Ethnic minorities in the Danish higher education system. A study on the intersection between ethnic and social inequalities with specific attention to written language skills.

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Felix Weiss


Aarhus University


DKK 3,456,114




Semper Ardens: Accelerate


The project will explore ethnic inequalities in the Danish postsecondary education system, both with regard to entry into and success within higher education. It will also study the relation between ethnicity and social origins in these inequalities and assess in how far ethnic inequalities are actually social inequalities. We attempt to break new methodological paths for inequality research by combining register data with data on the quality of written language based on natural language processing methods - i.e. automated text analysis. This will enable us to study writing skills, a core meta-competence needed in higher education, as a mechanism that potentially amplifies ethnic and social inequality and will create a unique and innovative database.


The project addresses questions that are highly relevant for sociology and related disciplines that engage in inequality studies in that it contributes to the understanding of the role of higher education systems for promoting intergenerational social mobility and for integrating first- and second-generation migrants into modern societies. It aims at improving the understanding of educational decision-making and educational performance of groups that often opt against higher education or face particular challenges during their studies. The project will analyze academic writing skills as potential reason for inequality in educational performance. It will work towards methodological improvements in the use of automated text analysis for the analysis of educational inequalities.


The project will analyze both Danish administrative register data, e.g. from the central admission system in order to investigate inequalities in educational choices by migrant background and social origin. In addition, we will apply automated, quantitative text analysis in order to explore if minority students face particular challenges with academic writing. Combining quantitative research methods from sociology and linguistic studies, we will relate text analyses to students' pathways through higher education. In order to ensure that automated text analyses-methods will be a valid and useful tool to analyze if first generation and migrant students face particular challenges on this dimension, we will validate computer based, automated analysis by expert coding.

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