Abstract
Little is known about the gendered dimension of anti-Semitism. Emerging from a literature review on social identity theory, anti-Semitism, sexism, and Jewish feminism, I demonstrate the urgency of examining the link between gender and experiences of anti-Semitism, using the FRA’s 2018 dataset “Experiences and Perceptions of Antisemitism: Second Survey on Discrimination and Hate Crime against Jews in the EU,” a large-scale survey of Jews in thirteen countries across Europe. The independent variable is gender identity. Five dependent variables relate to experiences of sex/gender discrimination, physical attacks, offensive/threatening comments, offensive gestures/staring, and online harassment. Using five control variables—being identifiable as a Jew in public, country, Jewish identity, education level, and Jewish population in one’s neighborhood—I engage with descriptive statistics and binary logistic regression analysis to analyze my variables. The findings show that while women are more likely to experience gender discrimination, men are significantly more likely to experience anti-Semitism.
1 Introduction1
Following World War II, there has been a growth of scholarly research on anti-Semitism. Anti-Semitism is crucial to research because the multidimensional concept affects multiple levels of social reality, including economic, social, political, and religious dimensions.2 In the past decade, scholars have reported a growth of anti-Semitism in Europe; including Belgium,3 England,4 France,5 Italy,6 The Netherlands,7 and Spain.8 While most quantitative studies on experiences of anti-Semitism have analyzed variables related to educational levels, household incomes, political affiliation, and ritual observance,9 much less is known about the role of gender.
This article seeks to account for the gendered dimension of experiences of anti-Semitism. The literature review will first describe relevant aspects of social identity theory, which it will apply to theories of anti-Semitism. Then, it will highlight debates on gender discrimination to identify the literature gap this article addresses. Particularly, this article is guided by the following research question: “To what extent is there a correlation between experiences of anti-Semitism and gender?”
To conceptualize the experiences of the approximately 1.3 million Jews in Europe, this article uses the European Union Agency for Fundamental Rights survey of 2018: “Experiences and Perceptions of Antisemitism: Second Survey on Discrimination and Hate Crime against Jews in the EU.”10 The representative sample consists of 16,395 responses from 13 EU member states.11 The independent variable is gender identity. There are five dependent variables: experiences of sex/gender discrimination, physical attacks, offensive/threatening comments, offensive gestures/staring, and online harassment. This project uses five control variables: being identifiable as a Jew in public, current Jewish identity, country of residence, educational level, and Jewish population in one’s neighborhood. I will first conduct a bivariate analysis, which will allow readers to gain an impression of the extent to which gender is relevant to the study of anti-Semitism. After that, I will use binary logistic regression to analyze the variables. Finally, the discussion and conclusion will highlight key findings that demonstrate gender is important to understanding experiences of anti-Semitism. Particularly, the results show that while women are more likely to experience gender-based harassment, Jewish men are more likely to experience all types of anti-Semitic expressions analyzed. This is a crucial contribution to this research area as it demonstrates that gender plays an important role in experiences of ethnically and religiously motivated harassment and discrimination.
2 Literature Review
In multicultural societies, attributes such as religion, race, culture, and sexuality have led to a “politics of difference.”12 This is linked to social imaginaries and psychological fears of sameness and difference that produce and reproduce an ‘us’ and ‘them.’ To elaborate, people’s imagined reality of social groups forms a common understanding that often manifests as an in-group and an ‘other.’ These imaginations are influenced by fears, symbols, fantasies, jokes, myths, caricatures, and nightmares; and by making the other significantly different, it can lead to inhumane expressions of hatred.13 Importantly, according to social identity theory, the binary between ‘us’ and ‘them’ gets increased by perceived social, symbolic, and realistic threats, which leads to negative prejudices and stereotypes. Moreover, leadership figures and ideology influence and legitimize people’s emotional responses to, and oppression and social exclusion of, the perceived ‘other.’14 This, Bar argues, is especially relevant to contemporary scholarly debate on anti-Semitism.15 It is similarly relevant to research on sexism.
Wieviorka contends racism can be understood as a dual logic.16 One aspect is inferiorization, whereby some people are oppressed. Another aspect is differential, whereby some people are excluded socially, culturally, and politically. This duality is, for example, evident in the Holocaust. However, Bauman adds that a third aspect is our notion of the stranger. In modern societies this, he argues, has often led to assimilation, which has destroyed cultural communities. One example of this is the Eastern European Yiddish culture.17 While some have located this debate in historical research, it is equally important to contextualize and examine contemporary studies on anti-Semitism.
2.1 Anti-Semitism
This article follows Vellenga’s definition of anti-Semitism as an “aversion to Jews based on negative stereotypes and prejudices against Jews.”18 These anti-Semitic social imaginaries often do not describe Jews. Instead, they relate to Jewish stereotypes, caricatures, and prejudices, which is especially evident in the European Jewish Diaspora. To elaborate, Vellenga adds that prejudices reflect macro negative feelings about the social group whereas stereotypes are features that are believed to reflect the particular collectivity.
Anti-Semitism is not new. It can be seen throughout history in, for example, the Crusades, the Great Plague, the Alhambra Decree, biological racism, eugenics, pogroms in Russia, and the Holocaust.19 Furthermore, Kushner claims that an outcome of the Holocaust is that anti-Semitism “has become regarded as natural and even inevitable.”20 Now, Ben-Moshe argues a “new antisemitism” is manifesting itself,21 which targets the Jewish state and Jews collectively rather than individually. The manifestation of the new anti-Semitism links the Jewish people in the diaspora to the State of Israel. During the 2014 Gaza War, eight synagogues in France were attacked and the Jewish community in England reported the second largest number of anti-Semitic incidents since they had started recording them.
