Funded research & research programmes

The project combines inequality research, political and economic education, and knowledge transfer. Its core output is a modular digital learning intervention on economic inequality, developed and tested together with a pilot school. A class of 11th-grade students was involved not only as learners, but as co-researchers and experts on their own social environments.

University partners in Bamberg, Bayreuth and Amsterdam work together with the Gymnasium bei St. Anna in Augsburg. The project treats data literacy as more than reading charts: students make real choices about questions, data, measurement and interpretation, and reflect on the limits of evidence.

Research strands

• Participatory inequality research and Citizen Education: co-research with adolescents, including research design, field work and reflection on epistemic roles.
• Inequality perceptions in social environments: qualitative and quantitative work on how visible life-worlds, peer networks and reference groups shape estimates of economic inequality.
• Student-led projects: housing and neighbourhood inequality, inequality and sustainability, perceptions of the super-rich and climate impacts, distributive justice experiments, and AI-assisted text analysis of political debates.
• Intersectionality and privilege: participatory research on economic gender inequality and intersectional disadvantage, feeding into educational material for the OPENvhb course.

MECAPHIST asks whether the striking stability of corporate profit rates is a fundamental property of capitalist economies rather than a recent or country-specific regularity. The project takes a long-run comparative perspective on France and Germany.

A central task is the construction of a new historical firm-level dataset covering 1907–2001 from archival and printed company records. The sources include profits, assets, debt, dividends and stock-market information and require substantial digitisation, OCR and harmonisation work.

Research embedded in the project

• Long-run distributions and persistence of corporate profitability in France and Germany.
• Digitisation and reconstruction of historical balance-sheet data, including difficult OCR and entity harmonisation.
• Corporate survival and the dynamics of long-lived firms.
• Dividend strategies, governance and the relationship between financial decisions and profitability.

SPINE was a two-week interdisciplinary research incubator at the University of Bamberg, organised by Daniel Mayerhoffer, Daria Tisch and Jan Schulz-Gebhard. Early-career researchers worked in seven project groups on the perception and reproduction of wealth inequality.

The school combined project-based research with expert talks and keynotes. The groups developed work on fairness perceptions, wealth-tax attitudes, media framing, networks of the super-rich, historical public discourse and agent-based models of opinion dynamics.

What came out of it?

• Seven collaborative research projects and draft articles.
• A planned special issue of Historical Social Research (HSR) on perceptions of wealth inequality.
• Graphical abstracts and public-facing summaries for broader dissemination.
• A durable interdisciplinary network spanning economics, sociology, political science, communication studies and history.

This project with Daniel Mayerhoffer studies a simple idea with broad consequences: social contacts are not random. When people mostly observe others who are economically similar to themselves, local social samples can systematically distort perceived rank, perceived inequality, wage gaps and preferences for redistribution.

The original project became a wider research programme on social sampling, privilege and network-based perception.

Selected publications & outputs

The project constructs new microdata from First World War casualty lists to study whether military risk was socially stratified in Imperial Germany. The broader research agenda asks how class, inequality and the social organisation of military service shaped who bore the human costs of the war.

The workflow combines large-scale historical record extraction with surname information and external socioeconomic sources. The source material contains millions of casualty-list entries, making data construction, historical denominator choices and validation central parts of the research design.

Current research questions

• Were casualties distributed differently across socioeconomic groups?
• How did military risk vary across places and social structures?
• Can surnames and historical occupational information recover socioeconomic gradients at very large scale?
• How should casualty counts be related to the relevant population at risk?