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America's Course on Poverty and Inequality

We’re in the midst of a special moment in U.S. history in which income inequality has reached unprecedented levels, poverty remains extreme, and racial and gender inequalities are intransigent. Why is there so much inequality and poverty? How might they be reduced? In this free online course, the country's top scholars take on these questions by laying out the research that underlies our country’s existing policy, the research that points us to new policies, and the research that stands behind the emerging science of poverty and inequality.

Enroll now through Stanford Online.

Introduction to Social Stratification (SOC 140 & 240)

The trajectory of inequality is more unclear than ever. The purpose of this class is to pose – and answer – key questions about where we’re going and how we’re getting there. Why is income inequality increasing in many countries? Why has the historic decline in gender inequality begun to stall out? Is there less social mobility now than before? Are educational degrees, social contacts, or luck increasingly important in matching individuals to jobs and class positions? Has discrimination weakened with the transition to late modernity? We attempt to answer these questions by examining past trends and the forces behind them.

Check out a sample syllabus.

Controversies About Inequality (SOC 141 & 241)

A unique course built around debates about pressing poverty and inequality issues. We proceed by reading the relevant texts, hosting a full-on public debate between top scholars, and following up with a debriefing in which we get to the heart of the differences. Examples of past debates:

  • What Duties Do People in Rich Countries Have to Relieve World Poverty? Peter Singer (Princeton University) vs. Richard Miller (Cornell University)
  • Why is There So Much Incarceration? Lawrence D. Bobo (Harvard University) vs. Christopher Uggen (University of Minnesota)

Check out a sample syllabus.

Ending Poverty with Technology (SOC 157 & 158)

There are growing worries that new technologies may eliminate work, increase inequality, and create a large dependent class subsisting on transfers. But can technology instead be turned against itself and used to end poverty? This class explores the sources of domestic poverty and then examines how new technologies might be developed to eliminate poverty. We first survey existing poverty-reducing products and then attempt to imagine new products that might end poverty by equalizing access to information, reducing transaction costs, or equalizing access to training.

Check out a sample syllabus.

Social Stratification (SOC 340)


This course reviews contemporary models of the distribution of valued goods and the processes by which inequality comes to be seen as legitimate or natural. Although egalitarian values are a fundamental feature of our post-Enlightenment heritage, these values exist in tension with the extreme and often increasing inequality in the late modern world. The purpose of this course is to understand how we reconcile our commitment to equality (esp. equality of opportunity) with the typically substantial departures from it.

Check out a sample syllabus.

Inequality Workshop (SOC 341)

A graduate workshop devoted to presenting, critiquing, and improving research in progress. If we’re going to get paid to do research, we have an obligation to select research problems that truly matter and to complete research of the highest quality.

New Models and Methods in the Social Sciences (SOC 384)

Throughout the social sciences, there has been an explosion of new research methods and statistics, with the result that standard graduate course sequences often cover a declining proportion of the methods and statistics that actually appear in leading journals. This course addresses the explosion of new methods and statistics by bringing in ten leading experts who then teach concentrated one-day modules. We explore new developments in natural language processing, predictive analytics, machine learning, experimental methods, qualitative and mixed methods, big data analysis, data visualization, network models, simulation models, and much more.

Check out a sample syllabus.