Anti-Semitism is a multidimensional concept. There are social, political, economic, and religious dimensions to it.22 The religious dimension, which is crucial in majority Christian (especially Catholic) countries, draws on the belief that Jews murdered Jesus.23 This Christian anti-Semitism is prevalent in Eastern European countries, where 50 percent of Poles and 33 percent of Hungarians hold Jews “responsible for the death of Christ.”24 The economic dimension reduces Jews and Jewishness to economic capital and contributes to the myth that Jews control the world economy. The political dimension is largely related to the Israeli-Palestinian conflict. For example, there are more anti-Semitic attacks committed in the diaspora when there is increased tension in Israel-Palestine. To elaborate, there were increases in incidents between 2000–2005 (the Second Intifada), 2006 (Lebanon War), 2008–2009, 2012, and 2014 (Gaza Wars), and the anti-Semitic attacks then decreased once the conflicts ceased.25 Thus, Jikeli26 explains that for some people “the demonization of Israel becomes a demonization of all Jews,” which is echoed by King and Wiener.27 The social dimension also includes exclusion and hostility in the public domain.28 This is similarly supported by Shenhav-Goldberg and Kopstein’s study on an American campus that found a statistically significant but modest relationship between anti-Israel attitudes and anti-Semitism.29 Hence, scholars contend that expressions of anti-Semitism are related to current affairs; during the economic crisis, the economic dimension was central and during increased tension in Israel-Palestine, the political dimension is key.
Jikeli30 and Padovan and Alietti31 observe that there has been a significant increase in anti-Semitic attacks in Europe since the beginning of the twenty-first century. Anti-Semitism can be manifested in behaviors and attitudes, and the spectrum is broad. It ranges from name-calling, hate letters, and online harassment to serious attacks such as assault, property damage, vandalism, and murder.32 FRA’s first study (N = 5,847) found that 21 percent of European Jews had experienced either harassment, verbal insults, or physical attacks in the past year because of their Jewish identity.33 Notably, both Jikeli34 and Padovan and Alietti35 found that, in the last two decades, the attacks have become more violent. As will be shown, the physically violent component is important to the understanding of the role of gender. Notably, Nadim and Fladmoe observe men are more likely than women to experience threats of physical attacks.36 However, this has not been analyzed in the context of anti-Semitism.
Similarly, Cohen observed that anti-Semitism has, generally, declined in the USA, but it has increased on colleges, where there appears to be a link between criticism of the State of Israel and anti-Semitic behavior. Cohen’s analysis found that perceptions of discrimination towards other minority groups affected Jews’ perceptions of anti-Semitism. As such, many feared that discrimination toward non-Jewish minority groups, such as Islamophobia, would gradually also develop into anti-Semitism.37 This could be an important observation since there has recently been a significant rise of Islamophobia and xenophobia in Europe.
Furthermore, qualitative research provides a more in-depth understanding of expressions and experiences of anti-Semitism. For example, Bear and López’s focus groups in Spain found that there is a decrease in religiously motivated anti-Semitism but a rise in political and economic anti-Semitic discourse. For example, the fact Jews constitute a minority in Spain feeds into conspiratorial anti-Semitic notions of Jews secretly overtaking the economy. The interpretative exploration also found a correlation between the Holocaust and the Israeli-Palestinian conflict. The victims of the Holocaust are presented as Israeli perpetrators and aggressors, which has reproduced negative stereotypes of Jews.38 Similarly, Thomas’s study on anti-Semitism in a Norwegian high school found that anti-Semitism is less likely to be religiously motivated. The majority said anti-Semitism in Norway was due to the Israeli-Palestinian conflict, and some believed that the majority of Jews support the oppression of Palestinians. More than half of the students had either heard people use, or had themselves used, the word “Jew” in a pejorative manner such as calling greedy people “Jews.” They said that it was not an expression of hate but, rather, a normalized expression. About half of the students also believed that Jews control the world (including the economy, media, and military) through the Illuminati.39
Alper and Olson40 found that people who have experienced anti-Semitic harassment are more likely to feel like outsiders because of their Jewish identity. Kelley and Iannaccone argue that, because Orthodox Jews adhere to the halakhah and often live isolated from the broader national society, they are more likely to feel like outsiders and therefore experience more discrimination.41 Indeed, Kremelberg and Dashefsky found that Orthodox Jews experience the highest level of anti-Semitism.42 They are followed by Reconstructivist, Conservative, Reform, and ‘just Jews’ who all experience similar rates of anti-Semitism. Notably, they argue that because Orthodox Jews are more identifiable because of their dress code and dietary requirements, they are at the highest risk of discrimination. Kremelberg and Dashefsky also observe that people with higher incomes, synagogue members, synagogue attendants, and those who belong to more traditional branches are more likely to experience incidents of anti-Semitism.43 This corresponds to theories of politics of difference since they are being ‘othered.’ As well as the social, political, and religious dimensions, the issue of gender is also relevant when investigating anti-Semitism.
2.2 Gender Discrimination
Women have historically been, and continue to be, discriminated against on a global scale. In recent years, this has been evident in the #MeToo global movement that has highlighted gender-based harassment. Delphy asserts that while sexism is a social construct, it has been biologically justified for centuries, which has led to patriarchal power structures that are continuously reproduced in socio-cultural contexts.44 Gender and sexual harassment are thus used to reinforce the gender binary where men dominate, and women are submissive.45 Walby contends that patriarchal systems produce and reproduce a gender binary in which women are both under- and misrepresented, sexually exploited, and objectified.46 Accordingly, Buchanan and Ormerod theorize gender harassment as being multidimensional. It includes sexual hostility (sexual comments and jokes), sexist hostility (misogyny), unwanted sexual interactions and attention, and explicit sexual harassment.47 Herzog adds that there are different dimensions to these types of harassment. There are legal crimes such as physical attacks, rape, and/or attempted rape; verbal attacks and sexualized displays of behavior; and sexual-related offensive behaviors that demean individuals because of their gender.48 These dimensions, in other words, contribute to normalizing a binary gender hierarchy in which women are othered.
