Arts and Social Sciences, Irving K. Barber Faculty of (Okanagan)
DSpace
UBCO
Mahmud, M H
Master of Arts - MA
University of British Columbia
In this thesis, we examined the impact of race on voter turnout in the 2021 Canadian Election using data from the Canadian Election Studies Survey 2021. The analysis was conducted using three models: a bivariate model, a socio-demographic model, and a complete model. Initially, the bivariate model showed a significant negative impact of race on voter turnout, with racialized minorities less likely to vote than White individuals. Adding socio-demographic factors in the second model reduced this effect but it remained significant. However, in the complete model, which included political engagement and socioeconomic status, the impact of race loses statistical significance. This suggests that other factors, such as political interest, partisanship, political knowledge, employment, and income, play a significant role in explaining voter turnout. This study reveals that political knowledge, civic responsibility, political interest, and partisanship significantly impact voter turnout. Higher levels of political knowledge and interest, a strong sense of civic duty, and political party identification positively correlate with increased participation. Economic stability, evidenced by higher income and employment, also significantly influences voter turnout, highlighting the critical role of financial stability in facilitating political participation. COVID-19 related variables provide mix insights into their impact on voter turnout, with satisfaction with the government's handling of the pandemic negatively impacting turnout, while views on public health measures positively impact turnout. Duration of residence in the current city also affects voter turnout, with longer residence fostering greater participation. Certain religious affiliations and regional factors also impact voter turnout. Agnostic and Jehovah's Witnesses show positive and negative impacts respectively, while regions like Nunavut, Saskatchewan, Quebec, and Northwest Territories show negative impacts. Other factors, such as education, gender, age, immigrant status, language, origin of the immigrant's country, frequency of political discussions at home, and attitudes towards immigrants, do not have a significant impact when considered alongside other variables. This study highlights the multidimensional nature of voter turnout, emphasizing the interplay of demographic, social, economic, and political factors.
Voting Behaviour and Racial Identity: Exploring the Relationship Between Ethnic Identity and Its Impact on Voter Turnout in the 2021 Canadian Federal Elections by M H Mahmud MSS, The University of Dhaka, 2019 BSS, The University of Dhaka, 2018 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS in The College of Graduate Studies (Interdisciplinary Studies) (Power, Conflict, and Ideas) THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan) March 2025 © M H Mahmud, 2025 ii The following individuals certify that they have read, and recommend to the College of Graduate Studies for acceptance, a thesis entitled: VOTING BEHAVIOUR AND RACIAL IDENTITY: EXPLORING THE RELATIONSHIP BETWEEN ETHNIC IDENTITY AND ITS IMPACT ON VOTER TURNOUT IN THE 2021 CANADIAN FEDERAL ELECTIONS Submitted by M H Mahmud in partial fulfillment of the requirements of the degree of Master of Arts . Maxime Heroux-Legault, Irving K. Barber Faculty of Arts and Social Sciences Supervisor Helen Yanacopulos, Irving K. Barber Faculty of Arts and Social Sciences Supervisory Committee Member Carey Doberstein, University of British Columbia (Vancouver) Supervisory Committee Member Min Hu, Irving K. Barber Faculty of Arts and Social Sciences Supervisory Committee Member Mike Zajko, Irving K. Barber Faculty of Arts and Social Sciences University Examiner iii Abstract In this thesis, we examined the impact of race on voter turnout in the 2021 Canadian Election using data from the Canadian Election Studies Survey 2021. The analysis was conducted using three models: a bivariate model, a socio-demographic model, and a complete model. Initially, the bivariate model showed a significant negative impact of race on voter turnout, with racialized minorities less likely to vote than White individuals. Adding socio-demographic factors in the second model reduced this effect but it remained significant. However, in the complete model, which included political engagement and socioeconomic status, the impact of race loses statistical significance. This suggests that other factors, such as political interest, partisanship, political knowledge, employment, and income, play a significant role in explaining voter turnout. This study reveals that political knowledge, civic responsibility, political interest, and partisanship significantly impact voter turnout. Higher levels of political knowledge and interest, a strong sense of civic duty, and political party identification positively correlate with increased participation. Economic stability, evidenced by higher income and employment, also significantly influences voter turnout, highlighting the critical role of financial stability in facilitating political participation. COVID-19 related variables provide mix insights into their impact on voter turnout, with satisfaction with the government's handling of the pandemic negatively impacting turnout, while views on public health measures positively impact turnout. Duration of residence in the current city also affects voter turnout, with longer residence fostering greater participation. Certain religious affiliations and regional factors also impact voter turnout. Agnostic and Jehovah's Witnesses show positive and negative impacts respectively, while regions like Nunavut, Saskatchewan, Quebec, and Northwest Territories show negative impacts. Other factors, such as education, gender, age, immigrant status, language, origin of the immigrant's country, frequency of political discussions at home, and attitudes towards immigrants, do not have a significant impact when considered alongside other variables. This study highlights the multidimensional nature of voter turnout, emphasizing the interplay of demographic, social, economic, and political factors. iv Lay Summary In modern democracies, it is important to understand what influences people to vote to ensure everyone is represented. According to Statistics Canada, 23% of Canada's population are immigrants, and over 26.5% are from racialized groups. This thesis looks at how race affects voting behavior, especially in the 2021 Canadian Federal Election. By using several models to analyze data, the study found that racialized minorities initially seemed less likely to vote than White individuals. However, when other factors like political interest, partisanship, and economic status were included, race became less important. This research shows that voting behavior is influenced by a complex interplay of demographic, social, economic, and political factors, highlighting the need to consider all of them to fully understand why people vote. v Preface This thesis, titled “Voting Behaviour and Racial Identity: Exploring the Relationship Between Ethnic Identity and Its Impact on Voter Turnout in the 2021 Canadian Federal Elections,” provides a comprehensive examination of the variations in voter turnout influenced by race, socio-demographic factors, and political and psychological factors. It identifies the most significant variables affecting voter turnout positively and negatively in the 2021 Canadian Federal Election, based on the Canadian Election Survey 2021 dataset. The research and writing of this thesis were primarily undertaken by me, with invaluable guidance and continuous support from my supervisor, Dr. Maxime Heroux-Legault. I was responsible for designing the research, contributing to nearly all aspects of the study, conducting the analysis, and preparing the manuscript. Professor Dr. Maxime offered crucial insights, valuable feedback, and thorough reviews that greatly improved the quality of this thesis. Generative artificial intelligence (AI) was not used in any part of this thesis. Specifically, no AI tools were employed in the research process, data analysis, drafting, or preparation of this work. All content presented here is the result of traditional research methods and personal effort. The data was analyzed using STATA. vi Table of Contents Abstract .......................................................................................................................................... iii Lay Summary ................................................................................................................................. iv Preface............................................................................................................................................. v Table of Contents ........................................................................................................................... vi List of Tables ................................................................................................................................. ix List of Figures ................................................................................................................................ xi Acknowledgments......................................................................................................................... xii Dedication .................................................................................................................................... xiii 1. Introduction ............................................................................................................................. 1 2. Literature Review.................................................................................................................... 7 2.1. Introduction ..................................................................................................................... 7 2.2. Race and Electoral Participation ..................................................................................... 7 2.3. Educational Attainment and Its Influence on Voting Patterns...................................... 12 2.4. Age Dynamics in Voter Turnout................................................................................... 15 2.5. Immigrant Voter Turnout .............................................................................................. 17 2.6. The Role of Language in Voter turnout ........................................................................ 20 2.7. The Impact of Political Knowledge on Voting Likelihood .......................................... 23 2.8. Civic Awareness and Voter Participation ..................................................................... 25 2.9. Income-Level Correlations with Voter Turnout ........................................................... 28 2.10. Employment Status as a Predictor of Voting Behavior ................................................ 30 2.11. Covid impact on Electoral Turnout Dynamics ............................................................. 33 2.13. Conclusion .................................................................................................................... 37 3. Theoretical Framework ......................................................................................................... 39 3.1. Introduction ................................................................................................................... 39 3.2. Social Identity Theory................................................................................................... 39 3.3. The Resource Model ..................................................................................................... 40 3.4. Straight Line Assimilation Theory................................................................................ 41 3.5. Conclusion .................................................................................................................... 43 4. Data, Research Design, Hypotheses, and Methodology ....................................................... 44 4.1. Data ............................................................................................................................... 44 4.2. Variables ....................................................................................................................... 45 vii 4.3. Main Hypothesis ........................................................................................................... 52 4.4. Related Hypotheses ....................................................................................................... 52 4.5. Methodology ................................................................................................................. 53 4.6. Conclusion .................................................................................................................... 55 5. Result Analysis ..................................................................................................................... 56 5.1. The Bivariate Model ..................................................................................................... 56 5.1.1. Predicted Probability of Turnout by Race for Bivariate Model ................................ 58 5.2. Socio-demographic Model ............................................................................................ 59 5.2.1. Predicted Probability of Turnout by Race for Socio-demographic Model ............... 61 5.2.2. Other Controlling Variables in Socio-demographic Model ...................................... 63 5.3. Complete Model............................................................................................................ 67 5.3.1. Predicted Probability of Turnout by Race for Complete Model: .............................. 70 5.3.2. Other Controlling Variables:..................................................................................... 71 5.4. Conclusion .................................................................................................................... 82 6. Discussion of Hypotheses ..................................................................................................... 84 6.1. Main Hypothesis 1: Race ............................................................................................. 84 6.2. Related Hypothesis 2: Socio-demographic and Behavioral Factors ............................. 85 6.3. Hypothesis 3: Education ............................................................................................... 86 6.4. Hypothesis 4: Age ......................................................................................................... 87 6.5. Hypothesis 5: Immigrant Status .................................................................................... 88 6.6. Hypothesis 6: Language ................................................................................................ 90 6.7. Hypothesis 7: Political Knowledge ............................................................................... 90 6.8. Hypothesis 8: Sense of Civic Responsibility ................................................................ 91 6.9. Hypothesis 9: Partisanship ............................................................................................ 92 6.10. Hypothesis 10: Political Interest ................................................................................... 93 6.11. Hypothesis 11: Income Level ....................................................................................... 94 6.12. Hypothesis 12: Employment ......................................................................................... 95 6.13. Hypothesis 13: Covid-19 .............................................................................................. 95 6.14. Conclusion .................................................................................................................... 96 7. Conclusion: ........................................................................................................................... 98 Bibliography ............................................................................................................................... 104 Appendices .................................................................................................................................. 119 Appendix A: Frequency Table and Summary Statistics ......................................................... 119 viii Appendix B: Impact of Gender with Immigrant Background and Race on Turnout.............. 130 Appendix C: Frequency Table and Summary Statistics: South Asian Voter turnout 2015 and 2019......................................................................................................................................... 133 Appendix D: Regression model results including Indigenous as a separate variable ............. 134 ix List of Tables Table 1: Cross tabulation between Turnout and Race .................................................................. 56 Table 2: Bivariate Regression Model Result ................................................................................ 57 Table 3: Socio-demographic Regression Model Results .............................................................. 63 Table 4 Changes of impact of racialized minorities while adding controlling variables in Socio-demographic model ....................................................................................................................... 64 Table 5: Changes of impact of racialized minorities while adding controlling variables in Complete model ............................................................................................................................ 72 Table 6: Complete Regression Model Results .............................................................................. 78 Table A1: Frequency Table and Summary Statistics: Turnout..…………………………..……119 Table A2: Frequency Table and Summary Statistics: Race........................................................ 119 Table A3: Frequency Table and Summary Statistics: Education ............................................... 120 Table A4: Frequency Table and Summary Statistics: Gender .................................................... 120 Table A5: Frequency Table and Summary Statistics: Region .................................................... 121 Table A6: Frequency Table and Summary Statistics: Age ......................................................... 122 Table A7: Frequency Table and Summary Statistics: Religion .................................................. 123 Table A8: Frequency Table and Summary Statistics: Immigrant Status .................................... 124 Table A9: Frequency Table and Summary Statistics: Allophone ............................................... 124 Table A10: Frequency Table and Summary Statistics: Income category ................................... 124 Table A11: Frequency Table and Summary Statistics: Political Knowledge ............................. 125 Table A12: Frequency Table and Summary Statistics: Discussion frequency about politics at home ............................................................................................................................................ 125 Table A13: Frequency Table and Summary Statistics: Voting is a duty .................................... 125 Table A14: Frequency Table and Summary Statistics: Partisanship .......................................... 126 Table A15: Frequency Table and Summary Statistics: Political Interest ................................... 126 Table A16: Frequency Table and Summary Statistics: Origin from non-democratic countries . 126 Table A17: Frequency Table and Summary Statistics: Employment ......................................... 127 Table A18: Frequency Table and Summary Statistics: Satisfaction with COVID-19 handling . 127 Table A19: Frequency Table and Summary Statistics: Views on COVID-19 public health measures against Liberty (Covid Views) .................................................................................... 127 x Table A20: Frequency Table and Summary Statistics: Duration of residence in the current city..................................................................................................................................................... 128 Table A21: Frequency Table and Summary Statistics: Do you think Canada should admit … immigrants .................................................................................................................................. 128 Table A22: Frequency Table and Summary Statistics: Feelings towards Immigrants 0-100 ..... 129 Table B1: Impact of Gender with Immigrant Background on Turnout………………………...130 Table B2: Impact of Gender with Race on Turnout……………………………………………130 Table B3: Regression model with two variables interacting gender with race and immigrant...131 Table C1: Frequency Table and Summary Statistics: South Asian Voter turnout 2015……….133 Table C2: Frequency Table and Summary Statistics: South Asian Voter turnout 2019…...…..133 Table D1: Regression model results including Indigenous as a separate variable…………......134 Table D2: Socio-demographic model result including Indigenous as a separate variable……..134 Table D3: Complete model result including Indigenous as a separate variable …...……...…...135 xi List of Figures Figure 1: Effect or Race on Turnout (Bivariate Model) ............................................................... 58 Figure 2: Predicted Probability of Turnout by Race for Bivariate Model .................................... 59 Figure 3: Effect of Race on Turnout (Socio-demographic Model)............................................... 60 Figure 4: Predicted Probability of Turnout by Race for Socio-Demographic Model................... 62 Figure 5: Effect of Race on Turnout (Complete Model) .............................................................. 69 Figure 6: Predicted Probability of Turnout by Race for Complete Model ................................... 70 xii Acknowledgments I would like to express my deepest gratitude to my supervisor, Dr. Maxime Heroux-Legault, for his invaluable guidance, support, and patience throughout the duration of this research. His expertise and encouragement have been instrumental in the completion of this thesis. I am also grateful to my committee members, Dr. Helen Yanacopulos, Dr. Carey Doberstein, and Dr. Min Hu, for their valuable feedback and suggestions, which have greatly improved this thesis. I would like to thank Dr. Geoffrey Sigalet for his valuable motivation and support during the final and most challenging stage of completing my thesis draft. I extend my heartfelt gratitude to my family, especially my wife, Umme Ayesha, for her unwavering mental and emotional support. A special thanks goes to my friends, Saifullah Mahfuz and Manish Kumar, for their motivation and guidance during this journey. Their support helped me stay focused and complete this work. xiii Dedication I dedicate this thesis to the martyrs of the Anti-discrimination Students Movement 2024 in Bangladesh, who sacrificed their lives to restore democracy and the rule of law in our country. I also dedicate this work to my parents and siblings, whose unwavering support has helped me reach this stage of my life. 1 1. Introduction In modern democracies, knowing what influences voter turnout is essential to encourage active civic engagement and ensure that diverse groups are represented. This thesis delves into the complex relationship between racial identity and voting behavior with a particular focus on the 2021 Canadian Federal Election. The significance of this study is underscored by the evolving demographic makeup of Canada, marked by increasing racial and ethnic diversity. Nearly 23% of Canada's population are immigrants, according to Statistics Canada (2022). Additionally, over 26.5% of the population is comprised of racialized groups, as reported by Statistics Canada (2023). This demographic shift necessitates a thorough examination of how these changes impact electoral participation and the overall democratic process. With the significant increase in immigration to Canada, addressing this issue has become more crucial than ever before. The growing diversity and influx of new residents heighten the relevance and urgency of this topic, making it imperative to understand and engage with it comprehensively. The primary objective of this thesis is to explore and interpret the relationship between racialized minority and voter turnout in the context of the 2021 Canadian Federal Election. By leveraging the comprehensive Canadian Electoral Studies (CES) dataset from 2021, this research aims to identify and analyze the factors that influence voting behavior among various racial groups. The study seeks to address several key questions: How does racialized identity influence voter turnout? What roles do socio-demographic factors like age, education, employment, income, and other contextual and behavioral factors play in mediating this relationship? How do theories like Social Identity Theory, the Resource Model, and Straight Line Assimilation Theory provide a framework for understanding these dynamics? The importance of studying race is gaining significance both in Canada and globally due to increasing public debates and awareness on the subject. Scholars such as Bilodeau et al. (2012), Thompson (2008), Gidengil et al. (2012), and O'Neill (2006) all noted that race has been insufficiently prioritized in political and social research. Recent attention on race-related research, along with access to extensive and rich datasets, has increased the focus on race and racialized minorities. Moreover, Reitz and Banerjee (2007), Tossutti (2005), Pikkov (2011), and Jedwab 2 (2006) have extensively studied race, focusing particularly on race and voting behavior. This study also uncovers new and unique insights into how race correlates with voting behavior, often influenced by other socio-demographic and behavioral characteristics. In this study I will be also discussing how political knowledge impacts on voter turnout. We find that political knowledge plays a crucial role in shaping democratic engagement and participation (Galston, 2001; Popkin and Dimock, 1999), significantly influencing voters' ability to make informed decisions. In the Canadian context, political knowledge not only affects voter turnout but also enhances citizens' understanding of public policies and their implications. Studies have consistently shown that well-informed individuals are more likely to engage in political discussions, participate in elections, and support democratic principles. This thesis examines the impact of political knowledge on Canadian voting behavior, revealing that higher levels of political knowledge lead to increased voter participation and a more robust democratic process. Findings suggest that educational initiatives aimed at improving political knowledge could bridge gaps in civic engagement and promote a more informed electorate, ultimately strengthening Canada's democratic framework. Civic awareness and a strong sense of civic duty are essential for fostering democratic engagement and participation, particularly within the Canadian context. Pammett and LeDuc (2003) define civic duty as the intrinsic value of participation for the health of the polity, while Blais (2000) emphasizes the moral obligation of voting as a norm. Riker and Ordeshook's (1968) revised voting calculus suggests that the intrinsic benefits of voting, such as fulfilling civic duty, can make voting rational despite the low probability of influencing the outcome. Bevelander and Pendakur (2009) highlight that in Canada, civic duty and awareness transcend ethnic and immigrant backgrounds, influenced by socio-demographic factors and community engagement. Research indicates that a strong sense of civic duty correlates with higher voter turnout, as demonstrated in the 2000 Federal Election (Pammett & LeDuc, 2003). Additionally, the decline in voter participation among younger demographics is linked to a reduced sense of civic responsibility (Blais et al., 2004; Blais & Rubenson, 2013). The 2021 Canadian Election underscored the importance of fostering civic awareness and duty, showing that these factors are crucial for enhancing voter participation. Findings from the analysis reveal a significant positive relationship between civic duty and voter turnout, with a coefficient indicating that individuals who view voting as a duty are substantially 3 more likely to participate in elections. This empirical evidence consistently underscores the motivational power of civic duty in driving electoral engagement, highlighting the need for initiatives that promote civic education and community involvement to strengthen Canada's democratic process. The COVID-19 pandemic has significantly impacted voter turnout and election management across Canada, highlighting the importance of government response in shaping electoral behaviors. Research by Erhan and Sıvış (2024) suggests that effective management of the pandemic, characterized by robust health policies and economic support, contributed positively to voter perceptions and outcomes in the 2021 Canadian Election. Prime Minister Justin Trudeau's government's handling of the crisis, marked by effective public health measures, appeared to bolster public approval and influence his re-election. The pandemic led to the implementation of new voting strategies, such as expanded mail-in and advance voting to address safety concerns, resulting in varied turnout rates across provinces. While most provinces saw a decrease in turnout, Nova Scotia experienced an increase, illustrating the complex dynamics between public health crises and voter participation (Harell and Stephenson, 2022). This study reveals that satisfaction with COVID-19 handling had a mixed impact on voter turnout; those dissatisfied with the government's response were more likely to vote, potentially driven by a desire for change, whereas those satisfied showed lower voter urgency. This underscores the multifaceted nature of voter behavior during the pandemic, emphasizing the significant role of civic awareness and governmental effectiveness in influencing electoral participation. Income levels play a crucial role in influencing voter turnout, particularly within the Canadian context. Higher income, closely linked to education, provides individuals with the necessary time and resources for civic engagement, enabling more informed participation and contributions to political causes (O'Neill, 2006). This study finds that stable financial status significantly enhances political involvement. The 2021 Canadian Election underscored this dynamic, with higher-income individuals showing a greater likelihood of voting. Immigrants and racialized minorities face economic integration challenges, such as lower entry earnings and barriers to credential recognition, which impact their voter turnout (Ruddick, 2003; Reitz & Banerjee, 2007). Studies highlight that racialized minorities and Indigenous populations generally report lower average incomes and higher poverty rates compared to their counterparts, leading to lower electoral 4 participation (Halli & Kazemipur, 2003; Silver et al., 2006). This thesis finds that higher income individuals are more likely to vote, indicating that economic stability is a key driver of political engagement. This relationship underscores the importance of addressing income disparities to enhance democratic participation in Canada. Moving forward, this study will be looking into how employment status significantly influences voter turnout, particularly within the Canadian context. Research shows that employed individuals are more likely to engage in political activities due to greater financial stability and access to social networks that encourage political participation (O'Neill, 2006; Uppal & LaRochelle-Côté, 2012). The 2021 Canadian Election highlighted this trend, with employed individuals showing a higher likelihood of voting compared to their unemployed counterparts. Additionally, systemic barriers such as racial discrimination in the job market further complicate this relationship, affecting different racial and ethnic groups disproportionately (Quillian et al., 2019; Oreopoulos, 2011). Studies reveal that racialized Canadians face higher unemployment rates and underemployment, impacting their voter turnout (Ng & Gagnon, 2020). Despite these challenges, the data show that employment status positively affects voter turnout, with employed individuals having a significantly higher probability of voting. This underscores the importance of economic stability and access to resources in facilitating political engagement. The findings emphasize the need to address systemic barriers and promote economic inclusivity to enhance democratic participation across all demographic groups in Canada. This thesis also focuses on the impact of various socio-demographic factors such as age, education, allophone status, and immigration on voter turnout in the 2021 Canadian Election. The findings indicate that these factors have a mixed or insignificant impact on voter turnout. Moreover, this study finds that political interest, partisanship, and certain religious and regional identities had a significant impact on voter turnout, highlighting the crucial role of political engagement and identity in electoral participation. Political interest emerged as one of the key predictors of voter turnout. Individuals with higher levels of political interest were significantly more likely to vote. A high level of interest in politics significantly boosts the likelihood of individuals participating in elections, as it fosters a deeper understanding of political issues, a sense of civic duty, and motivation to engage in the electoral process. In the 2021 Canadian Election, findings strongly support the idea that individuals with greater political interest were more likely to vote. This 5 underscores the critical influence of political engagement on electoral participation, highlighting that increased interest in politics is a key driver in motivating voters. Partisanship also serves as a critical factor that drives individuals to vote, reinforcing their sense of political efficacy and duty. Identifying with a political party often translates into a higher likelihood of voting, as party loyalty provides a sense of belonging and a psychological attachment that motivates individuals to participate in elections. In the 2021 Canadian Election, those who identified with a political party were significantly more likely to vote compared to non-identifiers. This suggests that party affiliation is a strong predictor of voter turnout, underscoring the importance of political party identification in mobilizing voters. This thesis indicates that party loyalty fosters a sense of duty and simplifies the voting decision, leading to increased electoral participation. This highlights the critical role of party identity in driving political engagement and shaping the democratic process in Canada. Furthermore, certain religious and regional identities were found to significantly impact voter turnout. For instance, individuals identifying with certain religious groups were more likely to vote, reflecting the influence of religious communities in mobilizing voters. Additionally, regional identities also affected voter turnout, with variations observed across different provinces. Regions with a stronger sense of community and local identity often saw higher voter turnout, indicating that regional belonging can enhance civic engagement. This thesis presents a novel contribution by revealing that in the 2021 Canadian Election, the influence of race on voter turnout is significantly diminished when considering a broader range of factors, including income, employment, political knowledge, partisanship, and COVID-19-related perceptions. The study uniquely demonstrates that higher income levels and stable employment are key predictors of voter participation, underscoring the importance of economic stability in fostering civic engagement. Furthermore, it highlights the critical role of political knowledge and a strong sense of civic duty in driving voter turnout, suggesting that these factors are more influential than race alone. Additionally, the research sheds light on the impact of public sentiment related to COVID-19, showing that dissatisfaction with pandemic handling and views on public health measures significantly affect electoral participation. By integrating these diverse factors, this thesis offers a comprehensive and nuanced understanding of the drivers of voter behavior in 6 Canada. It challenges traditional perspectives that view race as a primary determinant of electoral participation, demonstrating that its significance diminishes when considered alongside other social, economic, and political influences. This thesis is structured to provide a comprehensive analysis of voter turnout in the 2021 Canadian Election through the use of three distinct models. Initially, the bivariate model examines the direct relationship between race and voter turnout. Subsequently, the socio-demographic model incorporates additional variables such as age, education, gender, immigrant status, regional identities, income, and religious affiliations to understand their collective impact. Finally, the complete model integrates an extensive array of factors, including political interest, partisanship, civic engagement, political knowledge, employment status, income category, satisfaction with COVID-19 handling, views on COVID-19 public health measures, duration of residence in the current city, and origin from non-democratic countries, to capture the multifaceted nature of voter behavior. This structured approach allows for a detailed exploration of how various socio-demographic, behavioral, and political variables influence electoral participation. It also examines whether racial differences remain after the inclusion of other explanatory variables. The remainder of this thesis is organized into seven chapters to provide a comprehensive analysis of the factors influencing voter turnout in the 2021 Canadian Election. Chapter 2 offers a detailed review of the existing literature on voter turnout, focusing particularly on the impact of race and other socio-demographic, political, and behavioral factors. This section synthesizes past research findings to contextualize the current study. Chapter 3 discusses the relevant theories that explain the relationship between voter turnout and other variables. Chapter 4 provides a thorough description of the data and variables used in our analysis, explaining the sources of our data and the definitions and measurements of each variable. Chapter 5 presents and discusses our empirical findings, highlighting the results from the bivariate, socio-demographic, and complete models. This section interprets the statistical outputs and explores the findings. Chapter 6 of this thesis discusses the hypotheses and provides a comprehensive summary of the research findings. It explores each hypothesis in detail, examining the data and analysis that support or refute them. Chapter 7 concludes the thesis by summarizing the main insights, discussing the limitations of our study, and suggesting directions for future research. For readers interested in more detailed information about our variables, tables are provided in the appendix. 