Conference Agenda

This study provides an innovative, comprehensive investigation of Belief in a Just World (BJW) and extends research on its correlates: by using nationally representative samples from 27 European countries (N=47.086) included in the European Social Survey database (ESS9, 2018, Round 9); by validating the General Belief in a Just World - Short Version (GBJW-SV) scale; by considering for the first time a set of jointly individual correlates of BJW; by examining a set of country-level contextual moderators of BJW correlates. Our results showed that BJW was positively associated with religiosity, subjective income, and right-leaning political views. Conversely, older people, women, and those with higher levels of education expressed less support for BJW. We also found that gender and left-right ideologies were more strongly associated with BJW in countries with higher societal justice, while age and income were more strongly associated with BJW in countries with lower societal justice. These findings shed light on the interplay between justice motivation and various dimensions of individual and societal life and deepen our understanding of the contextual facets of BJW.

Unlike the existing substantial body of literature which focuses either on education-job mismatch or on active citizenship, this paper aims to explore the relationship between them and how this relationship is embedded in socio-economic environments, characterised with different income inequalities.

Theoretically, the analysis is based on the view of active citizenship as a multidimensional and domain-specific phenomenon. We define active citizenship as individuals’ engagement with and participation in the political sphere, civil society, workplaces, and community life in accordance with democratic values and for the benefit of broader society. We also rely on the capability approach in our conceptualisation of the roles of higher education and of notion of education-job mismatch. We argue that higher education fulfils a plurality of roles at both individual and societal levels, which go beyond the economic and instrumental benefits and has also intrinsic and transformative/empowering value (Boyadjieva & Ilieva-Trichkova 2016). Based on this perspective, we claim that the term ‘overeducation’ reduces the complexity of benefits from higher education to the labour market. That is why we will use instead the term ‘education-job mismatch’.

The most studied consequences of education job-mismatch are its effects on wages and its influence on job satisfaction and level of happiness. (Congredado et al. 2015; McGuinness et al. 2018; Voces & Caínzos 2020). To the best of our knowledge, there are no studies on the relationship of education-job mismatch and active citizenship.

Limiting our analysis to higher education, we ask the following research questions:

1) How are graduates’ education-job mismatches associated with active citizenship?

2) Does the relationship between graduates’ education-job mismatches and active citizenship differ in countries with different income inequalities?

To answer these questions, we use multilevel linear regression models (see Rabe-Hesketh & Skrondal 2012). The empirical basis of the paper are data from the ninth round of the European Social Survey (ESS) for 29 countries. As a dependent variable, we use an index of active citizenship, which we developed based on selected items from the ESS questionnaire. Taking into account that there is no uniform, undisputable typology or measurement framework regarding education-job mismatch (ILO 2014), we apply a normative approach for its assessment. Acknowledging that there are different forms of education-job mismatch (Støren & Arnesen 2011) we focus on vertical education-job mismatch, which refers to a lack of correspondence between one’s level of education acquired and the level required in a job. We use it as an independent variable at individual level. We include as control variables: gender, age and social origin. As independent variables at country level, we include two measures of income inequalities: Inequality adjusted income index and Gini coefficient as of 2018 and we test if there are cross-level interactions between them and graduates’ vertical education-job mismatch.

Our findings show that graduates’ mismatch is associated with lower levels of active citizenship. They also reveal that although there is a negative relationship between graduates’ mismatch and their active citizenship, it is mitigated when graduates are living in countries which are characterised with less income inequalities.

Since the initial diffusion of the digital technologies during the end of the 1990s, it quickly became evident that the adoption of these technologies was occurring unevenly, both between and within countries, and the term “digital divide” was early coined.

As digital technologies become more widespread, the focus shifted beyond mere access to an examination of how these technologies were being used, such as whether individuals possessed adequate skills to navigate the online landscape (van Deursen & van Dijk, 2014). In fact, digital skills today are practically indispensable and provide people who possess them with benefits in productivity, employment, and communication, being considered a key asset (Scheerder et al., 2017).

The great importance of these digital skills implies that inequalities presented in their distribution can have negative consequences, exacerbating other types of social inequalities (Witte & Mannon, 2007). This conceptual framework therefore highlights the importance of analysing the level of inequality in these digital skills and improving our understanding of the main drivers of the inequalities observed.

In this context, the aim of this paper is to measure inequality in digital skills and to better understand how these inequalities in digital skills are shaped, as there is little empirical evidence on the subject. Given that the acquisition and training in digital skills is a complex process, in order to unravel the roots of inequalities in these skills, we decided to use an Inequality of Opportunity approach (IOp henceforth).

This concept relies on distinguishing two main origins of the inequalities observed in a given outcome or variable. In this way, it is understood that individual achievements (the proficiency on digital skills in this case) are, on the one hand the result of circumstances beyond individual control (such as place of birth, ethnicity, gender, social and family background), and, on the other, are consequence of individual efforts and therefore their responsibility. IOp in digital skills would be the part that is due to circumstances outside individual control.

