Discrimination: Conceptualization, Causes, Measurement and Counteraction
Course content
What is discrimination, how do we measure it, and can it be countered? Are women discriminated as political candidates? Are men also subject to discrimination when applying for jobs? Are minority members discriminated against in the housing market? Even though formal rules and informal norms against discrimination are strong, existing evidence shows that discrimination continues to affect individuals’ chances of success in life. Understanding why discrimination occurs – and how it might be countered – is crucial for building critical awareness and informing policies.
This course offers students a broad introduction to the field of discrimination by using evidence from across the social sciences. The course has four different blocks. The first block begins by defining discrimination and exploring related concepts like prejudices and stereotypes as well as delving into the theories of discrimination. The second block focuses on how to measure discrimination, and we will assess the strengths and weaknesses of different research designs. We will give particular attention to the use of survey and fields experiments, which are frequently used designs for identifying discrimination. In the third block, we will investigate some of the most recent experimental evidence on discrimination. We will look at discrimination based on various socially salient characteristics such as gender, ethnicity, social class, sexual orientation, partisanship in both political and apolitical domains. In the fourth block, we will reflect (and debate!) on the policies and initiatives that aim to counteract discrimination, including affirmative action policies.
This seminar aims to be interactive and there will be group work, debates, presentations, among other interactive tasks. No previous methodological knowledge is required.
BA and MA elective course
Specialisation line/course package:
Welfare, inequality, and mobility
The course is open to:
- Exchange and Guest students from abroad
- Credit students from Danish Universities
Full-degree students enrolled at the Faculty of Social Science, UCPH
- Bachelor and Master Programmes in Political Science
- Bachelor and Master Programmes in Psychology
- Bachelor and Master Programmes in Economics
- Master Programme in Social Data Science
- Master Programme in Global Development
- Master Programe in Security Risk Management
Knowledge:
- Develop an understanding of discrimination, including its relevance, key theoretical frameworks and counteraction initiatives.
- Demonstrate an understanding of the measurement of discrimination and the use of different designs in studies of discrimination.
- Discuss the latest experimental evidence on discrimination in both political and apolitical domains in various areas, such as gender, class, ethnicity, sexual orientation and partisanship.
Skills:
- Critically evaluate designs employed in measuring discrimination, identifying their strengths, weaknesses, and potential biases.
- Analyse and evaluate the initiatives aiming to counteract discrimination.
- Being able to synthesize knowledge and information from the course and to independently formulate an accompanying research design to study discrimination.
Competences:
- Apply theoretical and methodological knowledge in analysing instances of discrimination across various social contexts.
- Integrate course knowledge to formulate research design that address different aspects of discrimination.
Lectures, presentations, exercises and debates
- Lippert-Rasmussen, K., 2013. ‘What is Discrimination’ (chapter 1). In Born Free and Equal? Oxford University Press. https://academic.oup.com/book/8942/chapter/155252515
- Tilcsik, A., 2021. ‘Statistical Discrimination and the Rationalization of Stereotypes’. American Sociological Review 86 (1). SAGE Publications Inc: 93–122. doi:10.1177/0003122420969399.
- Fiske, S. T., Cuddy AJC, and Glick P., 2007. ‘Universal dimensions of social cognition: Warmth and competence.’ Trends in cognitive sciences 11 (2): 77-83.
- Galos, D.R., 2023. Social Media and Hiring: A Survey Experiment on Discrimination based on Online Social Class Cues. European Sociological Review, 1-13.
- Olsen, A.L., Kyhse‐Andersen, J.H., and Moynihan, D., 2022. The unequal distribution of opportunity: A national audit study of bureaucratic discrimination in primary school access. American Journal of Political Science, 66(3): 587-603.
- Schaeffer, M., & Kas, J. (2024). The integration paradox: a review and meta-analysis of the complex relationship between integration and reports of discrimination. International Migration Review, 58(3), 1384-1409.
- Paluck, E. L., Porat, R., Clark, C. S., and Green, D. P., 2021. Prejudice reduction: Progress and challenges. Annual review of psychology, 72, 533-560.
- Eberhardt, J. L. (2019). Biased: Uncovering the hidden prejudice that shapes what we see, think, and do. Penguin Books.
When registered you will be signed up for exam.
- Full-degree students – sign up at Selfservice on KUnet
- Exchange and guest students from abroad – sign up through Mobility Online and Selfservice- read more through this website.
- Credit students from Danish universities - sign up through this website.
The dates for the exams are found here Exams – Faculty of Social Sciences - University of Copenhagen (ku.dk)
Please note that it is your own responsibility to check for overlapping exam date.
- ECTS
- 7,5 ECTS
- Type of assessment
-
Home assignment
- Type of assessment details
- The students are required to formulate their own exam questions
based on pre-defined guidelines provided by the teacher. Students
will receive the exam guidelines for formulating exam questions
during the ongoing semester. The teacher is required to provide at
least two exemplary exam questions that adhere to the guidelines.
The exam can be written individually or in groups of max. 4 students.
Length of the exam is 10 pages + 5 pages pr. extra group member. - Examination prerequisites
-
To get qualified to the exam, the students must have completed a classroom presentation.
- Aid
- Only certain aids allowed (see description below)
The Department of Sociology prohibits the use of generative AI software and large language models (AI/LLMs), such as ChatGPT, for generating novel and creative content in written exams. However, students may use AI/LLMs to enhance the presentation of their own original work, such as text editing, argument validation, or improving statistical programming code. Students must disclose in an appendix if and how AI/LLMs were used; this appendix will not count toward the page limit of the exam. This policy is in place to ensure that students’ written exams accurately reflect their own knowledge and understanding of the material. All students are required to include an AI declaration in their exam submissions regardless of whether they have used generative AI software or not. This declaration should be placed as the last page of the exam submission. Please note that the AI statement is not included in the calculation of the overall length of your assignment. The template for the AI statement can be found in the Digital Exam system and on the Study Pages on KUnet under “Written exam”. Exams that do not declare if and how AI/LLMs were used will be administratively rejected and counted as one exam attempt.
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
- Exam period
-
Exam information:
The examination date can be found in the exam schedule here
The exact time and place will be available in Digital Exam from the middle of the semester.
- Re-exam
-
Reexam info:
The reexamination date/period can be found in the reexam schedule here
Same as the ordinary exam.
Criteria for exam assessment
See learning outcome
- Category
- Hours
- Class Instruction
- 42
- Preparation
- 164
- English
- 206
Kursusinformation
- Language
- English
- Course number
- ASOA22213U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
Bachelor
- Placement
- Summer
Summer 2026
- Schedulegroup
-
The first seven classes will be 5 hours (10-15) and the last class 7 hours (09-16).
- Studyboard
- Department of Sociology, Study Council
Contracting department
- Department of Sociology
- Department of Anthropology
- Department of Psychology
- Department of Political Science
- Social Data Science
- Department of Economics
Contracting faculty
- Faculty of Social Sciences
Course Coordinator
- Diana-Roxana Galos (3-6a786d4679756934717b346a71)
Timetable
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Courseinformation of students