically significant, effect on protest participation (OR = 1.45).\u003c/p\u003e\n\u003cp\u003eIn Belgium, the results differ in several key aspects. Gender appears to be a significant predictor, with females exhibiting significantly lower odds of protest participation (OR = 0.56, p \u0026lt; 0.05). Age does not significantly predict protest likelihood (OR = 0.99), while the effect of education on protest participation is positive and significant (OR = 1.25, p \u0026lt; 0.01).\u0026nbsp;The odds ratio for citizenship status (OR = 1.85) is significant, highlighting that Belgian citizenship is associated with higher protest participation. However, being born in an EU country does not significantly affect protest behaviour (OR = 1.11).\u0026nbsp;The Wald chi-squared tests for both models confirm the models\u0026rsquo; significance in predicting protest participation in Vienna and Brussels.\u003c/p\u003e\n\u003cp\u003eWhen combining data from both Vienna and Brussels, it is observed that gender continues to influence protest behaviour, with an odds ratio of 0.73 (p \u0026lt; 0.05), suggesting lower participation rates for females across both cities. Age remains a strong negative predictor (OR = 0.98, p \u0026lt; 0.001), while education significantly increases the likelihood of participation (OR = 1.27, p \u0026lt; 0.01). The impact of citizenship is positive but not significant in the combined sample (OR = 1.42), and being born in an EU country also does not significantly affect protest participation (OR = 1.36). Local voting rights for non-nationals emerge as a significant predictor (OR = 0.68, p \u0026lt; 0.01), indicating that greater voting rights correlate with decreased protest participation. Earlier, the hypothesis posited that an the presence of \u0026nbsp;electoral rights for immigrants would lead to greater protest participation. The reasoning was that with more formal avenues for political expression\u0026mdash;such as voting rights\u0026mdash;immigrants might feel empowered and thus less likely to resort to protest as a means of voicing their grievances. However, the observed negative association suggests the opposite.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLastly, Model 4 introduces interaction terms to explore how the effects of education and citizenship on protest participation vary with local voting rights for non-nationals. The interaction between education and voting rights (OR = 1.01) and between citizenship and voting rights (OR = 1.71) are not statistically significant, suggesting that the presence of voting rights does not substantially alter the relationship between education or citizenship and protest participation. Higher levels of education do not have a markedly different impact on protest participation depending on whether immigrants have local voting rights. This finding implies that education\u0026apos;s influence on protest behaviour is independent of the local electoral rights immigrants possess. Similarly, the symbolic and practical value of citizenship in protest participation is not strongly affected by the availability of local voting rights. Other factors, such as the effectiveness of political representation or the specific political context, might be more influential in shaping the protest behaviour of citizens.\u003c/p\u003e"},{"header":"Concluding Remarks","content":"\u003cp\u003eThis article has aimed to explain the differences in protest participation patterns between migrants in two Western European contexts: Vienna and Brussels. By leveraging the theory of Political Opportunity Structures (POS) and analysing multilevel logistic regression models, the research has unravelled how institutional contexts and personal attributes influence political activism.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe POS theory posits that political opportunities, such as voting rights, shape the engagement of minority groups in political activities. Contrary to the initial hypothesis that greater electoral rights would lead to increased protest participation, the analysis revealed a negative association between local voting rights for non-nationals and protest participation. Specifically, in the presence of local voting rights (Brussels), migrants demonstrated lower rates of protest participation compared to non-migrants, while in Vienna (with no local voting rights), protest participation rates were relatively higher among migrants. This unexpected result suggests that the presence of formal political avenues, such as voting rights, may reduce the perceived need for protest as a method of political expression.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis interesting finding should caution us against adopting a simplistic understanding of political engagement that conflates electoral participation with overall political activism, particularly non-institutional forms like protest. While the presence of voting rights for non-nationals seems to be crucial for enabling and enhancing electoral participation, its impact on non-institutional forms of engagement, such as protests, can be markedly different. As illustrated by the findings, formal political opportunities might not always lead to increased protest participation. Instead, they may offer alternative means of engagement that reduce the need for protests. For instance, the presence of local voting rights in Brussels offers migrants a legitimate and structured avenue to express their political preferences and influence decisions through institutional means. This formal inclusion may lead to a decreased reliance on protest as a mode of political expression. When migrants perceive that they have adequate channels to address their grievances through voting and other institutional mechanisms, they may be less likely to resort to protest, which is often seen as a more confrontational and less formal method of political engagement.