Perceiving Migrants as a Threat: The Role of the Estimated Number of Migrants and Symbolic Universes

Abstract

As immigration is one of the dominant issues in contemporary public discourse, it is important to explain the mechanism of prejudice against immigrants from a cultural psychology perspective. Several studies in the literature have confirmed a significant relationship between perceptions of the estimated size of the immigrant population and negative attitudes towards them. This study aims to investigate whether this relationship is moderated by symbolic universes, i.e., affect-laden generalized worldviews. The study involves a representative sample of 3020 Italians who participated in a computer-assisted web survey and completed a questionnaire containing items measuring their estimates of the size of the migrant population in Italy, political orientation, cultural worldviews (symbolic universes), and the perceived threat posed by migrants. The results confirm that the relationship between the estimated size of the migrant population and the perceived threat is moderated by symbolic universes, being stronger for participants who hold both pessimistic and idealizing symbolic universes. The results are interpreted within the framework of semiotic cultural psychology theory.

1. Introduction

Several studies have shown that the perception of threat, real or imagined, is one of the most important predictors of attitudes and prejudice towards immigrants and other out-groups (e.g., Murray and Marx 2013; Pereira et al. 2010; Quillian 1995; for a review see Esses 2021; Esses et al. 2017; Riek et al. 2006). For example, from the European Social Survey (2002) in 21 European countries with a representative sample (N = 36,566), Pereira et al. (2010) found that the relationship between prejudice and opposition to immigration was more strongly mediated by realistic than by symbolic threat perceptions.

The group threat hypothesis (Blumer 1958; Blalock 1967) and the intergroup threat theory (Stephan and Stephan 2000; Stephan et al. 2016) are important theoretical frameworks for understanding the role of perceived threats in the development of intergroup prejudice. Perceived threat is the threat that group members believe they are experiencing, regardless of whether it exists or not. Intergroup threat theory distinguishes between two basic types of perceived threat: realistic threat and symbolic threat. Realistic threats refer to the perception that the in-group’s power, economy, security, politics and various resources such as employment, social services, education and health care are endangered or jeopardized by out-group members (e.g., Simonovits 2016; Vallejo-Martín et al. 2020). Instead, symbolic threats indicate menaces to the in-group values, culture, traditions, religion, moral standards and beliefs (Stephan et al. 2009, 2016).

Several studies have shown that the estimated size of the migrant population is positively and significantly related to perceived threats and negative attitudes towards migrants in North America and Europe (Rink et al. 2008; Semyonov et al. 2006, 2008). Increased numbers of international migrants can bring several changes and challenges to host communities (Simonovits 2016). They can increase competition for resources and facilitate cultural conflicts over norms and values, identity concerns and security worries (Ivarsflaten 2005; Simonovits 2016). Members of the host community may fear that their culture and privileges will be damaged or threatened (Esses et al. 2002).

1.1. Estimated Size of the Migrant Population

The relative size of the out-group population and economic conditions have long been regarded by social scientists as the two main contextual predictors of competitive threat (e.g., Quillian 1995; Scheepers et al. 2002; Coenders et al. 2004). For example, Semyonov et al. (2006) showed that xenophobic sentiments were more pronounced in places with a large foreign population, problematic economic conditions and higher support for extreme right-wing parties. Similarly, Rink et al. (2008) showed that the size of the immigrant population increases the likelihood of voting for the anti-immigrant party, and that this effect is curvilinear. In addition, Schneider (2008) found that, the higher the proportion of non-Western immigrants, the higher the average level of perceived threat from them. However, not all studies have confirmed this relationship. For example, in their meta-analysis, Pottie-Sherman and Wilkes (2017) concluded that some studies found a positive relationship between the size of the immigrant population and attitudes towards them, while others found a negative relationship or no relationship at all. Strabac (2011) showed that the actual size (number) did not significantly correlate with prejudice, but only the estimated size did so.

Several studies have found a tendency for a large proportion of the population in Western countries to overestimate the number of immigrants (e.g., Bonifazi 1992; Freeman 1995; Kosic et al. 2012; Sigelman and Niemi 2001). Overestimating the number of immigrants has been found to increase the likelihood of negative attitudes towards foreigners (Gordon et al. 2020).

