Joint work with Dr Jan Skopek (Lead: Marco Seegers)
Lifelong learning is a core policy ideal in modern societies, yet participation remains highly unequal. Those with higher qualifications and prior learning experience are far more likely to take part—while others, often with the greatest need, are left behind. This project explores the potential role of metacognitive monitoring—the ability to assess one’s own knowledge and recognise learning needs—in helping to explain this divide.
Drawing on the Dunning–Kruger effect, we examine whether individuals with low cognitive competencies and inflated self-assessments are especially unlikely to engage in adult education. We conceptualise this as a micro-cognitive mechanism of the theory of cumulative (dis)advantage, helping to explain how small initial differences compound into persistent inequalities in learning over the life course.
Our study focuses on Germany and considers both formal, work-related training and the growing role of informal and digital learning environments. By linking cognitive psychology with sociological theory, we aim to deepen the understanding of how metacognitive competencies influence lifelong learning trajectories. The findings have practical implications for policy, counselling, and curriculum design in adult education.
Joint work with Dr Eileen Peters & Mortimer Schlieker (Lead: Mortimer Schlieker)
This paper examines how an employee’s relative earnings position – their salary compared to colleagues in the same workplace and to their partner within the household – influences access to non-formal, job-related training. Building on Relational Inequality Theory, we interpret these earnings gaps as indicators of social positioning in two central spheres: the workplace, where employers act as gatekeepers to training opportunities, and the family, where household dynamics and divisions of labour can either enable or restrict participation.
Wwe use linked employer–employee data from Germany and apply longitudinal fixed-effects models to analyse how changes in these relative earnings positions affect the likelihood of training activities. Our approach captures both workplace and family effects simultaneously and allows us to examine how they interact over the life course.
The paper’s key innovation lies in the simultaneous analysis of workplace and family spheres and the interactions between them. This relational perspective enables us to move beyond studying training barriers in isolation, revealing how dynamics in one sphere can reinforce or offset those in the other. The findings will contribute to a deeper theoretical understanding of relational inequality and generate evidence that can inform targeted strategies to improve training access for underrepresented groups.
Joint work with Johanna Binnewitt (Lead: Johanna Binnewitt)
Occupations are central to social stratification, not only because they structure access to resources and life chances, but also because they are associated with symbolic capital such as recognition, prestige, and cultural esteem. Occupational stereotypes can therefore shape how workers are perceived and evaluated, and contribute to the reproduction of social inequalities.
The chapter examines how evaluative occupational stereotypes can be operationalised in text data and how text-based approaches complement established survey-based measures. Conceptually, we link the Stereotype Content Model with sociological theories of symbolic capital and occupational inequality. Empirically, we use German parliamentary debates from the GermaParl corpus, identify occupational titles with a fine-tuned BERT model, and annotate text passages using semantic differentials based on warmth and competence. These annotations are then used to train a classifier and generate occupational-level stereotype scores.
By comparing text-based stereotype scores with survey-based measures, the paper evaluates the validity and added value of computational approaches for studying latent evaluative representations of occupational groups. It highlights both the potential of naturalistic text data for analysing symbolic inequality and the methodological challenges involved, including contextual ambiguity, subjectivity, and algorithmic bias.
Single-authored
Research on gender differences in participation in non-formal job-related further training in Germany has produced fragmented and partly contradictory findings. While earlier studies frequently reported higher participation rates among men, more recent evidence increasingly suggests that women may participate at similar or even higher rates. At the same time, existing findings vary substantially depending on how further training is conceptually defined, which populations are analysed, and how participation is measured and operationalised. As a result, it remains unclear whether observed differences reflect substantive changes in participation behaviour or methodological inconsistencies across studies.
This work-in-progress paper addresses this gap through a systematic literature review. The review synthesises quantitative evidence published between 1990 and 2026 on gender differences in participation in non-formal job-related further training in Germany. Particular attention is paid to differences in conceptualisations of training, target populations, data sources, measurement strategies, and analytical approaches.
Beyond synthesising empirical evidence, the paper develops a historical-sociological interpretation of changing participation patterns. It investigates when and under which institutional conditions patterns of gender inequality in further training changed, which forms of training were affected, and how theoretical perspectives shape interpretations of the gender training gap. By combining systematic evidence synthesis with conceptual reflection and historical contextualisation, the paper contributes to current debates on adult learning, labour market inequalities, and the changing role of further training in contemporary Germany.