The present study proposes a meaningful multidimensional index of early job insecurity for European countries based on raw micro-data drawn from the European Union’s Labor Force Survey (EU-LFS), and captures its evolution over time, before and during the years of the post–2008 economic crisis. More specifically, a number of different indicators capturing various domains of early job insecurity are estimated, utilizing the data behind the EU-LFS survey for all European Union (EU) member states. These indicators are then composed into a single indicator of early job insecurity, which is used to apprehend and compare the degree of early job insecurity in EU member states, during these years. The proposed indicator captures the whole range of early job insecurity aspects, such as labor market conditions, job quality, school-to-work transitions, and job security, in an overall measurement providing a way of estimating and comparing early job insecurity among different countries. The results uncover the considerable differences between EU countries when early job insecurity is considered. Moreover, countries are ranked according to the degrees of early job insecurity for the years 2008-2014.

This study investigates the attitudes of young individuals aged 15–35 years toward digital communication, with a focus on digital skills, citizenship, and civic engagement. Utilising data from the European Social Survey (ESS) round 10 (2020), the research explores variations across over 30 European countries, examining responses to the ESS’s rotating module on “Digital social contacts in work and family life.” Key questions, such as exposure to misinformation and online political engagement, are analysed to uncover factors influencing young Europeans’ perceptions of information and communication technology (ICT). The study explores digital scepticism, optimism, and digital skills, linking them to civic participation and socio-demographic factors. Statistical analysis, including chi-square tests and multiple regression analysis, identifies predictors and disparities among countries. Correspondence analysis dissects interrelationships among categories, constructing plots to showcase proximity between factors. Evaluating Internet accessibility, civic engagement, and connectivity issues, the study also compares data with the prior ESS round (round 9, 2018) to assess changes over the past 4 years. Through empirical investigation, this study sheds light on young Europeans’ perspectives on ICT, offering valuable insights into the complex interplay between digital communication, civic engagement, and beneficial Internet time.

In this article, by applying k-means clustering, cut-off points are obtained for the recoding of raw scale scores into a fixed number of groupings that preserve the original scoring. The method is demonstrated on a Likert scale measuring xenophobia that was used in a large-scale sample survey conducted in Northern Greece by the National Centre for Social Research. Applying split-half samples and fuzzy c-means clustering, the stability of the proposed solution is validated empirically. Testing its performance against three single indicators of xenophobia shows that it differentiates well between non-xenophobic and xenophobic respondents. The proposed method may be easily applied to facilitate interpretation by providing a more concise and meaningful “profile” of Likert scale (or subscale) raw scores especially the negative and positive ends of the scale for evaluation and social policy purposes.