This study aims at an in-depth understanding of the relationship between size estimates and perceptions of migration. This issue is highly relevant, given the progressive increase in foreigners in host countries, including Italy. We want to investigate whether the relationship between the estimated number of migrants and the perceived threat can be moderated by so-called symbolic universes, which are affect-laden patterns of meaning that function as frames for perceptions, opinions and judgments about micro- and macro-social environments (e.g., how things are/should be).

1.2. Migrant Context in Italy

Since 2011, the increase in political instability in the countries of the Eastern and Southern Mediterranean has affected the dynamics of regional and international migratory flows. In this scenario, Italy, due to its geographical position at the southern border of Europe, is one of the most important entry points and one of the main destinations of migrants in the EU (Ambrosetti and Paparusso 2018; Kosic and Triandafyllidou 2007; Pastore and Villosio 2011). Migration to Italy has gradually increased since the 1990s. Since 2014, Italy has received an increasing number of asylum seekers: 64,886 in 2014, and 83,970 in 2015 (Ambrosetti and Paparusso 2018; ISTAT 2021c). There are currently 5 million foreigners legally resident in the country, which is almost 8.5% of the total resident population (Caritas and Migrantes 2021). It should also be taken into account that, over the years, Italy has had to deal with a large number of irregular migrants (estimated at 10% of the regular population), and the Italian government has used several amnesties to regularize their situation (Caritas and Migrantes 2021).

Some right-wing political leaders and the mass media have constantly drawn attention to the number of immigrants entering the country, portraying them as an invasion and contributing to the spread of negative attitudes towards them (Esses et al. 2013; Graf et al. 2020). When information is the target of high attention, it tends to become salient (e.g., McArthur Zebrowitz and Ginsberg 1981).

1.3. Symbolic Universes

In recent decades, several authors, especially from cognitive sociology (Zerubavel 1997) and cultural psychology (Trandis et al. 1988; Valsiner 2007), have pointed out that attitudes towards social objects—i.e., as of interest here, towards migrants—can be influenced, not only by the beliefs that social actors hold about this category, but also by the more general worldviews that they hold. Worldviews are broad assumptions about society and the world, specifically the ways things are and should be. They serve as overarching frameworks that shape how people interpret social objects and events (for a review, see Koltko-Rivera 2004; Salvatore 2018).

Recently, semiotic cultural psychology theory (SCPT, Salvatore 2018; Valsiner 2007) has introduced the notion of ‘symbolic universes’, defined as an affect-laden generalized pattern of meanings that acts as a basic framework for perceptions/opinions/judgments about micro- and macro-social environments (e.g., evaluations of the place where people live, living conditions, the level of trustworthiness of local services, attitudes towards their community and political elites, etc.). Symbolic universes do not refer to concrete objects (e.g., immigration, place of residence) or to a specific domain (e.g., institutions, family…), but to the more general context and to the way things are/should be. According to the SCPT, symbolic universes can indirectly guide feelings, thoughts and actions. This happens in two ways (Salvatore et al. 2018). On the one hand, the symbolic universes may limit the access to the information about the social object that may contrast with pre-existing beliefs. On the other hand, symbolic universes may moderate the salience of the information that confirms them. The more incoming information is congruent with the symbolic universe, the more the latter one is salient in framing the interpretation of the object and guiding behavior (Salvatore et al. 2018).

In a cultural milieu there is a plurality of symbolic universes. The fact that people are embedded in the same cultural milieu does not mean that they have the same feelings, ideas and behavioral responses. Rather, it means that the variability in their feelings, thoughts and activities reflects (i.e., is channeled and constrained by) the plurality of symbolic universes in their cultural context. Individuals make sense of their experiences in terms of a pattern of meanings—that is, ideas, attitudes and feelings that cut across different contexts and experiences in a sufficiently stable and homogeneous way, regardless of the semantic connections between them (Salvatore et al. 2018).

Previous studies suggested four clusters of symbolic universes (e.g., Kerušauskaitė et al. 2023; Salvatore et al. 2019c). These clusters have been interpreted as follows:

Symbolic Universe 1, “Discouraged members”, contains respondents characterized by moderate fatalism, mistrust of people and institutions, pessimism, conformity and passivity. For these individuals, society is a place to be accepted as it is, whose “rules of the game” require passive compliance.

Symbolic Universe 2, “Confident and engaged”, includes individuals who are characterized by a moderate rejection of fatalism and conformity, and a moderate trust in people, agencies and institutions. For these people, society is something to be engaged with.