Nonetheless, similar to the argument that anti-Semitism is normalized, Ridgeway49 and Storkey50 contend that there is a normalization of sexist behavior across socio-cultural spheres, which makes women more vulnerable to harassment and discrimination. This normalization is considered to be “everyday sexism.” To elaborate, studies in Europe, Canada, and the USA consistently show that women are significantly more likely to experience sexual harassment compared to men. In fact, almost 50 percent of women will experience sexual harassment from a non-stranger and almost all women will experience it from a stranger at some point in their lives. In most cases, findings show men are more likely to initiate sexually harassing behavior.51
Empirically, Madan and Nalla found that women are more likely to feel unsafe in public spaces due to fears of harassment, and women are more likely to experience harassment in public than men.52 Women also consider discriminatory incidents as being more serious than men. This could be because of the gender hierarchy where women do not hold a privileged position. While Nadim and Fladmoe found no significant gender differences in how likely one is to experience online harassment,53 they explain that men and women experience different types of harassment. Women, they observe, experience more gender-specific discrimination and men’s experiences are often linked to their religion, nationality, and ethnicity. Men often receive threats of physical violence whereas women are more likely to receive sexually harassing comments. As indicated, there appears to be a rise in violent anti-Semitic attacks, and, based on these studies that indicate men and women experience different types of discrimination, it is valuable to apply a gendered lens to the study of anti-Semitism. Nonetheless, scholars have barely sought to analyze the link between sexism and anti-Semitism.
2.3 Gender and Anti-Semitism
Research on anti-Semitism and gender has tended to focus on perpetrators rather than victims. D’Alessio and Stolzenberg54 and King and Weiner55 report that there is a strong correlation between gender and expressions of anti-Semitism. In fact, gender was the strongest variable in predicting who was the most likely to express anti-Semitic viewpoints. Specifically, they found that non-Jewish women were less likely to express anti-Semitic sentiments than non-Jewish men. In relation to Jews themselves, Cohen reports that Jewish “women are 11% more likely to see anti-Semitism as a serious problem.”56 This corresponds to the argument that women are more likely to feel unsafe in public places.
Rebhun suggests that there are no significant gender differences in experiencing anti-Semitism.57 On the one hand, women are more likely to experience sexual harassment. On the other hand, Jewish men, in particular Conservative and Orthodox, are sometimes more identifiable in public due to their distinctive dress code—i.e., kippot, payot, rekel/bekishe, and shtreimel. Contrastingly, Orthodox and Conservative Jewish women who dress modestly may not always immediately be identified as being Jewish—some may be perceived as a modestly dressed Catholic. Evidently, this could create a gender balance of experiences of harassment and discrimination. However, existing research has not further investigated the gendered dimension, which would clarify if there are gender differences.
One Canadian study has looked at Jewish women’s perceptions of sexism and anti-Semitism. Gold observes that while there is evidence that Canadian Jewish women experience double oppression due to their gender and Jewish identities,58 she found that the participants were ten times more likely to experience sexism than anti-Semitism; however, they were more concerned about experiencing anti-Semitism. This is primarily because, while sexism builds on a patriarchal hierarchy, anti-Semitism is paradoxical. To elaborate, Jews are sometimes perceived as both subhumans and superhumans. Some also believe Jews control the world, especially the media and economy, while Jews are also believed to be weak. This paradoxical identity perception is notable because it is often not an either/or—that Jews are either powerful or weak, but that Jews are believed to be both powerful and weak. Moreover, anti-Semitism is not addressed on the scale that sexism is. Notably, some women could predict expressions of sexism and be prepared, i.e., not walk alone at night and know how to react to catcalling. On the other hand, due to the complexity of anti-Semitism, they felt less prepared to deal with potential expressions and were, therefore, more worried.
Having presented some existing data and conversations on anti-Semitism and gender discrimination, it has become apparent that, while anti-Semitism and sexism are timely issues, there is a lack of scholarly understanding of correlations between them. Therefore, this project will address the following research question: To what extent is there a correlation between experiences of anti-Semitism and gender?
3 Methods
3.1 Data Set
To empirically examine the research question, I use the FRA cross-national survey. FRA has four primary aims:59 (1) to advance research methodologies for hard-to-access populations via online survey tools; (2) to identify changes since the first FRA survey on anti-Semitism; (3) to collect and present comparable data for EU Member States that can contribute to policy developments aimed to protect the rights of Jews in the EU; and (4) to raise awareness of fundamental human rights and address potential gaps in the protection of these rights. The dataset was acquired through the Leibniz Institute for the Social Sciences (GESIS). I submitted a request to gain access to the secured dataset and completed the necessary documents. Following the examination of my documents, they granted me access and sent me the data files.
Based on FRA’s aims, I use their cross-national survey data: “Experiences and Perceptions of Antisemitism: Second survey on discrimination and hate crime against Jews in the EU.” Conducted in 2018, this survey contains representative data from thirteen EU Member States (N = 16,395). Specifically, the participants are from the following countries: Austria (N = 527), Belgium (N = 788), Denmark (N = 592), France (N = 3,885), Germany (N = 1,239), Hungary (N = 596), Italy (N = 696), Latvia (N = 200), The Netherlands (N = 1,209), Poland (N = 425), Spain (N = 674), Sweden (N = 1,196), and the United Kingdom (N = 4,733). Due to the low response rate in Latvia, it is not included in their comparative presentations. The data collection strategy was an opt-in online survey targeting self-identified Jews; i.e., religion, ethnic background, culture, parentage, and/or other reasons. While an opt-in survey does not fulfil the requirement of random probability sampling, FRA argues the findings are the most reliable data currently available regarding the Jewish population in Europe.60 There are 386 variables in this dataset, yet my article only draws on some of the variables, due to the length of the article and the focus on gender.
