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In this study, we investigate whether, and why, individuals express different levels of acceptance of surveillance depending on their educational level, and whether this relationship varies with the level of digitalization and globalization expansion of their country. Additionally, we ask whether the type of surveillance (online surveillance vs cameras in public areas) conditions these differences. We build on two theoretical frameworks, one concerned with the resurgence of authoritarian values via the cultural backlash, and the other one explaining how different people analyse manufactured risks differently due to processes of reflexive modernization. In order to test the hypotheses, we employ data from the latest wave of the European Values Study (EVS) and implement multilevel multivariate regression models. Findings indicate that the lower educated individuals are more prone to accept online surveillance, due to their stronger authoritarianism and weaker reflexive mindset; however, there is no educational gradient in acceptance of video surveillance in public areas. Additionally, the countries' levels of digitalization and globalization expansion do not condition the educational gradient in acceptance of surveillance.

Educational gaps are increasingly salient as skills and knowledge gain prominence in digital societies. E-privacy management, namely, the ability to control the flow of information about the self, is an important asset nowadays, since a skillful use of digital technologies enables full participation in social life and limits the exposure to unwarranted algorithmic processes. We investigate whether and why education affects e-privacy management, and whether the educational gaps vary following a country's degree of digitalization. We empirically test two sets of mechanisms, one derived from the digital divide and diffusion of innovations theories and the other from the reflexive modernization theory. The study employs Eurobarometer 87.1 data ( N = 21,177), collected in 2017 among representative samples from 28 European countries, and uses multilevel linear regression model. Findings suggest that the years spent in education positively affect e-privacy management, and that this effect is largely mediated by digital skills and Internet use, and to a lesser extent by a reflexive mind-set. The educational gap in e-privacy management narrows in more digitalized countries.

This paper examines the feasibility of ex-post harmonisation strategies using European Values Study (EVS) Wave 5 (2017-2020) and European Social Survey (ESS) Round 9 (2018-2019) data across 17 countries. The study shows an empirical assessment of the comparability of four items measuring religious behaviours (belonging to a religious denomination at present/in the past, religious services attendance, and praying), captured in both surveys. The novelty of this paper lies in the analytical comparison of religiosity indicators that are rarely assessed from a comparative perspective. The harmonisation strategy was based upon several analytical techniques that seek to determine similarities and differences between the selected items in terms of (a) their validity, by examining their correlations with a set of sociodemographic and substantive correlates, (b) their distributions, supplemented by visual comparisons and relevant statistical tests, and (c) item non-substantive shares. The findings pointed to the most consistency among the partial correlations, where individual religiosity produced the most differences between the surveys. Distributions produced the most discrepancies that also corresponded to less similarity across variable categories as gauged by Duncan's index. This paper is descriptive and exploratory in its aim. It can be taken as a jumping-off point for future research where the time series of these two surveys, and potentially others, can be examined across aggregate levels (e.g. birth cohorts, countries).

AbstractThe social sciences have produced an impressive body of research on determinants of fertility outcomes, or whether and when people have children. However, the strength of these determinants and underlying theories are rarely evaluated on their predictive ability on new data. This prevents us from systematically comparing studies, hindering the evaluation and accumulation of knowledge. In this paper, we present two datasets which can be used to study the predictability of fertility outcomes in the Netherlands. One dataset is based on the LISS panel, a longitudinal survey which includes thousands of variables on a wide range of topics, including individual preferences and values. The other is based on the Dutch register data which lacks attitudinal data but includes detailed information about the life courses of millions of Dutch residents. We provide information about the datasets and the samples, and describe the fertility outcome of interest. We also introduce the fertility prediction data challenge PreFer which is based on these datasets and will start in Spring 2024. We outline the ways in which measuring the predictability of fertility outcomes using these datasets and combining their strengths in the data challenge can advance our understanding of fertility behaviour and computational social science. We further provide details for participants on how to take part in the data challenge.

The European Values Study (EVS) was first conducted in 1981 and then repeated in 1990, 1999, 2008, and 2017, with the aim of providing researchers with data to investigate whether European individual and social values are changing and to what degree. The EVS is traditionally carried out as a probability-based face-to-face survey that takes around 1 hour to complete. In recent years, large-scale population surveys such as the EVS have been challenged by decreasing response rates and increasing survey costs. In the light of these challenges, six countries that participated in the last wave of the EVS tested the application of self-administered mixed-modes (Denmark, Finland, Germany, Iceland, the Netherlands, and Switzerland). With the present data brief, we will introduce researchers to the latest wave of the EVS, the implemented mode experiments, and the EVS data releases. In our view, it is pivotal for data use in substantive research to make the reasoning behind design changes and country-specific implementations transparent as well as to highlight new research opportunities.

The European Values Study (EVS) was first conducted in 1981 and then repeated in 1990, 1999, 2008, and 2017, with the aim of providing researchers with data to investigate whether European individual and social values are changing and to what degree. The EVS is traditionally carried out as a probability-based face-to-face survey that takes around 1 hour to complete. In recent years, large-scale population surveys such as the EVS have been challenged by decreasing response rates and increasing survey costs. In the light of these challenges, six countries that participated in the last wave of the EVS tested the application of self-administered mixed-modes (Denmark, Finland, Germany, Iceland, the Netherlands, and Switzerland). With the present data brief, we will introduce researchers to the latest wave of the EVS, the implemented mode experiments, and the EVS data releases. In our view, it is pivotal for data use in substantive research to make the reasoning behind design changes and country-specific implementations transparent as well as to highlight new research opportunities.

The European Values Study (EVS) was first conducted in 1981 and then repeated in 1990, 1999, 2008, and 2017, with the aim of providing researchers with data to investigate whether European individual and social values are changing and to what degree. The EVS is traditionally carried out as a probability-based face-to-face survey that takes around 1 hour to complete. In recent years, large-scale population surveys such as the EVS have been challenged by decreasing response rates and increasing survey costs. In the light of these challenges, six countries that participated in the last wave of the EVS tested the application of self-administered mixed-modes (Denmark, Finland, Germany, Iceland, the Netherlands, and Switzerland). With the present data brief, we will introduce researchers to the latest wave of the EVS, the implemented mode experiments, and the EVS data releases. In our view, it is pivotal for data use in substantive research to make the reasoning behind design changes and country-specific implementations transparent as well as to highlight new research opportunities.