Diversity beyond migration background – new categories for equality data

• Applicant: Dr. Anne-Kathrin Will
• Subject Area: Empirical Social Research
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 466608607

To describe multidimensional and complex social inequality and disadvantage, it is essential to have categories at hand relevant to discrimination. That way, population groups with high and low risk of discrimination can be distinguished. To establish how much for example the educational system is affected by structural or institutional racist discrimination today, usually “persons with” and “persons without a migration background” are distinguished. In Germany a person is labelled to have a migration background if she or at least one of her parents has German citizenship not since birthor is immigrated. By now, every fourth person in Germany has a migration background. On the other hand, the groups most affected by racism, as Germany reports to the United Nations, are not persons with a migration background, but Jewish people, Black people, people of colour, persons of Muslim belief or perceived as Muslims, as well as Sinti and Rroma. Groups with high risk of discrimination partly have and don’t have a migration background. For inequality and discrimination research and with regard to equality and participation not categories of ethnic origin or identity (as collected officially in mostcountries of the world) are relevant, but the concept that needs to be measured is socially ascribed ethnicity: Discrimination always works through the gaze of Others. In the network, survey researchers and survey methodologists, migration, integration, racism and discrimination researchers, educational researchers, linguists and legal scholars as well as scholars of science and technology studies will cooperate to develop suitable survey questions. Questions and answer categories will be developed to capture ethnic difference that is relevant for discrimination in Germany via questions on selfreportedethnicity that will be interdisciplinary exchangeable in general social surveys as well as public health, educational or labour force survey research. Existing ethnic self-identifications in the population will be considered and data collection will be field-tested. The network will observe established standards for equality data collection. To find suitable indicators for discrimination beyond the migration background, the network will 1) conjoin the state of research for equality data collection in Germany 2) develop survey items 3) connect German and international debate more strongly, and 4) support academic debate on (statistical) representation and protection from discrimination for minoritized groups in the 21st century.

• DFG Programme: Scientific Networks
• Co-Investigator: Dr. Linda Supik