3.2 Independent Variable
The analysis uses one independent nominal variable (IV): gender: male (1) (N = 8,484) and female (0) (N = 7,865). There were 46 non-binary and trans people in the sample. As a gender and sexuality researcher, using gender binaries is problematic as it is not representative of social reality and lived experiences. However, since some of my variables had cells with few trans/non-binary responses (there were some with only one non-binary/trans response), it would have been statistically insignificant and possibly not representative. Alternatively, an option would have been to generate a predictive model for trans and non-binary respondents, which could have shown some trends. On the other hand, it was a concern that the small sample, in comparison to male and female respondents, would not have generated a representative predictive model. I will therefore note that future research would benefit from recruiting more non-binary and trans people.
3.3 Dependent Variables
This project has five dependent variables (DV). As all variables are nominal, they were converted into dummy variables, which is central to the statistical estimation analysis.
3.3.1 Sex/Gender Discrimination
As indicated in the literature review, women are more likely to experience sexism. Therefore, gender discrimination is used to observe gendered trends.
DV1: “Have you felt discriminated against in the past 12 months because of your sex/gender?”
The dummy variable consists of yes (1) and no/don’t know (0). On the one hand, one could argue that this could be a control variable since it is not directly about anti-Semitism. I treat sex/gender discrimination as a dependent variable because it is necessary for our conception of gendered experiences of discrimination. In other words, to better understand the extent to which anti-Semitism is gendered, one ought to understand societal patterns of gender discrimination too.
3.3.2 Experiences of Anti-Semitism
On the one hand, I could have created an index variable to analyze if anti-Semitism is gendered—and the extent of this. However, because the literature review identified that men and women have different experiences of harassment, with men being more likely to receive threats of physical violence, I treat my variables as multiple individual indicators, which will allow me to adequately investigate the relationship between sexism and anti-Semitism. Another reason for treating these variables as individual indicators is to better understand the spatial dimension. To elaborate, Cohen critiqued the Pew Research Center (2013) for having asked if they perceived that there was a lot of discrimination toward certain population groups, without specifying what constituted discrimination, what a lot meant, and which acts and behaviors were discriminatory because it leads to a vague analysis.61 Rather, FRA’s survey is useful in that it divides experiences of anti-Semitism into categories. This provides a spatial awareness of how and where people experience incidents. This contributes to conceptualizing what constitutes expressions and experiences of anti-Semitism in the twenty-first century in Europe. Thus, I will examine four variables from the dataset. Because I am only interested in people who have experienced harassment, N will vary for these DVs.
The dataset both considers experiences in the past five years and in the past twelve months. It was decided to use the ones from the past twelve months to reflect the most current experiences and to reduce the influence of other factors, such as the Israeli-Palestinian conflict. All variables were converted into dummy variables with the following codes: yes (1) and no/don’t know (0).
DV2: “Was the physical attack(s) in the past year due to antisemitism?”
DV3: “Was the offensive/threatening comment(s) in the past year due to antisemitism?”
DV4: “Was the offensive gesture(s) to you/staring at you inappropriately in the past year due to antisemitism?”
DV5: “Was the offensive comment(s) about you on the internet in the past year due to antisemitism?”
These dependent variables offer an important understanding of anti-Semitism in Europe. As identified in the literature review, there is evidence of more physical incidents, and DV2 will address this. Socially, it is also important to understand verbal and non-verbal episodes, which I will address by looking at anti-Semitic comments and gestures. In the past decade, social media has influenced most people’s lived experiences. As such, it is also important to look at online harassment. In fact, FRA’s survey found that 80 percent of participants identified the internet as the place with the most anti-Semitic expressions and attitudes. For instance, a result of the COVID-19 pandemic is online expressions of anti-Semitic conspiracy theories.62 Consequently, it is useful to understand the physical, verbal/non-verbal, and online dimensions of anti-Semitism; and the gendered aspect of this. Theoretically, and from a social scientific standpoint, it is important to understand these spatial trends.
It is important to underline that these experience variables ought to be contextually analyzed as experiences. Bryman63 and DellaPergola64 note that people have different definitions of what constitute experiences and incidents. Some participants may also over-report whereas others may under-report experiences. Thus, the data can provide some insights into socio-cultural landscapes such as overall tendencies, but it must not be considered definitive due to potential measurement errors.
3.4 Control Variables
Because the social world is complex, it is crucial to reduce the risk of incorrectly attributing the results to the IV. By introducing control variables, I have greater support for arguing that causal relations are linked to the IV and not based on other factors.65 Five control variables will therefore be used. The first is if people are identifiable as a Jew in public, which has been coded as: yes (1) and no (0). The second is how the participants describe their current Jewish identity. This has the following categories: Just Jewish (1), Reform/Progressive (2), Traditional (3), Orthodox (4), Haredi (5), Mixed (Jewish and another religion) (6), and None of these options (7). At face value, one could assume that anti-Semitism in Europe is ubiquitous and uniform; however, Rich argues it is also country-specific.66 Thus, I also control for country. The literature review identified that neighborhood demographics and educational levels have often been linked to perceptions and experiences of anti-Semitism too. Consequently, I control for these factors too. Education level has been coded the following way: no primary education completed (1), primary education (2), lower secondary education (3), upper secondary education (4), post-secondary education, but not tertiary (5), post-secondary, but not tertiary or short-cycle tertiary education (6) and tertiary education—first and advanced level (7). Finally, I also control for the Jewish population in the area. This question has the following categories: none or very few (1), a few (2), about half (3), a lot (4), and almost all or all (5).