Symbolic Universe 3, “Idealizing optimists”, refers to people who are characterized by a strong rejection of fatalism, amorality and conformity, and by a high level of trust in people, institutions, the future and the ability to change society (high agency). All positive qualities are exalted and all negative aspects are strongly rejected. For these individuals, society is a place to idealize.

Symbolic Universe 4 “Reactive Anomics”. People in this cluster are characterized by extreme distrust of institutions, extreme fatalism and pessimism. For them, society is a rejecting reality without meaning.

Recent studies have provided evidence for the role of symbolic universes in shaping attitudes and behaviors in areas such as voting behavior (Andreassi et al. 2023) and vaccination hesitancy (Cordella et al. 2023). A large-scale research project in several European societies led to the identification of a symbolic universe that connotes the world as a jungle, a threatening place (Salvatore et al. 2018). People who identify with this symbolic universe tend to interpret every event and circumstance as a potential source of threat from which one must protect oneself. Based on these findings, we hypothesize that symbolic universes may also play an important role in shaping attitudes towards migrants (for evidence consistent with this hypothesis, see Salvatore et al. 2019b). Furthermore, we expect that symbolic universes may influence the salience related to the size of migration and thus moderate the relationship between the estimated size of the migrant population and perceived threat.

1.4. Aims and Hypothesis

Based on the above considerations, this study aims to answer the following three questions:

• HP1: Is there a positive relationship between the estimated size of the migrant population and the perceived realistic threat they pose?

• HP2: Do symbolic universes predict the perception of migrants as a threat in all segments of the population (in the total sample as well as the sample divided into three groups: (a) those who underestimate the number of migrants; (b) those who make a correct estimate; and (c) those who overestimate the number of migrants)?

• HP3: Is the relationship between the estimated size of the migrant population and the perceived real threat moderated (i.e., exacerbated or reduced) by the symbolic universes that individuals hold?

2. Results

2.1. Descriptive Statistics

Estimation of the number of migrants in Italy. Participants were asked to estimate the number of migrants in Italy (regular and irregular) and to choose an answer from seven possible alternatives (100 thousand, 700 thousand, 1.5 million, 6 million, 12 million, 24 million, 32 million). About half of the participants (52.9%) think that there are 1.5 million or fewer migrants in Italy, followed by the 33.8% of the participants who think that there are about 6 million migrants (which is close to the correct number). Only 13.2% of participants overestimate the number of migrants in Italy (thinking that there are more than 12 million migrants).

To test the relationship between the estimated number of migrants and the perceived threat, we performed an analysis of variance with the perceived threat as a dependent variable (Table 1). There was a significant effect of the estimated number of migrants F(6,3020) = 17.27; p < 0.001). Specifically, participants who overestimate the number of migrants perceive them as a threat (H1). Of course, as this is a correlational study, we cannot state anything about the cause nor the effect.

In addition, participants were asked to estimate on a 5-point scale whether the number of migrants has increased or decreased in the period of 2018–2020, compared to 2015–2017. The majority of participants (68.2%) think that the number of migrants has increased.

2.2. Correlations

The correlations between the variables are presented in Table 2 and Table 3. In the first analysis we considered the following variables: the index of perceived threat from migrants, the estimated size of the migrant population, the perception that the number of migrants has increased in recent years, four clusters of symbolic universes and socio-demographics (gender, age, educational level and political orientation).

As we can see in Table 2, perceived threat is positively correlated with the estimated size of the migrant population, the perception that the number of migrants has increased in the last three years, and political orientation (higher for participants with a right-wing orientation) (H1). Furthermore, perceived threat is positively correlated with cluster 4 (“Reactive anomics”—high distrust in institutions and pessimism), but also with cluster 3 (“Idealizing optimists”—high trust in people and institutions and high agency). We find negative correlations between different clusters. We also found a negative correlation between perceived threat and educational attainment. Symbolic universes were not associated with any of the socio-demographic indicators—i.e., age, gender or level of education (the chi-square test, which is used to determine whether the data are significantly different from what is expected, was not significant).

In the second analysis (Table 3), we calculated the correlations using five factorial dimensions instead of clusters. The results showed that perceived threat is positively correlated with the negative vision of society and fatalism, as well as negatively correlated with a positive vision of society and a sense of agency. The factorial dimensions are not significantly correlated with the socio-demographic characteristics.

