771A27 · 7.5 credits · Advanced level (A1F) · Computational Social Science
Inequality and Segregation: Theory and Measurement
Status unknown
100%
passed the latest ordinary exam
HEM1 · 11 Oct 2024 · 16 students
100%
passed the ordinary exams, all sittings over the last 5 years
HEM1 · 35 students
Part of 1 programme
Exam
HEM1 Take home exam
- A
- B
- C
- D
- E
Ordinary exams
100% passed · 35 students
- 100%16
- 100%19
Re-exams
100% passed · 38 students
- 100%38
- Pass the re-exam: 100% (38 students), compared with 100% (35 students) on the ordinary exam
- Get B or A: 52% (73 students)
Show small sittings (2)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
- 100%1
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Hand-in or lab
LAB1 Laboratory
- P
Main rounds
100% passed · 34 students
- 100%15
- 100%19
Later rounds
100% passed · 39 students
- 100%39
- Pass a later round: 100% (39 students), compared with 100% (34 students) on the ordinary exam
Show small sittings (2)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
- 100%1
Other module
SKL1 Written reading responses
- A
- B
- C
- D
- E
Main rounds
100% passed · 35 students
- 100%16
- 100%19
Later rounds
100% passed · 40 students
- 100%40
- Pass a later round: 100% (40 students), compared with 100% (35 students) on the ordinary exam
- Get B or A: 81% (75 students)
Show small sittings (1)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
About the course
Aim
After completion of the course, the student should at an advanced level be able to:
- explain the ideal properties of segregation and inequality measures
- distinguish different dimensions of segregation, identify measures associated with these dimensions, and evaluate their relevance for analysing segregation across different organizational units
- use computational methods to calculate common measures of inequality and segregation using empirical data and compare measures across places and times
- assess the relative contributions of various mechanisms implicated in inequality and segregation dynamics
- critically examine research on resource inequalities and various forms of segregation
- integrate theories of segregation and inequality and evaluate interrelationships between the two
- formulate research questions of relevance to contemporary research on segregation and inequality
Content
This course engages with classical and contemporary research on inequality and segregation. The first part of the course explores the concepts and principles of segregation and inequality measurement. Issues related to comparisons across places and times are discussed. During computer laboratories, measures of inequality and segregation are calculated using empirical data and compared. The second part of the course reviews, evaluates, and synthesizes theories positing generative mechanisms underpinning segregation and inequality dynamics. Finally, the connection between inequality and segregation is explored. Special attention is paid to computational methods and their explanatory role in segregation and inequality research.
- Examiner
- Erik Liss
- Main field of study
- Computational Social Science