7 2. Literature Review 2.1. Introduction To understand why people vote, it is important to examine the wide range of factors that can influence their decisions. This literature review specifically explores how various factors such as race, education, age, immigrant status, language, political knowledge, sense of civic awareness, income, employment, COVID-19, and gender impact voting behavior. Canada, with its diverse population, provides an ideal context for studying these effects. This chapter synthesizes research on the influence of these factors on voting behavior, drawing from studies conducted in Canada and other democratic countries. By reviewing both past and current studies, it identifies gaps in the existing literature, particularly in understanding voter turnout in relation to these ethnic, social, and political factors. Highlighting these gaps sets the stage for the subsequent analysis of data from the 2021 Canadian Federal Election, offering a foundation for a more comprehensive understanding of voter participation in multicultural societies. 2.2. Race and Electoral Participation Canada is one of the most immigrant-friendly nations, welcoming people from various races. Immigrants constitute the primary driving force behind the increase in the population of racialized individuals in Canada (Reitz & Banerjee, 2007). According to Statistics Canada (2022), almost one-fourth (23%) of the total population are immigrants, and according to Statistics Canada (2023) more than one-fourth (26.5%) belong to racialized groups. Activist Kay Livingstone introduced the phrase “visible minority” in 1975 to describe racialized populations (Wharton-Zaretsky, 2000). Racialized minorities are widely known as visible minorities, which is defined by Statistics Canada as “persons, other than Indigenous peoples, who are non-Caucasian in race or non-white in colour.” The main groups designated as visible minorities are South Asian, Chinese, Black, Filipino, Arab, Latin American, Southeast Asian, West Asian, Korean and Japanese (Statistics Canada, 2022). Motivated by the Ontario Human Rights Commission’s (2005) policy and guidelines, we have chosen to use the term “racialized minority” rather than “visible minority.” It states, “when it is necessary to describe people collectively, the term “racialized person” or “racialized group” is preferred over "racial minority,” "visible minority," "person of colour" or “non-White” as it expresses race as a social construct rather than as a description based on perceived biological traits” 8 (p. 12). Although important distinctions exist, Indigenous people and other racialized groups were analyzed together in this study due to their shared experiences of racialization, marginalization from the dominant White majority, and underrepresentation in Canadian politics—all of which can affect political participation. Separate models for Indigenous respondents were also examined and are presented in the appendix, but they do not alter the study’s overall findings1. During the first and the beginning of the second decade of this century, scholars have observed that race has not been given as much attention as it should in the study of Canadian politics and policies. The relationship between race and voter turnout in the Canadian context is, for the same reasons, an under-researched topic. Bird et al. (2010) claim that minority and voter turnout research is not prominent in Canada. They highlight the historical lack of research on voter participation among immigrants and minorities in Canada, attributed to insufficient data. In the Canadian context, the recent availability of extensive datasets has allowed for a nuanced analysis of the impact of factors like nativity and ethnicity on voting patterns, although self-reported surveys reveal minimal differences between the voting behaviors of foreign-born and native-born Canadians. Bilodeau et al. (2012) also discover that racial considerations have not been significantly emphasized in the examination of political studies within Canada. Thompson (2008) highlights that despite the clear and vital role of race in research, it remains largely neglected in English Canadian political science due to methodological challenges and a focus on elite perspectives, contrasting with its acknowledgment in other social sciences. Gidengil et al. (2012) found race, as an increasingly significant aspect of Canada's multicultural landscape, has been given insufficient attention despite its growing importance. Racialized people has a relatively minor influence in shaping Canadian policy, reflecting its historically limited role within the political landscape of Canada (Banting, 2021). O'Neill also finds that research related to race, ethnic groups, and racialized minority is quite limited in Canada (O'Neill, 2006). However, in the context of Canada, certain studies have specifically examined the connection between race and voter turnout. It has been identified that recently immigrated racialized minorities are less likely to vote than the other minorities (Reitz & Banerjee, 2007). The same 1Additional models that account for Indigenous respondents separately are provided in a supplementary appendix (D1-D3) 9 study finds that overall turnout is lower for racialized minorities than White voters. Moreover, the voter turnout gap between the second-generation White and second-generation racialized minorities is about 20 percentage points (Reitz & Banerjee, 2007). Tossutti (2005) conducts research using data from the 2002 Ethnic Diversity Survey and reveals that irrespective of generational gap, racialized minorities have always a negative trend of voter turnout. Tossutti (2005) also finds that race continues to influence voting behavior, as evidenced by the lower turnout of young Chinese voters compared to their counterparts. This suggests that simple assimilation theories do not fully explain variations in voting participation among different racial groups. Assimilation theory, particularly in its classical or straight-line formulation, describes the process through which immigrants and their descendants integrate into the host society. This theory, as outlined by sociologists such as Warner and Srole (1945) and Park and Burgess (1969), suggests that successive generations achieve greater social mobility through improved occupational and educational opportunities. This advancement leads to a deeper engagement with and adoption of the cultural norms and values of the host society. Consequently, with each generation, the differences between immigrants and their descendants and the native-born population diminish, indicating a linear path towards full assimilation. Pikkov's (2011) study indicates that racial disparities among immigrants are evident and not just linked to the number of generations they have been in the country. This implies that being a White immigrant or a racialized minority immigrant affects their experiences differently, regardless of their family's history in the new country (Pikkov, 2011). Jedwab's analysis of the Ethnic Diversity Survey indicates a correlation between the importance of ethnic identity to Canadians and their likelihood of voting in the 2000 federal election, with a notably higher turnout among those who value their ethnic identity (Jedwab, 2006). Furthermore, Jedwab concludes that a sense of ethnic belonging does not adversely affect voting behavior, suggesting that the acknowledgment of ethnic identity may, in fact, coincide with higher electoral engagement. This claim emphasizes that holding a strong sense of ethnic identity does not negatively impact the likelihood of political involvement in Canada's diverse society. Another study reveals that ethnic identities do not have a significant impact on voter turnout (Bevelander & Pendakur, 2009). They find that there is no significant difference between ethnic minority and majority voters when socioeconomic and social capital attributes have been included in the study (p. 1420). A 1983 survey conducted in the Toronto area investigated electoral participation across 10 different immigrant demographics in Canada relative to Canadian-born citizens of British heritage. The study found that West Indian immigrants participated less in the latest federal and provincial elections than their British counterparts, a trend that remained consistent even after accounting for socio-economic factors, political beliefs, and levels of organizational involvement (Black, 2011). In another study focused on Canada, Black (1987) found that among the immigrant groups examined—British, West Indian, Southern European (specifically from Portugal, Italy, and Greece), and Eastern European (including various ethnicities such as Poles, Russians, Croatians, and Slovakians)—British immigrants demonstrated the highest level of political engagement. However, the study also highlights a significant capacity for political transferability across all these groups, indicating that immigrants, regardless of their origin, are able to translate their previous political experiences into effective participation in Canadian politics. This finding underscores the adaptability and resourcefulness of immigrants in engaging with the political processes of their new country, suggesting a broader potential for political integration and involvement among immigrant populations in Canada (Black, 1987). Studies on Indigenous voters find that, even after accounting for socio-demographic factors, the voter turnout for Indigenous voters in the Canadian Federal Election of 2000 remains consistently lower than that of the overall Canadian electorate (Guérin, 2003; Howe & Bedford, 2009). Stewart finds that racialized minority and non-white voters and renters tend to have less political knowledge. This often results in them being less likely to vote (Stewart, 2008). Fournier and Loewen (2011) examined the electoral participation of Indigenous Canadians, highlighting a significant turnout gap compared to their non-Indigenous counterparts—a concern given the importance of voting as a principal act of citizenship. The study reveals that the factors influencing Indigenous voters’ decision to vote are similar to those of other voters, including civic duty, political resources, registration status, and socio-economic indicators such as education and income. Contrary to earlier studies, this research identified living on a reserve as a negative factor affecting participation (Fournier & Loewen, 2011). There is extensive literature on the influence of race on U.S. and European voter turnout. Studies have found that in the U.S. minorities are significantly less likely to participate in elections compared to native-born majority populations, with variations in voting behavior observed across different ethnic groups (Ramakrishnan & Espenshade, 2001). Their study evaluates the impact of immigrant generational status on voting participation in U.S. elections, revealing that political 11 incorporation varies significantly among different racial/ethnic groups, thereby challenging straight-line assimilation theories. It demonstrates that voting participation patterns differ, with linear increases observed among Black across generations, a peak at the second generation for Whites, and fluctuating trends for Asian-Americans and Latinos, indicating segmented assimilation. The study also finds that factors such as anti-immigrant legislation, rather than prior political experience or linguistic barriers, significantly influence voting participation among first and second-generation immigrants. In the European context, a similar finding indicates that voter turnout and political participation vary based on ethnic identity (Messina, 2006). Wolfinger and Rosenstone (1980) find that lower voting level among Mexican American and African American can be attributed to factors like lower educational attainment. A study on the 2018 U.S. midterm election finds that voters who identify themselves as a part of majority White group are more likely to vote than those who identify with various minority group (Qi & Gonzalez, 2022). They also find that individuals with immigrant parents are less likely to vote than those with immigrant grandparents. Moreover, research on ethnic minorities in Denmark indicates that an individual's ties to their minority community influence their voting behavior, with this impact varying across different ethnic groups (Togeby, 2004). This suggests that the strength and nature of ethnic affiliations are important variables in understanding voter turnout within diverse communities. Maxwell's (2010) analysis of French voting data shows that racialized minorities, specifically Maghrebin-French, have lower voter turnout rates than native metropolitans, with significant differences observed in specific elections (Maxwell, 2010). However, after adjusting for demographic factors like age, education, and employment, ethnic origin does not significantly affect voting likelihood, indicating that ethnicity is not a determining factor in voting behavior in France (Bird et al., 2010). Xu finds that in the U.S., racial disparities in political participation persist among Asian Americans, Whites, and other races, mainly visible in the registration process (Xu, 2005). Another study suggests that voter turnout is influenced by the racial and ethnic composition of electoral districts, with increases observed among African Americans, Whites, and Asians in districts with co-ethnic incumbents, whereas Latino turnout decreases in majority-Latino districts after redistricting (Fraga, 2016). The literature on race and electoral participation highlights the intricate and multidimensional nature of this relationship within the Canadian context and beyond. Despite Canada's reputation 12 as an immigrant-friendly nation, there is a notable underrepresentation of racialized minorities in political research, with significant gaps in voter turnout among these groups. Recent studies reveal that racialized minorities, particularly newly immigrated individuals, are less likely to vote compared to their White counterparts. This trend persists across generations, challenging the assumptions of classical assimilation theories. Factors such as ethnic identity, socio-economic status, and generational differences play crucial roles in shaping voter turnout, with varied impacts observed across different racial and ethnic groups. Comparative analyses with the U.S. and European contexts further highlight the persistent disparities in electoral participation among racialized minorities, influenced by a myriad of socio-political factors. Overall, the literature emphasizes the need for more inclusive and comprehensive research to understand and address the barriers to electoral participation among racialized minorities, thereby fostering a more equitable and representative political landscape. 2.3. Educational Attainment and Its Influence on Voting Patterns Academic studies widely recognize that an individual's likelihood of voting increases with higher educational attainment (Bevelander & Pendakur 2009, DeSipio 1996, Tuckel and Maisel 994, Cho 1999, Verba & Nie 1972, Southwell & Everest 1998, Stewart et al., 2008, Wolfinger & Rosenstone 1980, and Blais 2000). Galston stated, “it is reasonably clear that good citizens are made, not born” (Galston, 2001, p. 217). Education serves as a key instrument in shaping an individual into a responsible citizen. Wolfinger and Rosenstone (1980) find that among different socioeconomic variables, education is the most influential in affecting voter engagement, effectively diminishing the relevance of income and social class with its inclusion. Cho (1999) argues that it is not merely education that shapes one's political actions, but the political socialization acquired through education that enhances the chances of registering and voting (Cho, 1999). Xu (2005) finds that being older, wealthier, more educated, married, and a homeowner positively influences registration and voting. Silver (2005) found that increasing post-secondary education among Indigenous people in Winnipeg is linked to a potential rise in their participation in mainstream elections, reflecting a significant positive correlation between education levels and voting likelihood (p. 35). The research conducted by Harrison and Krahn (2014) unveils a consistent pattern across multiple regions, including Alberta, where a lower educational attainment is significantly correlated with a 13 reduced likelihood of participating in electoral processes. This phenomenon suggests that educational level is a pivotal factor influencing an individual's propensity to engage in voting activities (Harrison & Krahn, 2014). O'Neill (2006) argues that distributing human capital more evenly through education, especially at secondary and post-secondary levels, directly helps citizens navigate political complexities and boosts their confidence to participate actively in civic activities, including voting (O'Neill, 2006). The 2000 Canadian Election Study reveals that, although the influence of education on overall voter turnout is limited, it substantially boosts participation among younger voters, especially those with university degrees, in stark contrast to the marked decline in turnout among the least educated (Blais et al., 2002). Research by Wesley and Summerlee (2012) in Manitoba indicates that constituencies with higher average household incomes and higher educational attainment levels experience greater voter turnout, while those with lower incomes and educational levels have reduced participation rates. Moreover, Dawson et al. (1990) have identified significant impacts of education and income on the participation rates of Black voters in America. Bird et al. (2010) have found that while immigrants/minorities in Norway generally show lower voter turnout, education positively influences their participation rates. Adjusting for education, along with age and income, to align with the general electorate's composition, demonstrates that higher education levels are associated with increased voter turnout among these groups (Bird et al. 2010, p. 45). They also find that the intention to vote among naturalized immigrants and non-nationals in Austria shows a clear link to education, with those having higher educational levels more inclined to participate in elections. A slight gender difference was observed, but the educational gap emerged as a more significant factor influencing voting intentions (p. 52). Though political science research often highlights a strong association between higher socio-economic status and educational levels with increased voter turnout, the surprisingly low engagement in voting by the generally well-educated and skilled Chinese and Korean immigrant population in New Zealand, Australia, and Canada challenges the application of traditional theories of electoral participation (Barker & McMillan, 2017). Furthermore, Xu (2005) finds racial identities and their social roles influence how minorities leverage education for political involvement and awareness, affecting their political behavior. The same study also suggests that the educational outcomes for Asian Americans and other minorities differ from those for Whites (Xu, 2005). Xu discovered that at lower educational levels, minorities 14 are more likely to vote than Whites. Yet, with an increase in education, the participation of Whites swiftly overtakes that of Asians and Hispanics, aligning closely with the voting rates of Black (Xu, 2005). Dassonneville and Hooghe (2017) reveal that education did not significantly influence voter turnout in the 1967 and 1971 elections in Netherlands. However, the abolition of compulsory voting led to a pronounced decrease in electoral participation, especially among the least educated, thereby creating an educational gap in voting rates. Gallego (2009) finds a positive effect of education on voting in Sweden and Norway, with a stable influence over time in Norway, but an increasing gap in voting probability between lower and higher educated citizens in Sweden (Gallego, 2009). Xu (2002) finds that educational attainment, together with immigration background, is believed to impact the political engagement and effectiveness of Asian Americans. Same research suggests that better educational levels could contribute to greater political involvement, but this is evaluated amidst a variety of other elements such as demographic characteristics, social network influences, and contextual challenges (Xu, 2002). Jones-Correa (2005) finds that among immigrant and various ethnic minority voters, education predicts higher voter turnout. On the contrary, Togeby's (2004) analysis indicates that for immigrants in Denmark, specifically ex-Yugoslavs, Pakistanis, and Turks, there is no significant relationship between their level of education and voter turnout (p. 522). Lien (1994) concludes that for Asian citizens, higher education does not significantly impact voting participation, whereas for Mexican-origin citizens, increased educational levels significantly boost their likelihood of voting (Lien, 1994). The literature robustly establishes that educational attainment is a critical determinant of voter turnout, consistently showing that individuals with higher education levels are more likely to participate in electoral processes. Education not only equips individuals with the knowledge and skills necessary for informed voting but also fosters a sense of civic duty and engagement. Studies across various contexts—ranging from Canada to the United States and including diverse immigrant populations—demonstrate that higher educational levels correlate strongly with increased voter turnout. However, this relationship is not uniformly observed in all demographics; for instance, certain immigrant groups may not follow this pattern due to varying socio-political contexts and cultural factors. The overall consensus highlights education as a vital component in 15 promoting political participation, suggesting that enhancing educational opportunities can be a powerful tool in increasing voter engagement and strengthening democratic processes. 2.4. Age Dynamics in Voter Turnout It is widely recognized that the likelihood of voting grows as individuals age (Blais 2006 & 2000, Wolfinger & Rosenstone 1980, Whiteley 2009, Southwell & Everest 1998, and Rosenstone & Hansen 1993). Bevelander and Pendakur (2009) find that age, level of schooling, and level of civic engagement affect Canadian voter turnout, both in federal and provincial elections. Nevitte et al. (2000) observe that voter turnout has a strong association with four key factors: a person's age, level of education, frequency of religious services attendance, and their income level. White et al. (2006) reveal a strong relation between the age and the political interest of immigrants in Canadian federal elections from 1997 to 2004. Their study reveals that age significantly influences political interest among immigrants in Canada, showing a positive correlation where interest in politics increases with age, regardless of immigrants' country of origin. However, the impact of age on partisan attachments and voter turnout is nuanced, with age having a positive effect on the strength of partisan attachments among immigrants from advanced industrial countries but not significantly affecting voter turnout for either group of immigrants (White et al., 2008). Godbout and Turgeon (2012) have pointed out that the likelihood of voting increases among individuals who are older, have higher levels of education, and possess greater wealth, while those who do not vote are typically from the lower socio-economic segments of society (Godbout & Turgeon, 2019). Black et al. (1987) identify a notable link between immigrant’s age and political participation within a host country, maintaining its significance even when factors such as the length of residency, country of origin, and initial political involvement in the country of origin are accounted for. Andre Blais’s (2000) research indicates that education and age are significant predictors of voting behavior, with a notable 20-point difference in voter turnout observed when comparing the most and least educated, as well as the oldest and youngest voters. This suggests that these two socio-economic factors have a substantial influence on the likelihood of an individual participating in elections (Blais 2000, p. 52). Silver (2005) indicates that as Indigenous individuals age, their likelihood of participating in voting increases. White et al. (2006) finds that estimated difference in voting rates between a 20-year-old immigrant Canadian and a 50-year-old is almost 40% when 16 no other factors change. For Canadians born in the country, the difference between these ages is under 20%. This suggests that the common pattern of older Canadians being more likely to vote is even stronger for immigrants. Howe and Bedford (2009) find that in the Indigenous demographic, individuals aged 50 and above show a voting turnout rate close to 80%. This rate declines among the younger population, with less than half of those younger than 30 turning out to vote. This reflects a broader trend seen across all populations, where voter turnout decreases progressively with each younger age group, from a high of around 90% among the oldest to slightly above 55% in the youngest category (p. 17). While voter turnout fluctuates with age, the gap in participation rates between Indigenous Canadians and the rest of the Canadian population is substantial, with Indigenous turnout consistently lower across all age groups (Howe & Bedford, 2009). Another study indicates that demographic profiles of non-voters in Alberta are comparable to those in other regions, characterized by being younger, less educated, and more likely to be renters (Harrison & Krahn, 2014). In discussing the life cycle effect on political participation, O'Neill (2006) identifies age as a significant predictor of political engagement, often exerting a stronger influence than even education. This highlights the tendency for political activity to increase with age, suggesting a maturation effect on participation rates. Ramakrishnan and Espenshade (2001) demonstrate that across different immigrant generations in the U.S., age consistently exerts a positive influence on voter turnout. Their research further indicates that immigrants aged between 70 and 79 years exhibit the highest levels of electoral participation (Ramakrishnan and Espenshade, 2001). In the same context Plutzer (2002) finds the trend where voter turnout tends to rise as people get older (Plutzer 2002, p. 48). Milbrath (1965) describes how voter turnout significantly increases as individuals move from youth into young adulthood. This increase then continues, albeit more slowly, as voters age, typically reaching a peak when they are in their sixties. Potochnick and Stegmaier (2020) find that age significantly influences Latino political engagement, with a notable portion of the U.S. Latino population being under 18. The difference in political participation rates across age groups suggests that the lower political involvement of the second-generation Latinos is largely due to the younger adults within this demographic. Qi and Gonzalez (2022) have observed in their study on political participation in the U.S. that as voters age, their likelihood to vote increases, a trend that is consistent among all 17 racial categories. This suggests that older individuals are generally more engaged in voting, regardless of their race or ethnic background (Qi & Gonzalez 2022, p. 236). Desipio (1996) finds that among Latino immigrants in the U.S., older age groups were more likely to register and vote (p. 206). Jones-Correa (2005) reveals that age consistently has a positive impact on voter turnout among immigrants and racialized minorities. The literature consistently shows a strong positive correlation between age and voter turnout across various demographics and regions. As individuals age, their likelihood of voting increases, a trend that holds true across different socio-economic groups and immigrant statuses. Studies indicate that older individuals are more likely to vote due to higher levels of political interest, education, and socio-economic status. This trend is particularly pronounced among immigrants, with older immigrants showing significantly higher voting rates compared to their younger counterparts. The influence of age on voter turnout is also evident among Indigenous populations and various racial and ethnic groups, underscoring the maturation effect on political participation. These findings highlight the critical role of age in shaping electoral engagement, suggesting that strategies to increase voter turnout should consider the unique challenges and opportunities associated with different age groups. 2.5. Immigrant Voter Turnout During the first decade of this century, many scholars argued that immigrants received limited attention in Canadian Political Studies (O'Neill, 2006; Thompson, 2008; Gidengil et al. 2012, and Bilodeau et al., 2012). During the 1960s and 1970s, scholars generally did not consider the study of immigrants and minorities to be of political relevance (Abu-Laban, 2002). Evidence from historical to current studies shows that the level of political engagement, such as voter turnout among immigrants, presents a varied and often conflicting picture. Black (1982) pioneered the immigrant research in Canadian context with his 1982’s comparative study on the immigrant and native-born Canadian voters. Black's research indicated that the political engagement of immigrants, as measured by voting campaigns, community activities, and interactions with politicians, aligns closely with that of native-born Canadian citizens (Black, 1982). His study also showed that immigrants from both democratic and non-democratic backgrounds do not exhibit significant differences in political participation, just as there is no notable difference in 18 partisanship and political engagement between immigrant and native Canadian citizens (Black, 1982). Although the same author found that an immigrant's origin influences their current political activities, and they can adapt their previous political experiences to the Canadian context, this adaptability is similar to that of Canadian-born voters (Black, 1987). Moreover, Black (2011) conducted a comparative study of immigrant and minority political incorporation between Canadian and American politics, demonstrating that Canadian politics incorporates immigrants almost as much as native-born citizens. He analyzed the 2004 Canadian National Election, showing that 85% of the foreign-born voters voted in that election, where the turnout for native-born voters was 87%, which is quite similar (Black, 2011, p. 1166). Chui et al. (1991) analyzed the 1984 Canadian Election Survey, focusing on seven electoral participation attributes, including voting, through Multiple Classification Analysis. They discovered that although immigrant participation was lower, their descendants either matched or exceeded the participation rates of long-established Canadians. Furthermore, in terms of campaign involvement, political membership, and interest in elections, they found no significant differences between immigrant and Canadian-born respondents (Chui, Curtis, & Lambert, 1991). Wiseman classified the Canadian immigrant influx into five categories (Wiseman, 2007, 2008, 2014). The fifth wave includes immigrants from diverse ethnicities and races, including people from Asia, Southern Europe, the Caribbean, and Latin America. His study suggests that despite the substantial size of the fifth wave of immigration, its influence on political culture remains minimal (p. 34). However, Thompson (2008) presents a contradictory finding to Wiseman and argues that racialized immigrants have an impact on Canadian politics. Though Ramakrishnan and Espenshade (2001) argue against straight-line assimilation theory, Reitz and Banerjee (2007) indicates that the lower voting rates among immigrant and racialized minorities can be attributed to their relatively recent arrival. Initially, there is no voting disparity between newly arrived racialized minorities and European-origin immigrants. However, as they examine earlier cohorts of racialized minority immigrants, their voting rates lag behind those of White populations, which is unexpected given their higher citizenship eligibility (Reitz and Banerjee, 2007). The most pronounced racial disparities in voting emerge among the second-generation immigrant, with a significant gap between White individuals and various racialized minority groups. This gap highlights a broader issue of political engagement across generations within immigrant and 19 racialized minority communities (Reitz and Banerjee, 2007). White et al. (2006) find no evidence supporting the idea that immigrants from non-democratic countries are less inclined to vote than those from advanced industrial nations. Using data from 1997 to 2019, Taylor analyzes the Canadian political parties in relation to their policy formulation and immigration policies in order to attract immigrants and win their votes (Taylor, 2021). According to him, none of the major political parties in Canada have anti-immigrant policies. His study also suggests that immigrant voters have a significant presence in metropolitan areas of Canada where multiculturalism predominates. Additionally, he states that the Greater Toronto and Hamilton Area (GTHA) has increased in electoral importance due to the influx of immigrants. For political parties, these geographic and demographic characteristics are essential to developing their electoral and party policy (Taylor, 2021). Ramakrishnan and Espenshade (2001) expanded the model of immigrant voting behavior to include factors such as generational status, English language proficiency, duration of residency in the U.S., ethnic residential density, and political socialization in their home country. Their findings indicate that voting participation varies across different ethnic groups. While a prolonged stay in the U.S. generally increases voting likelihood for most groups, this does not hold true for Black and Asian-American immigrants (Ramakrishnan and Espenshade, 2001). The impact of originating from a repressive regime is slightly negative on voting participation. Interestingly, language proficiency and proximity to co-ethnics, despite expectations, do not significantly influence voting probabilities. However, they observed that the political culture within a state plays a role in shaping voting behavior (Ramakrishnan and Espenshade, 2001). Tuckel and Maisel (1995) have found that, contrary to the other findings, under various conditions, naturalized immigrants in the U.S. were more active in using their voting rights compared to the native-born population (Tuckel & Maisel, 1994). Their finding suggests that there is no direct link between immigration and the decline in voter participation (pp. 413-414). Bevelander and Hutcheson (2022) find that, regarding Sweden, immigrants born in the country show a greater tendency to vote than those immigrants who were born abroad (Bevelander & Hutcheson, 2022). Togeby (1999) notes that in Sweden, substantial immigrant clusters have led to widespread demobilization, which in turn has markedly decreased voter turnout within these communities (Togeby, 1999). Xu (2005) reveals that naturalized citizens in the U.S. are generally less likely to 20 register to vote than natives, but the likelihood increases with their duration of stay in the host country. No clear trends emerge for voter turnout based on immigration status, showing similar voting rates between immigrants and natives post-registration. This dynamic particularly affects Asian Americans' registration but not their turnout (Xu, 2005). The exploration of immigrant voter turnout in Canada, the U.S. and other European countries reveals a nuanced and evolving landscape. While early scholarship often overlooked the political relevance of immigrant communities, subsequent research has illuminated the varied and complex patterns of political engagement among immigrants. Early studies, such as those by Black (1982, 1987), indicate that immigrants' political participation is comparable to that of native-born Canadians, suggesting a significant capacity for political adaptation. However, more recent analyses present a mixed picture: while some findings highlight substantial political incorporation and engagement among immigrants, others point to persistent disparities, particularly among racialized immigrant groups. Factors such as generational status, duration of residency, and socio-economic conditions significantly influence voter turnout. Moreover, the political landscape, characterized by multiculturalism and the strategic importance of immigrant-dense regions, underscores the critical role of immigrants in shaping electoral outcomes. Overall, the literature underscores the importance of understanding the diverse experiences of immigrant communities to foster more inclusive political participation and representation. 