Furthermore, we checked the correlations between the variables when selecting each of the three categories of participants: those who underestimate the size of the migrant population, those who overestimate it, and those who are informed about the statistical data. First, we selected the participants who underestimate the size of the migrant population and found the same correlations as for the total sample: the perceived threat of migrants is positively correlated with clusters 3 (“Idealizing optimists”; r = 0.18) and 4 (“Reactive anomics”; r = 0.21). Similar correlations were found for participants who are more realistic about the statistical data regarding the number of migrants in Italy: the perceived threat of migrants is positively correlated with clusters 3 (“Idealizing optimists”; r = 0.18) and 4 (“Reactive anomics”; r = 0.23). Instead, for those who overestimate the number of migrants, perceived threat from migrants is only positively correlated with cluster 3 (“Idealizing optimists”; r = 0.26). Thus, cluster 3 is significantly associated with perceived threat in all subcategories of participants (H2).

We repeated the analyses to test the correlations between perceived threat and the factorial dimensions. When the participants who underestimated the size of the migrant population were selected, we found that perceived threat was positively associated with fatalism (r = 0.22) and negatively associated with a positive vision of society (r = −0.22) and a sense of agency (r = −0.28). For participants who were informed about the statistics, we found that perceived threat was positively correlated with a negative vision of society (r = 0.18) and fatalism (r = 0.27), and negatively correlated with a positive vision of society (r = −0.18) and a sense of agency (r = −0.27). Finally, similar results were found for participants who overestimated the number of migrants: perceived threat was positively correlated with a negative vision of society (r = 0.27) and fatalism (r = 0.24), as well as negatively correlated with a positive vision of society (r = −0.24) and a sense of agency (r = −0.17).

2.3. Predicting the Perceived Threat

In order to individuate the most important factors in predicting the perception of migrants as a threat, we conducted a linear multiple regression analysis using SPSS, which allows for the examination of the percentage of variance in perceived threat accounted for by our predictors. We considered, as predictors, the estimated number of migrants in Italy, the perception that the number of migrants has increased in the last three years, four clusters of symbolic universes and socio-demographic variables (gender, age, educational level, and political orientation). All variables were standardized before being included in the analysis. We also considered interaction effects between the estimated number of migrants in Italy and the four clusters of symbolic universes.

The regression model accounted for 40% of the variance (F(14,1902) = 88.09, p < 0.001). The use of interdependent explanatory variables should be treated with caution, as multicollinearity is associated with unstable estimates of regression coefficients (Ibe, 1989; Yakubu, 2009), making it impossible to estimate the unique effects of these antecedents. We computed a test for multicollinearity between the value of the variance inflation factor (VIF) and the tolerance statistic. All other variables have VIFs below 10 and tolerance indices below 0.1.

We can see in Table 4 that the perception of migrants as a threat is positively predicted by the estimation of the size of their population (β = 0.08, t = 4.40, p < 0.001), by the perception that their number has increased in the last three years (β = 0.20, t = 10.23, p < 0.001), by cluster 1 (“Discouraged members”: moderate fatalism, distrust of people, conformity, passivity, pessimism) (β = 0. 05, t = 1.97, p < 0.05) and by clusters 3 (“Idealizing optimists”: trust in people and institutions, high agency and reflection of fatalism) (β = 0.17, t = 6.73, p < 0.001) and 4 (“Reactive anomics”: high distrust in institutions, fatalism and pessimism) (β = 0.21, t = 9.60, p < 0.001) of the symbolic universes. Among the socio-demographic variables, we found a significant negative effect of education (β = −0.06, t = −3.14, p < 0.002) and political orientation (β = 0.41, t = 20.79, p < 0.001). We also found effects of interaction between the estimation of the number of migrants with cluster 1 (β = −0.06, t = −2.66, p < 0.008) and with cluster 3 “Idealizing optimists” (β = −0.06, t = −2.65, p < 0.008) (H3).

In order to better understand the interactions, we performed simple slope analyses (Aiken and West 1991). We found that the relationship between the estimation of the number of migrants and the perceived threat was significant for the participants belonging to cluster 1 (“Discouraged members”) (β = 0.13, t = 5.86, p < 0.001), whereas it was not significant for the participants NOT belonging to cluster 1 (β = −0.06, t = −0.76, p = n.s.).