3.5 Statistical Estimation
All the dependent variables are nominal, which means they do not have distance and order. By using dichotomous dependent variables, it will be possible to conduct logistic regression analyses. I will use binary logistic regression (BLR) for my statistical analysis. Unlike ordinary least squares (OLS), which is used for scale variables, BLR is used “to test whether the mean of the outcome variable differs among categories of a predictor variable.”67 In other words, BLR is used for dichotomous dependent variables, which all the dependent variables are in this article. In particular, the BLR technique is used to understand how various experiences of discrimination relates to one’s gender identity. This will be illustrated by odds ratios. BLR produces odds ratios, which will here indicate that odds ratios greater than ‘1’ suggest there is an increased likelihood of experiencing anti-Semitism as a result of one’s gender identity, whereas odds ratios of ‘1’ suggest a lower likelihood of a gender correlation.68 The variables have been converted into dummy variables for the regression analysis.
Before estimating and analyzing the models, two methodological issues should be addressed. Firstly, this research is cross-national and macro-scale. This article aims to provide insights into European experiences. Consequently, it is also likely to introduce country-specific factors and effects.69 In this dataset, the majority of participants reside in England and France. One must therefore be careful to not let these countries drive the data analysis. I, therefore, weigh the country variables, which will help reduce the impact of country-specific factors and the population differences. Another issue is that correlation research often focuses on unidirectional patterns rather than accounting for circular patterns. This means that, one’s likelihood to experience anti-Semitism not only relates to one’s gender identity, but the reverse could be true—that one’s gender identity heightens one’s chances of experiencing anti-Semitism. There are regression instruments that can be used to account for these potential loops; however, they are often complicated processes. As a result of the robustness of the findings that I will present, it was decided that further regression techniques to control for circular patterns would not alter the substantive and statistically significant findings in this study.
4 Bivariate Findings
To empirically assess whether there is a link between gender and experiences of anti-Semitism, I ran multiple basic descriptive statistical models. Organizing my analysis with bivariate and multivariate models will allow me to make maximum use of the variables I use from the dataset. It will also help to identify a varied empirical perspective on correlations between the variables. All the variables that I use are nominal, so the bivariate statistical analysis consisted of cross tabulations and chi-square tests that tested for p (cut off value at p <. 05),70 which will help identify some emerging findings of the relationship between gender and anti-Semitism.
4.1 Dependent Variables
The analysis of DV1: sex/gender discrimination, showed that 2013 participants had experienced discrimination. Of the whole sample, 22.2 percent of women (N = 1745) and 3.2 percent of men (N = 268) had felt discriminated against in the past year because of their sex/gender. Here,
I then analyzed the variables that related to experiences of anti-Semitism. DV2: experiences of physical harassment due to anti-Semitism. 205 participants had experienced one or more physical attacks in the past year due to anti-Semitism: 138 men and 67 women. The chi-square test showed that
4.2 Control Variables
Following the bivariate analysis of the dependent variable, I similarly constructed bivariate models of the control variables.
Of the full sample (N = 16.349), 8391 respondents wore, carried, or displayed something that might help people recognize them as Jews in public. Here, that was 51.2 percent of men (N = 4346) and 51.4 percent of women (N = 4045). Here
5 Inferential Statistics: Multivariate Findings
Following the results of the descriptive statistics, I engage with regression analysis techniques. This will clarify the significance of the correlations between gender identity and experiences of anti-Semitism, which will thereby enable me to discuss the significance of the findings. I first recoded my control variables into dichotomous variables. Next, I weighted the country variable so that the results would not be skewed due to the fact the majority of participants are from France and the United Kingdom. All variables were tested with male and female reference categories to determine the most effective way to present the data. For Jewish identity, I use ‘None of these’ as the reference category, and for country, I use Belgium.71 For educational level, I use ‘no primary education’ as the reference, and for the Jewish population in the neighborhood, I use ‘almost all or all’ as reference. It was considered to apply statistical matching techniques to the multivariate analysis. However, the BLR, as will be shown, identifies statistically significant correlations between gender and anti-Semitism, so it was decided that BLR sufficiently demonstrates the correlation between gender and experiences of anti-Semitism.
Multiple tables were produced for this analysis. For the data presentation, I created two tables: one for sex/gender discrimination and one for the experiences of anti-Semitism variables. The tables consist of odds ratios and the significance level (p-value). It was decided to combine the experiences of anti-Semitism for multiple reasons. Firstly, the bivariate model indicated men were more likely to experience anti-Semitism, so I was able to consistently use the same reference category; and, secondly, the overview makes it easier to compare and contrast the different types of discrimination.
5.1 Sex/Gender Discrimination
The bivariate model showed that women were more likely to experience gender/sex discrimination. This is similarly evident in the multivariate model. Here, the odds ratio is 1 male : 7.7 women (p = .000), which makes it statistically significant. In other words, European Jewish women are 7.7 times more likely to experience sex/gender discrimination than men. Those who are identifiable as Jews are 1.3 times more likely to experience discrimination too (p = .000). In relation to current Jewish identity, those who identify as ‘Mixed (Jewish and another religion)’ are more likely to experience harassment than those who identify as ‘None of these’ (p = .017). Regarding country, Austria, Germany, and Poland were statistically significant. Notably, the results suggest that those who live in predominantly Jewish areas are less likely to experience gender/sex discrimination. Finally, regarding educational level, those who have completed upper secondary education (odds ratio 1.5, p =.000) and tertiary education (odds ratio 1.4, p =.000) were the most likely to experience sex/gender discrimination (see Table 1).