2.6. The Role of Language in Voter turnout In 2021, statistics revealed that a significant portion of the Canadian population is linguistically diverse, with 25% reporting a mother tongue other than English or French. Additionally, 12.5% of Canadians predominantly spoke a language other than English or French in their homes, setting a new record for linguistic diversity in the country (Statistics Canada, 2022). The same survey finds that between 2016 and 2021, there was a notable rise in the number of Canadians primarily using South Asian languages, such as Gujarati, Punjabi, Hindi, or Malayalam, at home. In 2021, aside from English and French, Mandarin and Punjabi emerged as Canada's most widely spoken languages, with over half a million Canadians predominantly using each language at home (Statistics Canada, 2022). This significant increase was largely driven by immigration. Indeed, the expansion of the population speaking these languages surpassed the growth rate of the overall 21 Canadian population by at least eightfold during the same timeframe. Immigrants from non-democratic countries and racialized minorities in the first-generation, who arrive in Canada with English as their second language, face challenges due to the dominant roles of French and English in all aspects of life. Weinstein (1983) emphasizes that language is closely linked to forms of political participation, suggesting that the way language is used and regulated within a society can significantly influence who gets to participate in political processes and how (Weinstein, 1983). Wolfinger and Rosenstone (1980) found that language barriers, particularly for racialized minorities like Hispanics in the U.S., affect their educational achievements, which in turn leads to lower voter turnout (Wolfinger & Rosenstone, 1980). Qi and Gonzalez (2022) contend that language barriers pose significant obstacles for non-white immigrants, rendering them less likely to participate in elections. McLaughlin (2015) highlights the profound effect that government policies on language have on democratic engagement, especially in terms of voter turnout, stressing that voter participation is boosted when the home languages of citizens are incorporated into official language policies. The language used in electoral campaigns significantly influences voter participation among racialized minorities and immigrants and this impact is reflected in the voter turnout rates (Abrajano & Panagopoulos 2011; Barreto 2005). Parkin and Zlotnick (2011) find that English proficiency significantly impacts Latino voter registration and turnout in the U.S., with higher fluency leading to greater political participation. While larger Latino communities boost overall registration, bilingual ballots specifically help non-English-speaking Latinos, particularly in areas with fewer Spanish speakers (Parkin & Zlotnick, 2011). All these literatures consistently indicates that language fluency significantly influences voter turnout, particularly among racialized minority and immigrant communities. Moreover, in the U.S. the provisions under Section 203 of the Voting Rights Act (VRA), which mandate language assistance for voters from linguistic minorities, have shown a significant positive effect on Latino voter turnout (Jones‐Correa, 2005). However, the same study finds that the impact of VRA on Asian-American communities is more nuanced, with variations in voter turnout among different Asian national-origin groups and a lack of significant boost in turnout for some groups. This suggests that while language assistance provisions can enhance electoral participation for some linguistic minorities, their effectiveness varies across different ethnic and 22 immigrant populations. Ramakrishnan and Espenshade (2001) find that the likelihood of voting was not significantly impacted by language fluency, as determined by the availability of ballots in Spanish and the presence of similar ethnic groups within the state. Lago et al. (2018) conclude from their study of aggregated data across 22 countries that ethnic and, particularly, linguistic diversity negatively impacts voter turnout. Anderson and Stephenson’s (2022) study examines the impact of linguistic diversity on the 2017 municipal election turnout in Montreal and Quebec City, finding lower participation in linguistically diverse Montreal and varied turnout rates among different language groups. While social capital differences exist among these groups in Montreal, individual-level analysis shows limited impact of linguistic diversity on overall turnout, highlighting the complexity of language's role in voting behavior (Anderson & Stephenson, 2022). Curtis and Lambert (1976) highlight significant differences in political engagement between English-Canadians and French-Canadians, suggesting that language and associated cultural backgrounds profoundly impact political behaviors and attitudes. It underscores that, even after adjusting for other factors, language remains a critical variable influencing political involvement, with English Canadians being generally more politically active than their French-Canadian counterparts. These differences are attributed to varying political cultures shaped by linguistic distinctions (Curtis & Lambert, 1976). Another study finds that speaking English or French at home, as opposed to other languages, is correlated with higher voter participation (Bevelander & Pendakur, 2009). In Manitoba constituencies, lower voter turnout is linked to higher proportions of allophone residents, who speak neither of Canada's official languages, English or French (Wesley & Summerlee, 2012). This suggests that language barriers and cultural differences may hinder political engagement among these communities. Therefore, targeted outreach and education could help increase their electoral participation. The study of Hendren (2018) on Vancouver highlights significant linguistic diversity, with a notable percentage of residents, especially seniors, unable to speak English or French, particularly in areas like Renfrew-Collingwood and Victoria-Fraserview. This lack of language proficiency correlates with lower voter turnout in these regions, suggesting that language barriers may hinder civic participation and understanding of the political system (Hendren, 2018). Another study suggests that voters who neither speak English at home nor are 23 native-born tend to exhibit lower levels of political knowledge, which in turn leads to reduced voter turnout (Stewart et al., 2008). The influence of language on voter turnout is profound, particularly among immigrant and racialized minority communities. Studies consistently highlight that language proficiency, especially in English and French within Canada, significantly impacts political participation. Linguistic barriers can hinder voter registration, reduce political engagement, and ultimately lead to lower voter turnout among non-native speakers. The effectiveness of language assistance provisions, such as those mandated by the Voting Rights Act in the U.S., varies across different linguistic groups, demonstrating that while such measures can enhance electoral participation, their impact is not uniform. Research indicates that areas with higher proportions of residents speaking neither of the official languages often experience lower voter turnout. Therefore, targeted outreach, bilingual ballots, and inclusive language policies are essential to mitigate these barriers and promote greater electoral engagement among linguistically diverse populations. Overall, addressing language-related challenges is crucial for fostering an inclusive and participatory democratic process. 2.7. The Impact of Political Knowledge on Voting Likelihood Galston (2001) analyzes and finds that political knowledge affects the acceptance of democratic principles, attitudes toward specific issues, and political participation. Galston (2001) also reveals “the more knowledge people have, the better they can understand the impact of public policies on their interests, and the more effectively they can promote their interests in the political process” (p. 223). He also discusses that lack of civic knowledge makes citizens unable to appreciate new information and cannot compare new information to the existing political framework (Galston, 2001). Similarly, Popkin and Dimock (1999) identify similar findings in the U.S. context that political knowledge has a strong and independent influence on vote choice and political participation. They state, “contextual knowledge impacts the cues that will be salient for evaluating candidates” (p. 122). In addition, they find that citizens with less political knowledge have difficulty distinguishing between candidates and parties (p. 122). Delli Carpini and Keeter (1996) analyze the U.S. National Elections from 1982 to 1992 and discover that political knowledge promotes political values such as tolerance, minority rights, 24 freedom of the press, and the rule of law. Furthermore, political knowledge enhances political participation, consistent support for parties and candidates, political interest, and the ability to bridge the gap between attitudes and interests. Delli Carpini and Keeter (1996) define political knowledge as “the range of factual information about politics that is stored in long-term memory” (p. 10). They also analyze this term as similar to civic competency. Political knowledge has a huge impact on political behaviours. Political behaviour includes the discussion of citizen activities related to governmental institutions, election, voting, political party, political activities, and political movements. A study by Stewart et al., (2008) indicates that individuals who seldom discuss politics at home are almost twice as likely to possess low levels of political knowledge than those who regularly engage in political conversations. Additionally, being part of a racialized minority, not owning a home, lacking a university degree, and being foreign-born were all identified as significant factors contributing to lower levels of political knowledge (Stewart et al., 2008). O’Neill (2006) and Stewart et al. (2008) have conducted studies that indicate a significant positive relationship between the level of education a person has and their understanding of political matters. Their research suggests that higher educational attainment is associated with an increased awareness and comprehension of political issues and processes. Since Lambert et al. (1988) demonstrated that political knowledge positively influences voter turnout, it is reasonable to infer variations in the impact of political knowledge on turnout among White and other racial groups of voters. Howe (2007) highlights that new immigrants in Britain and Canada initially face a significant deficit in political knowledge. However, he found that immigrants in Canada overcome this knowledge gap more rapidly than those in Britain (Howe, 2007). Kanji and Bilodeau (2006) find that a significant number of immigrants eventually acquire greater political knowledge and engagement in Canadian politics compared to those born in Canada (Kanji & Bilodeau, 2006). It is observed that a minority individual's political knowledge tends to rise with the expansion of minority groups within a population, and this phenomenon applies not only to those who participate in elections but also to those who abstain from voting (DeSante & Perry, 2016). Quintelier et al., (2009) also reveales a similar finding. Milner (2007) highlights a significant positive relationship between political knowledge and voter turnout, particularly among young people. It suggests that higher levels of political knowledge among youth are associated with 25 higher rates of participation in democratic processes, including voting (Milner, 2007). This implies that improving political knowledge can potentially lead to increased voter turnout, as individuals with a better understanding of political issues and processes are more likely to engage in voting and other forms of political participation. Silver et al. (2006) highlight that increased educational efforts and community engagement could enhance political knowledge and voter turnout among inner city Indigenous people. Milner (2002) identifies a direct relationship between the extent of political knowledge and voter participation rates, suggesting that informed individuals are more likely to engage in voting, whereas those with limited understanding of politics are less inclined to do so. Similar to Milner, Verba et al. (1995) also observed that individuals with comprehensive and profound political knowledge are more likely to participate in electoral processes and political activities. The extensive body of literature consistently demonstrates that political knowledge is a pivotal factor influencing voter turnout. Individuals with a deeper understanding of political issues, processes, and candidates are more likely to participate in elections. This enhanced participation is attributed to their ability to comprehend and evaluate public policies, effectively promoting their interests in the political process. Political knowledge fosters democratic values such as tolerance, minority rights, and the rule of law, and bridges the gap between political attitudes and actions. Additionally, factors such as education, regular political discussions, and community engagement significantly boost political knowledge, thereby increasing voter turnout. Addressing disparities in political knowledge, particularly among minorities and immigrants, is crucial for promoting broader and more equitable political participation. By enhancing civic education and fostering inclusive political environments, we can ensure that more citizens are informed and engaged in the democratic process. 2.8. Civic Awareness and Voter Participation According to Pammett and LeDuc ( 2003) “civic duty is the feeling that participation is to be valued for its own sake, or for its contribution to the overall health of the polity, and does not need to be justified on instrumental grounds” (p. 38). Blais (2000) states that "a sense of duty entails adherence to a norm that establishes that voting is right and not voting is wrong" (p. 93). Riker and Ordeshook (1968) offer a new perspective on voter behavior, emphasizing the role of intrinsic 26 motivations in the decision to vote. They argue that beyond material considerations, individuals derive a sense of fulfillment from participating in elections, particularly through the fulfillment of civic duty. This perspective helps explain why people vote even when their individual impact on the outcome is minimal. Empirical evidence supports this view, suggesting that non-material benefits, such as personal satisfaction and adherence to democratic norms, play a crucial role in voter participation. By highlighting the importance of civic duty, Riker and Ordeshook (1968) provide a more comprehensive understanding of why citizens engage in the electoral process. Bevelander and Pendakur (2009) indicate that in Canada, civic duty and awareness, particularly regarding electoral participation, transcend ethnic and immigrant backgrounds, primarily influenced by socio-demographic factors and social capital attributes like community engagement. Voting is identified as a fundamental aspect of civic responsibility, heavily dependent on one's sense of belonging in the local community and level of formal social interaction (Bevelander & Pendakur, 2009). Therefore, fostering civic awareness and community involvement are essential for enhancing democratic engagement and fulfilling civic duties. The study by Purdam et al. (2002) on the UK's Electoral Commission's examination of the 2001 general election found that, like the wider population, minority turnout varied, being higher for those who felt voting was a civic duty and lower for those who considered it inconvenient. Blais et al. (2004) find that the decrease in voter participation is indicative of wider societal shifts, such as a reduced sense of civic responsibility and decreased involvement in politics, especially among the younger demographics. The overall decrease in turnout, not only among younger demographics but also across all age groups, is attributed to a diminishing sense of voting as a duty (Blais, 2000; Blais & Rubenson, 2013). The observed generational decline in deference to authority and societal norms may contribute to lower voter turnout rates among newer generations, who view citizenship more as a right than a duty and prefer direct action over traditional voting (Kostelka & Blais, 2021). Pammett and LeDuc (2003) highlight that during the 2000 Federal Election, a significant portion of Canadian voters considered voting as "essential" or "very important," showing a strong correlation between a sense of civic duty and actual voting behavior, as those who voted were more likely to view voting as crucial, while non-voters showed a lesser sense of civic duty. A similar trend is also identified in the research of Dalton (2008). Blais and Achen (2019) highlight the significant role of civic duty in influencing voter turnout, presenting evidence that individuals 27 who perceive voting as a moral obligation are more likely to participate in elections. They distinguish between ethical motivations, driven by a sense of civic duty, and non-ethical (expressive) motivations, based on personal preferences, demonstrating a complex interaction between these factors in the decision-making process. Their research underscores the importance of civic duty as a fundamental component in understanding electoral participation dynamics (Blais & Achen, 2019). Gidengil (2004) emphasizes that higher education cultivates a heightened sense of civic duty, significantly contributing to an individual's motivation for political engagement. In their study on social fractionalisation and voter turnout, Lago et al. (2018) emphasize the intricate relationship between civic duty and ethnolinguistic diversity. They highlight that individuals who show aversion to ethnolinguistic diversity display a diminished sense of civic duty, particularly evident in minority groups. In contrast, those aligned with the majority or open to ethnolinguistic integration retain a robust commitment to voting as a civic responsibility. This dichotomy is notably observed in areas like Catalonia and Quebec, where ethnolinguistic fragmentation is prevalent. The findings suggest that social fragmentation and ethnic identity significantly influence the perception of voting as a moral and civic duty, thereby affecting democratic engagement and participation (Lago et al., 2018). The literature underscores the critical role of civic awareness and the sense of civic duty in driving voter participation. Civic duty, defined as the intrinsic value and moral obligation associated with voting, plays a significant role in motivating individuals to engage in the electoral process. Studies highlight that this sense of duty can outweigh the perceived low impact of an individual vote, making voting a rational and valued act. Factors such as socio-demographic attributes, community engagement, and higher education levels contribute to heightened civic awareness and participation. However, there is a noted generational decline in the perception of voting as a civic duty, contributing to lower voter turnout rates, particularly among younger demographics. The interplay between civic duty and social fragmentation, particularly in ethnolinguistically diverse regions, further influences voting behaviors. Promoting civic education and fostering a strong sense of community involvement are essential strategies for enhancing democratic engagement and ensuring robust voter participation. 28 2.9. Income-Level Correlations with Voter Turnout O'Neill (2006) finds that income connected to education significantly impacts political involvement; higher earnings provide the necessary time and resources for civic engagement. This study also finds stable financial status enables more informed participation and contributions to political causes (O'Neill, 2006). In the changing landscape of Canada's labour market, immigrants face distinct challenges compared to native Canadians, including lower entry earnings, difficulties in credential recognition, and reduced access to government assistance due to stringent eligibility criteria (Ruddick, 2003). Ruddick (2003) also finds that while both groups are impacted by shifts towards more precarious forms of employment, immigrants' economic integration is further complicated by institutional barriers and language hurdles, delaying their path to achieving economic parity with their Canadian-born counterparts. According to data from the Ethnic Diversity Survey, Reitz and Banerjee (2007) find that racialized minorities earn, on average, $7,686 less than the local median in metropolitan areas, whereas White individuals earn $1,895 more, resulting in a disparity of $9,581 or 23.2% against the national mean. Additionally, the poverty rate for racialized minorities in 2001 was nearly twice that of Whites, with 26.6% of racialized minorities living below the poverty line compared to 14.2% of the broader population, highlighting significant income and poverty disparities among different ethnic groups (Reitz & Banerjee, 2007). Halli and Kazemipur (2003) find that immigrants in Canada, especially in urban centers, generally face higher poverty rates than native-born Canadians due to factors such as arrival timing, education, and language barriers. Notably, the impact of educational attainment and linguistic skills on poverty alleviation is less significant for immigrants than for their native-born counterparts, highlighting systemic inequalities (Halli & Kazemipur, 2003). Additionally, that same study finds, race plays a critical role, with racialized minority immigrants experiencing more pronounced economic challenges, suggesting underlying issues of discrimination and unequal access to opportunities. Income and income disparity significantly influence the economic, social, and political aspects of individuals' lives. Typically, households of racialized minorities report lower average incomes and face higher rates of poverty compared to those from European backgrounds (Halli & Kazemipur 2001, Reitz & Banerjee 2005). Jedwab (2005) finds that greater electoral participation is linked to higher income levels, revealing significant economic disparities 29 in voting patterns. Areas with many allophones, typically from immigrant and minority backgrounds, exhibit lower turnout due to lower average incomes, underlining how financial difficulties, along with other socio-demographic elements, affect voter involvement and demonstrate the interconnectedness of economic, racial, and immigration factors in electoral participation (Jedwab, 2005). A study on British population finds generally negative association between income inequality and voter turnout across different models and measures, with poverty rate showing a significant relationship (Horn, 2011). Galbraith and Hale (2008) indicate a minor correlation between greater income disparities and lower voter participation. Income influences not only the rate of voter participation but also affects the preferences voters have when choosing between different political parties or candidates (Franko et ai., 2016). Their research suggests that greater income inequality tends to increase support for conservative parties, while lower income inequality tends to bolster support for more liberal parties. Contrary to the findings mentioned above, Harrison and Krahn (2014) discovered that in Alberta, income does not affect voter turnout. Howe and Bedford (2009) find a relationship between income and voting patterns within the Indigenous electorate, which is less significant than age but still notable. Socio-economic status, reflected through income and education levels, shows a discrepancy of 15 to 18 percentage points between the highest and lowest ends, a gap that is more pronounced among Indigenous people compared to others, where the influence is only 5 to 8 percentage points. Silver et al. (2006) indicates that there is a correlation between income levels, or socio-economic status, and voter turnout, highlighting a disparity between Indigenous and non-Indigenous people in Canada. Specifically, Indigenous people have lower average incomes compared to the national average: over $19,000 versus close to $30,000, according to the 2001 Census. Moreover, the prevalence of low income is significantly higher among Indigenous populations at 55.9% compared to 34% for the overall Canadian population (Silver et al., 2006). Blais et al. (2002) find the key factors affecting the likelihood of voting in 2000 were income, education level, how recently one arrived in Canada, and particularly the generational group they belonged to. Polacko (2020) reveals that there is a considerable difference in voting rates between the wealthiest and poorest segments of the population, with the turnout rates being fairly consistent 30 across provinces, Newfoundland being the notable exception. Another study on Canadian provinces finds that areas with more high-income residents and higher educational achievements tend to have increased voter turnout, whereas regions with predominantly low-income families and fewer high school or college graduates experience reduced electoral participation (Wesley & Summerlee, 2012). Another study indicates that wealthier individuals with higher levels of education and income are more inclined to participate in voting compared to those with lower socioeconomic status (Gallego, 2009). Tate (1991) found that in the U.S., higher income levels significantly increased the likelihood of Black Americans participating in the 1988 presidential primary elections. Qi and Gonzalez (2022) also observed that in the U.S., immigrants and racialized minorities possessing higher income levels tend to be more engaged in voting activities. Individuals from wealthier backgrounds and higher family incomes are more inclined to participate in voting (Southwell & Everest, 1998). The correlation between income levels and voter turnout is well-documented, highlighting that higher income significantly boosts political participation. Financial stability provides individuals with the resources and time necessary for civic engagement, fostering more informed and active participation in the political process. Immigrants and racialized minorities, particularly those from racialized minority groups, often face economic challenges that impede their voter turnout, due to factors such as lower incomes, higher poverty rates, and systemic barriers. Studies reveal that income disparities influence not only the likelihood of voting but also voter preferences, with greater income inequality often correlating with lower voter turnout and shifts in political support. While some regional studies show exceptions to these trends, the overall evidence underscores the critical role of economic stability in fostering democratic participation. Addressing income inequality and enhancing economic opportunities for all demographic groups are essential steps toward achieving more equitable and representative voter turnout. 2.10. Employment Status as a Predictor of Voting Behavior The relationship between employment status and voting behaviour has been shown to change across different generations and over time, displaying inconsistent patterns in research findings. A study by Statistics Canada regarding the determinants of voting behavior indicates that individuals who are employed tend to vote more frequently than those who are unemployed (Uppal & 31 LaRochelle-Côté, 2012). Blais (2000) also examined how economic well-being positively influences voter participation. A U.S.-based study highlights that increased labor market activity, marked by higher employment levels per adult, tends to decrease voter turnout in various local elections (Charles & Stephens, 2013). It suggests that as people become busier with work, they have less leisure time to stay informed about political affairs, which in turn reduces their likelihood of voting. However, this trend does not significantly affect presidential election turnout (Charles & Stephens, 2013). Another finding states that individuals without employment tend to participate less in political activities, not solely due to their generally reduced income but also because they are not involved in social networks at work, which typically encourage engagement in political matters (Rosenstone & Hansen 1993, Wolfinger & Rosenstone 1980). Quillian et al. (2019) find that racial discrimination in hiring persists in Canada, with non-white applicants receiving fewer callbacks than their white counterparts, even when qualifications are equivalent. While Canada falls in the mid-range of discrimination levels among the countries studied, the findings indicate that hiring biases remain a significant barrier for racial minorities in the Canadian labor market. Research examines wage differences across various ethnic groups in Canada compared to those of British descent (Pendakur & Pendakur, 2011). It reveals that European-origin women generally have similar wages to British women, while women from racialized minority groups typically earn less. In addition, European-origin men often have higher wages than their British counterparts, but racialized minority men see a decrease in their earnings over time. The study suggests that job characteristics can lessen, but not fully resolve, these wage gaps, highlighting persistent wage inequality in Canada (Pendakur & Pendakur, 2011). The findings by Oreopoulos (2011) not only highlight earnings disparities but also expose the enduring presence of racial discrimination within the Canadian labor market. Oreopoulos (2011) uncovers evident racial biases in the job selection process, showing a clear preference for resumes bearing Western names and Canadian work background, thereby reflecting deep-seated prejudices within the hiring landscape. This study also reveals a marked favoritism towards individuals with English-sounding names and domestic experience, highlighting ingrained biases against those with non-English names or overseas experiences. This scenario underscores the challenges faced by candidates in overcoming societal stereotypes, demonstrating the enduring nature of racial and ethnic discrimination in professional settings within the context of the Canadian job market (Oreopoulos, 2011). 32 O'Neill (2006) discusses that employment status significantly influences voter registration and turnout, with employed individuals more likely to engage in political activities. However, the impact of employment and other socioeconomic factors on political participation varies across different racial and ethnic groups, particularly affecting Asian Americans differently compared to other groups. Among European immigrant and ethnic racial groups, employment has an impact on voting behavior, mainly on vote choices (Bird et al., 2011). Togeby (2004) discovers that within the immigrant population in Denmark, the effects of employment and unemployment on voting behavior and casual political involvement are varied and not always consistent. Block and Galabuzi (2011) find that in 2006, racialized Canadians displayed marginally higher employment participation rates than non-racialized Canadians but faced notably higher unemployment rates, especially among racialized women and specific groups such as Chinese, West Asian/Arab, and Black Canadians. Japanese, Chinese, Korean, and Arab/West Asian communities showed lower participation rates, with most racialized groups enduring greater unemployment challenges than their non-racialized counterparts (Block & Galabuzi, 2011). In a recent study Ng and Gagnon (2020) reveal that racialized Canadians and immigrants, particularly those from non-European countries, face greater unemployment and underemployment than their non-racialized and Canadian-born counterparts. The disparities are largely attributed to systemic barriers, such as the devaluation of foreign credentials and workplace discrimination. Additionally, racialized women experience a compounded disadvantage, resulting in even poorer labor market outcomes compared to racialized men and non-racialized individuals (Ng & Gagnon, 2020). The relationship between employment status and voting behavior is multifaceted, reflecting broader socio-economic dynamics and systemic inequities. Employment provides not only financial stability but also social networks that encourage political engagement, thereby increasing voter turnout. However, busy work schedules can also limit the time and energy available for political participation, particularly in local elections. Racial and ethnic disparities in employment significantly impact political engagement, with systemic barriers and discrimination further complicating the integration of immigrants and racialized minorities into the labor market. These groups often face higher unemployment rates and wage disparities, which can deter their political involvement. Addressing these socio-economic challenges is crucial for fostering a more inclusive and participatory democratic process. Ultimately, employment status serves as a crucial 33 determinant of voter behavior, intertwined with broader issues of racial equality and economic justice. 