We obtained similar findings when analyzing the effect of interaction between the estimation of the number of migrants and cluster 3. It emerged that the relationship between the estimation of the number of migrants and the perceived threat was significant for the participants belonging to cluster 3 (“Idealizing optimists”) (β = 0.12, t = 5.33, p< 0.001), and it was not significant for those NOT belonging to cluster 3 (β = 0.02, t = 0.24, p = n.s.).

3. Discussion

This study aimed to examine the relationship between the perception of the size of the migrant population in Italy and negative attitudes toward them. In addition, it wanted to investigate whether such a relationship may be moderated by the symbolic universes.

Preliminary results confirmed the “innumeracy” about the number of migrants in Italy in a certain percentage of participants. About 13.2% of participants overestimate the numbers, thinking that there are more than 12 million migrants in Italy. In addition, the majority of the participants think that the number of migrants has increased in the period of 2018–2020. Both these two estimations are positively correlated with the perceived threat from migrants.

Among socio-demographic variables, only participants’ level of education emerged as significant: people with higher levels of education perceive migrants as less threatening.

More interestingly, the perception of migrants as a threat is positively associated with cluster 1 (“Discouraged members”), cluster 3 (“Idealizing optimists”) and cluster 4 (“Reactive anomics”). People in cluster 1 are characterized by moderate distrust in others, pessimistic attitudes about conditions of life, conformity, passivity and adherence to power, whereas those in cluster 4 are characterized by extreme distrust in institutions, extreme fatalism and pessimism, adherence to power and conformism. While the relationships between the perceived threat and clusters 1 and 4 were expected, it is surprising that a significant positive relationship also emerged with cluster 3, considering that this cluster is characterized by trust in people and institutions, by the rejection of conformism and by positive attitudes towards community, conditions of life and high agency/internal locus of control. This surprising result thus contradicts the commonsense expectation that people’s positive vision of society is not associated with the perception of migrants as a threat. Our explanation of this finding is based on the highly emotional valence of the idealizing view of society. Accordingly, the migrants could have been perceived by these people as a rupture of their idyllic picture of their community and culture.

An important result emerging from the study is the role played by symbolic universes—i.e., generalized cultural worldviews—in moderating the relationship between the perceived statistics about migrants and the perceived threat posed by them. Our study showed that the relationship between the estimation of the number of migrants and the perception of threat is moderated by cluster 1 (“Disheartened affiliates”) and by cluster 3 (“Idealizing optimists”) of symbolic universes. The relationship between the estimation of the number of migrants and the perceived threat is stronger for the participants who are classified in cluster 1 and cluster 3. As mentioned before, cluster 1 contains respondents characterized by a distrust of people, pessimism, conformity, passivity, amorality and adherence to power. Thus, a strong moderation effect of this cluster was expected. As for the moderation effect of cluster 3, we can extend the explanation made above to the effect of this symbolic universe on the perception of threat. The estimated number of migrants is associated with the perceived threat, especially if people belong to the cluster 3, which is the symbolic universe that reflects a positive/idealized/generalized connotation of the society. These individuals are probably afraid that migrants will destabilize the idealized order of society. Overall, consistently with the way they have been theorized (Salvatore et al. 2018, 2019a, 2019b, 2019c), our results confirmed that symbolic universes or our generalized worldviews and meanings have a significant function in modifying our perceptions and, consequently, our attitudes.

In conclusion, this study reveals that personal viewpoints about some aspects of the society may predict attitudes towards migrants. However, our results depend on the context, and thus it would be important to verify if the same pattern of results could be obtained in other cultural contexts.

Our study has some limitations that should be acknowledged. First, a cross-sectional study cannot establish causality. However, we are confident that further studies could replicate our findings, using an experimental design, to assess cause and effect. Second, caution should be exercised in generalizing the results. In particular, our sample consisted only of Italians, and the data were collected during the pandemic period, when mass media attention was less focused on migrants. Therefore, further studies are needed to test the hypotheses in other populations and at other times. Furthermore, most of the statements in the symbolic universes measure are formulated in a negative way. A future study should test whether this might lead respondents to think in a negative way.