\u003c/p\u003e\n\u003cp\u003eConversely, in Vienna, where local voting rights for non-nationals are limited, migrants may face barriers to formal political participation. The lack of electoral rights can heighten their sense of political marginalization and restrict their avenues for institutional political engagement. As a result, protest may become a more prominent and accessible way for migrants to express their dissatisfaction and seek change. This higher protest participation among migrants in Vienna reflects their limited opportunities within the formal political system and underscores their reliance on non-institutional forms of political action. This highlights the importance of considering how different forms of political engagement interact with one another and how formal political rights can alter the dynamics of non-institutional activism.\u003c/p\u003e\n\u003cp\u003eMoving on to the individual-level determinants of protest participation amongst migrants, the analysis revealed nuanced insights that both support and challenge existing literature. They suggest that while traditional SES factors like income might play a role in broader political engagement, education emerges as a more salient factor in the context of protest participation in this study. This points to the complexity of socio-economic influences on political behaviour, as outlined by Jones-Correa (1998) and others, who have noted the multifaceted relationship between SES and political involvement among ethnic minorities. The lack of a significant relationship between income and protest participation in this study aligns with findings from Atger (2009), suggesting that SES factors might interact differently within various socio-political contexts. It underscores the importance of distinguishing between different dimensions of SES when analysing political engagement and suggests that educational attainment may be a more critical factor in understanding migrant protest participation.\u003c/p\u003e\n\u003cp\u003eIn conclusion, this study contributes to the understanding of protest behaviour by highlighting the complex interplay between institutional contexts and individual characteristics. By shedding light on the factors that influence protest participation among migrants, the research offers valuable insights for policymakers and scholars interested in fostering more inclusive and effective political engagement. Future research should explore the underlying mechanisms behind the negative relationship between voting rights and protest participation. Qualitative studies could provide deeper insights into how migrants perceive and utilize different political opportunities.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlberti, G., \u0026amp; Per\u0026ograve;, D. (2018). Migrating industrial relations: migrant workers\u0026rsquo; initiative within and outside trade unions. \u003cem\u003eBritish Journal of Industrial Relations\u003c/em\u003e, \u003cem\u003e56\u003c/em\u003e(4), 693-715.\u003c/li\u003e\n\u003cli\u003eAlberti, G., Holgate, J., \u0026amp; Tapia, M. (2013). Organising migrants as workers or as migrant workers? Intersectionality, trade unions and precarious work. \u003cem\u003eThe International Journal of Human Resource Management\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(22), 4132-4148.\u003c/li\u003e\n\u003cli\u003eArrighi, J. 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Multilevel Models: Applications Using SAS. Berlin, Germany: Walter de Gruyter.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"migration background, political participation, protest participation, right to vote, Vienna, Brussels, opportunity structures, minority rights, European Social Survey","lastPublishedDoi":"10.21203/rs.3.rs-6022305/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6022305/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWhile much research has focused on the electoral participation of voters with migration backgrounds, the political engagement of migrants beyond the ballot box remains significantly underexplored in Western Europe. This article examines migrants’ involvement in public protests in two distinct contexts—at the national and city levels—in Vienna and Brussels. Using an original empirical approach, the analysis draws on data from the European Social Survey (ESS) regional statistics (NUTS) \u003cem\u003eRound 1-11\u003c/em\u003e, exploring protest participation patterns among migrant respondents in these cities. A key question addressed is how different opportunity structures, such as the right to vote at the local level, influence the likelihood of participating in protests. The findings indicate that the presence (or absence) of local voting rights for non-nationals is a strong predictor of minority protest participation. While the right to vote at the local level is shown to impact protest involvement, the comparative analysis reveals divergent patterns in the two cases. In Brussels, where local voting rights are present, and more inclusive, migrants exhibit lower protest participation rates, whereas in Vienna, where such rights are restricted, migrants participate in protests at higher rates. This suggests that formal political avenues, such as voting rights, may reduce the need for protests as a form of political expression.\u003c/p\u003e","manuscriptTitle":"Migrant Political Activism in Vienna and Brussels: How Voting Rights Shape Protest Behaviour","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-14 10:58:36","doi":"10.21203/rs.3.rs-6022305/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"91e575c2-3060-42e6-ba18-4dde780d2604","owner":[],"postedDate":"February 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":44281378,"name":"Comparative Political Science"}],"tags":[],"updatedAt":"2025-02-14T10:58:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-14 10:58:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6022305","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6022305","identity":"rs-6022305","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}