2.11. Covid impact on Electoral Turnout Dynamics The relationship between COVID-19 management and voter turnout, as outlined in the research of Erhan and Sıvış (2024), suggests a significant impact of the pandemic response on electoral participation in both the United States and Canada. In the United States, the perceived mishandling of the COVID-19 crisis under President Donald Trump's administration, characterized by a lack of effective public health measures and political divisiveness, is associated with increased voter turnout in the 2020 elections, indicating public mobilization in response to governmental handling of the pandemic. Conversely, in Canada, Prime Minister Justin Trudeau's government's approach, marked by robust health policies and economic support measures, appears to have contributed positively to his re-election in the 2021 elections, reflecting public approval of his pandemic management. This juxtaposition between the two countries underscores the influence of governmental responses to COVID-19 on electoral behaviors and outcomes (Erhan & Sıvış, 2024). They also indicate that the COVID-19 pandemic exacerbated existing racial inequalities, particularly affecting Black and Latino populations in the United States, which may have influenced political mobilization and voter turnout. While it does not explicitly link these racial disparities to specific changes in voter turnout, the context suggests that the heightened racial tensions and systemic inequalities, amplified by the pandemic and the social climate, could have led to increased political engagement among minority groups (Erhan & Sıvış, 2024). This potential increase in engagement might have been a response to the urgent need for addressing racial injustice and health disparities, thereby influencing electoral participation. The COVID-19 pandemic has significantly impacted voter turnout and election management across Canada, as described by Harell and Stephenson (2022). Challenges posed by the pandemic forced election management bodies (EMBs) to implement new strategies, such as expanded mail-in and advance voting options, to meet public health guidelines and address safety concerns. While these adjustments were critical for ensuring voter safety, they led to varying turnout rates in different provinces. In particular, five out of six elections saw reduced turnout compared to pre-pandemic times, with the most significant drop occurring in Newfoundland and Labrador. In 34 contrast, Nova Scotia experienced an uptick in voter participation. This variation highlights the complex relationship between pandemic conditions and voter turnout (Harell & Stephenson, 2022). Hasen (2020) discusses the impact of COVID-19 on voting, highlighting the situation in Milwaukee during the Wisconsin elections. While White wards experienced an average voter turnout of 49%, Black and Hispanic wards saw a significantly lower turnout, averaging around 18%. This indicates a notable decrease in minority voter participation. The challenges included issues with absentee ballots, such as many not being received by voters and inconsistencies in the treatment of absentee ballots without postmarks. These issues, combined with the state legislature's refusal to delay the election, led to lower turnout among minority voters, reflecting the broader challenges and systemic issues faced by minority communities during the pandemic (Hasen, 2020). According to Jahan's study (2022), the COVID-19 pandemic significantly impacted voter turnout in parliamentary and presidential elections across various democratic and hybrid regimes during 2020 and 2021. The research demonstrated a general decline in voter turnout, highlighting a negative correlation with the increase in COVID-19 cases per million each week. Despite controlling for factors such as GDP growth, political equality, and electoral autocracy, these variables showed no significant relationship with changes in voter turnout during the pandemic. This underscores the pandemic's dominant role in influencing electoral participation (Jahan, 2022). Garnett et al. (2021) evaluate the Canadian provincial elections held during the COVID-19 pandemic, focusing on adaptations such as increased mail-in voting and health safety measures. Despite public skepticism regarding the timing of the elections, incumbent governments were generally re-elected. The pandemic influenced changes in voter behavior, particularly a rise in mail-in and advance voting, though overall voter turnout was slightly lower (Garnett et al., 2021). Regarding Covid-19 and voter turnout, Merkley et al. (2022) also find the similar finding that COVID impacted voter turnout in Canada negatively. Haute et al. (2021) find that the COVID-19 pandemic significantly impacted voter turnout, particularly during the 2020 municipal elections in France. The public health crisis led to a general increase in abstention rates, influencing traditional turnout inequalities. Notably, the pandemic resulted in a narrowing of the age-related participation gap, likely due to heightened concerns among older voters about the risk of infection (Haute et al., 2021). However, disparities in turnout based on socio-economic status not only persisted but, in some cases, intensified. The crisis 35 particularly demobilized citizens with little interest in politics, exacerbating the pre-existing gap between different social groups in terms of electoral participation (Haute et al., 2021). Overall, the pandemic underscored the multifaceted nature of voter turnout, revealing how external shocks like health crises can alter established voting patterns and deepen societal divides in political engagement. In their investigation into the effects of the COVID-19 pandemic on voter turnout, Constantino et al. (2021) present compelling evidence on how the timing of Covid-19 cases influences voter behavior. Their study, set against the backdrop of the 2020 Brazilian municipal elections, reveals a nuanced dynamic: proximity to the election date significantly dictates the pandemic's impact on voter turnout. Specifically, their analysis shows that an increase in Covid-19 cases and deaths close to the election correlates with reduced voter turnout, attributable to heightened health concerns and the perceived costs of in-person voting. Conversely, they find that earlier instances of higher infection rates can lead to increased voter engagement and turnout, driven by heightened political interests and a perceived greater benefit in participating in the electoral process (Constantino et al., 2021). Vázquez et al. (2020) investigate how the COVID-19 pandemic affected voter participation by studying the Basque Country regional elections, which took place after the peak of the pandemic's first wave. The authors hypothesized that the fear associated with in-person voting during the pandemic would decrease voter turnout. Their findings, based on a difference-in-difference model, confirmed this hypothesis: COVID-19 led to a turnout decrease of about 4.7% in municipalities affected by the virus compared to those not affected at the time of the election. The decrease was even more significant in municipalities that experienced deaths due to the virus, demonstrating the pandemic's impact on voter behavior (Vázquez et al., 2020). Similarly, Scheller's (2021) study examines the impact of COVID-19 rates and voter age on turnout during the Florida Presidential Preference Primary on March 17, 2020. Findings indicate that higher COVID-19 prevalence and greater age were associated with reduced likelihood of voting, particularly among Republicans. The research suggests that pandemic conditions and demographic factors significantly influence voter behavior (Scheller, 2021). Parker and Hutti (2023) use county-level data from twelve Midwest states to predict voter turnout in St. Louis City and County, focusing on race, poverty rates, and unemployment rates. Findings indicate that despite higher poverty levels and a significant percentage of Black residents, voter turnout was higher than expected. This study introduces physical risk due to COVID-19 and police violence as new factors in voter turnout, 36 suggesting modifications to the rational choice theory used to explain electoral behavior (Parker & Hutti, 2023). The COVID-19 pandemic has profoundly influenced electoral turnout dynamics, with varying impacts observed across different regions and demographics. Research highlights that governmental responses to the pandemic, public health concerns, and socio-economic factors significantly shaped voter behavior. In the United States, dissatisfaction with pandemic management drove increased voter turnout, while in Canada, effective handling of the crisis bolstered electoral participation and incumbents' re-election prospects. The pandemic exacerbated existing racial and socio-economic inequalities, particularly affecting minority groups and those in lower socio-economic brackets, often leading to reduced voter turnout due to health concerns and logistical challenges. Conversely, expanded mail-in voting and early voting options provided alternative pathways for participation, albeit with mixed effectiveness. Overall, the pandemic underscored the importance of adaptive electoral management and highlighted the complex interplay between public health, political engagement, and social equity in shaping voter turnout during crises. 2.12. Gender Dynamics and Voter Turnout In the 2021 general election, women had a higher voter turnout (63.8%) compared to men (60.6%), a trend observed across all age groups until age 65, above which men participated at rates equal to or higher than women. This pattern has been consistently observed in every general election since 2008. Erickson and O'Neill (2002) analyze gender voting trends in Canada from 1965 to 1997, highlighting a modest gender gap in support for national parties until the 1990s. However, the 1997 election marked the emergence of a modern gender gap outside Quebec, with a complex realignment of women from right to left in federal partisan politics. This shift was influenced by brokerage politics, the multiparty system, and Quebec's unique political landscape. The study emphasizes that gender differences in cultural values significantly shaped this realignment, though the patterns varied across elections. Lastly, Houle (2022) investigates gender differences in political participation in Canada, finding that while men and women participate at similar overall rates, the nature of their participation differs significantly. Women are more likely to engage in private, flexible forms of political activity, such as signing petitions, whereas men are more 37 inclined to participate in public, collective activities like attending political meetings and demonstrations. These differences are influenced by traditional gender roles, political socialization, and conflict avoidance tendencies. The study highlights the need for further research to explore the impact of these factors on gendered political participation. If we look at other democratic elections, Dassonneville and Kostelka (2021) examine voter turnout, specifically in European Parliament (EP) elections, and reveal that women consistently vote less than men in these elections. This enduring gender gap is primarily driven by women's lower levels of political interest, which are heavily influenced by cultural perceptions of gender roles. The study argues that achieving full gender equality in voter turnout requires addressing these cultural stereotypes, as societal gender equality alone is insufficient to close the gap. Kostelka, Blais, and Gidengil (2019) find that while no significant gender gap exists in national elections, women are less likely to participate than men in second-order elections, such as subnational and supranational elections. This persistent gap is largely due to lower levels of political interest and knowledge among women, especially in less important elections. The study suggests that these disparities are deeply rooted in political socialization and must be addressed to reduce gender bias in voter turnout. These literatures generally indicate that gender does not play a significant role in determining voter turnout in Canadian elections. While some studies suggest that men might participate more in national elections, this trend is not consistent across the literature. However, there is growing evidence that female participation in national elections is increasing, indicating a shift toward greater gender parity in voter turnout. This suggests that women are becoming increasingly engaged in the electoral process, narrowing the gap between male and female voter participation. 2.13. Conclusion The literatures reviewed in this chapter provide a comprehensive examination of the various factors that influence voter turnout, particularly within the Canadian context. Through an exploration of race, education, age, immigrant status, language, political knowledge, civic awareness, income, employment, the impact of COVID-19, and gender, the chapter highlights the complex interplay of these factors in shaping electoral participation. While certain demographic factors like age and education consistently show a strong positive correlation with voter turnout, 38 other variables such as race and immigrant status reveal more nuanced and sometimes contradictory influences, reflecting broader socio-political dynamics. The literature underscores the importance of socio-economic stability, civic awareness, and political knowledge in fostering voter engagement, while also pointing out significant gaps in research, particularly regarding the electoral participation of racialized minorities and immigrant communities. This review sets the stage for further investigation into these underexplored areas, providing a critical foundation for understanding the diverse and evolving landscape of voter behavior in Canada and other democratic societies. 39 3. Theoretical Framework 3.1. Introduction In understanding voter behavior and turnout in the 2021 Canadian Election, it is essential to examine the theoretical underpinnings that explain the complex interplay of social, economic, and political factors. Theoretical frameworks provide the necessary lens through which these dynamics can be analyzed and understood in greater depth. This section introduces three prominent theories that inform the analysis of voter turnout: Social Identity Theory, the Resource Model of Political Participation, and Straight Line Assimilation Theory. Each of these frameworks offers unique insights into the factors influencing electoral participation, particularly concerning race, ethnicity, and immigration status. By applying these theories, we can better comprehend how individual and group identities, access to resources, and processes of assimilation shape voter behavior. These theoretical perspectives are crucial for interpreting the empirical findings presented later in this thesis and for situating them within the broader context of political science literature. The following paragraphs provide a detailed discussion of each theory and its relevance to the study of voter turnout in the Canadian context. 3.2. Social Identity Theory Social Identity Theory is a psychological framework developed to explain the psychological underpinnings of intergroup behaviors, such as prejudice, discrimination, and conflict (Tajfel & Turner, 1979). Originating from Henri Tajfel's efforts to understand the findings of minimal group experiments, the theory integrates his extensive research on categorization, social perception, and his commitment to addressing social issues. Central to this theory is Tajfel's definition of social identity as an “individual’s knowledge that he belongs to certain social groups together with some emotional and value significance to him of this group membership” (Tajfel, 1972, p. 292). This theory explains how individuals' self-concepts are shaped by their membership in social groups, influencing their behaviors and attitudes through processes of social categorization, identification, and comparison for positive distinctiveness. Using Social Identity Theory, Turnbull-Dugarte and Wagner (2025) show that individuals with strong political identities perceive others’ actions through partisan lenses, thereby reinforcing in-group political behavior and participation. Ben-Bassat and Dahan (2012) explore the implications of Social Identity Theory on voter behavior in Arab communities in Israel. Their study finds that individuals are significantly more likely to vote 40 for candidates who share their hamula (extended family group, proxied by surname), supporting the idea that group affiliation enhances political participation. Moreover, the paper demonstrates that Arab municipalities exhibit substantially higher voter turnout than Jewish ones, aligning with the prediction that stronger group identities increase civic engagement. Moreover, Social Identity Theory explains partisanship as a deeply internalized group identity that motivates individuals to protect their party’s status and electoral success, often independent of policy alignment (Huddy & Bankert, 2017). This study emphasizes emotional attachment and group-based loyalty, which generate political engagement and biased reasoning. The theory's cognitive and motivational elements clarify how party affiliation becomes a stable, expressive identity rooted in social belonging rather than purely ideological agreement (Huddy & Bankert, 2017). On the contrary, Spies et al. (2020) examine Social Identity Theory in the context of immigrant-origin voter turnout in Germany, emphasizing that ethnic identity—framed through social categorization into in-groups and out-groups—can influence political participation. While strong host-country identity (e.g., feeling "German") correlates with higher turnout, the study finds that once standard political engagement variables (e.g., political interest, education, party affiliation) are controlled for, ethnic identity alone does not significantly predict voting behavior. Thus, social identity theory contributes limited explanatory power beyond established models in the German electoral context. However, we will explore how this theory may also help explain the connection between racial identity and voting behavior in the 2021 Canadian federal election 3.3. The Resource Model The Resource Model of political participation is a theoretical framework positing that political engagement is determined not just by an individual's socioeconomic status but by their access to three essential resources: time, money, and civic skills. These resources are critical for undertaking various political activities, and their availability can significantly influence the extent and form of an individual's political participation. This model was developed by Brady, Verba, and Schlozman in 1995 (Brady et al., 1995). They argued that motivations such as political interest are not sufficient to explain citizens' participation in politics. Rather, the resources mentioned above are powerful predictors of political participation (p. 285). Using this theory, Leighley and Vedlitz (1999) found that resources impact political participation among Anglos, African-Americans, 41 Asian-Americans, and Mexican-Americans. Smets and van Ham (2013) find strong support for the resource model of voter turnout, demonstrating that variables such as education, age, and income consistently show significant positive relationships with individual-level turnout across studies. Education and age emerge as particularly robust predictors, while other resource-related factors like homeownership and residential mobility also show moderate effects. However, variables such as gender, race, and contextual resource measures generally fail to show consistent significance, highlighting the uneven influence of different resources on turnout behavior. Moreover, Nadeau et al. (2019) argue that wealth significantly enhances the explanatory power of the resource model of electoral participation, serving both as a facilitator and motivator for voter turnout across diverse democracies. Their findings indicate that asset ownership not only provides individuals with the means to engage in politics but also increases their perceived political stakes, thereby reinforcing turnout beyond traditional measures like income or education. Schaub (2021) examines the impact of acute financial hardship on voter turnout in Germany, utilizing a natural experiment based on bank payment schedules. This study supports the voter resource model, showing that short-term financial stress reduces political participation by undermining individuals’ psychological and material capacity to engage in politics. These effects are especially pronounced among the working poor and during end-of-month periods (Schaub, 2021). This has been discussed in the literature review, which examines how employment, income, education, and political knowledge influence voter participation. The model may support the description of the relationship between ethnic identity, immigration, and voter turnout in the Canadian context. 3.4. Straight Line Assimilation Theory The classical or straight-Line assimilation model posits that the integration of immigrants and their offspring into the receiving society occurs progressively over generations. According to Warner and Srole (1945) and Park and Burgess (1969), this gradual process is facilitated by enhanced access to educational and employment opportunities, fostering closer ties with the host society's cultural practices and values. As a result, the distinction between the descendants of immigrants and the local population becomes increasingly blurred, illustrating a linear trajectory towards complete assimilation into the societal fabric. The classical assimilation theory can offer a lens through which to examine the dynamics of race and voter turnout. According to this framework, 42 as immigrants and their descendants progressively integrate into the host society, they adopt its norms and behaviors, including political participation patterns. This theory suggests that racial and ethnic disparities in voter turnout might narrow over successive generations as these groups achieve greater socioeconomic status, educational levels, and cultural assimilation, factors known to correlate with higher political engagement (Warner & Srole, 1945; Park & Burgess, 1969). Despite valid criticisms that early assimilation theory framed immigrant cultures as "inferior" and promoted ethnocentric ideals, Alba and Nee (1997) argue that the concept still holds analytical value. They maintain that, when redefined as a spontaneous social process rather than a normative program, assimilation remains a useful framework for understanding immigrant incorporation. Bueker’s (2003) dissertation offers empirical support for the Straight-Line Assimilation theory, particularly in terms of the relationship between duration of residence in the United States and immigrant political incorporation. While she acknowledges the significance of segmented assimilation and considers a range of multi-level influences—such as family structure, community characteristics, and country of origin—her findings consistently demonstrate that longer time spent in the U.S. increases the likelihood of both naturalization and voter participation (Bueker’s, 2003). This pattern reinforces the core premise of straight-line assimilation, in which prolonged exposure to the host society leads to increased integration across domains. On the contrary, the study by Ramakrishnan and Espenshade (2001) finds little support for the straight-line assimilation theory in the context of immigrant political participation. Instead of a linear increase in participation across generations, the authors observe distinct patterns across racial and ethnic groups, such as a “second generation advantage” among whites and persistent gaps among Latinos and Asian-Americans. These findings suggest that assimilation is segmented rather than uniform, challenging the applicability of traditional straight-line models to contemporary immigrant incorporation (Ramakrishnan and Espenshade, 2001). Moreover, Heath and Schneider (2021) provide robust empirical support for straight-line assimilation theory, showing that integration across structural, cultural, and civic domains generally increases from the first to the third generation of migrants in Western Europe. Their findings suggest that while many ethnic minority groups follow the expected linear trajectory of assimilation, some—particularly those from Middle Eastern, North African, and Sub-Saharan African backgrounds—face persistent disadvantages. Additionally, certain dimensions, such as interethnic friendships, deviate from the 43 straight-line pattern, reflecting more complex dynamics in social integration. Building on this theoretical foundation, the present study adopts the straight-line assimilation framework to examine whether it can explain patterns of voter turnout among racialized minorities, with particular attention to how the duration of residence influences electoral participation. 3.5. Conclusion The theoretical frameworks discussed in this chapter will provide essential insights into the complex dynamics of voter turnout in the 2021 Canadian Election. Social Identity Theory helps to explain how individuals' racial and ethnic identities influence their voting behavior, emphasizing the role of group membership in shaping political attitudes and actions. The Resource Model of Political Participation highlights the importance of access to resources such as time, money, and civic skills in determining the extent of political engagement, offering a practical lens to understand how socioeconomic factors influence voter turnout. Finally, Straight Line Assimilation Theory offers a perspective on how immigrants and their descendants integrate into the host society over generations, affecting their political participation patterns. Together, these theories create a robust framework for analyzing voter turnout in Canada, particularly among racialized and immigrant groups, and set the stage for the empirical analysis that follows in this thesis. 44 4. Data, Research Design, Hypotheses, and Methodology 4.1. Data This study utilizes the Canadian Electoral Studies (CES) dataset from 2021 (Stephenson et al., 2021) to examine the voting behavior of Canadians during the 2021 federal election. The primary objective is to explore the relationship between racial identity and its effect on voting behavior, with a particular focus on voter turnout. Previous literature highlights race as a pivotal factor influencing voter turnout, though its impact varies; it can be negative, positive, or in some cases, not significant. This research aims to clarify how racial factors influence voting behavior within the Canadian context, acknowledging that race is not the sole determinant. Additional variables, such as demographic characteristics, COVID-19 effects, and immigration status, will also be considered. The 2021 Canadian Electoral Studies (CES), a comprehensive national survey aimed at eligible voters, assesses Canadians' voting behaviors and their opinions on a wide array of social, economic, and political issues. In 2021, the CES featured two main components: a campaign period survey (CPS) and a post-election survey (PES). The CPS was organized into three waves—“CPS,” “CPS Modules,” and “CPS Oversample”—which were merged to achieve a final sample size of 20,968 respondents, collected between August 17 and September 19, 2021. Following this, the PES was conducted from September 23 to October 4, 2021, resulting in a sample of 15,069 individuals. The survey's core questions, consistent with previous CES iterations to maintain continuity, covered key areas such as voting intentions, issue positions, partisanship, and political engagement. Most of the variables used in this study are from the CPS, except for a few, such as turnout, allophone, frequency of political discussions at home, and duration of residence in the current city. These variables are explained in detail later in this chapter. Considering all the variables, the three regression analyses include a total of 7,630 observations across the three models after listwise deletion. To compare gender participation across different immigrant origins, this study also utilized the 2015 Canadian Election Study dataset (Fournier et al., 2015) and the 2019 Canadian Election Study dataset (Stephenson et al., 2020). Three regression models—Bivariate, Socio-Demographic, and Complete—are used to analyze voter turnout. These three regression models are employed to systematically assess the influence 45 of race on voter turnout in the 2021 Canadian Election. The Bivariate model focuses solely on the relationship between race and voter turnout, establishing a baseline for understanding this direct impact. The Socio-Demographic model adds demographic factors such as age, gender, and education to analyze how these variables interact with race in influencing voter participation. Finally, the Complete model incorporates additional socio-economic and political variables, offering a comprehensive view of how race, alongside these factors, affects voter turnout. These models are chosen to progressively build complexity in the analysis, providing a clear and detailed understanding of the various influences on electoral participation. 4.2. Variables The dependent variable in this analysis is voter turnout, derived from respondents' answers to whether they participated in the 2021 federal election. This variable is coded as a binary dummy variable with two categories: 0 for respondents who did not vote and 1 for those who did vote. The data encompasses 7,630 observations, with 91.35% (6.970 respondents) indicating they voted and 8.65% (660 respondents) indicating they did not. The summary statistics mentioned in Table A1 reflects a high voter turnout and some variability in voting behavior. This analysis incorporates a simplified categorization where responses indicating any form of non-participation (such as "I usually vote but didn't this time," "I thought about voting but didn't," "I wasn't registered to vote," "Don't know/Don't remember," and "Prefer not to answer,") are consolidated under the "no" category. Respondents who were not eligible to vote (responded as "I was not eligible to vote") were excluded from the analysis. This approach ensures clarity in analyzing the dependent variable by merging nuanced responses into a binary "yes" or "no" framework, effectively streamlining the interpretation of voter turnout as either participation or non-participation in the election. Consequently, the analysis focuses on the binary distinction between voters and non-voters, allowing for a more straightforward and robust examination of the factors influencing voter turnout in the sample. Descriptive statistics for this variable and all independent variables are presented in the Appendix. To investigate the influence of race on voter turnout in the 2021 Canadian Election, we identify race as our main independent variable (See Table A2). The CES 2021 data provides a detailed tabulation of respondents across various racial categories, including Arab, Asian, Black, Indigenous, Latino, South Asian, Southeast Asian, West Asian, and White. We created a binary 46 variable where White is coded as 0 and racialized minorities are coded as 1. In our total sample 79.82% are White and 20.18% are racialized minorities. This binary coding simplifies the analysis of racial composition within the dataset. It allows for a straightforward analysis of racial identity and its impact on the voter turnout, facilitating a robust comparison between White and other racial groups. Although Indigenous peoples could be considered separately in analyses of race and voter turnout, doing so does not alter the overall findings. For further details, refer to the Appendix. Additional models that account for Indigenous respondents separately are provided in a supplementary appendix (Table D1-Table D3 ). Our approach involves three models, starting with a baseline (Bivariate) model that examines the impact of race alone on turnout. This methodological framework aims to uncover the nuanced dynamics of race and electoral participation, exploring whether and how different racial identities influenced turnout in the context of the 2021 Canadian Election. Through this analysis, we seek to contribute to a deeper understanding of the interplay between race and voter engagement, offering insights into the factors that may motivate or deter electoral participation among diverse populations. In the Socio-Demographic model of our analysis on the 2021 Canadian Election, we incorporate demographic variables alongside race to examine the robustness of race's impact on voter turnout. These demographic variables include age, gender, region, education, religion, immigrant status, and language. This approach allows for a more comprehensive understanding of voter behavior by accounting for the multifaceted nature of societal and individual experiences. Demographic factors have been consistently significant in electoral studies, influencing individuals' likelihood to vote. For instance, education levels can enhance political awareness and engagement, gender may affect political priorities and participation, and immigrant status can reflect different levels of integration and political involvement. Furthermore, controlling for the immigration variable is essential because of its significant correlation with race, which helps illuminate the complexities of voter behavior. By analyzing these variables in conjunction with race, we aim to determine the extent to which race remains a significant predictor of voter turnout when these other influential factors are considered. This holistic approach underscores the complex interplay of individual and societal characteristics in shaping electoral participation. Descriptive statistics of the variables mentioned in the appendices reveal a diverse and multifaceted dataset. The education variable, a categorical variable, ranging from "No schooling" 47 to "Professional degree or doctorate" on an 11-point scale. The majority of respondents are well-educated, with 29.79% holding a Bachelor’s degree, 11.02% a Master’s degree, and 4.42% a professional degree or doctorate. In contrast, only 0.03% have no schooling, and 0.14% completed only elementary school. Intermediate education levels are also well-represented, with 13.03% completing secondary school, 7.99% having some technical or community college education, and 21.91% completing such programs (Table A3). This broad range of educational attainment provides a comprehensive basis for analyzing its impact on voter turnout, highlighting how different education levels correlate with electoral participation. Another independent variable in this analysis is gender, which includes three categories coded as separate dummy variables: male, female, and non-binary. Out of all samples, 49.07% identify themselves as male, 50.51% as female, and 0.24% as non-binary with male as the reference category (Table A4). These gender categories provide a basis for examining how gender differences impact voter turnout, offering insights into the relationship between gender identity and electoral participation. The analysis includes region as an independent variable, with Ontario serving as the reference category. The proportion of each region in the sample is detailed in the descriptive statistics Table A5 in the Appendix. This comprehensive regional categorization allows for an in-depth analysis of how geographical location impacts voter turnout, enabling a comparison across different regions while highlighting Ontario as the baseline for these comparisons. Age is another crucial variable in this analysis. The variable is coded as a quantitative variable ranging from 18 to 95 years. The descriptive statistics mentioned in Table A6 indicates a diverse age distribution among the 7,630 respondents. This broad age range allows for a comprehensive examination of how age impacts voter turnout, providing insights into the voting behaviors of different age demographics. Religion is another independent variable with atheist serving as the reference category. The summary statistics (Table A7) show the diversity of religious affiliations, helping to analyze how each religious identity, compared to atheism, affects voter turnout and its relationship with electoral participation. Immigrant status is another important independent variable (Table A8). Among the respondents, 15.39% (1,174) are immigrants while 84.61% (6,456) are Canadian-born. Immigration variables are significant because of their strong correlations with race, helping to analyze how immigrant status influences voter turnout and providing insights into the relationship between being an 48 immigrant and electoral participation. Additionally, the variable indicating origin from non-democratic countries is binary, with a significant majority of respondents (92.31%) coming from other regions and 7.69% originating from non-democratic countries (Table A16). The categorization of democratic and non-democratic countries is done based on global freedom score of Freedom House report (House, 2024). Countries scoring more than 80 out of 100 and categorized as "free" are classified as democratic. Furthermore, this analysis considers Canadian-born voters as originating from a democratic background. The other regions include respondents born in Canada as well as those from all other democratic countries. This reflects different trajectories of political assimilation, as posited by the Straight Line Assimilation Theory, affecting their political participation patterns in a new democratic context. The duration of residence in the current city, an ordinal variable, further provides context for political engagement. The majority of respondents (71.19%) have lived in their current city for more than 10 years, while 17.31% have been residents for 3-10 years, 8.18% for 1-3 years, and 3.32% for less than 1 year (Table A20). These variables collectively offer a comprehensive view of the factors influencing voter turnout, highlighting the interplay between socioeconomic resources, employment stability, political assimilation, and community integration. The variable language categorizes respondents into Anglophones/Francophones and Allophones. Out of all respondents, 93.79% speak English or French, which are the official languages in Canada, while 6.21% speak other languages. The summary statistics (Table A9) indicate a significant presence of non-English and non-French speakers in the sample. This separation of Allophones from Anglophones and Francophones in the analysis highlights the impact of language proficiency differences on voter turnout. Given the substantial portion of non-English and non-French speakers, this categorization helps better understand how language background influences electoral participation. Furthermore, considering the intersection of language barriers with race and immigration status provides more detailed insights into voter turnout dynamics. This categorization allows for a comprehensive analysis of how language background impacts voter turnout, particularly among respondents who speak languages other than English and French. These statistics lay the foundation for analyzing how demographic factors, intersecting with race, influence voter turnout in the Canadian electoral context. 