Logistic regression (odds ratios) of experiences of gender discrimination in past 12 months on gender, Jewish identity, country, neighborhood demographics, and educational level
Citation: European Journal of Jewish Studies 16, 2 (2022) ; 10.1163/1872471X-bja10043
Logistic regression (odds ratios) of experiences of gender discrimination in past 12 months on gender, Jewish identity, country, neighborhood demographics, and educational level
Citation: European Journal of Jewish Studies 16, 2 (2022) ; 10.1163/1872471X-bja10043
Logistic regression (odds ratios) of experiences of gender discrimination in past 12 months on gender, Jewish identity, country, neighborhood demographics, and educational level
Citation: European Journal of Jewish Studies 16, 2 (2022) ; 10.1163/1872471X-bja10043
Overall, the binary logistic regression model shows that gender is the most significant factor. Following the presentation of the data on experiences of anti-Semitism, I will engage with a discussion of the findings.
5.2 Experiences of Anti-Semitism
The multivariate analysis considered all dependent variables 2–5 individually, and for presentation purposes, I combined the tables into one. The top number is the odds ratio and the second is the p-value. For this overview, I will first evaluate the gendered aspect, and then compare and contrast the control variables (see Table 2).
Logistic regression (odds ratios) of experiences of anti-Semitism in past 12 months on gender, Jewish identity, country, neighborhood demographics, and educational level*
Citation: European Journal of Jewish Studies 16, 2 (2022) ; 10.1163/1872471X-bja10043
Logistic regression (odds ratios) of experiences of anti-Semitism in past 12 months on gender, Jewish identity, country, neighborhood demographics, and educational level*
Citation: European Journal of Jewish Studies 16, 2 (2022) ; 10.1163/1872471X-bja10043
Logistic regression (odds ratios) of experiences of anti-Semitism in past 12 months on gender, Jewish identity, country, neighborhood demographics, and educational level*
Citation: European Journal of Jewish Studies 16, 2 (2022) ; 10.1163/1872471X-bja10043
Logistic regression (odds ratios) of experiences of anti-Semitism in past 12 months on gender, Jewish identity, country, neighborhood demographics, and educational level*
Citation: European Journal of Jewish Studies 16, 2 (2022) ; 10.1163/1872471X-bja10043
Logistic regression (odds ratios) of experiences of anti-Semitism in past 12 months on gender, Jewish identity, country, neighborhood demographics, and educational level*
Citation: European Journal of Jewish Studies 16, 2 (2022) ; 10.1163/1872471X-bja10043
Logistic regression (odds ratios) of experiences of anti-Semitism in past 12 months on gender, Jewish identity, country, neighborhood demographics, and educational level*
Citation: European Journal of Jewish Studies 16, 2 (2022) ; 10.1163/1872471X-bja10043
Logistic regression (odds ratios) of experiences of anti-Semitism in past 12 months on gender, Jewish identity, country, neighborhood demographics, and educational level*
Citation: European Journal of Jewish Studies 16, 2 (2022) ; 10.1163/1872471X-bja10043
Jewish men are consistently more likely than Jewish women to experience antisemitic discrimination. They are 1.8 (p = .000) times more likely to experience a physical attack, 1.4 (p = .000) times more likely to experience offensive and/or threatening comments, 2.3 (p = .000) times more likely to experience offensive gestures or staring in public, and 1.5 (p = .000) times more likely than women to be subject to online harassment. While the literature review made me predict men would be more likely to be physically attacked, it is notable that men are also more likely to experience offensive comments, gestures, and staring.
While there evidently is a gendered dimension to experiences of antisemitism, the control variables are important to discuss too as they nuance the results and discussion. Firstly, being identifiable as a Jew in public is clearly correlated to experiences of antisemitism: DV2 has an odds ratio of 3.2 (p = .000), DV3 has an odds ratio of 1.4 (p = .000), DV4’s odds ratio is 1.8 (p = .000), and DV5’s odds ratio is 1.7 (p = .000).
The respondent’s current Jewish identity is similarly relevant to the results. The reference category is, as stated, ‘None of these.’ Interestingly, those who identified as ‘Just Jewish’ were often more likely to experience antisemitism than those who identified as ‘Reform/Progressive’, with the exception of online discrimination. Overall, Traditional, Orthodox, and Haredi Jews were significantly more likely to experience antisemitism (p = .000). For example, Haredi are almost 11 times more likely to experience a physical attack than those who identify as ‘None of these.’ Evidently, the table shows that the most important factor in one’s likelihood to experience antisemitism is one’s current Jewish identity.
Next, for countries, a weighted variable, I used Belgium as the reference category. Here, it was primarily Germany, The Netherlands, Sweden, and Denmark that had some high odds that were statistically significant. A lot of the p-values, however, were not statistically significant to the analysis.
For the Jewish population in the area, I used ‘almost all or all’ as the reference category. In relation to DV2, those who lived in areas with none or very few Jews were 2.3 (p = .000) times more likely to experience discrimination than those who lived in areas that are predominantly Jewish. The odds ratios are relatively similar for DV3, although, people who live in areas with a lot of Jews are the most likely to experience offensive and/or threatening comments. This is also the case for DV4. Interestingly, for both DV3 and DV4, those who live in areas with a lot of Jews are closely followed by those who live in places with none or very few Jews. Finally, people who live in areas where almost all or all are Jews are more likely to experience online harassment than the other groups.
