ESRA logo

ESRA 2023 Glance Program

All time references are in CEST

Attitudes towards migrant and intergroups dynamics: insights from survey research

Session Organiser Dr Veronica Riniolo (Università Cattolica del Sacro Cuore, Milan)
TimeThursday 20 July, 09:00 - 10:30
Room U6-11

This session explores attitudes toward migration and intergroup dynamics in different EU countries. It
offers both a cross-national comparison of attitudes toward ethnic groups in several EU countries
and it proposes a focus on two national contexts, Germany and Belgium.
Different factors - at micro, meso, and macro level - are considered in the analysis of intergroup
dynamics, such as low SES, feelings of insecurity and marginalization, the role of urban
environment, and the role of the same composition of refugee flow, considering the refugee sex
ratio, on the attitudes towards migration. In addition to this, the panel offers a reflection on the
consequences of the Covid-19 pandemic on the attitudes toward ethnic minorities.
These multiple perspectives and different empirical studies stimulate a theoretical and
methodological reflection on how to study attitudes toward ethnic minorities. It also offers fresh
insights on the most recent evolution on intergroup dynamics in Europe in the light of the most
recent crises.

Keywords: intergroup dynamics, attitudes toward ethnic groups


Understanding the impact of the pandemic crisis on attitudes toward immigration and multiple discrimination. Evidence from the European Social Survey

Dr Veronica Riniolo (Università Cattolica del Sacro Cuore, Milan) - Presenting Author
Dr Vera Lomazzi (University of Bergamo)

The impact of the Covid-19 pandemic – and of its consequent economic crisis – on the intergroup relationships has not been deeply investigated so far, often because of lack of data. Recently released data from the 10th round of the European Social Survey, combined with round 9th, allows for investigating this issue by using data collected before and after the pandemic outbreak. Building on the Group Conflict Theory, the Group Relative Deprivation, and Schwartz’s and Inglehart’s Value Theories, we aim addressing the following research questions: 1) How do attitudes toward immigration and the perception of ethnic groups as a threat change after the Covid-19 pandemic in EU countries? 2) to what extent contextual factors, such as the Political Opportunity Structure (POS) and economic conditions, contribute explaining these changes while controlling for individual factors? Our preliminary analysis shows that, after the pandemic crisis and in opposition to our initial hypotheses, negative attitudes towards ethnic groups decreased in several EU countries, but not in all countries and not with the same intensity. The role of contextual factors, such as economic conditions, is crucial to explain this heterogeneity. The consequences of the crisis may have impacted on the priorities of EU citizens and immigration was no longer at the centre of the public debate. Therefore, alongside descriptive statistics, we apply multilevel modelling to contribute explaining these changes while controlling for individual factors.

Using OpenStreetMap, Census and Survey Data to Predict Interethnic Group Relations in Belgium: A Machine Learning Approach

Ms Daria Dementeva (KU Leuven) - Presenting Author
Professor Cecil Meeusen (KU Leuven)
Professor Bart Meuleman (KU Leuven)

Over the past decades, spurred anti-immigration rhetoric, the success of radical parties, the overall political polarization coupled with a transformation of a majority of Belgian neighborhoods into areas with diverse ethnolinguistic profiles, cultural mix, and in-migration, accelerated exposure to negative attitude formation towards people of different ethnic and religious backgrounds.

To date, the quantitative scholarship on interethnic group relations only sporadically focused on the residential context. Although empirical research on the link between attitudes towards ethnic minority groups and local neighborhood context produced mixed results, it does remain scarce. While objective and subjective measures of neighborhood (dis)advantage and ethnic composition were employed to contextualize intergroup relations, another natural aspect of neighborhood context, such as the spatial organization of interethnic contact opportunities in residential areas tends to be neglected.

The components of the urban built environment, such as local leisure spaces, shopping facilities, catering venues, and points of worship are building blocks for enhancing social life in neighborhoods as they act as shared exact spaces for (in)direct contact, intercultural mixing, increasing social capital, and civil inattention between residents of different ethnic and religious backgrounds. Thus, we seek to answer the following questions: What is the relationship between attitudes towards people of different ethnic origins and the urban built environment? To what extent may urban destinations of neighborhoods explain these attitudes, and which are the most salient? We draw on a combination of random probability survey data, census data, and geodata obtained from the OpenStreetMap, which is a global database of spatial attributes with a granular spatiotemporal resolution.

We present and discuss the predictive spaces of the built environment for interethnic group relations by applying machine learning algorithms for prediction and spatial feature engineering to describe the residential built environment in the Belgian context.

Measurement invariance and quality of attitudes towards immigration in the European Social Survey

Ms Amelie Nickel (University Bielefeld ) - Presenting Author
Dr Wiebke Weber (LMU Munich )

While the European Social Survey (ESS) is one of the most widely used surveys for cross-national research on attitudes towards migration, only few studies have evaluated whether the used measurements are comparable across countries and over time. Those that did used different methods and analytic strategies which complicate the comparison of their results. To ensure comparability of results, we employ Multigroup Confirmatory Factor Analysis (MGCFA) and test for measurement invariance of attitudes towards immigration with the same approach in each round of the ESS.

Our results reveal that metric invariance holds for all countries but one in all rounds, indicating that covariances and regression coefficients can be compared meaningfully. While scalar invariance only holds for different subgroups of countries within each round, partial invariance is fulfilled in all countries, meaning that at least one indicator is equal for all countries allowing for latent mean comparisons. Moreover, we estimate the measurement quality and find that the attitudes towards immigration index is similarly good across the different countries and rounds.