49 We also incorporate demographic variables alongside race to examine the robustness of race's impact on voter turnout, taking into account theories like Social Identity Theory, the Resource Model, and Straight Line Assimilation Theory. These demographic variables, which include age, gender, region, education, religion, immigrant status, and language, are explored under the lens of these theories to understand voter behavior more comprehensively. The Resource Model shifts the focus towards the tangible assets individuals possess, such as time, money, and civic skills, suggesting that access to these resources is crucial for political engagement. This model helps in evaluating how socioeconomic factors, including education and immigrant status, affect voter turnout, offering insights into the disparities in political participation across different demographic segments. Finally, Straight Line Assimilation Theory provides a framework for understanding the dynamics of immigrant integration and its effect on voting patterns. According to this theory, as immigrants and their descendants assimilate into the host society, they gradually adopt its cultural norms and practices, including political participation. This theory is pertinent in analyzing how the process of assimilation influences the voting behavior of immigrants and ethnic minorities, suggesting that racial and ethnic disparities in voter turnout might diminish over generations as these groups integrate more fully into the societal fabric. By analyzing these variables in conjunction with the mentioned theories, we aim to determine the extent to which race remains a significant predictor of voter turnout when other influential demographic factors are considered. This holistic approach underscores the complex interplay of individual and societal characteristics in shaping electoral participation, offering a comprehensive perspective on the multifaceted nature of voter behavior in the 2021 Canadian Election. Incorporating additional variables such as political knowledge, discussion frequency about politics at home, perception of voting is a duty, partisanship, political interest, income categories, origin from non-democratic countries, employment status, satisfaction with COVID-19 handling, views on COVID-19 public health measures, duration of residence in the current city, and attitudes towards immigration and immigrants, the Complete model extends our analysis to explore the multifaceted influences on voter turnout and race in the 2021 Canadian Election. These variables interact with the phenomena explained by Social Identity Theory, the Resource Model, and Straight-Line Assimilation Theory to provide a nuanced understanding of electoral participation. 50 Political knowledge and the frequency of political discussions play into the resource model theory, suggesting that individuals with higher political knowledge and engagement in political discourse are more likely to vote, possessing greater civic skills. In this analysis, political knowledge is an independent variable, measured on a scale from 0 to 3, where higher values indicate greater awareness. The data (Table A11) shows that a considerable percentage of the electorate demonstrates substantial political awareness, with 34.29% having a knowledge level of 2 and 34.59% having a level of 3, while 21.65% have a score of 1 and 9.48% have no political knowledge (score of 0). Additionally, a significant portion of respondents engage in political discussions with family and friends, with 25.29% doing so often and 5.50% discussing politics all the time, while 60.33% discuss politics sometimes and 8.87% never engage in such discussions (Table A12). This engagement is complemented by the perception of voting as a civic duty, with 78.17% of respondents viewing it as such, compared to 21.83% who do not see it as a duty. The descriptive statistics in Table A13 depicts that the political knowledge indicates a diverse range of awareness among respondents, while the score for discussing politics demonstrates frequent engagement. The strong sense of civic responsibility, reflected in the high percentage of respondents who see voting as a duty, underscores the internalized motivations driving electoral participation. These factors collectively provide a nuanced understanding of the determinants of voter turnout, highlighting the interplay between political knowledge, discussion, and civic duty. The Resource Model and Straight Line Assimilation Theory are reflected in variables such as income, employment status, origin from non-democratic countries, and duration of residence in the current city. Income levels, an ordinal variable, categorized into four quantiles (0-40k, 40k-71k, 71k-110k, and 110k-higher), are evenly distributed among respondents, highlighting socioeconomic diversity within the electorate and suggesting varied access to resources that influence political participation (Table A10). Employment status is a binary variable, nearly equally divided between employed (47.43%) and unemployed (52.57%) respondents, underscoring the importance of economic stability as a resource for political engagement (Table A17). We categorized self-employed, retired, unemployed/looking for work, student, caring for a family, disabled as unemployed. On the other hand, working full time, working part time, student and working for pay, caring for family and working for pay, and retired and working for pay were categorized as employed. Categorizing individuals as either employed or unemployed simplifies the analysis of voter turnout by highlighting economic stability and social integration, which can 51 influence voting behavior. This approach provides a clearer understanding of how different socioeconomic experiences impact the likelihood of individuals to participate in elections. The incorporation of variables related to COVID-19 perceptions, satisfaction with governmental handling, and public health measures indicates the contemporary contextual factors that may influence voter behavior. One variable titled as ‘The public health recommendations aimed at slowing the spread of the COVID-19 virus are threatening my liberty’ (Views on COVID-19 public health measures against Liberty) captures public health recommendations' perceived threat, ranging from strongly agree (10.01%) to strongly disagree (53.21%), highlighting diverse attitudes toward pandemic measures (Table A19). Another covid-19 related variable (Satisfaction with COVID-19 handling) reflecting satisfaction with how authorities handled the outbreak, ranges from not at all satisfied (17.59%) to very satisfied (13.38%), indicating mixed satisfaction levels (Table A18). Views on immigration, captured through ‘Do you think Canada should admit ……. immigrants’, show that 29.93% of respondents think Canada should admit fewer immigrants, 44.67% believe the current numbers should be maintained, and 25.40% support admitting more immigrants (Table A21). Additionally, another variable measure feeling toward immigrant groups on a scale from 0 to 100, illustrating a broad spectrum of attitudes toward immigrants (Table A22). After the listwise deletion of PES variables, the distributions of key responses remained largely consistent, with minimal differences that were typically within a few percentage points between the original and post-deletion values. These small shifts are statistically negligible and indicate that the deletion had no meaningful impact on the overall representativeness of the dataset. One exception is the language variable, where the proportion of allophones, which was previously 33.13 percent, dropped significantly to 6.21 percent, reflecting a notable change in group representation. For the CPS dataset, the scenario mirrors the general trend observed here: most variables show negligible differences in proportions before and after listwise deletion, indicating that the deletion process largely preserved the representativeness of the sample. However, there are a few exceptions worth noting. For instance, the proportion of females increased from 45.18% to 50.51% (+5.33%), while males decreased from 54.23% to 49.07% (-5.16%). Similarly, the proportion of non-partisan identifiers dropped from 18.25% to 14.67% (-3.58%), and those who do not believe voting is a duty decreased from 25.04% to 21.83% (-3.21%). Despite these 52 examples, these shifts are neither deliberate nor drastically large—most remain within a few percentage points and do not suggest a systematic distortion of the dataset’s structure. These variables intersect in ways consistent with Social Identity Theory, influencing electoral participation through the formation of societal and political identities. Together, these variables enrich the analysis, offering insights into the complex interplay of individual characteristics, societal conditions, and political beliefs in shaping voter turnout and the impact of race in the Canadian electoral landscape. Based on the extensive analysis and incorporation of various theories and variables in the models discussed, we can formulate a series of hypotheses to systematically explore the factors influencing voter turnout in the 2021 Canadian Election. The primary hypothesis and subsequent related hypotheses are as follows: 4.3. Main Hypothesis H1: Race has a significant impact on voter turnout in the 2021 Canadian Election. H2: The impact of race on turnout in the 2021 Canadian Election can be explained by the correlation of race with the factors below. 4.4. Related Hypotheses H3: Individuals with higher levels of education are more likely to vote, suggesting that education positively influences voter turnout. H4: Older individuals are more likely to vote than younger ones, indicating that the likelihood of voting increases with age. H5: Immigrants exhibit lower voter turnout compared to native-born citizens in the 2021 Canadian Election. H6: Allophones, individuals whose home-speaking language is neither English nor French, are less likely to vote than Anglophones and Francophones, suggesting that linguistic barriers or differences may negatively influence voter turnout among this demographic group. 53 H7: Individuals with greater political knowledge are more likely to vote, indicating that political awareness positively influences voter participation. H8: People with a stronger sense of civic responsibility (civic duty) are more likely to vote, implying that a higher civic duty leads to higher voter turnout. H9: Party identification increases the likelihood of voter turnout in the 2021 Canadian Election. H10: Political Interest Positively Influences Voter Turnout in the 2021 Canadian Election. H11: Higher income individuals are more likely to vote, proposing that income level is positively associated with voter turnout. H12: Employed individuals are more likely to vote than unemployed ones, suggesting that employment status positively affects voter turnout. H13: Individuals with a positive view of COVID-19 public health measures and government handling are more likely to vote, indicating that positive perceptions of COVID-19 responses increase voter turnout. 4.5. Methodology This section outlines the methodology used in the analysis of voter turnout in the 2021 Canadian Federal Election. By employing logistic regression models, including a bivariate model, a socio-demographic model, and a complete model, we systematically assess how various factors influence voter turnout. To examine the relationship between the selected variables and voter turnout, we use logistic regression modeling due to the binary nature of the dependent variable. The models are specified as follows: Bivariate Model: This initial model assesses the impact of race alone on voter turnout. It serves as a baseline for understanding how race, as a singular factor, influences the likelihood of voting. ln (𝑃(Turnout = 1)1 − 𝑃(Turnout = 1)) = β0 + β1 ⋅ Race where β1 represents the log-odds of voter turnout for racialized minorities relative to White. 54 Socio-Demographic Model: This model incorporates additional socio-demographic variables alongside race, including education, gender, region, religion, immigrant status, and income category. This model assesses how race interacts with these factors in determining voter turnout. ln (𝑃(Turnout = 1)1 − 𝑃(Turnout = 1))= β0 + β1 ⋅ Race + β2 ⋅ Education + β3 ⋅ Gender + β4 ⋅ Region+. . . .. Complete Model: This final model extends the socio-demographic model by adding political engagement and COVID-19-related variables. It provides a comprehensive view of how both individual characteristics and contextual factors jointly influence voter turnout. ln (𝑃(Turnout = 1)1 − 𝑃(Turnout = 1))= β0 + β1 ⋅ Race + β2 ⋅ Education + β3 ⋅ Gender + β4 ⋅ Region + β5⋅ COVID-19 + β6 ⋅ Political Knowledge+. . . .. Here, 𝛽𝑖 coefficients represent the log-odds impact of each independent variable on the likelihood of voting, with all variables held constant. Model Estimation and Interpretation: The logistic regression models are estimated using the maximum likelihood estimation (MLE) method in Stata. Model goodness-of-fit is evaluated using the Likelihood Ratio (LR) chi-square test and pseudo R-squared values. These metrics provide insights into how well each model explains the variability in voter turnout. The significance of individual predictors is evaluated at conventional levels (p < 0.05, p < 0.01, p < 0.001), and robust standard errors are reported to address potential heteroscedasticity. Each model's output includes estimated log-odds coefficients, which indicate the direction and strength of each variable's impact on voter turnout. For instance, in the bivariate model, the coefficient for race is -0.51 (p < 0.001), indicating that racialized minorities are less likely to vote compared to Whites. This is supported by predicted probabilities, where racialized minorities show a voter turnout probability of 88%, compared to 92% for Whites, controlling for other factors. 55 Model Validation and Sensitivity Analysis: To ensure the robustness of findings, a sensitivity analysis is conducted by sequentially adding socio-demographic, political engagement, and COVID-19-related variables to the model. This approach allows examination of changes in the race coefficient across models, highlighting the extent to which additional factors account for variations in voter turnout. This progressive modeling approach reveals how the inclusion of socio-demographic and political variables reduces the independent effect of race, supporting the hypothesis that broader social and contextual factors contribute significantly to voter turnout differences. 4.6. Conclusion In this chapter, the study has outlined the data sources, research design, hypotheses, and research methodology that will guide the analysis of voter turnout in the 2021 Canadian Election. Utilizing the 2021 Canadian Electoral Studies (CES) dataset, this research seeks to explore the intricate relationship between racial identity and voter behavior, particularly focusing on turnout. The chapter provides a detailed description of the dependent and independent variables, emphasizing the role of race alongside various demographic, socio-economic, and attitudinal factors. Through the use of three models—Bivariate, Socio-Demographic, and Complete—this study aims to assess the robustness of race as a predictor of voter turnout when controlling for additional variables such as education, age, gender, immigrant status, and political knowledge. The hypotheses presented serve as a framework for systematically testing the influence of these variables, with a particular focus on understanding how race intersects with other factors to shape electoral participation. This comprehensive approach sets the stage for the empirical analysis that follows, aiming to contribute valuable insights into the factors influencing voter turnout in a diverse and complex electoral landscape. 56 5. Result Analysis This chapter analyzes the findings from regression models. I discuss the hypotheses based on the findings from these regression analyses. Table 1, Table 2, and Table 5 present the results of the regression models, which show the coefficient (log-odds) of each variable in the analysis. The bivariate model examines the impact of race specifically racialized minority on voter turnout in the 2021 Canadian Election. The socio-demographic model includes demographic variables along with race to explain how these factors impact voter turnout. Finally, the complete model incorporates additional controlling variables along with racialized minority and demographic variables. The three models are designed to clarify the impact of race independently, with socio-demographic factors, and with other socio-economic and political factors, providing a comprehensive understanding of the variables influencing voter turnout. 5.1. The Bivariate Model The bivariate model from the logistic regression analysis examines the relationship between race and voter turnout in the 2021 Canadian Federal Election. The model includes two racial categories, White and racialized minorities, where White is the reference category and racialized minority is the predictor of voter turnout. Before running the bivariate model, we observe that among the 6,090 White respondents, 7.73% reported not voting, while 92.27% reported voting in the recent federal election (see Table 1). In contrast, among racialized minority respondents, 12.27% did not vote and 87.73% reported that they did. The bivariate model's likelihood ratio chi-square test yields a value of 29.58 with a p-value of less than 0.001, indicating strong statistical significance. The pseudo R-squared value is 0.0066, suggesting that race explains a small portion of the variability in voter turnout (Table 1). Table 1: Cross tabulation between Turnout and Race Turnout White Racialized Minority Total No 471 (7.73%) 189 (12.27%) 660 (8.65%) Yes 5619 (92.27%) 1351 (87.73%) 6970 (91.35%) Total 6090 (100%) 1540 (100%) 7630 (100%) Note: Table 1 presents the cross-tabulation of turnout and race, including both frequencies and percentages. 57 The log-odds value of -0.51 for race means that being a member of a racialized minority group is associated with a lower likelihood of voting in the 2021 Canadian Election compared to White individuals. The model is statistically significant, and despite the low pseudo R-squared, it highlights a meaningful relationship between race and voter turnout. The constant term in the model was 2.48 with a p-value less than 0.001, which is highly significant. This term represents the log odds of turnout for the reference group (Whites) when all other variables are at zero, indicating a high baseline likelihood of turnout in this group. Overall, the findings suggest that race has a significant impact on voter turnout in the Canadian Election of 2021, with non-white racial groups generally showing a lower likelihood of turning out to vote compared to the White population. Table 2: Bivariate Regression Model Result Variable Coefficient (log-odds) Std. Error Race -0.51*** 0.09 Constant 2.48*** 0.05 Legend: *: p < 0.05, **: p < 0.01, ***: p < 0.001 Note: Table 1 presents the Bivariate regression results including variable turnout and race. The findings indicate significant negative impact of race on voter turnout. However, this model has 7,630 observations with only 29.58 LR Chi2, and 0.0066 pseudo R2. This analysis is based on data from the 2021 Canadian Electoral Study (CES) dataset, with White as the reference group for race. Figure 1 illustrates the estimated effect of being part of the racialized minorities group on the likelihood of voter turnout, as derived from the bivariate model. The central point on the graph represents the coefficient for racialized minorities, estimated at approximately -0.51, indicating a negative association with turnout. This negative coefficient suggests that individuals identified as racialized minorities are less likely to turn out to vote compared to White respondents. The vertical line extending from the coefficient shows the 95% confidence interval, which ranges from about -0.69 to -0.33. 58 Figure 1: Effect or Race on Turnout (Bivariate Model) Note: Figure 1 illustrates the effect of racialized minority status on voter turnout, as indicated by the coefficient from the bivariate model. It highlights the significant negative association between racialized minority status and voter turnout. Importantly, this confidence interval does not cross zero, signifying that the effect is statistically significant at the 95% confidence level. In other words, we can be confident that the observed negative association between racialized minority status and turnout is unlikely to be due to random variation. This figure visually reinforces the finding that race, specifically racialized minority status, is significantly associated with a reduced likelihood of voter turnout in this model. 5.1.1. Predicted Probability of Turnout by Race for Bivariate Model In Figure 2, the y-axis represents the predicted probability of voter turnout, while the x-axis categorizes the race variable into White and racialized minorities. For White individuals, the predicted probability of turnout is approximately 92%, which aligns with the positive constant in the logistic regression indicating high turnout for the reference group. In contrast, the predicted probability of turnout for racialized minorities drops to around 88%. This decrease reflects the negative coefficient for the race variable, highlighting the lower likelihood of voting among racialized minorities compared to Whites. Figure 2 also includes 95% confidence intervals, which illustrate the range within which we can be 95% confident the true predicted probabilities lie. For 59 White individuals, the confidence interval is narrow, indicating a precise estimate of the turnout probability. For racialized minorities, the confidence interval is slightly wider, but it still clearly shows a lower predicted turnout compared to Whites. In summary, Figure 2 effectively visualizes the logistic regression findings, demonstrating a significant difference in predicted voter turnout between White individuals and racialized minorities. This aligns with the regression results, highlighting the significant impact of race on voter turnout in the 2021 Canadian Election. The clear downward trend from White to racialized minorities visually represents the negative effect of being a racialized minority on voter turnout probability, reinforcing the statistical findings from the regression analysis. Figure 2: Predicted Probability of Turnout by Race for Bivariate Model Note: Figure 2 illustrates the significant difference in predicted voter turnout between White individuals and racialized minorities. This observation aligns with the statistical findings from the Bivariate model. 5.2. Socio-demographic Model The bivariate model and the socio-demographic model represent two different approaches to understanding voter turnout in the 2021 Canadian Election. The bivariate model focuses solely on 60 the relationship between racialized minorities and voter turnout, while the socio-demographic model incorporates a range of additional variables to provide a more comprehensive analysis. It expands the analysis to include various other predictors, such as education, gender, region, age, religion, immigrant status, language spoken at home (allophones), and income category. The model's likelihood ratio chi-square value is 317.49, with a highly significant p-value of 0.00, indicating that these additional socio-demographic factors collectively have a significant impact on voter turnout. The pseudo R-squared value is 0.0707, showing an improvement in explanatory power compared to the bivariate model (Table 2). Figure 3: Effect of Race on Turnout (Socio-demographic Model) Note: Figure 3 illustrates the effect of racialized minority status on voter turnout, as indicated by the coefficient from the socio-demographic model. It highlights the significant negative association between racialized minority status and voter turnout. The socio-demographic model provides a more nuanced understanding of voter turnout by incorporating multiple predictors. The coefficient for race is -0.27, still significant at the 0.01 level, but smaller in magnitude compared to the bivariate model. This indicates that while race remains a significant predictor of turnout, its apparent effect is partially accounted for by other socio-demographic factors included in the model. The negative coefficient of -0.27 indicates that being classified as a racialized minority decreases the likelihood of voter turnout compared to being 61 White, which is the reference category. Specifically, for individuals identified as racialized minorities, the log-odds of voting are lower by 0.27 units compared to White individuals, when all other variables in the model are held constant. Given the statistical significance of the race coefficient, this result suggests that race plays a significant role in predicting voter turnout, even when controlling for other socio-demographic factors. The figure 3 above shows that being in the racialized minorities group is associated with a lower likelihood of voter turnout, with an estimated coefficient of around -0.3. The 95% confidence interval (spanning from about -0.5 to -0.1) does not cross zero, indicating statistical significance. This suggests that race, specifically being a racialized minority, significantly reduces the likelihood of voting in this model. 5.2.1. Predicted Probability of Turnout by Race for Socio-demographic Model Figure 4 illustrates the predicted probability of voter turnout for two racial categories: White and racialized minorities, based on the socio-demographic logistic regression model. This model, which incorporates a variety of predictors such as education, gender, region, age, religion, immigrant status, and language spoken at home, aims to control for a wide range of socio-demographic factors to provide a comprehensive analysis of voter turnout. The predicted probabilities depicted in the figure 4 reflect these findings. For White individuals, the predicted probability of turnout is approximately 0.92, or 92%. This high probability aligns with the positive constant in the logistic regression, which reflects a high baseline log-odds of turnout for the reference category. In contrast, the predicted probability of turnout for racialized minorities is lower, around 0.9, or 90%. This decrease in predicted probability corresponds with the negative coefficient for the race variable, indicating a lower likelihood of voting for racialized minorities compared to White individuals. The figure 4 also includes 95% confidence intervals, providing a visual representation of the precision of these estimates. For White individuals, the confidence interval is narrow, indicating precise estimates of turnout probability. For racialized minorities, the confidence interval is slightly wider, but it still shows a clear decrease in predicted turnout compared to White individuals. This visual confirmation of the logistic regression findings reinforces the significant impact of race on voter turnout, even when controlling for various other socio-demographic factors. 62 Figure 4: Predicted Probability of Turnout by Race for Socio-Demographic Model Note: Figure 2 illustrates the significant difference in predicted voter turnout between White individuals and racialized minorities. This observation aligns with the statistical findings from the Socio-Demographic model. In summary, Figure 4 effectively demonstrates the significant difference in predicted voter turnout between White individuals and racialized minorities, aligning with the statistical findings from the regression model. The clear downward trend from White to racialized minorities visually represents the negative effect of being a racialized minority on the probability of turnout, highlighting the importance of considering race in understanding voter behavior in the 2021 Canadian Election. However, the diminishing gap between racial groups suggests that some of the apparent differences observed in the bivariate model were due to other socio-demographic variables. 63 Table 3: Socio-demographic Regression Model Results Variable Coefficient (log-odds) Std. Error Variable Coefficient (log-odds) Std. Error Race -0.27** 0 .11 Muslim 0.20 0.30 Education 0.13*** 0.02 Sikh 1.39 0.74 Gender -0.10 0.09 Anglican 0.42 0.27 Alberta 0.07 0.16 Baptist 0.51 0.38 British Columbia -0.10 0.15 Catholic 0.29** 0.11 Manitoba -0.10 0.24 Orthodox 0.25 0.38 New Brunswick -0.24 0.30 Jehovah's Witnesses -3.44*** 0.80 Newfoundland and Labrador -0.63 0.38 Lutheran -0.11 0.37 Northwest Territories -2.64** 0.73 Mormon -0.86 0.69 Nova Scotia -0.43 0.26 Pentecostal -0.06 0.28 Nunavut -2.64 1.50 Presbyterian 0.52 0.47 Prince Edward Island -1.29** 0.48 Protestant 0.27 0.22 Quebec -0.24* 0.11 United Church of Canada 0.97** 0.37 Saskatchewan -0.72** 0.26 Christian Reformed Church 2.02* 1.02 Yukon -0.91 0.78 The Salvation Army -0.43 0.65 Age 0.02*** 0 (0.003) Mennonite -0.82 0.58 Agnostic 0.52** 0.20 Immigrant -0.47*** 0.12 Buddhist 0.11 0.37 Allophones -0.30 0.17 Hindu 0.36 0.36 Income Category 0.27*** 0.04 Jewish 0.21 0.38 Constant -0.20 0.27 Legend: *: p < 0.05, **: p < 0.01, ***: p < 0.001 Note: Table 2 presents the Bivariate regression results including socio-demographic variables. This model has 7,630 observations with 317.49 LR Chi2, and 0.0707 pseudo R2. This analysis is based on data from the 2021 Canadian Electoral Study (CES) dataset, with White as the reference group for race, Ontario as the reference group for region, male as the reference group for gender, and atheist as the reference group for religion 5.2.2. Other Controlling Variables in Socio-demographic Model The Socio-demographic Model for the 2021 Canadian Election voter turnout also incorporates multiple socio-demographic factors, providing a nuanced view of how various characteristics influence voter participation. Table 3 examines the impact of race on voter turnout, specifically focusing on racialized minorities, while progressively adding various socio-demographic control 64 variables to the model. Initially, race alone has a significant negative effect on voter turnout (coefficient = -0.51, p < 0.001). As other factors such as education, gender, region, age, religion, immigrant status, language, and income are included, the magnitude of this negative effect decreases, ultimately reaching -0.27 with all controls. This reduction suggests that part of the lower voter turnout among racialized minorities can be explained by these socio-demographic factors. However, the race coefficient remains statistically significant even after controlling for all these variables, indicating that race independently contributes to reduced voter turnout. This underscores the complex interplay between race and other social factors in influencing political participation. Table 4 Changes of impact of racialized minorities while adding controlling variables in Socio-demographic model Variables Race coefficient Race -0.51*** Race and Education -0.58*** Race, Education, and Gender -0.57*** Race, Education, Gender, and Region -0.63*** Race, Education, Gender, Region, and Age -0.48*** Race, Education, Gender, Region, Age, and Religion -0.46*** Race, Education, Gender, Region, Age, Religion, and immigrant -0.32** Race, Education, Gender, Region, Age, Religion, immigrant, and Language -0.28* Race, Education, Gender, Region, Age, Religion, immigrant, Language, and Income -0.27* Legend: *: p < 0.05, **: p < 0.01, ***: p < 0.001 Note: This table is derived from the CES 2021 dataset and illustrates how the inclusion of socio-demographic control variables alters the impact of racialized minority status on voter turnout. Now we will discuss the coefficients of other controlling variables. Education has a positive coefficient of 0.13, suggesting that higher levels of education are associated with higher probabilities of voter turnout, a finding significant at the 0.000 level. It also displays a negligible standard error (see Table 2) along with the statistically significant coefficient. The coefficient for gender variable is -0.10, indicating that being female is associated with a lower likelihood of voting compared to males (as the reference category). However, this relationship is not statistically significant, as the p-value is greater than the conventional threshold of 0.05. This suggests that, after accounting for other variables in this model, there is no strong evidence to conclude that gender (female) significantly impacts voter turnout in the 2021 Canadian Election. 65 The logistic regression model includes various regional dummy variables to understand the impact of different regions on voter turnout, with Ontario serving as the reference category. The results highlight the influence of regional differences on voter turnout in the 2021 Canadian Election. The model reveals that several regions show a statistically significant decrease in voter turnout compared to Ontario. The Northwest Territories, with a strongly negative coefficient of -2.64, show a substantial decrease in voter turnout likelihood. Quebec also displays a significant negative effect with a coefficient of -0.24, and Prince Edward Island follows suit with a negative coefficient of -1.29 (see Table 2). Saskatchewan shows significant negative effect with a coefficient of -.72. These results collectively suggest that individuals in these regions are less likely to turn out to vote compared to those in Ontario. Other regions, including Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Nunavut, and Yukon, do not show statistically significant differences in voter turnout when compared to Ontario. This indicates that living in these regions does not significantly affect the probability of voter turnout in the context of the 2021 Canadian Election (see Table 2). In summary, the socio-demographic model demonstrates that regional differences can significantly impact voter turnout. Regions such as Northwest Territories, Saskatchewan, Quebec, and Prince Edward Island show a lower likelihood of turnout compared to Ontario. These findings underscore the importance of considering regional factors when analyzing voter behavior and turnout patterns in elections. The logistic regression model also examines the impact of age on voter turnout. Age is treated as a continuous variable, and its coefficient indicates the change in the log-odds of voting associated with each one-year increase in age. The coefficient for age is 0.02, and it is highly statistically significant with a p-value of less than 0.001 (see Table 2). This positive coefficient suggests that as age increases, the likelihood of voter turnout also increases. Specifically, for each additional year of age, the log-odds of voting increase by 0.02. This finding is consistent with the well-documented trend that older individuals are more likely to vote compared to younger individuals. In practical terms, this means that age is an important predictor of voter turnout in the 2021 Canadian Election. As individuals get older, they are increasingly likely to participate in voting. The highly significant result underscores the robust nature of this relationship, indicating that age plays a critical role in influencing voter behavior. 