We believe that the present study makes an important theoretical contribution to understanding prejudice against immigrants and has some potentially important social implications. The results show a strong effect of the estimated number of migrants on perceived threat. Thus, we suggest that it is important to find a way to counterbalance the alarmist information and images often presented by the mass media and some politicians in order to reduce perceptions of threat. We also suggest that it would be important for the mass media and educational institutions to provide more information about the number of immigrants and the composition of the immigrant population, in order to avoid misinformation and ‘innumeracy’, which can distort the ‘picture’ and lead to the perception of threat and an increase in prejudice. Finally, to the best of our knowledge, our study is the first to highlight the role of generalized worldviews on attitudes towards migrants and, more specifically, in moderating the relationship between the estimation of the number of migrants in the host country and the perception of the threat of migration. This result suggests the need for communication strategies aimed at preventing the salience of symbolic universes that—because of the negative connotation of the world they convey or, ultimately, because of the idealized view of the in-group—promote negative attitudes towards migrants and the interpretation of the increasing number of migrants as a threat. Further research should use structural equation models to test whether estimates of the number of migrants can determine the salience of symbolic universes, or vice versa, and the attitudes towards migrants.

4. Materials and Methods

4.1. Participants

This study included 3020 randomly selected participants in Italy (age M = 47.61 years; SD = 14.46; range 18–75), of whom 51.3% were women and 48.7% were men. The sampling criteria was to obtain a representative Italian population, stratified by sex, age and geographical area in Italy. The proportion of respondents per Italian regions (north-west 26%, north-east 19%, central 20%, south 11% and islands 24%) in the study sample was similar to the national population (respectively: 27%, 19%, 20%, 11%, 23%; ISTAT 2021a). Respondents were similarly distributed by gender across all Italian regions: 48 to 49% of males per region in the study sample; 49 to 50% of males per region in the national population. The majority of participants (58%) had completed high school, 23% had a university degree, 6% had a post-graduate degree, 12% had completed secondary school and 1% had only completed primary school. The study sample’s education level was slightly higher than the national population (40% completed high school and 18% have a university degree, ISTAT 2021b).

4.2. Procedure

A quantitative survey was carried out. Respondents completed either a computer-assisted web survey (CAWI; N = 2574, 85.2% of the sample, 18–65 years) or a computer-assisted structured telephone interview (CATI; N = 446, 14% of the sample, 66–75 years) conducted by the specialized agency Teseo srl. The CATI procedure was used to avoid sampling bias related to the lower computer literacy of older people (e.g., De Leeuw 2005). Respondents were randomly selected from the subscriber lists. They were asked whether they wished to participate in the survey or if they were available for a follow-up interview. All items in both procedures had a modality that took into account the respondent’s reluctance to answer (e.g., ‘I prefer not to answer’; ‘I don’t know’). However, neither of these two modalities was chosen by the respondents. The survey was conducted in the last week of April 2021.

The study was approved by the Ethics Committee of the Department of Clinical Psychology and Health Studies, Sapienza University of Rome (Protocol n. 0000116/2021).

4.3. Measures

A questionnaire was used. It included the following measures.

Estimated number of migrants in Italy. We asked participants to estimate the number of migrants in Italy by choosing one of the seven alternatives proposed (100,000, 700,000, 1.5 million, 6 million, 12 million, 24 million or 32 million).

They were also asked to estimate, on a 5-point scale, whether the number of migrants had increased or decreased in the period of 2018–2020, compared to 2015–2017 (1 = significantly decreased; 2 = moderately decreased; 3 = remained stable; 4 = moderately increased; and 5 = significantly increased).

Perceived realistic threat from migrants (4 items). Participants were asked to indicate, on a 4-point scale, their level of agreement with four statements: (1) “Migrants have an overall positive impact on the Italian economy”; (2) “They are a burden on our social wellbeing (health, school, pensions)”; (3) “They take jobs away from Italians”; and (4) “They do jobs for which it is difficult to find Italian workers”. The principal components analysis revealed a factor that explains 57.88% of the total variance. We created an aggregate index after recoding the positive items. Higher scores indicated a higher level of perceived threat.

Symbolic universes: The mapping of symbolic universes was based on the short version of the view of context questionnaire (VOC; Ciavolino et al. 2017; 29 items), which assesses how people make sense of important aspects of their lives and context. The following aspects are considered: (1) local context and institutions (e.g., the reliability of agencies and services such as public transport, the health system, public forces, the school system, public administration and businesses); (2) interpersonal relationships and belonging to the community; (3) society as a whole and life in general (e.g., trust in political leaders and perceptions of living conditions); and (4) sense of agency, people’s ability to make changes in society, locus of control and values (see Table S1). Participants were asked to rate their level of agreement on a scale from 1 = strongly disagree to 4 = strongly agree. Previous studies have confirmed that the VOC has satisfactory construct (Ciavolino et al. 2017) and criterion validity (e.g., Cordella et al. 2023; Salvatore et al. 2019a; Veltri et al. 2019).