Finally, the educational level shows some high odds ratios, however, they are statistically insignificant. A couple of results show an extremely high odds ratio. These are outliners. In some cases, people with some educational backgrounds, who had experienced discrimination, had all experienced anti-Semitic discrimination; i.e., one person with secondary but not tertiary education had experienced online discrimination and it was due to anti-Semitism, which created this outliner result. In such cases, it would have been good to have weighed this variable, however, it was prioritized to weigh for countries. While sometimes not statistically significant, generally, those with a primary, lower secondary, and tertiary education are the most likely to experience physical discrimination. Those with lower secondary, post-secondary but not tertiary, and tertiary are the most likely to experience offensive and/or threatening comments. Those with lower secondary and no primary education are the most likely to experience offensive gestures/staring in public. And none of the results are statistically significant for experiences of online harassment.
Having presented an overview of the findings, the following section will discuss these results by evaluating them and relating them to the literature review.
6 Discussion
The data analysis suggests that there is a statistically significant gendered dimension to experiences of anti-Semitism, an aspect that has previously been ignored in most scholarly research on experiences and perceptions of anti-Semitism. The analysis consistently showed that Jewish men were more likely to experience anti-Semitic incidents, whereas women were more likely to experience gender-based discrimination, which was supported by statistical significance. Following these results, I will discuss the findings further in this section.
The findings of DV1 correspond to existing research. Madan and Nalla similarly found that women were significantly more likely to experience public harassment.72 Nadim and Fladmoe also found that women were more likely to experience gender-based harassment in public.73 As such, it was not surprising that the odds ratio were 7.7 women per 1 man. As stated, the primary reason for including this variable was to give a clear indication of the respondents’ experiences of gender harassment, which then provides ample ground for the comparison with experiences of anti-Semitism as the variables derived from the same dataset.
Results indicate that compared to women, men are significantly more likely to experience anti-Semitic incidents. This is the case for all the examined variables. It was predicted that men would be more likely to experience physical attacks. In fact, 80 percent of physical assaults against men are by strangers. The perpetrators are also often men.74 The other results, however, were not expected. Studies from the literature review, such as Buchanan and Ormerod (2002)75 and Madan and Nalla (2016),76 suggested women would be more likely to experience verbal insults and offensive gestures in public. This, therefore, provides an important gendered dimension to the process of ‘othering’ based on one’s ethnic and religious identity.77 Additionally, Nadim and Fladmoe’s (2019)78 study suggested men’s experiences of online harassment are often related to their ethnic and religious identities. Drawing on the bivariate findings, however, women’s experiences of online harassment were also linked to anti-Semitism but not to the same degree as men. To summarize, the results suggest that the process of gendering anti-Semitism contributes to important conversations on experiences of discrimination. The next question is why?
It should be noted that, while the gender variable is statistically significant across all the analyzed variables, it is not the most important factor. Being identifiable as a Jew in public and current Jewish identity are the most important factors. Now, one explanation for the gendered aspect of these findings is that Jewish women might be less identifiable in public. As argued, modest dress is not necessarily always an indication of which religion someone belongs to—strangers might not immediately identify them as Jewish at least. Contrastingly, Jewish men tend to be more identifiable in public because some wear kippah, rekel/bekishe and shtreimel and have payot. This is especially the case for Orthodox and Haredi men. As such, this corresponds to previous studies that note Orthodox Jews are the most likely to experience discrimination.79 As such, it is surprising that research has not focused on the gendered aspect of religious visibility before.
Anti-Semitism is, as mentioned, not solely religiously motivated. It is also political and economic. The financial sector tends to be male dominated, so Jewish men might be more likely to be exposed to economically motivated anti-Semitic comments. Similarly, the political and military spheres are also male dominated.80 As such, Jewish men are more visible than women. FRA’s quantitative study did not offer the possibility to investigate the nature of the comments/gestures nor where they were experienced. As such, qualitative research is needed to accurately explain and contextualize the nature of offensive comments/gestures and how they are experienced. Building on the qualitative empirical research in the literature review, numerous participants in both Baer and López81 and Thomas’s82 research expressed a belief that Jews control the economy, and many see Israelis as aggressors and oppressors due to the Israeli-Palestinian conflict. However, one must be careful to not draw conclusions without adequate evidence to support these claims. Qualitative research ought to add a gendered lens to research on anti-Semitism to appropriately situate the role of gender in conversations on anti-Semitism.
Space is important to conversations on anti-Semitism. Visibility is not merely about physical visibility. It is also a matter of online presence. In line with how scholars argue anti-Semitic incidents are becoming more aggressive, they are similarly becoming more aggressive online, where there is also a growth of anti-Semitism. For example, Buarque identifies a spread of anti-Semitic conspiracy theories related to COVID-19.83 It will, thus, be crucial to monitor and navigate these online expressions of anti-Semitism to further draw conclusions on the role of gender.
Thus, the findings demonstrate that gender is correlated to experiences of anti-Semitism, although it is not the most important factor. That does not make it any less important, and research is needed to further investigate this. Current Jewish identity and Jewish visibility have the highest influence on one’s likelihood to experience anti-Semitism. This corresponds to social identity theories and the process of ‘othering’ people based on their religious and ethnic identities.84 This furthermore highlights the social aspect of anti-Semitism in that some people are socially excluded and experience hostility in the public domain.85 Nonetheless, gender is an important characteristic to consider, which has previously often been either ignored or downplayed in existing research. Men were consistently more likely to experience anti-Semitism than women. This is notable as the literature review identified that women were more likely to be concerned about experiencing an anti-Semitic attack.
