Racial and Ethnic Diversity: Causes and Effects
Examines causes and effects of racial and ethnic diversity globally, covering measurement, migration, segregation, conflict, political behavior, and policy interventions.
Summary
Recent recorded grades — Spring 2023: 3.83 GPA, 100.0% A/AB (n=6 letter grades).
What you’ll be able to do
Gain an understanding of the meaning and measurement of racial and ethnic diversity.
Become familiar with the social science literature on the causes and effects of ethnic and racial diversity and segregation.
Identify and learn about research methods used in the study of racial and ethnic diversity.
Develop critical reading, writing, collaboration, and presentation skills.
Source: UW Guide
Grade history
↗All recorded terms · compare terms & instructors
Prerequisites
Course mapGraduate/professional standing
- Graduate/professional standing
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Prerequisite text tree
- Graduate/professional standing
Professors
Spring 2027No instructors recorded for this selection.
Historical instructors & teaching patterns
Recorded history may be incomplete and does not establish a future schedule.
Calendar & sections
Spring 2027Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
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Meeting source records
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Student experience
the class
Recent recorded grades — Spring 2023: 3.83 GPA, 100.0% A/AB (n=6 letter grades).
difficulty & workload
No workload feedback recorded.
Topics
- Definitions and measurement of diversity
- Causes: migration, ethnic cleansing, colonialism, segregation
- Effects on social relations, conflict, public goods, politics, and organizations
- Policy interventions: affirmative action, quotas, diversity training
Skills
- Measuring racial and ethnic diversity
- Research methods for studying diversity
- Critical reading, writing, collaboration, and presentation
Grades
Latest available · Spring 2023— not enough history to project Spring 2027.
Grade distribution · % of letter grades
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Catalog & offerings
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Grade history
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Explore recorded gradesRecorded 2026-10-14
Model outputs & technical records
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
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"requirements_status": "valid",
"dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
"observed_at": "2026-10-14 17:50:09.728220+00:00"
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