Welcome to the Segregation Models module! This section explores computational models of residential segregation, building on Thomas Schelling’s groundbreaking work Schelling (1971) on how individual preferences can lead to collective patterns of segregation. We will generalize the residential model and see ways to apply it to other contexts.
Segregation models help us understand how micro-level individual choices can lead to macro-level social phenomena Schelling (1978). Through agent-based modeling, we’ll explore how even mild preferences for similarity can result in highly segregated neighborhoods, providing insights into urban dynamics and social processes.
Module Duration: 2 weeks
Student Learning Objectives (SLOs)¶
By the end of this module, students will be able to:
Increase students’ knowledge of social systems and of human behavior within such systems
Apply algorithmic, statistical, and/or mathematical methods to solve problems, broadly defined to find the answers to questions in various domains (as appropriate).
Represent, interpret, and process information in graphical, numeric, and/or symbolic forms.
Explain the difference between individual preferences and collective outcomes
Analyze how threshold models work in social systems
Evaluate the relationship between micro-motives and macro-behavior
Navigate the NetLogo interface and basic programming concepts
Create simple agent-based models with basic behaviors
Run simulations and collect data from model outputs
Interpret basic visualization and data outputs
Implement Schelling’s segregation model in NetLogo
Modify agent rules and parameters to test different scenarios
Collect and analyze data from agent-based simulations
Assess the implications of segregation models for real-world policy
Compare model predictions with empirical data on residential patterns
Critique the assumptions and limitations of segregation models
Present findings from simulation experiments clearly
Discuss ethical implications of segregation research
Connect model insights to contemporary social issues
📋 Weekly Breakdown¶
Week 3: Tuesday, September 16
Heckman Library 406C
Session A: History of segregation in social research.
Summary:
Traditions: Du Bois’ The Philadelphia Negro, Chicago School, Massey & Denton’s structural view.
Concepts: de jure vs. de facto segregation; neighborhood effects; systemic racism.
Slides: Segregation
Session B: Discussion of readings.
Summary:
Massey & Denton, American Apartheid (1993), Ch. 1.
Banaji, Fiske & Massey, “Systemic Racism” (Cognitive Research, 2021).
Deliverable: SRG prep sheet.
Week 3: Thursday, September 18
Heckman Library 406C
Session A (Lab): Schelling segregation model.
Summary: Building Schelling’s model
Slides: Schelling Model
Session B:
Summary:
Explore tolerance thresholds, group asymmetry, neighborhood sizes.
Class critique: What’s realistic? What’s missing (e.g., structural constraints)?
Deliverable: Lab Memo #2.
Week 4: Tuesday, September 23
Heckman Library 406C
Session A (SRG):
Summary: Talking about segregation models in social research
Bruch, Elizabeth E., and Robert D. Mare. “Neighborhood choice and neighborhood change.” American Journal of sociology 112.3 (2006): 667-709.
Session B:
Summary: From Checkerboards to Cities
Slides: Checkerboards to Cities
Week 4: Thursday, September 25
Heckman Library 406C
Session A (Lab): Adding plots, monitors, and reporters to the Schelling model
Session B (Lab): Running batch experiments with BehaviorSpace in NetLogo
📝 Assignments & Due Dates (Weeks 3–4)¶
Due: 9/23 before class | Points: 20 points
Prompt (1-2 pages):
Take the code for the Schelling model implemented in class in the link above (Lecture 6). Your task is to modify the model in some way and analyze the results. You can choose one of the following options:
Add a reporter: e.g., track the number of moves, average satisfaction, or segregation index over time.
Change the neighborhood definition: e.g., use a larger or smaller neighborhood size.
Introduce heterogeneity: e.g., allow agents to have different tolerance levels or preferences.
Add mobility constraints: e.g., limit how far agents can move in a single step.
Write your Lab Memo. You can download the template in here.
Make sure you add the codes you’ve changed, as well as interface modifications.
Submit your Lab Memo in PDF format through Moodle.
Due: 10/2 before class | Points: 30 points
Prompt (1-2 pages):
Take the code for the Schelling model implemented in class in the link above (Lecture 6). Your task is to analyze the results of the model. You will run a batch experiment varying the parameters of the model (e.g., tolerance level, density of agents) and collect data on the outcomes (e.g., number of happy agents, segregation index). You can use the BehaviorSpace tool in NetLogo to set up and run the batch experiment. Here are some steps to guide you:
Define the parameters you want to vary and their ranges.
Set up the metrics you want to record during the simulations.
Run the batch experiment and collect the data.
Analyze the results using statistical or graphical methods. Look for patterns or trends in how the parameters affect the outcomes. You may use LLM tools to help you with the analysis. Make sure you are bringing up your own insights and interpretations also.
Write your Lab Memo. You can download the template in here.
Make sure you add the codes you’ve changed, as well as interface modifications.
Submit your Lab Memo in PDF format through Moodle.
📚 Readings and Extra Materials¶
Bruch, Elizabeth E., and Robert D. Mare. “Neighborhood choice and neighborhood change.” American Journal of sociology 112.3 (2006): 667-709.
Bruch, Elizabeth E. “How population structure shapes neighborhood segregation.” American Journal of Sociology 119.5 (2014): 1221-1278.
Schelling, T. C. (1971). Dynamic models of segregation. Journal of Mathematical Sociology, 1(2), 143-186.
Ryan Burge. “The Most Segregated Hour? Rethinking Race and Religion in America”.
🎥 The Power of Models (4 min)
🎥 Top 3 aspects people get wrong about Agent Based Modeling (9 min)
🎥 When is a system complex? (3 min)
🎥 Emergence – How Stupid Things Become Smart Together (7 min)
- Schelling, T. C. (1971). Dynamic models of segregation. Journal of Mathematical Sociology, 1(2), 143–186.
- Schelling, T. C. (1978). Micromotives and macrobehavior. WW Norton & Company.
- Schelling, T. C. (1971). Dynamic models of segregation†. The Journal of Mathematical Sociology, 1(2), 143–186. 10.1080/0022250x.1971.9989794