Understanding the Fading American Dream
A student guide to economic mobility, algorithmic bias, big data, and redlining — and how data reveals the systems shaping your future.
Beyond the ZIP Code: The Opportunity Challenge
Exploring how social geography, economic mobility, and social connectedness shape access to opportunity — and how evidence, diplomacy, and partnerships can help expand it.
Quality Education
How does where a student lives influence access to quality education and pathways to future opportunity?
Reduced Inequalities
Why do people and communities face different opportunities, and which inequalities can public policy address?
Partnerships for the Goals
Who needs to work together to make opportunity more accessible, and how can we measure progress?
Three Prioritized Learning Goals
Students will investigate how opportunity varies across places and how data can help describe — but not by itself explain — those differences. Geography is more than location or a boundary on a map: places are shaped by social relationships, institutions, economic resources, public policies, and infrastructure.
Analyze data about opportunity
Calculate and interpret percentages and rates; represent paired data in scatterplots; compare distributions using mean and median; and use a linear model to interpret slope as a rate of change.
Interpret evidence carefully
Describe patterns and associations, distinguish correlation from causation, and explain how outliers, data choices, geographic boundaries, and missing context may affect conclusions.
Develop an evidence-informed proposal
Identify an opportunity-related question, consider relevant geographic and social conditions, and propose a response that recognizes both community assets and barriers.
What Students Will Explore
Economic Mobility & Life Trajectories
Students consider how social and economic position may change over time and how individual experiences interact with broader conditions, using Life Maps as visual timelines of events, transitions, and influences.
Social Geography & the Organization of Opportunity
Students explore how places are shaped by institutions, public policy, housing, transportation, schools, employment, and access to resources — and how these conditions vary geographically.
Geographic Access & Opportunity Conditions
Students examine how distance, transportation, infrastructure, and community resources may affect access, distinguishing geographic proximity from meaningful access.
Social Connectedness & Social Capital
Students consider how relationships across socioeconomic groups may influence access to information, mentorship, support, and opportunities, and how those connections interact with the geographic distribution of resources.
Data, Indicators & Geographic Boundaries
Students investigate how ZIP Codes and other geographic units are used to describe places and populations, asking what an indicator measures, what it leaves out, and how using a place as a proxy for an individual can mislead.
Opportunity Gaps & Community Action
Students use evidence to frame an opportunity-related question, examine relevant conditions, and propose a response that could improve access or strengthen existing community assets.
Connection to OI's Mission
This project connects to Opportunity Insights' mission of understanding the determinants of economic opportunity and identifying ways to improve upward mobility. Students use social geography as a framework for asking how place, institutions, resources, and relationships may shape access to opportunity. The project emphasizes a distinction between patterns and mechanisms: data may show that an indicator varies across places, but further evidence is needed to understand why.
Teaching and Learning Context
Designed for Grade 9 & 10 Algebra I students in New York, this project fits after students have worked with data displays and measures of center, and while they are learning or reviewing bivariate data, scatterplots, correlation, and linear models. Students connect familiar ideas about neighborhoods and communities to questions about economic mobility, social connectedness, and the distribution of opportunity.
A Dream Deferred by Data
The decline in absolute income mobility is one of the most consequential economic shifts of the past century. It is not evenly distributed — where you grow up, the color of your skin, and the income of your parents all predict your economic future with striking accuracy. This is not fate. It is policy.
From Data to Understanding
This unit asks a fundamental question: why do some neighborhoods produce far more economic mobility than others? Using real data from the Opportunity Atlas and other civic datasets, students explore how geography, race, and policy have shaped — and continue to shape — who gets ahead in America.
As you work through the material, pay attention to the patterns. Where do you see algorithmic bias reinforcing historical inequities? How did redlining create the neighborhood boundaries that still define opportunity today? What does big data reveal — and what does it hide?
How to Read This Unit
Read actively
Annotate as you go. Mark claims that surprise you, data you want to verify, and questions the material raises but doesn't answer.
Connect to your community
Look up your ZIP code in the Opportunity Atlas. How does your neighborhood compare? What historical policies might explain the patterns you see?
Question the data
Ask who collected this data, how, and why. What populations might be undercounted? What does the dataset make visible — and what does it obscure?
Discuss and debate
These are contested topics. Bring your analysis to class discussion. The goal is not a single answer but a sharper set of questions.
Statistics Can Be Misleading
Watch these short videos to build your critical data literacy before diving into the unit material.
How Statistics Can Be Misleading
Comment les statistiques peuvent induire en erreur
Read the Unit
Use the viewer below to read the full unit. Navigate page by page, or download a copy to annotate offline.
Student Curriculum
Unit 1, Lesson 1: Understanding Economic Mobility
Think Critically. Talk It Through.
These questions are designed to push your thinking beyond the data. There are no single correct answers — the goal is a sharper, more evidence-grounded argument.
The data shows that where you grow up predicts your income as an adult. Does this mean the American Dream is a myth — or that it is unevenly distributed? What is the difference?
If an algorithm was trained on data from a period of legal discrimination, can its outputs ever be fair? What would it take to fix it — and who should decide?
Redlining ended as official policy in 1968. Look up your own neighborhood in the Opportunity Atlas. Do you see patterns that might trace back to those historical boundaries?
Big data can reveal systemic inequity — but it can also be used to surveil and control communities. How do we decide when data collection serves the public good?
Chetty's research shows that some low-income neighborhoods produce high mobility outcomes. What do those places have in common? What policy levers might replicate those conditions?
Who is missing from the datasets we use to measure opportunity? What groups are systematically undercounted, and how does that shape the policies built on this data?
Explore the Opportunity Atlas
After reading the unit, use the interactive Opportunity Atlas to explore economic mobility data in your own community.