In order to detect the symbolic universes active in the Italian population, the study adopted the procedure used by Salvatore et al. 2018. Specifically, the responses to the VOC were subjected to a combination of multidimensional correspondence analysis (MCA) and cluster analysis (CA). MCA was used to transform the categorical variables into continuous dimensions, mapping their covariation. The preliminary MCA extracted five main factors explaining 96.07% of the total inertia (according to Ben-Zecri’s “optimistic” formula of regression). Each factorial dimension is considered as a marker of a latent dimension of meaning (Landauer et al. 1998). The first factorial dimension is represented by items related to a negative vision of society (institutions and services, people, the place where one lives, the country and the future), which is seen as unfair, meaningless and unreliable, whereas the second factorial dimension is related to a positive vision of society, which is seen as trustworthy and lends itself to engagement with it. The third dimension represents fatalism as well as untrustworthiness of agencies and institutions. The fourth dimension is characterized by a sense of agency versus a sense of powerlessness and passivity. The fifth dimension concerns the sense of belonging to the community and the need to make life meaningful through active participation in the community.

A cluster analysis (CA) (hierarchical classification method) was then performed using the five main factors extracted by MCA as classification criteria. The CA identified four valid clusters and a residual group (8.3%) (intra-class inertia 0.377; to-total ratios 0.711: 0.442) (see Table S2). According to the SCPT framework, each cluster obtained by CA was interpreted as a marker of a symbolic universe associated with a particular group of participants (for details on the methodology, see Kerušauskaitė et al. 2023; Salvatore et al. 2019c). These clusters were interpreted as described in Table 5:

We can see that about half of the sample is characterized by a negative world view (“Discouraged members” and “Reactive anomics”).

Sociodemographic data. Participants were asked to answer a series of questions aimed at gathering information on the socio-demographic characteristics of the respondents: gender, age and level of education. For the level of education, respondents were grouped into three categories: primary/secondary, tertiary or university.

Political orientation. This was measured by an item asking which party the respondent would vote for if the election were held at that time. The respondents could choose between the parties that obtained the highest electoral support in the last political election (“Movimento 5 Stelle” (5-Star Movement), “Partito Democratico” (Democratic Party), “Lega” (League), “Forza Italia”, “Fratelli d’Italia” (Brothers of Italy), “Liberi e Uguali” (LEU) (Free and Equal), “+Europe”). Other alternatives included: autonomous/local parties (e.g., “Sud tiroler Volkspartei”), other center parties, other left parties, other right parties; and, finally, a “no/don’t know” answer alternative. The responses were then recoded into 10 groups, starting with left/center-left parties (“Liberi e Uguali” (LEU) (Free and Equal), “Partito Democratico” (Democratic Party), other left parties), center (“5 Star Movement” and other center parties); center-right/right parties; and autonomous/local parties. Unfortunately, about a third of the sample chose “no answer/don’t know” and were excluded from the analyses.

Author Contributions

Conceptualization, A.K., B.C., S.A., S.D.D., A.G., T.M. and S.S.; methodology, A.K., B.C., S.A., S.D.D., A.G., T.M., S.K., A.R., F.S. and S.S.; formal analysis, A.K., F.S., A.G., M.R., G.R. and S.S.; resources, S.A., S.I., A.R. and S.S.; data curation, F.S., A.G., S.K., M.R., G.R. and S.S.; writing—original draft preparation, A.K.; writing—review and editing, A.K. and S.S.; visualization, S.S.; supervision, S.S.; project administration, S.K.; funding acquisition, A.K., B.C., S.A., A.G. and S.S. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Department of Dynamic and Clinical Psychology and Health Studies, Sapienza University of Rome, Italy (protocol N. 0000116/2021).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available in https://osf.io/hqvm2/ (accessed on 4 March 2022).

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Footnotes

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Tables

Table 1

Results of ANOVA to test the relationship between the perceived threat from migrants and estimated size of migrants.

Perceived Number of Migrants	N	%	M Threat
100 thousand	106	3.5	2.25 a
700 thousand	329	10.9	2.26 a
1.5 million	1162	38.5	2.33 a
6 million	1022	33.8	2.35 a
12 million	245	8.1	2.57 b
24 million	95	3.1	2.74 c
32 million	61	2.0	2.91 d

Note: Duncan’s test to measure specific differences between pairs of means. Same letters = no significant differences; different letters = significant differences.