66 This model also includes various religious affiliations to understand their impact on voter turnout, with Atheists serving as the reference category. The results highlight how different religious affiliations influence voter turnout in the 2021 Canadian Election. Several religious affiliations show a statistically significant increase in the likelihood of voter turnout compared to Atheists. Agnostics, for instance, have a positive coefficient of 0.52, indicating that individuals identifying as Agnostic are more likely to vote (see Table 2). Similarly, Catholic, United Church of Canada, and Christian Reformed Church exhibit positive coefficient of 0.29, 0.97, and 2.02 respectively, suggesting higher likelihood of voter turnout. On the other hand, Jehovah's Witnesses exhibit a significantly negative impact on voter turnout with a coefficient of -3.44. This substantial negative coefficient indicates that individuals identifying as Jehovah's Witnesses are much less likely to vote compared to Atheists. Other religious affiliations, including Buddhists, Hindus, Jews, Muslim, Sikh, Anglican, Baptists, Orthodox Christians, Lutherans, Mormons, Pentecostals, Presbyterians, Protestand, members of the Salvation Army, and Mennonites, do not show statistically significant differences in voter turnout compared to Atheists. This suggests that these religious affiliations do not significantly affect the probability of voter turnout in the context of the 2021 Canadian Election. In summary, the socio-demographic model reveals that religious affiliation can significantly influence voter turnout. Agnostics, Catholics, and individuals affiliated with the United Church of Canada and Christian Reformed Church are more likely to vote compared to Atheists. Conversely, Jehovah's Witnesses are less likely to vote. These findings highlight the importance of considering religious factors when analyzing voter behavior and turnout patterns in elections. This model also includes the variable for immigrant status to understand its impact on voter turnout. The coefficient for immigrant status is -0.47, and it is highly statistically significant with a p-value of less than 0.001 (see Table 2). This negative coefficient indicates that being an immigrant decreases the likelihood of voter turnout compared to being a non-immigrant. Specifically, the log-odds of voting are lower by 0.43 units for immigrants compared to non-immigrants. This significant negative effect suggests that immigrants are less likely to vote than native-born individuals. This finding aligns with some of the previous research indicating that various barriers and constraints can contribute to lower voter turnout among immigrants. 67 According to this model immigrant status is a crucial predictor of voter turnout in the 2021 Canadian Election. The substantial and statistically significant negative coefficient for immigrant status underscores the importance of addressing the unique barriers faced by immigrants to increase their electoral participation. This model also includes the variable for allophones to understand its impact on voter turnout. In this context, allophones refer to individuals whose first language is neither English nor French. The coefficient for allophones is -0.33, which is not statistically significant with a p-value of greater than 0.05. It reflects that the languages people speak at home do not significantly influence their decision to participate in the election. The variable "income category" is divided into four quantiles: 0-40k, 40k-71k, 71k-110k, and 110k and higher. This categorical variable captures the respondents' household income levels, providing insight into the economic dimension of voter turnout in this model. The finding in socio-demographic model represents income categories has a significant positive impact on voter turnout. The coefficient for income category is 0.27 with a p-value less than 0.001, indicating that higher income categories are associated with an increased likelihood of voting. This suggests that individuals with higher income levels are more likely to participate in the election. In summary, the socio-demographic model provides a comprehensive analysis of voter turnout, revealing that race, while still significant, is one of many factors influencing voting behavior. Other significant predictors include education, gender, age, region, religion, immigrant status, income category. This model highlights the importance of considering a wide range of socio-demographic factors to fully understand voter turnout patterns. 5.3. Complete Model The complete model presents a more refined logistic regression analysis of voter turnout for the 2021 Canadian Election, incorporating an extensive array of socio-demographic, political, and psychological variables, reflecting a significant improvement in the model's explanatory power. This model includes 51 predictors, significantly expanding on the variables considered in the bivariate and socio-demographic models. This is a subset of the original dataset used in the bivariate and socio-demographic models. The reduction in the number of observations may be due to missing data for some of the additional variables included in the complete model. 68 The LR chi-square for the complete model is 962.72 (Table 3). This value is substantially higher than the LR chi-square values for the bivariate model (29.58) and the socio-demographic model (271.18). The LR chi-square statistic tests the null hypothesis that all coefficients are equal to zero. The higher value in the complete model indicates a much better fit of the model to the data, suggesting that the additional variables significantly improve the explanation of voter turnout. The p-value associated with the LR chi-square statistic is less than 0.0000 in the complete model. This is the same for both the bivariate and socio-demographic models. A p-value this low indicates that the likelihood of observing the data given that all coefficients are zero is extremely small, leading us to reject the null hypothesis. This confirms that the complete model, like the previous models, significantly predicts voter turnout. The pseudo R-squared for the complete model is 0.2143. This is a marked improvement compared to the bivariate model (0.0066) and the socio-demographic model (0.0604). The pseudo R-squared value indicates the proportion of variance in the dependent variable (voter turnout) that is explained by the independent variables. The substantial increase in the pseudo R-squared value in the complete model indicates that the additional variables included provide a much more comprehensive explanation of voter turnout. In the complete model, the coefficient for race is -0.22 and a p-value of more than 0.05. This indicates that, holding all other variables constant, being a racialized minority reduces the likelihood of voter turnout compared to being White. However, this effect is not statistically significant at the conventional 5% level, as the p-value is above 0.05. This suggests that when a comprehensive set of socio-demographic, political, and contextual variables are considered, the direct impact of race on voter turnout becomes less pronounced and is not statistically significant. The impact of race on voter turnout diminishes as more variables are included in the model. In the bivariate model, race appears to be a strong and significant predictor of voter turnout, with racialized minorities being significantly less likely to vote compared to White individuals. When additional socio-demographic variables are added in the socio-demographic model, the coefficient for race decreases in magnitude but remains significant. This indicates that some of the apparent impact of race is in fact linked to other socio-demographic factors such as income, education, gender, and region. These additional variables likely account for some of the disparities in voter turnout initially attributed to race alone. In the complete model, the coefficient for race further decreases and loses statistical significance. This suggests that when political engagement 69 variables (such as political knowledge, voting duty, and partisanship) and contextual factors (such as COVID satisfaction and current city residence) are included, the direct effect of race on voter turnout is further attenuated. The reduction in the magnitude and significance of the race coefficient highlights that the relationship between race and voter turnout is influenced by a complex interplay of various factors. Figure 5: Effect of Race on Turnout (Complete Model) Note: Figure 5 illustrates the effect of racialized minority status on voter turnout, as indicated by the coefficient from the complete model. It highlights that the negative association between racialized minority status and voter turnout loses statistical significance when all control variables are included. The figure illustrates the effect of race on voter turnout among racialized minorities, using data from the complete model. The coefficient for race (-0.22) indicates a slight negative association with turnout, suggesting that racialized minorities might have lower voting rates compared to non-racialized minorities. However, this effect is not statistically significant (p-value = 0.078), and the confidence interval includes zero, implying uncertainty around this estimate. Therefore, while there may be a trend, the result is not conclusive enough to assert a clear impact of race on turnout within this model. 70 5.3.1. Predicted Probability of Turnout by Race for Complete Model: The figure 6 presents the predicted probability of voter turnout for two racial categories: White individuals and racialized minorities, based on the complete model. The predicted probability of voter turnout for White individuals is approximately 0.92. In contrast, for racialized minorities, the predicted probability is slightly lower, around 0.90. This slight difference suggests that, on average, racialized minorities are predicted to have a marginally lower likelihood of voting compared to White individuals. However, the small magnitude of this difference reflects the findings from the complete model, where the race variable has a coefficient of -0.22 with a p-value of greater than 0.05, indicating that the effect of race on voter turnout is not statistically significant. Figure 6: Predicted Probability of Turnout by Race for Complete Model Note: Figure 6 illustrates the significant difference in predicted voter turnout between White individuals and racialized minorities. This observation aligns with the statistical findings from the Complete model. The confidence intervals provide additional insight into the precision of these predictions. For White individuals, the confidence interval is relatively narrow, suggesting a more precise estimate of their predicted probability of turnout. In contrast, the confidence interval for racialized 71 minorities is wider, indicating greater variability and less precision in the predicted probability for this group. The overlap between the confidence intervals of the two groups further supports the conclusion that the difference in predicted probabilities is not statistically significant. This figure's visualization reinforces the notion that, while there may be a small difference in voter turnout probability between White individuals and racialized minorities, this difference is not substantial enough to be deemed statistically significant. The complete model, which controls for a comprehensive set of socio-demographic, political, and contextual variables, shows that the direct impact of race on voter turnout diminishes when these factors are considered. In summary, figure 6 illustrates that the predicted probability of voter turnout is slightly lower for racialized minorities than for White individuals. However, the small difference and overlapping confidence intervals indicate that this difference is not statistically significant. This aligns with the findings from the complete model, suggesting that race, when considered alongside a range of other variables, does not have a significant direct effect on voter turnout. 5.3.2. Other Controlling Variables: Table 4 expands on the previous analysis by incorporating additional political and attitudinal variables to create a comprehensive model for understanding the impact of race on voter turnout. Initially, with only socio-demographic controls, the race coefficient is -0.27 (significant at p < 0.05), indicating a negative effect of being a racialized minority on voter turnout. However, as further political and attitudinal factors are added—such as political knowledge, frequency of political discussions at home, sense of duty to vote, partisanship, political interest, origin from non-democratic countries, employment status, Covid-19 impacts, and attitude towards immigrants—the race coefficient decreases to approximately -0.22. Importantly, these additional variables eliminate the statistical significance of the race coefficient, as it no longer meets the p < 0.05 threshold. This reduction in significance suggests that the initial negative effect of race on voter turnout can largely be explained by these added socio-demographic and political factors. In other words, once these comprehensive controls are included, race alone does not significantly impact voter turnout. This finding highlights that racial disparities in voter participation are largely associated with broader socio-political and attitudinal influences rather than race itself. 72 Table 5: Changes of impact of racialized minorities while adding controlling variables in Complete model Variables Race Coefficient Race, Education, Gender, Region, Age, Religion, immigrant, Language, and Income (Socio-Demographic Model) -0.27* Race, Education, Gender, Region, Age, Religion, immigrant, Language, Income, and Political Knowledge -0.27* Race, Education, Gender, Region, Age, Religion, immigrant, Language, Income, Political Knowledge, and Discussion frequency about politics at home -0.24* Race, Education, Gender, Region, Age, Religion, immigrant, Language, Income, Political Knowledge, Discussion frequency about politics at home, and Voting is a duty -0.24* Race, Education, Gender, Region, Age, Religion, immigrant, Language, Income, Political Knowledge, Discussion frequency about politics at home, Voting is a duty, and Partisanship -0.23 Race, Education, Gender, Region, Age, Religion, immigrant, Language, Income, Political Knowledge, Discussion frequency about politics at home, Voting is a duty, Partisanship, Political Interest -0.24* Race, Education, Gender, Region, Age, Religion, immigrant, Language, Income, Political Knowledge, Discussion frequency about politics at home, Voting is a duty, Partisanship, Political Interest, and Origin from non-democratic countries -0.21 Race, Education, Gender, Region, Age, Religion, immigrant, Language, Income, Political Knowledge, Discussion frequency about politics at home, Voting is a duty, Partisanship, Political Interest, Origin from non-democratic countries, and Employment -0.22 Race, Education, Gender, Region, Age, Religion, immigrant, Language, Income, Political Knowledge, Discussion frequency about politics at home, Voting is a duty, Partisanship, Political Interest, Origin from non-democratic countries, Employment, and Covid-19 Impacts -0.21 Race, Education, Gender, Region, Age, Religion, immigrant, Language, Income, Political Knowledge, Discussion frequency about politics at home, Voting is a duty, Partisanship, Political Interest, Origin from non-democratic countries, Employment, and Covid-19 Impacts, and Attitude towards Immigrant -0.22 Note: This table is derived from the CES 2021 dataset and illustrates how the inclusion of all other control variables alters the impact of racialized minority status on voter turnout. This section will discuss the coefficient of other variables and how they affect the voter turnout in 2021 Canadian Election. In the complete model, the coefficient for education is 0.01, with a p-value greater than 0.05. This coefficient indicates that, holding all other variables constant, an increase in the level of education slightly increases the log-odds of voter turnout, suggesting a very modest positive impact of education on the likelihood of voting. However, the effect of education 73 on voter turnout is not statistically significant, as the p-value is well above the conventional 0.05 threshold. This lack of significance suggests that, within the context of the complete model, education does not have a strong independent effect on voter turnout when other socio-demographic, political, and contextual factors are considered. When moving from the socio-demographic model to the complete model, the coefficient for education decreases substantially from 0.13 to 0.01, and the statistical significance is lost (p-value increases from less than 0.001 to greater than 0.05). This change indicates that the initially observed strong positive effect of education on voter turnout in the socio-demographic model is largely explained by other factors included in the complete model. These additional variables, such as political knowledge, voting duty, and partisanship, likely account for much of the explanatory power previously attributed to education. In summary, while education appears to be a strong predictor of voter turnout in the socio-demographic model, its effect is significantly diminished in the complete model. This suggests that the relationship between education and voter turnout is more complex and is influenced by other variables that better capture the nuances of political engagement and behavior. The coefficient for gender is 0.03 in the complete model. This coefficient indicates that, holding all other variables constant, being female has a very slight positive effect on the likelihood of voter turnout compared to being male. However, similar to education this effect is also not statistically significant, as the p-value is greater than 0.05. This suggests that, within the context of the complete model, gender does not have a significant independent effect on voter turnout when other socio-demographic, political, and contextual factors are considered. In order to better understand the possible relationship between gender, race, and immigration status, additional analyses are presented in the Appendix. Table B1 (see the Appendices) presents the individual and combined impacts of immigrant and gender on voter turnout. The results indicate that being an immigrant is associated with a significant decrease in voter turnout, with a coefficient of -0.57. Additionally, being female is linked to a further reduction in turnout, with a coefficient of -0.34. However, the interaction between immigrant status and gender shows a positive coefficient of 0.20, suggesting a slight increase in turnout for immigrant women compared to their male counterparts, though this effect is not statistically significant. Overall, the individual 74 impacts of immigrant status and gender on voter turnout are significant, while their combined effect does not show a distinct influence. This regression (Table B2) includes race with gender identity to identify the impact of gender of racialized minorities on voter turnout. The results show that being from a racialized minority group is associated with a significant decrease in voter turnout, with a coefficient of -0.55. Similar to the findings in Table B1, being female is also associated with a decrease in turnout, with a coefficient of -0.31. The interaction between race and gender yields a small positive coefficient of 0.09, indicating a slight increase in turnout for women from racialized minority groups compared to their male counterparts, but this effect is not statistically significant. Thus, while both race and gender independently affect voter turnout, their combined effect does not significantly differ from their individual impacts. Similar to the Complete model when we add all the confounding variables in this analysis gender itself does not significantly impact voter turnout, as indicated by a non-significant coefficient of 0.04 (See Table B3 in Appendices). Furthermore, when examining the interaction between gender and race, as well as gender and immigrant status, the results show no statistically significant effects on voter turnout. Specifically, the gender-race interaction and the gender-immigrant interaction both have non-significant coefficients, suggesting that the impact of gender does not vary significantly by race or immigration status. The analysis in Table 5 shows that several regions demonstrate a statistically significant impact on voter turnout in this model. Specifically, residents of the Northwest Territories, Nunavut, Quebec, and Saskatchewan are less likely to vote compared to the reference category (Ontario), with coefficients of -2.28, -3.58, -0.74, and -0.70, respectively, all showing p-values smaller than 0.05. These coefficients indicate that living in these regions decreases the log-odds of voter turnout, suggesting a significant negative effect on the likelihood of voting in these areas. Conversely, other regions such as Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Prince Edward Island, and Yukon do not exhibit statistically significant impacts on voter turnout, as their p-values are greater than 0.05. These results suggest that while some regional differences significantly and negatively affect voter behavior, others do not, highlighting the complex interplay of regional factors in determining voter turnout. 75 In comparing the socio-demographic model to the complete model, there are notable changes in the significance and impact of regional variables on voter turnout. In the socio-demographic model, regions such as Northwest Territories, Saskatchewan, Quebec, and Prince Edward Island showed significant negative impacts on voter turnout. However, some of these effects lose statistical significance in the complete model, except Northwest Territories, Quebec, and Saskatchewan, suggesting that additional variables in the complete model, like political knowledge, voting duty, and partisanship, explain much of the previously attributed regional variability. Overall, the complete model provides a more nuanced understanding of regional impacts on voter turnout, highlighting the importance of considering a comprehensive set of variables. In the complete model, the coefficient for age is 0.00 (0.003), indicating a very slight positive effect on voter turnout with each additional year of age; however, this effect is not statistically significant as the p-value is greater than 0.05. This suggests that, within the context of the complete model, age does not have a significant independent impact on voter turnout when other socio-demographic, political, and contextual factors are considered. This impact does not align with common patterns observed in electoral studies. The transition from the socio-demographic model to the complete model reveals that the initially strong and significant positive effect of age on voter turnout diminishes and becomes statistically insignificant when additional variables are included. The increased pseudo R-squared value of 0.2143 in the complete model suggests a better fit and more comprehensive explanation of voter turnout. This shift underscores the importance of considering a broader set of factors to fully understand the influences on voter behavior, illustrating that age alone, when isolated from other influences, does not significantly impact voter turnout in the context of the complete model. The effect of religion on voter turnout varies across different religious affiliations in the complete model, with some showing significant impacts and others not. Among the significant ones, Jehovah's Witnesses have a substantial negative effect on voter turnout, with a coefficient of -2.37 and a p-value smaller than 0.01, indicating they are significantly less likely to vote compared to the reference category (Atheists). Additionally, individuals identifying as agnostic also show a significant positive effect on voter turnout, with a coefficient of 0.45 and a p-value smaller than 0.05. These findings suggest that while Jehovah's Witnesses are less likely to vote, agnostics are 76 more likely to participate in voting. Conversely, other religious affiliations (Table 5) do not show statistically significant impacts on voter turnout in the complete model, as their p-values are greater than 0.05. This indicates that, for these groups, religion does not independently influence voter turnout when considering the broader set of socio-demographic, political, and contextual variables included in the complete model. Comparing these findings to the socio-demographic model, there are notable changes in the significance and impact of religious affiliations. In the socio-demographic model, several religious groups, such as Agnostics, Catholics, and individuals affiliated with the United Church of Canada and Christian Reformed Church, showed significant positive effects on voter turnout, indicating that individuals from these religious backgrounds were more likely to vote compared to Atheists. Jehovah's Witnesses also had a significant negative effect on turnout, similar to the complete model. However, in the complete model, the significance of many religious groups diminishes. For instance, Catholics, and individuals affiliated with the United Church of Canada and Christian Reformed Church, who were significant in the socio-demographic model, become statistically insignificant in the complete model. This shift indicates that the additional variables in the complete model account for much of the variability in voter turnout that was previously attributed to religious affiliation. In summary, while certain religious affiliations like Jehovah's Witnesses and agnostics continue to show significant effects on voter turnout in the complete model, many other groups that were significant in the socio-demographic model lose their significance. This highlights the importance of a comprehensive approach in understanding voter behavior, showing that the relationship between religion and voter turnout is more complex and influenced by a broader range of factors than initially observed in the simpler model. For immigrant status, the coefficient is -0.29 with a p-value greater than 0.05, indicating that being an immigrant has a marginally negative but not statistically significant impact on voter turnout when considering all other variables in the model. This suggests that immigrant status alone does not independently affect voter turnout significantly in the context of the complete model. In the socio-demographic model, the coefficient for immigrant status is -0.47 with a p-value smaller than 0.001, indicating a significant negative impact on voter turnout. This suggests that, in the socio-77 demographic model, being an immigrant appears to significantly reduce the likelihood of voting. When moving to the complete model, the coefficient for immigrant status decreases in magnitude to -0.29 and becomes statistically insignificant (p-value greater than 0.05). This change indicates that the significant negative effect of immigrant status on voter turnout observed in the socio-demographic model is mitigated when additional variables, such as political knowledge, voting duty, partisanship, and other contextual factors, are included in the analysis. These additional variables likely capture the complex factors influencing voter behavior that were previously attributed to immigrant status alone. The variable Origin from non-democratic countries, which captures whether an individual comes from a non-democratic country, has a coefficient of -0.23 with a p-value greater than 0.05. This indicates that originating from a non-democratic country has a negative but statistically insignificant effect on voter turnout. This suggests that, within the context of this model, there is no strong evidence to conclude that immigrants from non-democratic countries have different voter turnout rates compared to those from democratic countries, whether immigrants or Canadian-born. Attitudes towards immigrants are captured through two variables: 1. Do you think Canada should admit ……. immigrants and 2. Feelings towards Immigrants. Both variables have coefficients that are not statistically significant, with the former having a coefficient of 0.03 and a p-value greater than 0.05, and later having a coefficient of 0.00 with a p-value greater than 0.05. This indicates that neither the general attitude towards admitting immigrants nor the likability of immigrants significantly influences voter turnout in the complete model. In the complete model, the "duration of residence in the current city " variable, which measures the length of residence in the respondents' current city or community, has a coefficient of 0.23 and a p-value smaller than 0.001. This indicates that the length of residence has a statistically significant positive impact on voter turnout. Specifically, longer-term residents are more likely to vote, suggesting that stability and integration within a community enhance civic engagement. The significant positive effect highlights that individuals who have lived in their current city for longer periods are more likely to participate in voting, reflecting stronger community ties and a greater sense of civic duty. 78 Table 6: Complete Regression Model Results Variable Coefficient (log-odds) Std. Error Variable Coefficient (log-odds) Std. Error Race -0.22 0.13 Jehovah's Witnesses -2.37** 0.84 Education 0.01 0.03 Lutheran -0.45 0.39 Gender 0.03 0.1 Mormon -1.16 0.74 Alberta -0.26 0.18 Pentecostal -0.26 0.31 British Columbia -0.25 0.17 Presbyterian 0.22 0.49 Manitoba -0.39 0.26 Protestant 0.08 0.24 New Brunswick -0.21 0.32 United Church of Canada 0.72 0.39 Newfoundland and Labrador -0.71 0.41 Christian Reformed Church 1.88 1.03 Northwest Territories -2.28** 0.91 The Salvation Army -0.29 0.7 Nova Scotia -0.46 0.28 Mennonite -0.67 0.63 Nunavut -3.58** 1.44 Immigrant -0.29 0.18 Prince Edward Island -1.05 0.58 Allophones -0.24 0.19 Quebec -0.74*** 0.14 Income Category 0.14** 0.05 Saskatchewan -0.70* 0.29 Political knowledge 0.23*** 0.06 Yukon -0.59 0.88 Discussion frequency about politics at home 0.14 0.08 Age 0 (0.004) 0 (0.004) Voting is a duty 1.55*** 0.1 Agnostic 0.45* 0.21 Partisanship 0.55*** 0.11 Buddhist 0.22 0.41 Political Interest 0.16*** 0.02 Hindu 0.12 0.39 Origin from non-democratic countries -0.23 0.23 Jewish 0.09 0.4 Employment 0.32** 0.1 Muslim 0.22 0.33 Satisfaction with COVID-19 handling -0.14* 0.06 Sikh 0.76 0.77 Views on COVID-19 public health measures against Liberty 0.07* 0.03 Anglican 0.29 0.29 Duration of residence in the current city 0.23*** 0.05 Baptist 0.37 0.4 Do you think Canada should admit ……. immigrants 0.03 0.08 Catholic 0.21 0.12 Feelings towards Immigrants 0 0 Orthodox 0.14 0.4 Constant -2.01*** 0.38 Legend: *: p < 0.05, **: p < 0.01, ***: p < 0.001 79 Note: Table 5 presents the Complete regression results including all the confounding variables. This model also has 7,630 observations with 962.72 LR Chi2, and 0.2143 pseudo R2. This analysis is based on data from the 2021 Canadian Electoral Study (CES) dataset, with White as the reference group for race, Ontario as the reference group for region, male as the reference group for gender, and atheist as the reference group for religion. The coefficient for the allophone variable is -0.24, with a p-value greater than 0.05. This indicates that being an allophone (a person whose first language is neither English nor French) has a slight negative effect on the likelihood of voter turnout. However, this effect is not statistically significant, suggesting that, within the context of the complete model, being an allophone does not have a significant independent impact on voter turnout when other socio-demographic, political, and contextual factors are accounted for. This finding is consistent with the results of the socio-demographic model, indicating that language does not impact voter turnout during the 2021 Canadian Election. The variable "voting as a duty" captures whether respondents perceive voting as a civic obligation. In the complete model, this variable has a coefficient of 1.55, with a p-value smaller than 0.001, indicating a highly significant positive effect on voter turnout. This suggests that individuals who view voting as a duty are substantially more likely to vote. The strong significance of this variable underscores the importance of civic duty in motivating electoral participation, suggesting that a sense of responsibility towards voting significantly boosts turnout rates. Political knowledge measures the extent of respondents' understanding of political matters. It is divided into four categories based on the level of knowledge. In the complete model, the coefficient for political knowledge is 0.23, with a p-value smaller than 0.001, indicating a statistically significant positive effect on voter turnout. This means that individuals with higher political knowledge are more likely to vote. This finding highlights the crucial role that being informed about political issues plays in driving voter participation. Knowledgeable voters are likely more aware of the importance of their vote and the impact of elections on their lives, thereby increasing their propensity to vote. Frequency of discussing politics at home assesses how often respondents talk about politics with family and friends. This variable has a coefficient of 0.14 with a p-value of 0.08 in the complete model. Although the effect is positive, it is not statistically significant. This suggests that while 80 frequent political discussions can slightly increase the likelihood of voting, this effect is not significant as the effects of viewing voting as a duty or having high political knowledge. In the complete model, the variable "partisanship" captures whether respondents identify with a political party in federal politics. This is a categorical variable with two categories: "non-identifier" and "identifier." An "identifier" refers to respondents who align themselves with a specific political party, while a "non-identifier" refers to those who do not. The coefficient for partisanship in the complete model is 0.55, with a p-value smaller than 0.001, indicating a highly significant positive effect on voter turnout. This suggests that individuals who identify with a political party are significantly more likely to vote compared to those who do not. The strong significance of this variable highlights the critical role of political party identification in motivating electoral participation. Partisanship as a variable reflects a psychological attachment to a political party, which often translates into a higher likelihood of voting. Party identifiers are more likely to feel a sense of loyalty and obligation to support their party during elections, contributing to higher voter turnout. This finding underscores the importance of party affiliation in driving political engagement and participation. In the complete model, the variable "political interest" measures respondents' general interest in politics. This is a continuous variable ranging from 0 to 10, with higher values indicating greater interest in politics. The coefficient for political interest in the complete model is 0.16, with a p-value smaller than 0.001, indicating a highly significant positive effect on voter turnout. This means that as an individual's interest in politics increases, their likelihood of voting also increases significantly. The strong significance of this variable underscores the importance of political engagement in driving electoral participation. Political interest as a variable reflects an individual's general enthusiasm and attention towards political matters. Higher levels of political interest often translate into greater awareness of political issues, candidates, and the importance of elections, all of which contribute to a higher propensity to vote. This finding highlights that individuals who are more politically interested are more likely to engage in the voting process, reaffirming the crucial role of political engagement in fostering democratic participation. 