Through the IOp approach, we will be able to quantify and better understand the importance of certain social characteristics in shaping digital inequalities and answer two main research questions. (1) What are the main determinants of individuals' digital skills, (2) How do individual circumstances contribute to the observed inequalities in digital skills?

To carry out this analysis, the European Social Survey (ESS) is used and, in particular, Round 10, which provides information of two essential pieces of information 1) Individuals’ circumstances, such as parental education or occupation and 2) The level of digital skills of individuals on three different dimensions, only available for this latter round of the ESS.

Given the ordinal nature of the three digital skills variables, the analysis is carried out using a Dissimilarity Index. Additionally, we compute the contribution of each circumstantial variable to IOp using a Shapley value procedure. Our analysis allows us to obtain measures of IOp in digital skills for 22 European countries and preliminary results show that parental education is a key determinant of these inequalities.

It is widely assumed that Western societies have undergone a process of social polarisation which is reflected in a range of socio-economic, socio-cultural, spatial and political phenomena (Savage 2015; Stiglitz 2012; Reckwitz 2021 [2019]). In this paper, we focus on the link between socio-economic and spatial polarisation. The basic argument is that in post-industrial knowledge-based societies, high-income jobs are predominantly created in the metropolises and regional tech hubs, while at the same time labor market opportunities have worsened in peripheral and de-industrialized regions (Antonelli and Tubiana 2020; Crouch 2019). As a consequence, the highly skilled members of the new middle classes are increasingly attracted to economic and cultural centers, while less privileged social classes remain ‘left behind’ in small towns and peripheral regions (Florida 2004; Reckwitz 2021).

Against this background, our paper addresses changes in socio-spatial disparities in a European perspective. Using data from rounds 1 to 10 of the European Social Survey (ESS), we investigate whether social class differentials in places of residence have increased over a time period of 20 years in six European countries. Using the class scheme proposed by Daniel Oesch (2006), we particularly look at rising residential disparities between the upper, middle and lower social classes. Regarding spatial information, we rely on the self-assessed settlement type as well as information on NUTS-districts. On this ground, we distinguish four categories: capital cities, large cities/outskirts of large cities, small towns, and rural areas. Comparing Belgium, Germany, France, Spain, Sweden, and the United Kingdom we ask if in all countries under consideration, the members of the upper classes tend to live more likely in the large cities, while the lower classes increasingly reside in peripheral towns and rural areas.

Preliminary results do not support the view that socio-spatial disparities have systematically risen in European countries since the turn of the millennium. On the one hand, the data show no evidence that the upper classes have become more likely to live in the capital or large cities over the time period under consideration. Nor do we observe a decline in the likelihood of members of these classes to live in small towns or rural areas. On the other hand, the results also show no clear trend regarding the likelihood for the lower classes to live in small towns and rural areas.. Thus, our results raise doubts on the popular narrative that socio-spatial disparities are growing in European countries.

The reference income (RI) is the average income in one’s reference group. It influences subjective well-being (SWB) through two different channels - comparison and information effects. Usually, the relationship between RI and SWB is negative. The reason is that the comparison effects (using others’ income to determine one’s rank in society) are stronger than the information effects (using others’ income to make future expectations and hopes). The previous research demonstrated, however, that, in post-communist countries, the relationship was positive at the beginning of the 21st century, i.e., higher RI implied greater happiness. This phenomenon was named the “tunnel effect” that appears in uncertain or highly mobile environments where information effects predominate the comparison effects.

In this study, we examine the trends in the relationship between RI and SWB in the context of comparison and information effects in 36 European countries over the last two decades (2002-2020). While adopting a broad European perspective, we aim at identifying regional differences with respect to the relationship between RI and SWB. In particular, we examine circumstances in which the “tunnel effect” occurs and focus on its specific dynamics in the post-transition context. We also examine whether the pandemic has influenced trends relating to the “tunnel effect” and how this differs across Europe. An important contribution of our research is the discussion of the differences in the results depending on the dimension of SWB implemented (i.e., self-reported happiness and life satisfaction). We also introduce a novel definition of RI that takes into account the type of place of residence of an individual (big cities, small towns, villages). By including this characteristic, we are able to account for the social differences between urban and rural areas.

Using all 10 waves of the European Social Survey, we model life satisfaction and happiness and their relationships with RI. Based on income deciles reported in ESS, we calculate the reference income as the average income decile among people who share similar socio-economic characteristics (e.g., age, sex, education, and place of residence). We run separate analyses using ordered probit models for each wave to measure the differences in RI effects in the period 2002-2020 in European regions. As a robustness check, we run five parallel analyses using different measures of an RI including our novel definition.

We find that the “tunnel effect” has had a diminishing trend in post-communist countries – both CEE countries and former Yugoslavia. We also observe that the relationship between RI and SWB reacts to the major economic events in Europe and its regions, such as CEE countries’ accession to the European Union in 2004 or the Global Financial Crisis in 2008. However, the effect of the pandemic on the RI-SWB relationship is ambiguous. For some definitions of a reference income, we observe a “tunnel effect” in happiness models for 2020. However, in the case of the models on life satisfaction, the effect is insignificant. Our findings emphasize the complicated role of uncertainty and contextual factors in shaping people’s SWB.