Maria Symeonaki

Background: Many countries around the world are expanding the enrollment of children in early childhood education (ECE) outside the home to improve school readiness and, ultimately, academic achievement. While socioeconomically disadvantaged children are typically underrepresented in ECE, they are often thought to benefit the most from participation. This study empirically tests whether increasing ECE participation rates are associated with reductions in socioeconomic inequalities in ECE participation and, consequently, with decreases in socioeconomic inequalities in reading achievement at the end of primary school. Methods: The study draws on data from 64 education systems participating in PIRLS cycles between 2001 and 2021, comprising 225 country-by-year observations. Using country-fixed effects, we estimate a mediation model to test whether socioeconomic inequalities in ECE participation mediate the relationship between overall ECE participation rates and socioeconomic inequalities in reading achievement. This fixed effects approach controls for time-invariant differences between education systems. We include a set of control variables to account for economic, demographic, and policy-related changes that might confound within-country trends and discuss untestable assumptions that have to be met to interpret the mediation relationship causally. Additionally, we examine international trends in all three variables of interest. Results: As hypothesized, we find that countries with increasing ECE participation rates and decreasing socioeconomic inequalities in ECE participation also show declining socioeconomic inequalities in reading achievement. Internationally, ECE participation rates have risen over time, while both socioeconomic inequalities in participation and socioeconomic inequalities in reading achievement did not show clear trends over time. Conclusions: According to our interpretation, increasing ECE participation rates seem to help reduce socioeconomic inequalities in reading achievement—provided that the increases also reduce disparities in access to ECE. This finding, together with previous research, offers encouraging evidence for countries investing in or planning to expand ECE. Moreover, this study highlights the importance of ensuring that ECE expansion policies specifically address socioeconomic inequalities in participation to mitigate later educational inequalities.

The interplay between technology and societal norms often reveals a troubling reality: machine learning systems not only reflect existing gender stereotypes but can also amplify and entrench them, making these biases harder to detect and address. This paper adopts an interdisciplinary approach, combining quantitative and qualitative methods with recent technological advancements, such as machine learning techniques for textual analysis and computational linguistics, to offer a new framework for understanding occupational gender bias in machine learning. The study is motivated by persistent gender inequalities in the labour market and rising concerns about gendered algorithmic bias, as outlined in the European Commission’s Gender Equality Strategy 2020–2025. Focusing on language translation technologies, the research explores how machine learning may perpetuate or amplify gender stereotypes, aiming to foster more inclusive digital systems aligned with EU strategic goals. More specifically, it investigates occupational gender segregation and its manifestations in various forms of gender bias in machine learning across English, French, and Greek. The study introduces a classification of gender biases in machine learning, providing insights into professional areas needing intervention to address gender imbalances and identifying enduring stereotypical representations in textual data. To support this, statistical analysis is conducted to explore gender variations in occupations over the past thirteen years, using official data and international classifications such as the International Standard Classification of Occupations (ISCO-08). Moreover, gendered occupational distributions are extracted from 200,920 text instances in the three languages, revealing significant discrepancies between official labour statistics and the training data.

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.

Orfeas Menis Mastromichalakis, Giorgos Filandrianos, Maria Symeonaki, Giorgos Stamou. Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing. 2025.

This study offers an insightful glimpse into the experiences of working men and women in Greece during the unprecedented first lockdown from March to May 2020. As the pandemic enforced restrictions that led to teleworking, parents found themselves overwhelmed with the simultaneous demands of work, home-schooling, and childcare, all without external support. This situation severely tested work-life balance and placed additional strain on relationships between partners due to the increased burden of unpaid work. This paper shares findings from the Greek segment of the "Covid19-Health emergency and work-life balance" research, conducted across six countries during the pandemic's initial surge using a standardized online questionnaire and quota sampling. The study included 840 Greek participants aged 18 to 70, analysing the pandemic's effects on work relations, workspace and time organization, job performance, the balance between paid and unpaid work, domestic roles and tasks division, and familial and partner relationships. Employing a work-life balance Likert scale (WLB) with 8 items based on Hayman (2005) and Fisher-McAuley et al. (2003), the study utilized multinomial logistic regression to delve into factors affecting work-life balance during COVID-19. This statistical method predicts outcomes based on a mix of continuous and categorical predictors, aiming to identify individuals with high or low WLB scores using sociodemographic variables such as gender, education level, age group, and marital status.

This paper investigates the transmission of educational attainment from parents to offspring as a mediator of intergenerational class mobility in Europe. The study covers the last two decades with data drawn from a cross-national large-scale sample survey, namely the European Social Survey (ESS), for the years 2002–2018. Interest has focused on the question of the persistence of inequality of educational opportunities by examining the attainment of nominal levels of education and the association between the educational attainment of the parent with the highest level of education and their descendants. The study also covers new trends in social mobility that consider education as a “positional good”, and a novel method of incorporating educational expansion into the transition probabilities is proposed, providing answers to whether the rising accessibility of educational qualifications attenuates the association between social origin and educational attainment. Therefore, the concept of positionality is taken into account in the estimation of intergenerational transition probabilities, and to complement the analysis, mobility measures are provided for both methods, nominal and positional. The proposed positional method is validated through a correlation analysis between the upward mobility scores (nominal and positional) with the Education Expansion Index (EEI) for the respective years. The upward mobility scores estimated via the positional method are more highly correlated with the EEI for all years, indicating a better alignment with the broader trends in educational participation and achievement.