Table 2

Correlations between the variables (including the symbolic universes).

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)
(1) Threat	-
(2) Estimated number	0.16 *	-
(3) Perceived increase in migrant flows	0.34 **	0.12	-
(4) Cluster 1 (Discouraged members)	−0.10	0.01	−0.03	-
(5) Cluster 2 (Confident and engaged)	−0.10	0.04	0.05	−0.25 **	-
(6) Cluster 3 (Idealizing optimists)	0.20 **	0.02	0.13	−0.40 **	−0.24 **	-
(7) Cluster 4 (Reactive anomics)	0.19 **	−0.03	0.02	−0.24 **	−0.14	−0.23 **	-
(8) Gender	0.03	0.05	0.08	−0.05	0.06	0.03	−0.01	-
(9) Age	0.00	−0.05	0.04	−0.04	0.09	−0.02	0.01	0.01	-
(10) Education	−0.16 *	−0.02	−0.10	0.04	−0.02	−0.05	−0.03	−0.01	−0.14	-
(11) Political orientation	0.54 **	0.16 *	0.30 **	−0.10	−0.03	0.18 *	0.10	0.06	−0.02	−0.15 *

Note: * p < 0.05; ** p < 0.01.

Table 3

Correlations between the variables (including the factorial dimensions).

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)
(1) Threat	-
(2) Estimated number	0.16 **	-
(3) Perceived increase in numbers	0.34 **	0.12 *	-
(4) Negative vision of society	0.17 **	0.04	0.22 **	-
(5) Positive vision of society	−0.21 **	−0.01	−0.10	−0.22 **	-
(6) Fatalism	0.25 **	−0.01	0.12 *	0.53 **	−0.19 **	-
(7) Sense of agency	−0.25 **	0.04	−0.01	0.18 **	0.27 **	−0.13 *	-
(8) Sense of community	0.08	0.03	−0.04	−0.11	0.40 **	−0.03	0.25 **	-
(9) Gender	0.03	0.05	0.08	0.08	0.00	0.04	0.07	−0.01	-
(10) Age	0.00	−0.05	0.04	0.09	−0.05	0.06	0.09	0.02	0.01	-
(11) Education	−0.16 **	−0.02	−0.10	−0.08	−0.02	−0.13	0.05	0.03	−0.01	−0.14 *	-
(12) Political orientation	0.54 **	0.16 *	0.30 **	0.14	−0.13	0.12	−0.13	−0.03	0.06	−0.02	−0.15 *

Note: * p < 0.05; ** p < 0.01.

Table 4

Results of the multiple regression analysis considering the perceived threat as a criterion variable.

	β	t	p
Estimated number of migrants	0.08	4.40	0.001
Perceived increase in numbers of migrants in last 3 years	0.20	10.23	0.001
Cluster 1 (Discouraged members)	0.05	1.97	0.05
Cluster 2 (Confident engaged)	−0.01	−0.29	n.s.
Cluster 3 (Idealizing optimists)	0.17	6.73	0.001
Cluster 4 (Reactive anomics)	0.21	9.60	0.001
Gender	0.02	0.89	n.s.
Age	−0.03	−1.56	n.s.
Level of education	−0.06	−3.14	0.002
Political orientation	0.41	20.79	0.001
Estimated numbers of migrants × Cluster 1	0.06	2.66	0.008
Estimated numbers of migrants × Cluster 2	−0.03	−1.40	n.s.
Estimated numbers of migrants × Cluster 3	−0.06	−2.65	0.008
Estimated numbers of migrants × Cluster 4	0.01	0.09	n.s.

Table 5

Clusters of symbolic universes.

	Characteristics
“Discouraged members” (34.5% of the respondents)	Moderate fatalism, distrust in people and institutions, conformity, passivity and pessimism.
“Confident and engaged” (31.0% of the respondents)	Moderate rejection of conformity and fatalism and moderate trust in people and institutions.
“Idealizing optimists” (11.8% of the respondents)	Strong rejection of conformity, of fatalism and amorality and high trust in people and institutions, as well as in the capacity to change the society (high agency).
“Reactive anomics” (14.5% of the respondents)	Extreme distrust in institutions, extreme pessimism and fatalism.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genealogy7040099/s1.

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