81 The coefficient for the income category in the complete model is 0.14, with a p-value smaller than 0.01, indicating a statistically significant positive effect on voter turnout. This suggests that higher income levels are associated with a greater likelihood of voting. However, in the complete model, the coefficient for the income category decreases to 0.14. While it remains positive and significant, the reduced coefficient implies that the impact of income on voter turnout is less pronounced when additional factors, such as political knowledge, interest, partisanship, and other socio-political variables, are accounted for. This finding underscores the importance of economic status in influencing electoral participation. Income as a variable reflects not only the economic capacity of individuals but also their potential access to resources that facilitate political engagement, such as information, time, and social networks, due to their economic well-being. Higher income individuals may have more opportunities to engage with political processes and are more likely to perceive voting as a way to protect their economic interests. The significant positive effect of income category on voter turnout indicates that economic stability and prosperity are important factors in motivating individuals to participate in elections. The variable "employment status" distinguishes between employed and unemployed individuals. This categorical variable encompasses a range of employment situations: unemployed individuals include those who are self-employed, retired, unemployed/looking for work, students, caregivers, and disabled persons. Employed individuals include those working full-time, part-time, students working for pay, caregivers working for pay, and retirees working for pay. The coefficient for employment status in the complete model is 0.32, with a p-value smaller than 0.01, indicating a statistically significant positive effect on voter turnout. This suggests that being employed is associated with a higher likelihood of voting compared to being unemployed. The significant positive coefficient indicates that employment status is a crucial factor influencing electoral participation. Employment as a variable reflects not only the economic stability of individuals but also their social engagement and integration into the community. Employed individuals may have more regular schedules, greater access to information, and stronger social networks, all of which can facilitate political engagement and increase the propensity to vote. The significant positive effect of employment on voter turnout highlights the importance of economic and social stability in motivating individuals to participate in elections. 82 The variable "satisfaction with COVID-19 handling" measures respondents' satisfaction levels with how authorities managed the COVID-19 outbreak. It is categorized into four levels: not at all satisfied, not very satisfied, fairly satisfied, and very satisfied. In the complete model, the coefficient for satisfaction with COVID-19 handling is -0.14, with a p-value smaller than 0.05, indicating a statistically significant negative effect on voter turnout. This suggests that higher satisfaction with COVID-19 handling is associated with a slight decrease in the likelihood of voting, as indicated by the log-odds. This counterintuitive finding may reflect complex underlying dynamics, such as a perception of government performance reducing the urgency to vote for change. The variable "views on COVID-19 public health measures against liberty" measures respondents' agreement with the statement that public health recommendations aimed at slowing the spread of COVID-19 are threatening personal liberties. This variable is categorized into five levels: strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, and strongly disagree. In the complete model, the coefficient for views on COVID-19 public health measures against liberty is 0.07, with a p-value smaller than 0.05, indicating a statistically significant positive effect on voter turnout. This suggests that individuals who do not perceive public health measures as a threat to their liberties are more likely to vote. This could be driven by a desire to influence policy decisions or express content with the current handling of public health measures. The inclusion of COVID-19 related variables in the complete model reveals significant insights into voter behavior during the pandemic. Higher satisfaction with COVID-19 handling slightly decreases the likelihood of voting, possibly reflecting complacency or contentment with the status quo. Conversely, perceiving public health measures as not a threat to personal liberties increases the likelihood of voting, indicating that concerns over personal freedoms can drive electoral participation. These findings highlight the nuanced and multifaceted impacts of the COVID-19 pandemic on voter turnout, emphasizing the importance of considering public health perceptions and satisfaction with governmental responses in understanding electoral behavior. 5.4. Conclusion In conclusion, the result analysis presented in this chapter offers a comprehensive examination of the factors influencing voter turnout in the 2021 Canadian Election. Through the use of three 83 regression models—Bivariate, Socio-Demographic, and Complete—we were able to isolate and understand the varying impacts of race, socio-demographic characteristics, and additional socio-economic and political variables on electoral participation. The Bivariate model highlighted race as a significant predictor of voter turnout, while the Socio-Demographic model revealed that race, though still significant, was partially mediated by other factors such as education, gender, and region. The Complete model further demonstrated that when a broad range of variables are considered, the direct impact of race diminishes, underscoring the complex interplay of factors that influence voter behavior. Moreover, the findings from the Complete model indicate that income, employment, partisanship, political interest, political knowledge, and civic awareness are significant predictors of voter turnout. Additionally, the analysis revealed that perceptions related to COVID-19, such as satisfaction with the handling of the pandemic and views on public health measures, also played a role in influencing voter participation. This highlights the importance of these socio-economic and political factors, alongside race, in shaping electoral behavior. Overall, this analysis underscores the value of a multifaceted approach to understanding voter turnout, revealing the nuanced ways in which individual characteristics and broader socio-political contexts interact to shape electoral participation. 84 6. Discussion of Hypotheses This chapter provides a critical examination of the hypotheses formulated in light of the findings from the regression analyses. This chapter goes beyond simply presenting the results; it explores how the empirical data either supports or challenges each hypothesis, offering deeper insights into the factors that influenced voter turnout during the 2021 Canadian Federal Election. The discussion is structured to analyze the interplay between various demographic, socio-economic, and political factors, examining their respective roles in shaping electoral behavior. By systematically evaluating the hypotheses, this chapter aims to elucidate the significant predictors of voter turnout identified in the analysis, such as race, age, immigrant status, income, employment, partisanship, language, political knowledge, political interest, and the impact of the COVID-19 pandemic. It also seeks to interpret these findings within the broader context of existing political science literature, providing a comprehensive understanding of the complex dynamics at play. The chapter thus serves as a bridge between the empirical results and their theoretical implications, offering nuanced explanations for the observed patterns in voter behavior and contributing to the ongoing discourse on electoral participation in Canada. 6.1. Main Hypothesis 1: Race The hypothesis H1 posits that race has a significant impact on voter turnout in the 2021 Canadian Election. To evaluate this hypothesis, logistic regression models were constructed, each adding layers of complexity by including additional socio-demographic and behavioral variables. In the bivariate model, race has a significant negative impact on voter turnout, with a coefficient of -0.51 and a p-value smaller than 0.001. This suggests that racialized minorities are less likely to vote compared to the reference group (White individuals). The pseudo R-squared value suggests that race alone explains only a small portion of the variance in voter turnout, indicating that other factors likely contribute to voting behavior. In the socio-demographic model, the coefficient for race decreases to -0.27 but remains statistically significant with a p-value smaller than 0.01. This indicates that even after controlling for various socio-demographic factors like education, gender, and age, racialized minorities still exhibit lower voter turnout compared to White individuals. The pseudo R-squared value increased, indicating that the expanded model explains more variability in voter turnout than the bivariate model. In the complete model, the coefficient for race further 85 decreases to -0.22 and becomes statistically insignificant. This change indicates that the apparent effect of race on voter turnout is largely explained by additional variables included in the complete model, such as political knowledge, voting duty, partisanship, and other contextual factors. As we have discussed above, Social Identity Theory posits that individuals' self-concepts are shaped by their membership in social groups, influencing behaviors and attitudes. This theory can help explain the initial significant negative impact of race on voter turnout in the bivariate model. Racial minorities may feel a weaker identification with the mainstream political system or may face discrimination that discourages participation. However, the diminishing effect of race in the complete model suggests that when individuals' political engagement, resources, and civic skills are accounted for, the direct impact of racial identity on voter turnout becomes less pronounced. The literature on race and electoral participation in Canada indicates that racialized minorities generally exhibit lower voter turnout compared to White individuals. Studies such as those by Reitz and Banerjee (2007) and Tossutti (2005) highlight the persistent turnout gap between racialized minorities and White voters. This aligns with the initial findings in the bivariate model. However, the findings from the complete model, where race loses statistical significance, resonate with the conclusions of Bevelander and Pendakur (2009), who found that when socioeconomic and social capital attributes are considered, ethnic identities do not significantly impact voter turnout. In summary, the analysis across the bivariate, socio-demographic, and complete models indicates that race initially appears to have a significant negative impact on voter turnout. However, this effect diminishes and loses statistical significance when accounting for additional variables related to political engagement and socioeconomic status. This suggests that while racial identity plays a role in voter turnout, its impact may be mediated by other factors such as political knowledge, civic duty, and resources. Though the bivariate model supports this hypothesis, the complete model does not, which leads us to hypothesis 2 discussed below. 6.2. Related Hypothesis 2: Socio-demographic and Behavioral Factors Hypothesis 2 posits that the impact of race on voter turnout in the 2021 Canadian Election can be explained by the correlation of race with various socio-demographic and behavioral factors. 86 Examining the related hypotheses (H3-H13), we can understand how these factors, rather than race alone, might influence voter turnout. 6.3. Hypothesis 3: Education The hypothesis 3 (H3) posits that higher levels of education positively influence voter turnout. This assertion aligns with the Resource Model of political participation, which emphasizes the importance of resources—time, money, and civic skills—in facilitating political engagement (Brady et al., 1995). Education, as a pivotal resource, can enhance an individual's civic skills and political knowledge, thereby increasing their likelihood of voting. The Resource Model suggests that beyond mere socioeconomic status, the availability of essential resources determines political participation. Education, a key resource, equips individuals with the civic skills necessary for political activities. According to Brady et al. (1995), these resources are more potent predictors of political participation than intrinsic motivations like political interest. Education, therefore, becomes a significant factor as it enhances an individual's capability to engage in the political process, providing them with the knowledge and skills to navigate political complexities. Numerous academic studies support the hypothesis that higher educational attainment correlates with increased voter turnout. Education is a strong predictor of voting behavior, often outweighing factors like income and social class (Wolfinger & Rosenstone, 1980; Cho, 1999). It supports political socialization, increasing voter registration and participation, especially among younger voters and some minority groups (Xu, 2005; Bird et al., 2010). However, exceptions exist; for example, Togeby (2004) found no link between education and turnout for certain immigrant groups in Denmark, and Lien (1994) found similar results for Asian citizens. These cases suggest that education’s impact on political engagement may vary by demographic and cultural context. The empirical findings provide mixed support for the hypothesis. The socio-demographic model shows that higher levels of education substantially increase the likelihood of voting. However, the complete model presents a contrasting result. It shows a minimal and not statistically significant effect of education on voter turnout. This discrepancy suggests that while education can have a positive impact on voter turnout, its influence may not always be consistent or conclusive across different analytical models. H3 is not conclusively supported by the data. While there is some 87 evidence of a positive relationship between higher levels of education and voter turnout, the inconsistency across different models suggests that this relationship is not universally robust. 6.4. Hypothesis 4: Age Hypothesis 4 (H4) posits that older individuals are more likely to vote than younger ones, indicating that the likelihood of voting increases with age. The socio-demographic model suggests that the likelihood of voting increases with age. In contrast, the complete model suggests that when controlling for other factors, age does not have a substantial impact on voter turnout. Therefore, the complete model does not support the H4 that older individuals are more likely to vote than younger ones. Theoretical frameworks provide context for these findings. Social Identity Theory suggests that aging strengthens identification with civic roles, like voting, thus boosting turnout among older individuals. The Resource Model (Brady et al., 1995) argues that as people age, they accumulate resources (time, money, skills) that facilitate political participation. Straight line assimilation theory posits that integration into the host society increases over generations, leading to higher political participation, particularly among long-term immigrant residents. The literature presents mixed evidence. Blais (2000, 2006) finds age to be a significant predictor of voting, with older individuals more likely to vote, showing a notable turnout difference between age groups. Bevelander and Pendakur (2009) also confirm that age, education, and civic engagement strongly influence voter turnout in Canadian elections, reinforcing the trend that older people are more likely to participate. Nevitte et al. (2000) list age, along with education, religious attendance, and income, as strongly associated with voter turnout. White et al. (2008) find that political interest in Canadian federal elections increases with age, particularly among immigrants. The socio-demographic model for the 2021 Canadian Election similarly highlights a positive relationship between age and turnout. Godbout and Turgeon (2012) confirm that older, educated, and wealthier individuals are more likely to vote. Howe and Bedford (2009) observe higher turnout among older Indigenous individuals (50+). Ramakrishnan and Espenshade (2001) show age positively impacts immigrant voter turnout across generations in the U.S., while Milbrath (1965) notes that turnout rises from youth through adulthood, peaking in the sixties. Potochnick and Stegmaier (2020) demonstrate 88 higher turnout among older Latinos, and Qi and Gonzalez (2022) find a similar trend across racial groups, with older individuals generally more engaged in voting. In conclusion, while the socio-demographic model supports H4 by showing a statistically significant positive relationship between age and voter turnout, the complete model does not provide the same support due to the lack of statistical significance. This discrepancy suggests that other factors may mitigate the impact of age on voter turnout. Therefore, based on the complete model, this study does not fully support the hypothesis that older individuals are more likely to vote than younger ones. The theoretical frameworks and literature review provide additional context, highlighting the complexity of the relationship between age and voter turnout. 6.5. Hypothesis 5: Immigrant Status The hypothesis H5 suggests that immigrants have lower voter turnout compared to native-born citizens in the 2021 Canadian Election. The results from the logistic regression analysis across two models provide mixed support for this hypothesis. The socio-demographic model shows a significant negative relationship with voter turnout. Specifically, immigrants are significantly less likely to vote compared to native-born citizens, underscoring barriers to political participation within immigrant communities. This finding aligns with existing literature that highlights the challenges immigrants face in electoral engagement (Reitz & Banerjee, 2007). The complete model suggests that this effect diminishes when accounting for a broader range of additional factors related to political engagement and socio-economic conditions. Therefore, the complete model does not fully support H5. In the complete model, the duration of residence in the current city is a significant predictor, with longer residence associated with higher voter turnout. This suggests that greater local integration over time enhances political participation, as immigrants who have lived in their city longer are more likely to vote. This finding supports the Resource Model, which emphasizes that resources like time and civic skills, accumulated through extended residence, are essential for political engagement. Social Identity theory helps explain the initial significant negative impact of immigrant status on voter turnout in the socio-demographic model. Immigrants may feel less connected to the host 89 society’s political system or face discrimination, which can hinder participation (Quillian et al., 2019; Oreopoulos, 2011; Ng & Gagnon, 2020). However, the reduced effect of immigrant status in the complete model suggests that political engagement and contextual factors lessen this impact. The significance of residence duration underscores the role of local integration and the development of a political identity in overcoming initial barriers to participation. The socio-demographic model supports the Resource Model theory, suggesting that immigrants may have fewer resources than native-born citizens (Quillian et al., 2019; Oreopoulos, 2011; Ng & Gagnon, 2020). Additionally, the positive effect of longer residence indicates that accumulated civic skills and local knowledge enhance political participation. Straight Line Assimilation Theory suggests that over generations, immigrants integrate into the host society, including in political participation. The socio-demographic model indicates that newer immigrants may still be in early assimilation stages, while the complete model’s reduced significance of immigrant status suggests alignment with native-born turnout as socioeconomic status and political engagement increase. The positive effect of longer residence supports this theory, as greater integration enhances voter turnout. Literatures on immigrant voter turnout in Canada shows mixed results. Reitz and Banerjee (2007) and Black (1982) suggest lower turnout among immigrants, particularly recent arrivals and racialized minorities, which aligns with the socio-demographic model’s findings. However, the complete model’s loss of statistical significance for immigrant status supports studies like Bevelander and Pendakur (2009), indicating socioeconomic factors mitigate turnout barriers. Longer residence duration, as Xu (2005) suggests, boosts local integration and participation, while findings by Black (1982) and White et al. (2006) indicate that the host country's political environment outweighs immigrants’ countries of origin in influencing turnout. In summary, H5 is partially supported by the findings of the regression analyses. Immigrant status initially emerges as a significant predictor of lower voter turnout in the socio-demographic model. However, this effect loses statistical significance in the complete model, suggesting that differences are mitigated by factors such as political knowledge, civic duty, and local integration. Considering the complete model, we can state that being an immigrant alone does not have an impact on voter turnout; hence, this study does not support H5. 90 6.6. Hypothesis 6: Language Hypothesis 6 (H6) states that allophones, individuals whose home-speaking language is neither English nor French, are less likely to vote than Anglophones and Francophones. The logistic regression analysis for the complete model shows that allophones are less likely to vote compared to non-allophones. However, this relationship is not statistically significant. This differs from the socio-demographic model, where allophone status appears to have a significant impact on voter turnout. The addition of more variables in the complete model likely diminished the effect of allophone status, rendering it insignificant in this more comprehensive model. Consequently, hypothesis H6 is not supported. The Resource Model of Political Participation argues that political engagement depends on resources like time, money, and civic skills, with language proficiency as a crucial component. Limited proficiency in dominant languages can restrict access to political knowledge and participation. Linguistic diversity thus impacts voter turnout: Weinstein (1983) notes that language regulation affects participation, while language barriers reduce educational attainment and turnout among minorities (Wolfinger & Rosenstone, 1980; Qi & Gonzalez, 2022). McLaughlin (2015) highlights that inclusive language policies boost democratic engagement, and Abrajano and Panagopoulos (2011) and Barreto (2005) find campaign language influences minority and immigrant turnout. The hypothesis H6 is not supported by the findings in the regression models. While there is a tendency for allophones to vote less, this relationship is not statistically significant. The inclusion of additional variables in the model likely diluted the effect of allophone status on voter turnout. Though the literature review and the Resource Model of Political Participation suggest that linguistic barriers can negatively impact voter turnout among allophones, empirical study does not support these for 2021 Canadian Election. 6.7. Hypothesis 7: Political Knowledge Hypothesis 7 (H7) posits that individuals with greater political knowledge are more likely to vote, indicating that political awareness positively influences voter participation. As per the regression analysis, political knowledge emerges as a significant predictor of voter turnout (Table 5). The 91 finding underscores the importance of political awareness in motivating individuals to participate in elections, highlighting that well-informed citizens are more likely to exercise their voting rights. The Resource Model of Political Participation suggests that political engagement relies on access to time, money, and civic skills, with political knowledge as a key civic skill. Individuals with greater political knowledge are better able to navigate the political landscape and make informed voting choices, thus more likely to vote. This model aligns with findings that political knowledge boosts voter turnout by equipping individuals with essential tools for participation. The literature strongly supports the positive link between political knowledge and voter turnout. Galston (2001) finds that well-informed citizens are better able to understand and advocate for their interests. Popkin and Dimock (1999) emphasize that political knowledge independently shapes vote choice and participation, as knowledgeable citizens better assess candidates and issues. Delli Carpini and Keeter (1996) show that political knowledge promotes consistent, informed behavior by bridging attitudes and interests. Stewart et al. (2008) link political discussion to higher political knowledge, which boosts voting likelihood. Educational attainment is also tied to political knowledge. O’Neill (2006) and Stewart et al. (2008) reveal that higher education correlates with increased awareness, and Lambert et al. (1988) confirm that political knowledge enhances turnout. Milner (2007) highlights that politically informed youth participate more actively in democracy. This relationship, supported by the Resource Model of Political Participation, which stresses the role of civic skills, aligns with the complete model’s findings, reinforcing that political knowledge is essential for voter participation. This evidence underscores the value of initiatives to improve political knowledge for fostering democratic engagement. 6.8. Hypothesis 8: Sense of Civic Responsibility Hypothesis 8 (H8) posits that people with a stronger sense of civic responsibility are more likely to vote, implying that a higher civic sense leads to higher voter turnout. This hypothesis is supported by the findings in the Complete Model, indicating a strong positive relationship between viewing voting as a duty and the likelihood of voter turnout. The statistical significance of this relationship confirms the robust effect of civic responsibility on voting behavior. This finding 92 underscores the motivational power of civic duty in driving voter participation, suggesting that fostering a sense of duty towards voting can substantially enhance voter turnout. If we analyze H8 by comparing existing literature and above mentioned theories, Pammett and LeDuc (2003) describe civic duty as essential for participation and political health, while Blais (2000) notes that seeing voting as a moral obligation strongly influences behavior. Riker and Ordeshook’s (1968) voting calculus includes civic duty, arguing that intrinsic benefits can make voting rational. Bevelander and Pendakur (2009) find that civic duty in Canada transcends ethnic backgrounds, shaped by social capital and demographic factors. Purdam et al. (2002) show higher turnout among those seeing voting as a civic duty, and Blais et al. (2004) link declining turnout among youth to a weakening sense of responsibility. Pammett and LeDuc (2003) observed a strong correlation between civic duty and voting in the 2000 Federal Election, and Blais and Achen (2019) emphasize the ethical motivations tied to civic duty. Gidengil (2004) finds that education boosts civic duty, while Lago et al. (2018) note that aversion to ethnolinguistic diversity reduces civic commitment. The Resource Model of Political Participation suggests that civic duty, like time and civic skills, is a critical motivator for voting. The complete model’s positive relationship between civic duty and turnout underscores its role in electoral participation, supported by extensive literature and empirical evidence. We can conclude that this study supports H8. 6.9. Hypothesis 9: Partisanship Hypothesis 9 (H9) posits that individuals who identify with a political party are more likely to vote in the 2021 Canadian Election. This hypothesis is grounded in theories such as the Resource Model theory of Political Participation and Social Identity theory, both of which suggest that strong identification with a social or political group can significantly enhance political engagement and participation. The findings from the complete model support this hypothesis. The logistic regression analysis reveals that party identification is a significant predictor of voter turnout. Individuals who identify with a political party are more likely to vote. This positive relationship underscores the idea that party loyalty provides motivation and a sense of duty to participate in elections. 93 The literature consistently supports the hypothesis that party identification enhances voter turnout. Studies have shown that individuals with strong party affiliations are more likely to be mobilized and motivated to vote because party identification provides a clear political choice, simplifies the voting decision, and fosters a sense of civic duty (Brady et al., 1995). Additionally, the literature on electoral participation highlights that party loyalty is a significant factor in predicting voter turnout, as individuals with strong party ties are more engaged and likely to participate in elections (Campbell et al., 1960). Empirical research on voter turnout in various contexts, including the United States and Europe, consistently finds that party identification is a strong predictor of voting behavior (Dalton, 2008; Green et al., 2002). Thus, H9 is strongly supported by the findings of the regression analyses, theoretical frameworks, and existing literature, highlighting the critical role of party loyalty in enhancing electoral participation. The persistence of this effect, even when controlling for various other factors, underscores the importance of party identification in driving voter turnout in the 2021 Canadian Election. 6.10. Hypothesis 10: Political Interest Hypothesis 10 (H10) posits that political interest positively influences voter turnout in the 2021 Canadian Election. The findings from the complete regression model robustly support this hypothesis. In this model, political interest emerges as a significant and positive predictor of voter turnout. This suggests that political interest is a critical factor in driving electoral participation, even when controlling for a wide range of other variables. The significant impact of political interest in the complete model underscores the importance of this variable in understanding voter behavior in the 2021 Canadian Election, thereby supporting the hypothesis H10. The positive relationship between political interest and voter turnout is well-documented in the literature and supported by relevant theories. Brady et al. (1995) argue that political interest is one of the most potent predictors of political participation, as it enhances individuals' motivation to engage with political processes. Dalton (2008) and Franklin (2004) further support this notion, demonstrating that higher levels of political interest are consistently associated with increased voter turnout across various democratic contexts. Political interest fosters a sense of civic duty, increases political knowledge, and motivates individuals to participate in elections, thereby playing a critical role in enhancing voter turnout. Thus, H10 is well-supported by both the empirical 94 findings from the complete model and the broader literature, highlighting the significant influence of political interest on voter turnout in the 2021 Canadian Election. 6.11. Hypothesis 11: Income Level Hypothesis 11 (H11) posits that higher income individuals are more likely to vote, proposing that income level is positively associated with voter turnout. In the complete model it shows a significant positive relationship with voter turnout. This indicates that higher income levels are associated with a greater likelihood of voting. Similar to this finding the relationship between income and voter turnout is well-documented. O'Neill (2006) finds that higher earnings provide essential resources for civic engagement, with financial stability enabling informed political participation. Jedwab (2005) links higher voter turnout to higher income, emphasizing economic disparities in voting patterns. Reitz and Banerjee (2007) and Halli and Kazemipur (2003) note significant income disparities among racialized minorities and immigrants, affecting their turnout, while Silver et al. (2006) highlight similar income gaps impacting Indigenous voter participation in Canada. Horn (2011) and Galbraith and Hale (2008) report a negative association between income inequality and voter turnout, as larger income disparities lead to lower participation. Conversely, Blais et al. (2002) and Wesley and Summerlee (2012) find that high-income areas show increased turnout, supported by Gallego (2009), who observes that wealthier, educated individuals are more likely to vote. In the U.S., Tate (1991) and Qi and Gonzalez (2022) similarly find that higher income levels boost voting likelihood among Black Americans and racialized minorities. The Resource Model theory also explains that higher income individuals typically have greater financial resources, which facilitate their political participation. This model supports the finding that income positively influences voter turnout, as economic stability provides the necessary resources for engaging in political activities. H11 is supported by the findings in socio-demographic and complete model and aligns with the literature. Higher income individuals are indeed more likely to vote, reflecting the positive impact of income level on voter turnout. This relationship underscores the importance of economic stability and access to resources in facilitating political engagement, as highlighted by the Resource Model of Political Participation. 95 6.12. Hypothesis 12: Employment Hypothesis 12 (H12) states that employed individuals are more likely to vote than unemployed ones, suggesting that employment status positively affects voter turnout. In the complete model, the employment variable shows a significant positive relationship with voter turnout. This result suggests that economic stability and financial resources play crucial roles in political engagement. Research on employment status as a predictor of voting behavior is mixed. Rosenstone and Hansen (1993) and Wolfinger and Rosenstone (1980) find that unemployed individuals participate less due to lower income and lack of workplace social networks that foster engagement. O'Neill (2006) and Statistics Canada (Uppal & LaRochelle-Côté, 2012) confirm that employed individuals are more likely to vote, with Blais (2000) linking economic well-being to higher turnout. Conversely, Charles and Stephens (2013) suggest that increased labor demands may lower local election turnout due to time constraints. Additionally, racial discrimination in employment, as noted by Quillian et al. (2019) and Oreopoulos (2011), impacts political participation, with Block and Galabuzi (2011) and Ng and Gagnon (2020) highlighting higher unemployment among racialized Canadians, negatively affecting their turnout. The Resource Model theory argues that political engagement depends on access to time, money, and civic skills. Employed individuals, with more financial resources and civic skills, are generally more likely to vote, supporting H12 and findings in the complete model. This relationship highlights the role of economic stability in fostering political participation. However, systemic barriers and discrimination may impact employment and political engagement differently across demographic groups, adding nuance to this relationship. 6.13. Hypothesis 13: Covid-19 Hypothesis 13 (H13) suggests that individuals who view COVID-19 public health measures and the government's handling of the situation positively are more likely to vote. However, the results are mixed: greater satisfaction with COVID-19 handling is associated with lower voter turnout, while those who see public health measures as non-threatening to their liberty are more inclined to vote. This indicates that these factors have a varied impact on voter turnout. It suggests that those dissatisfied with the handling of the COVID-19 pandemic are more likely to vote, possibly motivated by a desire to effect change. Conversely, those who are satisfied with the response may 96 feel less urgency to participate in the electoral process, reflecting a sense of complacency or contentment with the status quo. The literature highlights the complex relationship between pandemic management and voter turnout. Erhan and Sıvış (2024) find that perceived mishandling of the pandemic mobilized voters in the 2020 U.S. elections, while positive views in Canada favored the incumbent without boosting turnout. Harell and Stephenson (2022) show varied turnout across Canadian provinces, generally decreasing due to pandemic-related changes in election management, with some exceptions. This illustrates how public health crises can alter voting patterns. Hasen (2020) and Jahan (2022) find that COVID-19 negatively impacted voter turnout, especially among minority communities, with declines linked to rising cases. These findings align with the Resource Model, which ties political engagement to resources like time and civic skills. Positive views on COVID-19 measures reduced the perceived need for change, lowering turnout, while dissatisfaction mobilized voters. The mixed support for H13 shows that dissatisfaction with pandemic management, rather than positive perceptions, drove higher electoral participation. 