7 Conclusion and Limitations
This project shows that while women are more likely to experience sexist discrimination, men are significantly more likely to experience anti-Semitic attacks in all areas analyzed. There is therefore a great correlation between gender and experiences of anti-Semitism. This article, therefore, counters Rebhun’s view that there are no significant gender differences in experiencing anti-Semitism.86 It also supports Gold’s finding that Canadian Jewish women are more significantly more likely to experience sexism than anti-Semitism.87 The findings are a valuable addition to Nadim and Fladmoe’s study,88 which found that women’s experiences of harassment are more often linked to their gender and men’s to their ethnic and religious identities. Nonetheless, Jewish identity is statistically the most important factor.
There are limitations to this study. While the overall sample was large, several of the DV s had a smaller sample, since it only analyzed people who had experienced harassment. Next, as a gender and sexuality scholar, I do not see gender as a binary. However, due to the very small trans and non-binary sample (N = 46), it was decided to focus on men and women, since it would have been difficult to create a representative insight into trans and non-binary experiences. Alternatively, I could have, as mentioned, created a model in SPSS that draws on existing data to produce a representative sample. Nonetheless, it was decided that 46 responses across Europe, with sometimes only one response in a DV, would not be sufficient to create a representative model. While the findings do show a gendered dimension of experiences of anti-Semitism, it is not fully representative of social reality as it does narrate a social reality based on a gender binary. Future research could benefit from a more gender-inclusive sampling strategy to conceptualize trans and non-binary Jews’ experiences, which will allow for more accurate insights into gender and anti-Semitism research. The third limitation is that Judaism is not uniform. Being Reform in England means something different to being Reform in Germany, thus one’s Jewish identity can be affected by that. Hence, while country findings were not statistically significant, Jewish identity can be informed by one’s country of residence.89 This will undoubtedly affect the way the control variable should be read and understood.
This project provides evidence to expand research on gender-based harassment since men are more likely to experience anti-Semitic attacks. Because most research on anti-Semitism has undermined the role of gender, and because most research on gendered discrimination focuses on women’s experiences, there is currently little theoretical and empirical understanding of why men experience more anti-Semitic attacks. This article, therefore, invites future research to focus on men’s experiences of harassment and discrimination. Notably, it invites researchers to conduct qualitative research on experiences of anti-Semitism to further contextualize experiences and expressions of anti-Semitism. This will further enable researchers to understand the gendered dimension. Furthermore, this article identifies the importance of ethnic and religious discrimination in gender studies, which is vital to understanding social reality. This must therefore be further examined from an intersectional standpoint.
The author would like to thank the EJJS editors and two anonymous referees for their constructive feedback. She would also like to thank Dr. Christopher Kollmeyer for teaching her advanced quantitative analysis and reading her draft, and her brother Mikkel Astrup Jensen for assisting with the statistical models. The author is an ESRC-funded doctoral student, http://dx.doi.org/10.13039/501100000269 ES/P000592/1.
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Rebhun, “Correlates of Experiences,” 52.
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Ibid., 14.
Cohen, “Generalized Discrimination Perceptions,” 416.
Beatriz Buarque, “An Anti-Semitic Wave May Hit the World in the Aftermath of the Pandemic,” OpenDemocracy (2020), https://www.opendemocracy.net/en/democraciaabierta/anti-semitic-wave-may-hit-world-aftermath-pandemic/ (accessed 6 May 2020); CTS, Coronavirus and The Plague of Antisemitism (London: CTS, 2020).
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Ibid., 50; Alper and Olson, “Do Jews Feel,” 825.
Rich, “IS IT GOOD,” 15.
Rachel A. Gordon, Regression Analysis for the Social Sciences, 2nd ed. (New York: Routledge, 2015), 216.
Christopher Kollmeyer, “Why Workers (Don’t) Join Labour Unions,” Comparative Sociology 12(4) (2013): 548–574.
Ibid., 559–560.
John H. McDonald, “Fisher”s Exact Test of Independent,” Handbook of Biological Statistics (2014), http://www.biostathandbook.com/fishers.html (accessed 2 May 2020).
I also tested with Denmark and Sweden. Since there were no major statistical differences, I chose to use Belgium as the reference country.
Madan and Nalla, “Sexual Harassment in Public Spaces.”
Nadim and Fladmoe, “Silencing Women.”
Government of Canada, “SNAPSHOT: Male Victims of Violent Crime,” Victims and Survivors of Crime Week (2015), https://www.victimsweek.gc.ca/res/r512.html (accessed 9 May 2020).
Buchanan and Ormerod, “Racialized Sexual Harassment.”
Madan and Nalla, “Sexual Harassment in Public Spaces.”
See Romeyn, “Liberal Tolerance”; Vellenga, “Anti-Semitism and Islamophobia.”
Nadim and Fladmoe, “Silencing Women.”
Alper and Olson, “Do Jews Feel”; Ira M. Sheskin, “American Jews,” in Ethnicity in Contemporary America: A Geographical Approach, ed. J.O. McKee, 2nd ed. (Oxford: Rowman & Littlefield Publishers, 2000), 227–261; Kremelberg and Dashefsky, “Targets of Out-Group Hostility.”
Baer and López, “Blind Spots”; Jikeli, “Explaining the Discreprancy.”
Baer and López, ibid.
Thomas, “Exploring Anti-Semitism in the Classroom.”
Buarque, “Anti-Semitic Wave.”
Romeyn, “Liberal Tolerance”; Werbner, “Folk Devils.”
Vellenga, “Anti-Semitism and Islamophobia.”
Rebhun, “Correlates of Experiences.”
Gold, “Sexism and Antisemitism.”
Nadim and Fladmoe, “Silencing Women,” 3–11.
Erik H. Cohen, “Values and Religious Identification among Affiliated Jews in Eastern Europe,” International Journal of Jewish Education Research 2013(4) (2013): 69–102.