6.14. Conclusion In conclusion, this chapter has critically examined the hypotheses regarding voter turnout in the 2021 Canadian Federal Election by analyzing various demographic, socio-economic, and political factors. The analysis reveals that race, while initially significant, loses its impact when additional variables are considered, suggesting that its influence is mediated by factors such as political engagement, socioeconomic status, and local integration. Education, traditionally seen as a strong predictor of voter turnout, shows mixed results, with its significance diminishing in more comprehensive models. Age follows a similar pattern, with older individuals more likely to vote in simpler models, but this relationship weakens when other factors are controlled. Immigrant status emerges as a complex factor, initially showing lower voter turnout but losing significance in the complete model, indicating that other variables like duration of residence play a crucial role. Language, particularly allophone status, does not show a significant impact on voter turnout, contrary to some expectations. Political knowledge, civic responsibility, and partisanship are consistently strong predictors, highlighting the importance of political engagement and identity in driving voter turnout. 97 Income and employment status are also significant, with higher income and employment being associated with increased voter participation, emphasizing the role of economic stability in political engagement. The impact of COVID-19 on voter turnout presents a nuanced picture: dissatisfaction with pandemic handling motivates higher turnout, while those who do not see public health measures as a threat are more likely to vote. Overall, this chapter demonstrates that voter turnout is influenced by a complex interplay of factors, where traditional demographic variables like race, education, and age interact with socio-economic conditions, political engagement, and contextual factors like the COVID-19 pandemic. The findings underscore the need for a comprehensive approach to understanding electoral participation, considering the multifaceted nature of voter behavior in contemporary elections. 98 7. Conclusion: In this thesis, we examined the impact of race on voter turnout in the 2021 Canadian Election, utilizing data from the Canadian Election Studies Survey 2021. The analysis of race's impact on voter turnout in the 2021 Canadian Election was conducted using three models. Initially, the bivariate model showed a significant negative impact, with racialized minorities less likely to vote than White individuals. Adding socio-demographic factors in the second model reduced this effect but it remained significant. However, in the complete model, which included political engagement and socioeconomic status, the impact of race loses statistical significance. While the bivariate and socio-demographic models support the hypothesis that race affects voter turnout, the complete model indicates that other factors play a significant role in explaining this relationship. When we include variables such as political interest, partisanship, political knowledge, employment, attitudes towards immigrants, COVID-19-related factors, and sense of civic awareness in the analysis, the significance of race diminishes. We analyzed the relationship between voter turnout and a broad spectrum of demographic, social, economic, and political/ideological factors. Our comprehensive analysis reveals that political knowledge significantly impacts voter turnout, with higher levels of political knowledge positively correlating with increased participation. Similarly, a strong sense of civic responsibility also positively affects turnout in the 2021 Canadian Election; the more individuals perceive voting as a duty rather than a choice, the more likely they are to participate. Additionally, higher levels of political interest motivate people to vote. We also found that partisanship plays a crucial role in voter turnout. Respondents who identify with political parties are more inclined to vote than those who do not affiliate with any party. This highlights the importance of political identification and engagement in fostering higher voter participation. Economic status significantly influences voter turnout, as evidenced by the significant impact of income and employment in the complete model. Individuals in higher income categories are more likely to vote, suggesting that financial stability provides the resources and sense of security needed to engage in the political process. Similarly, being employed is associated with an increased likelihood of voting. Employment not only provides financial stability but also fosters a sense of social integration and responsibility, which can translate into greater political engagement. 99 This underscores the importance of economic stability in facilitating political participation, as those with higher incomes and stable employment are better equipped to navigate and participate in the electoral process. These findings highlight the critical role that economic factors play in shaping voter behavior and the need to consider these elements in efforts to increase voter turnout. The analysis of COVID-19 related variables provides significant insights into their impact on voter turnout in the 2021 Canadian Election. Specifically, satisfaction with the handling of the COVID-19 pandemic negatively impacts voter turnout, suggesting that individuals dissatisfied with the government's response are more motivated to vote, potentially seeking change through the electoral process. Conversely, views on public health measures against liberty positively impact voter turnout, indicating that those who do not see these measures as a threat to personal freedoms are more likely to participate in the election. This can be interpreted as a mobilizing factor where concerns about civil liberties drive individuals to the polls. These findings underscore the complex interplay between public health crises, government responses, and political behavior, highlighting how contemporary issues and public sentiment significantly influence electoral participation beyond traditional demographic and socio-economic factors. The duration of residence in the current city has a noteworthy impact on voter turnout in the 2021 Canadian Election. Individuals who have lived in their current city for more than ten years are significantly more likely to vote compared to those who have lived there for a shorter period. This indicates that a longer duration of residence fosters a stronger sense of community and civic engagement, encouraging greater participation in the electoral process. Along with the variables discussed, some religious and regional factors also impact voter turnout in the 2021 Canadian Election. When everything is included in the analysis, certain religious affiliations, such as being Agnostic and Jehovah’s Witnesses have a positive and negative impact respectively on voter turnout. Conversely, some regions, like Nunavut, Saskatchewan, Quebec, and Northwest Territories, show a negative impact on voter turnout, suggesting that regional dynamics and local political climates can significantly influence voter engagement. Additionally, when all variables are included in the analysis, factors such as education, gender, other religious and regional factors beyond those specifically mentioned above, age, immigrant status, language, the origin of the immigrant's country, frequency of political discussions at home, 100 and attitudes towards immigrants do not have a significant impact on voter turnout. This suggests that these variables, while potentially influential individually, do not independently predict voter participation in the 2021 Canadian Election when considered alongside the broader spectrum of demographic, social, economic, and political factors. Based on the comprehensive analysis conducted in this thesis, several potential reforms could be suggested to boost voter turnout in future elections. Firstly, enhance civic education: strengthening civic education programs that focus on increasing political knowledge can significantly boost voter turnout. Government initiatives and collaborations with educational institutions can help equip citizens with a deeper understanding of the political process, thereby fostering a more informed and engaged electorate. Secondly, enhancing political knowledge: enhancing political knowledge among citizens through educational programs and public awareness campaigns can significantly increase voter participation. Emphasizing the importance of voting as a civic duty, rather than a mere choice, can also foster a stronger sense of responsibility and encourage higher turnout. Thirdly, promote political engagement: Creating opportunities for political discussions and activities, especially in communities with lower voter turnout, can help increase political interest. By making political information more accessible and encouraging civic participation, the government can motivate more citizens to vote. Fourthly, strengthening party identification: political parties can contribute here to enhance voter turnout by takins some steps. Strengthening party identification by making political parties more relatable and connected to the daily lives of citizens can also enhance voter turnout, as those with a strong partisan identity are more likely to vote. Fifthly, economic stability is another critical factor influencing voter turnout. Policies aimed at improving employment rates and providing economic security can indirectly boost voter participation. Ensuring that citizens feel economically stable and integrated within their communities can lead to higher levels of political engagement. Sixthly, address public sentiment and trust: public dissatisfaction with government responses, particularly in handling crises like the COVID-19 pandemic and trade war can influence voter turnout. Transparent and effective communication from the government can help rebuild trust and encourage citizens to participate in elections, potentially mitigating the negative impact of dissatisfaction on voter turnout. Seventhly, foster community ties: local governments and Elections Canada should focus on 101 building a stronger sense of community, especially among long-term residents. Community-building initiatives that promote civic engagement and local participation can lead to higher voter turnout, reflecting the importance of social integration in electoral participation. Eighthly, targeted outreach to racialized minorities: special attention should be given to increasing voter turnout among racialized minorities. This can be achieved through targeted voter mobilization efforts, including outreach programs that address the specific barriers faced by these communities, such as language, economic barriers or political disengagement. Finally, support for minority leaders: encouraging and supporting political candidates from minority backgrounds could help mobilize racialized voters, particularly when they see themselves represented in the political landscape. This can be further explored through the concept of affinity voting, where voters are more likely to participate if candidates share their identity traits. While this study provides valuable insights into the complex relationship between race and voter turnout in Canada, several limitations should be acknowledged. First, the use of a binary classification of race—distinguishing only between racialized minorities and White individuals—may overlook significant intra-group differences. This binary treatment may not fully capture the diverse experiences, cultural contexts, or political behaviors of specific ethnic communities, potentially limiting the depth of the analysis. Second, the reliance on self-reported survey data from the Canadian Election Studies (CES) introduces the possibility of social desirability bias and inaccuracies in recall, particularly around sensitive topics such as political participation and civic engagement. Additionally, the cross-sectional design of the study constrains causal interpretations and does not account for temporal shifts in voter behavior. In some cases, the CES dataset does not fully reflect the demographic realities reported by Statistics Canada—for instance, in the proportions of immigrants, racialized minorities, or overall voter turnout—which may affect the generalizability of the findings. The exclusion of certain contextual variables, such as local-level mobilization efforts, access to voting infrastructure, and personal experiences of discrimination, may also limit the explanatory scope of the models. Future research would benefit from incorporating more detailed racial and generational breakdowns, qualitative insights, and longitudinal data to better capture the evolving dynamics of electoral participation in Canada. Based on this analysis, several future research prospects emerge. Firstly, more nuanced studies could explore the intersectionality of race with other socio-demographic variables to understand 102 better the multifaceted barriers to voter turnout among racialized minorities. Secondly, longitudinal studies tracking changes in political participation across different generations of immigrants could provide insights into the assimilation process and its impact on electoral behavior. Additionally, research could investigate the role of digital and social media in shaping political knowledge and engagement among various demographic groups. There is also a need to examine the effects of targeted voter mobilization efforts and civic education programs in increasing turnout, particularly among underrepresented communities. Qualitative research involving in-depth interviews and focus groups could complement quantitative findings, offering a richer understanding of the motivations and obstacles faced by different voter groups. These areas of inquiry could help develop more effective strategies for fostering inclusive and robust democratic participation. Future research could investigate the influence of political leaders from minority backgrounds, particularly through the lens of affinity voting—a heuristic where voters select candidates based on shared identity traits such as gender, race, or ethnicity (McGregor et al., 2017, p. 139)—and examine the intersection of race and gender on voting behavior. O’Reilly (2021) found that while the presence of racialized candidates did not broadly increase voter turnout among all racialized communities in the 2015 and 2019 Canadian Federal Elections, specific ethnic groups like Chinese and South Asian voters were more likely to vote when a co-ethnic candidate was running, emphasizing the need for improved data collection and further research on race and ethnicity in voting behavior. However, it is unclear whether this effect can be extended to party leaders. An examination of data from the CES 2015 and CES 2019 surveys and reveals that there is no upward trend in voter turnout among South Asian voters, even after the election of a minority candidate at the head of a major national Canadian party (refer to Appendices Tables C1 and C2). Notably, 83.33% of South Asian voters participated in the 2015 election, whereas 90.91% did so in the 2019 election, when Jagmeet Singh was elected as NDP leader (Fournier et al., 2015; Stephenson et al., 2019). The analysis of the trend indicating that the election of a South Asian leader, such as Jagmeet Singh, increased voter turnout among South Asians is not statistically significant. The analysis produced a t-score of 1.55 with 104 degrees of freedom, and the p-value was 0.1243. Since the p-value is greater than the standard significance threshold of 0.05, there is insufficient evidence to conclude that the presence of a South Asian leader significantly impacted voter turnout among South Asians. Moreover, exploring the impact of new technologies and voting methods, such as mail voting or advance voting could reveal how these innovations affect turnout 103 among different demographic groups. Furthermore, analyzing the influence of misinformation and fake news on voter behavior and turnout could address contemporary challenges in the electoral process. The overall novelty of this thesis lies in its comprehensive examination of the multifaceted impact of race on voter turnout in the 2021 Canadian Election, particularly through the use of three distinct regression models that highlight how the significance of race diminishes when considering a broad spectrum of socio-demographic, political, and economic factors. This study uniquely integrates the influence of variables such as political knowledge, civic duty, political interest, and the handling of COVID-19 into the analysis, offering a more nuanced understanding of voter behavior. 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Min Max Turnout 7,630 0.91 91.35 0.28 0 1 Note: This table is generated from the CES 2021 dataset. This is a categorical variable. Table A2:Frequency Table and Summary Statistics: Race Variable Percent Race White 79.82 Racialized minorities 20.18 Summary Statistics: Race Variable Observations Mean Mean (%) Std. Dev. Min Max Race 7,630 .20 20.12 0.40 0 Note: This table is generated from the CES 2021 dataset, where White is the reference category. This is a categorical variable. 120 Table A3:Frequency Table and Summary Statistics: Education Variable Percent Education No schooling 0.03 Some elementary school 0.7 Completed elementary school 0.14 Some secondary/ high school 1.90 Completed secondary/ high school 13.03 Some technical, community college, CEGE 7.99 Completed technical, community college 21.91 Some university 9.70 Bachelor's degree 29.79 Master's degree 11.02 Professional degree or doctorate 4.42 Summary Statistics: Education Variable Observations Mean Mean (%) Std. Dev. Min Max Education 7,630 7.79 7.79 1.78 1 11 Note: This table is generated from the CES 2021 dataset. Table A4: Frequency Table and Summary Statistics: Gender Variable Percent Gender Female 50.51 Male 49.07 Non-Binary 0.24 Summary Statistics: Gender Variable Observations Mean Mean (%) Std. Dev. Min Max Gender 7,630 1.51 37.88 0.52 0 4 Note: This table is generated from the CES 2021 dataset, where male is the reference category. 121 Table A5:Frequency Table and Summary Statistics: Region Variable Percent Region Alberta 11.77 British Columbia 11.51 Manitoba 3.51 New Brunswick 2.02 Newfoundland & Labrador 0.92 Northwest Territories 0.12 Nova Scotia 2.4 Nunavut 0.03 Ontario 34.3 Prince Edward Island 0.37 Quebec 30.93 Saskatchewan 1.93 Yukon 0.21 Summary Statistics: Region Variable Observations Mean Mean (%) Std. Dev. Min Max Region Alberta 7,630 0.12 11.77 0.32 0 1 British Columbia 7,630 0.02 2.02 0.14 0 1 Manitoba 7,630 0.01 0.92 0.1 0 1 New Brunswick 7,630 0 0.12 0.03 0 1 Newfoundland and Labrador 7,630 0.02 2.40 0.15 0 1 Northwest 7,630 0 0.03 0.02 0 1 Nova Scotia 7,630 0 0.37 0.06 0 1 Nunavut 7,630 0.31 30.93 0.46 0 1 Ontario 7,630 0.02 1.93 0.14 0 1 Prince Edward Island 7,630 0 0.21 0.05 0 1 Quebec 7,630 0.12 11.77 0.32 0 1 Saskatchewan 7,630 0.02 2.02 0.14 0 1 Yukon 7,630 0.01 0.92 0.1 0 1 Note: This table is generated from the CES 2021 dataset, where Ontario is the reference category. 122 Table A6: Frequency Table and Summary Statistics: Age Age Percent Age Percent Age Percent 18 0.18 45 1.47 71 2.36 19 0.43 46 1.53 72 2.19 20 0.56 47 1.13 73 1.87 21 0.59 48 1.23 74 1.82 22 0.67 49 1.21 75 1.77 23 0.67 50 1.35 76 1.18 24 0.75 51 1.76 77 1.21 25 0.96 52 1.63 78 1.1 26 1.05 53 1.8 79 0.92 27 1.07 54 1.9 80 0.5 28 1.09 55 1.77 81 0.52 29 1.51 56 1.85 82 0.43 30 0.97 57 1.86 83 0.37 31 1.65 58 2.12 84 0.18 32 1.7 59 2.04 85 0.3 33 1.48 60 2.39 86 0.08 34 1.48 61 2.73 87 0.13 35 1.35 62 2.25 88 0.07 36 1.32 63 2.37 89 0.04 37 1.26 64 2.46 90 0.08 38 1.14 65 2.56 92 0.03 39 1.36 66 2.56 93 0.01 40 1.45 67 2.94 95 0.01 41 1.74 68 2.65 42 1.52 69 2.37 43 1.39 70 2.27 44 1.3 Summary Statistics: Age Variable Observations Mean Mean (%) Std. Dev. Min Max Age 7,630 54.07 54.07 16.46 18 95 Note: This table is generated from the CES 2021 dataset. This is a continuous variable. 123 Table A7: Frequency Table and Summary Statistics: Religion Religion Percent Religion Percent Atheist 30.62 Jehovah's Witness 0.14 Agnostic 6.66 Lutheran 1.35 Buddhist 0.93 Mormon 0.17 Hindu 1.09 Pentecostal 1.8 Jewish 1.73 Presbyterian 1.21 Muslim 1.35 Protestant 4.73 Sikh 0.5 United Church of Canada 3.54 Anglican 3.88 Christian Reformed 0.66 Baptist 1.56 Salvation Army 0.24 Catholic 30.25 Mennonite 0.29 Orthodox 1.32 Summary Statistics: Religion Variable Observations Mean Mean (%) Std. Dev. Min Max Atheist 7,630 30.62 30.62 0.46 0 1 Agnostic 7,630 6.66 6.66 0.25 0 1 Buddhist 7,630 0.93 0.93 0.1 0 1 Hindu 7,630 1.09 1.09 0.1 0 1 Jewish 7,630 1.73 1.73 0.13 0 1 Muslim 7,630 1.35 1.35 0.12 0 1 Sikh 7,630 0.5 0.5 0.07 0 1 Anglican 7,630 3.88 3.88 0.19 0 1 Baptist 7,630 1.56 1.56 0.12 0 1 Catholic 7,630 30.25 30.25 0.46 0 1 Orthodox 7,630 1.32 1.32 0.11 0 1 Jehovah's Witness 7,630 0.14 0.14 0.04 0 1 Lutheran 7,630 1.35 1.35 0.12 0 1 Mormon 7,630 0.17 0.17 0.04 0 1 Pentecostal 7,630 1.8 1.8 0.13 0 1 Presbyterian 7,630 1.21 1.21 0.11 0 1 Protestant 7,630 4.73 4.73 0.21 0 1 United Church of Canada 7,630 3.54 3.54 0.18 0 1 Christian Reformed Church 7,630 0.66 0.66 0.08 0 1 Salvation Army 7,630 0.24 0.24 0.05 0 1 Mennonite 7,630 0.29 0.29 0.05 0 1 Note: This table is generated from the CES 2021 dataset, where atheist is the reference category. These are categorical variables. 124 Table A8: Frequency Table and Summary Statistics: Immigrant Status Variable Percent Immigrant Status Non-Immigrant 84.61 Immigrant 15.39 Summary Statistics: Immigrant Status Variable Observations Mean Mean (%) Std. Dev. Min Max Immigrant 7,630 0.15 15.39 0.36 0 1 Note: This table is generated from the CES 2021 dataset. This is a categorical variable. Table A9: Frequency Table and Summary Statistics: Allophone Variable Percent Linguistic Background (allophone) Anglo/Francophones 93.79 Allophones 6.21 Summary Statistics: Allophone Variable Observations Mean Mean (%) Std. Dev. Min Max Allophones 7,630 0.06 6.21 0.24 0 1 Note: This table is generated from the CES 2021 dataset. This is a categorical variable. Table A10: Frequency Table and Summary Statistics: Income category Variable Percent Income category 0-40k 25.39 40k-71k 24.97 71k-110k 26.15 110k-higher 25.29 Summary Statistics: Income category Variable Observations Mean Mean (%) Std. Dev. Min Max Income Category 7,630 2.53 2.43 1.11 1 4 Note: This table is generated from the CES 2021 dataset. This is a continuous variable. 125 Table A11: Frequency Table and Summary Statistics: Political Knowledge Variable Percent Political Knowledge 0 9.48 1 21.65 2 34.29 3 34.59 Summary Statistics: Political Knowledge Variable Observations Mean Mean (%) Std. Dev. Min Max Political Knowledge 7,630 1.94 1.94 0.97 0 3 Note: This table is generated from the CES 2021 dataset. This is a continuous variable. Table A12: Frequency Table and Summary Statistics: Discussion frequency about politics at home Variable Percent Discussion frequency about politics at home Never 8.87 Sometimes 60.33 Often 25.29 All the time 5.50 Summary Statistics: Discussion frequency about politics at home Variable Observations Mean Mean (%) Std. Dev. Min Max Discussion frequency about politics at home 7,630 2.27 2.27 0.70 1 4 Note: This table is generated from the CES 2021 dataset. This is a continuous variable. Table A13: Frequency Table and Summary Statistics: Voting is a duty Variable Percent Voting is a Duty No 21.83 Yes 78.17 Summary Statistics: Voting is a duty Variable Observations Mean Mean (%) Std. Dev. Min Max Voting is a duty 7,630 0.78 78.17 0.41 0 1 Note: This table is generated from the CES 2021 dataset. This is a categorical variable. 126 Table A14: Frequency Table and Summary Statistics: Partisanship Variable Percent Partisanship Non-Identifier 14.67 Identifier 85.33 Summary Statistics: Partisanship Variable Observations Mean Mean (%) Std. Dev. Min Max Partisanship 7,630 0.85 85.33 0.35 0 1 Note: This table is generated from the CES 2021 dataset. This is a categorical variable. Table A15: Frequency Table and Summary Statistics: Political Interest Variable Percent Political Interest 0 1.97 1 2.16 2 3.81 3 5.49 4 5.07 5 8.57 6 12.65 7 19.06 8 19.06 9 11.86 10 10.3 Summary Statistics: Political Interest Variable Observations Mean Mean (%) Std. Dev. Min Max Political Interest 7,630 6.61 6.61 2.44 0 10 Note: This table is generated from the CES 2021 dataset. This is a continuous variable. Table A16: Frequency Table and Summary Statistics: Origin from non-democratic countries Variable Percent Origin from non-democratic countries All Others 92.31 Origin non-democratic 7.69 Summary Statistics: Origin from non-democratic countries Variable Observations Mean Mean (%) Std. Dev. Min Max Origin from non-democratic countries 7,630 0.85 7.69 0.27 0 1 Note: This table is generated from the CES 2021 dataset. This is a categorical variable. 127 Table A17: Frequency Table and Summary Statistics: Employment Variable Percent Employment Unemployed 52.57 Employed 47.43 Summary Statistics: Employment Variable Observations Mean Mean (%) Std. Dev. Min Max Employment 7,630 0.47 47.43 0.50 0 1 Note: This table is generated from the CES 2021 dataset. This is a categorical variable. Table A18: Frequency Table and Summary Statistics: Satisfaction with COVID-19 handling Variable Percent Satisfaction with COVID-19 handling Not at all 17.59 Not very 24.15 Fairly satisfied 44.88 Very satisfied 13.38 Summary Statistics: Satisfaction with COVID-19 handling Variable Observations Mean Mean (%) Std. Dev. Min Max Satisfaction with COVID-19 handling 7,630 2.54 2.54 0.93 1 4 Note: This table is generated from the CES 2021 dataset. This is a continuous variable. Table A19: Frequency Table and Summary Statistics: Views on COVID-19 public health measures against Liberty (Covid Views) Variable Percent Covid Views Strongly agree 10.01 Somewhat agree 10.21 Neither agree nor disagree 9.33 Somewhat disagree 17.23 Strongly disagree 53.21 Summary Statistics: Covid Views Variable Observations Mean Mean (%) Std. Dev. Min Max Covid Views 7,630 3.93 3.93 1.39 1 5 Note: This table is generated from the CES 2021 dataset. This is a continuous variable. 128 Table A20: Frequency Table and Summary Statistics: Duration of residence in the current city Variable Percent Duration of residence in the current city Less than 1 year 3.32 1-3 years 8.18 3-10 years 17.31 More than 10 years 71.19 Summary Statistics: Duration of residence in the current city Variable Observations Mean Mean (%) Std. Dev. Min Max Duration of residence in the current city 7,630 3.56 3.56 0.78 1 4 Note: This table is generated from the CES 2021 dataset. This is a continuous variable. Table A21: Frequency Table and Summary Statistics: Do you think Canada should admit … immigrants Variable Percent Do you think Canada should admit … immigrants Fewer immigrants 29.93 The same number of immigrants 44.67 More immigrants 25.40 Summary Statistics: Do you think Canada should admit … immigrants Variable Observations Mean Mean (%) Std. Dev. Min Max Do you think Canada should admit ……. immigrants 7,630 1.95 1.95 0.74 1 3 Note: This table is generated from the CES 2021 dataset. This is a continuous variable. 129 Table A22: Frequency Table and Summary Statistics: Feelings towards Immigrants 0-100 Frequency Table and Summary Statistics: Feelings towards Immigrants 0-100 Variable Percent Variable Percent Variable Percent 0 1.51 34 0.37 68 0.94 1 0.21 35 0.54 69 0.98 2 0.1 36 0.25 70 3.77 3 0.14 37 0.28 71 2.04 4 0.09 38 0.3 72 1.48 5 0.09 39 0.42 73 1.34 6 0.1 40 1.45 74 1.42 7 0.1 41 0.54 75 2.35 8 0.1 42 0.58 76 1.14 9 0.2 43 0.34 77 1.09 10 0.29 44 0.39 78 1.11 11 0.17 45 0.52 79 1.04 12 0.09 46 0.46 80 3.46 13 0.13 47 0.37 81 1.86 14 0.17 48 0.35 82 1.77 15 0.18 49 0.39 83 1.31 16 0.12 50 6.45 84 1.13 17 0.17 51 5.81 85 1.4 18 0.21 52 1.57 86 0.8 19 0.33 53 1.06 87 0.67 20 0.63 54 0.66 88 0.66 21 0.31 55 1.06 89 0.58 22 0.21 56 0.55 90 2.98 23 0.22 57 0.54 91 1.31 24 0.12 58 0.75 92 1.01 25 0.47 59 1.06 93 0.68 26 0.25 60 3.55 94 0.42 27 0.2 61 1.6 95 0.76 28 0.24 62 1.36 96 0.46 29 0.28 63 0.98 97 0.31 30 0.84 64 0.85 98 0.24 31 0.35 65 1.42 99 0.43 32 0.33 66 0.98 100 10.8 33 0.42 67 1.09 Summary Statistics: Feelings towards Immigrants 0-100 Variable Observations Mean Mean (%) Std. Dev. Min Max Feelings towards Immigrants 7,630 66.07 66.07 23.63 0 100 Note: This table is generated from the CES 2021 dataset. This is a continuous variable. 130 Appendix B: Impact of Gender with Immigrant Background and Race on Turnout Table B1: Impact of Gender with Immigrant Background on Turnout Variable Coefficient Standard Error Immigrant -0.57*** 0.15 Gender -0.34*** 0.09 Immigrant and Gender Interaction 0.2 0.2 Legend: *: p < 0.05, **: p < 0.01, ***: p < 0.001 Note: This table presents the interaction of gender with immigrant status and how it impacts voter turnout in the 2021 Canadian Election. This is only a partial model that includes only immigrant status and gender in relation to turnout. Table B2: Impact of Gender with Race on Turnout Variables Coefficient Standard Error Race -0.55*** 0.14 Gender -0.31*** 0.1 Race and Gender Interaction 0.09 0.18 Legend: *: p < 0.05, **: p < 0.01, ***: p < 0.001 Note: This table presents the interaction of gender with racial identity and how it impacts voter turnout in the 2021 Canadian Election. This is only a partial model that includes only race and gender in relation to turnout. 131 Table B3 Regression model with two variables interacting gender with race and immigrant Variable Coefficient Std. Err. Variable Coefficient Std. Err. Race -0.19 0.18 Catholic 0.21 0.12 Gender 0.01 0.11 Orthodox 0.14 0.4 Gender Race Interaction -0.05 0.23 Jehovah's Witnesses -2.36** 0.84 Immigrant -0.37 0.21 Lutheran -0.45 0.39 Gender Immigrant Interaction 0.17 0.25 Mormon -1.15 0.74 Education 0.01 0.03 Pentecostal -0.26 0.31 Alberta -0.27 0.18 Presbyterian 0.21 0.49 British Columbia -0.26 0.17 Protestant 0.08 0.24 Manitoba -0.39 0.26 United Church of Canada 0.72 0.39 New Brunswick -0.2 0.32 Christian Reformed Church 1.88 1.03 Newfoundland and Labrador -0.71 0.41 The Salvation Army -0.29 0.71 Northwest Territories -2.28** 0.92 Mennonite -0.67 0.63 Nova Scotia -0.46 0.28 Allophones -0.24 0.19 Nunavut -3.58** 1.44 Political knowledge 0.23*** 0.06 Prince Edward Island -1.04 0.58 Discussion frequency about politics at home 0.14 0.08 Quebec -0.74*** 0.14 Voting is a duty 1.55*** 0.1 Saskatchewan -0.70* 0.29 Partisanship 0.55*** 0.11 Yukon -0.59 0.88 Political Interest 0.16*** 0.02 Age 0 0 Income Category 0.14** 0.05 Agnostic 0.45* 0.21 Origin from non-democratic countries -0.24 0.23 Buddhist 0.23 0.41 Employment 0.32** 0.1 Hindu 0.12 0.39 Satisfaction with COVID-19 handling -0.14* 0.06 Jewish 0.08 0.4 Views on COVID-19 public health measures against Liberty 0.07* 0.03 Muslim 0.22 0.33 Duration of residence in the current city 0.23*** 0.05 Sikh 0.77 0.77 Do you think Canada should admit ……. immigrants 0.03 0.08 Anglican 0.29 0.29 Feelings towards Immigrants 0 0 Baptist 0.36 0.4 Constant -2.00*** 0.38 132 Legend: *: p < 0.05, **: p < 0.01, ***: p < 0.001 Note: Table B3 presents the regression results, including the interaction between gender and both race and immigrant status. The findings indicate no significant differences when considering gender within immigrant or other ethnic backgrounds. Additionally, the analysis aligns with the Complete model's outcome, showing that gender did not have a significant impact on the 2021 Canadian Election. This model also has 7,630 observations with 963.18 LR Chi2, and 0.2144 pseudo R2. 133 Appendix C: Frequency Table and Summary Statistics: South Asian Voter turnout 2015 and 2019 Table C1: Frequency Table and Summary Statistics: South Asian Voter turnout 2015 Variable Percent South Asian Voter Turnout 2015 No 16.67 Yes 83.33 Summary Statistics: South Asian Voter Turnout 2015 Variable Observations Mean Mean (%) Std. Dev. Min Max South Asian Voter Turnout 2015 66 0.83 83.33 0.38 0 1 Note: This table is generated from the CES 2015 dataset, where 132 respondents identified as South Asian (Indian), and 24.24% of them reported they voted in the election. Table C2: Frequency Table and Summary Statistics: South Asian Voter turnout 2019 Variable Percent South Asian Voter Turnout 2019 No 9.09 Yes 90.91 Summary Statistics: South Asian Voter Turnout 2019 Variable Observations Mean Mean (%) Std. Dev. Min Max South Asian Voter Turnout 2019 176 0.91 90.9 0.29 0 1 Note: This table is generated from the CES 2019 dataset, where 882 respondents identified as South Asian (Indian), and 8.96% of them reported they voted in the election. 134 Appendix D: Regression model results including Indigenous as a separate variable Table D1: Regression model results including Indigenous as a separate variable. Variable Coefficient Std. Error Race -0.52 *** 0.09 Indigenous -0.36 0.23 Constant 2.48 *** 0.05 This table presents the bivariate logistic regression results examining the relationship between voter turnout and race. The model includes 7,630 observations, with an LR chi² of 29.57 and a pseudo R² of 0.0066. This analysis is based on data from the 2021 Canadian Electoral Study (CES), using White as the reference group for race. Table D2: Socio-demographic model result including Indigenous as a separate variable. Variable Coefficient (log-odds) Std. Error Variable Coefficient (log-odds) Std. Error Race -0.28* 0.12 Muslim 0.20 0.3 Indigenous -0.18 0.24 Sikh 1.39 0.74 Education 0.13*** 0.03 Anglican 0.42 0.27 Gender -0.1 0.09 Baptist 0.5 0.38 Alberta 0.07 0.16 Catholic 0.29** 0.11 British Columbia -0.09 0.15 Orthodox 0.25 0.38 Manitoba -0.1 0.24 Jehovah's Witnesses -3.45*** 0.8 New Brunswick -0.24 0.3 Lutheran -0.11 0.37 Newfoundland and Labrador -0.63 0.38 Mormon -0.85 0.69 Northwest Territories -2.64*** 0.73 Pentecostal -0.06 0.28 Nova Scotia -0.43 0.26 Presbyterian 0.52 0.47 Nunavut -2.66 1.5 Protestant 0.26 0.22 Prince Edward Island -1.29** 0.48 United Church of Canada 0.98** 0.37 Quebec -0.23* 0.11 Christian Reformed Church 2.01* 1.02 Saskatchewan -0.71** 0.26 The Salvation Army -0.43 0.65 Yukon -0.89 0.78 Mennonite -0.83 0.58 Age 0.02*** 0 Immigrant -0.47*** 0.13 Agnostic 0.52** 0.2 Allophones -0.3 0.17 Buddhist 0.11 0.37 Income Category 0.27*** 0.04 Hindu 0.36 0.36 Constant -0.21 0.27 Jewish -0.21 0.38 Note: Table D2 presents the multivariate logistic regression results examining voter turnout as a function of race, region, religion, and several socio-demographic variables. The model includes 7,630 observations, with an LR chi² of 317.46 and a pseudo R² of 0.0707, indicating a modest improvement in explanatory 135 power over the previous (D1) model. This analysis is based on data from the 2021 Canadian Electoral Study (CES), using White as the reference group for race. Table D3: Complete model result including Indigenous as a separate variable Variable Coefficient (log-odds) Std. Error Variable Coefficient (log-odds) Std. Error Race -0.22 0.13 Jehovah's Witnesses -2.39** 0.85 -0.1 0.26 Lutheran -0.45 0.39 Education 0.01 0.03 Mormon -1.15 0.74 Gender 0.03 0.1 Pentecostal -0.26 0.31 Alberta -0.26 0.18 Presbyterian 0.21 0.49 British Columbia -0.25 0.17 Protestant 0.08 0.24 Manitoba -0.39 0.26 United Church of Canada 0.73 0.39 New Brunswick -0.21 0.32 Christian Reformed Church 1.88 1.03 Newfoundland and Labrador -0.72 0.41 The Salvation Army -0.30 0.7 Northwest Territories -2.28* 0.91 Mennonite -0.67 0.63 Nova Scotia -0.46 0.28 Immigrant -0.29 0.18 Nunavut -3.58* 1.44 Allophones -0.24 0.19 Prince Edward Island -1.05 0.58 Income Category 0.23*** 0.06 Quebec -0.74*** 0.14 Political knowledge 0.14 0.08 Saskatchewan -0.70* 0.29 Discussion frequency about politics at home 1.55*** 0.1 Yukon -0.57 0.88 Voting is a duty 0.55*** 0.11 Age 0 0 Partisanship 0.16*** 0.02 Agnostic 0.45* 0.21 Political Interest 0.15** 0.05 Buddhist 0.22 0.41 Origin from non-democratic countries -0.23 0.23 Hindu 0.12 0.39 Employment 0.32** 0.1 Jewish 0.09 0.4 Satisfaction with COVID-19 handling -0.14* 0.06 Muslim 0.22 0.33 Views on COVID-19 public health measures against Liberty 0.07* 0.03 Sikh 0.77 0.77 Duration of residence in the current city 0.23*** 0.05 Anglican 0.3 0.29 Do you think Canada should admit ……. immigrants 0.03 0.08 Baptist 0.37 0.4 Feelings towards Immigrants 0 0 Catholic 0.21 0.12 Constant -2.02*** 0.38 Orthodox 0.14 0.4 136 Table D3 presents the full logistic regression results examining the predictors of voter turnout, including race, religion, region, political attitudes, and pandemic-related views. The model is based on 7,630 observations, with an LR chi² of 962.56 and a pseudo R² of 0.2143, indicating a substantial improvement in explanatory power compared to previous models. This analysis utilizes data from the 2021 Canadian Electoral Study (CES), with White as the reference category for race.
Thesis/Dissertation
eng
Interdisciplinary Studies
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Heroux-Legault, Maxime
Voting behaviour and racial identity : exploring the relationship between ethnic identity and its impact on voter turnout in the 2021 Canadian federal elections
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