Teaching

Stanford English: Literary Text Mining

Computational methods have made it possible to analyze literature in new ways and at new scales. This course trains students in theories and methods of computational literary studies. It requires no background in computer programming or literary criticism. We begin with fundamentals of the Python programming language before moving on to computational analyses of literary texts. Our analyses will be informed by critical readings.

The City College of New York: World Humanities 101, “What it is like to be alive”

Among many other things, literature tells us about what it is like to be alive. Reading the literature of the past can help us see that question in a historical sense: “What was it like to be alive then?” But it also makes possible another question that readers ask themselves as they try to relate to literature today: “Is this still what it is like to be alive?” This class reflects on these questions by reading epics, tragedies, religious texts, narrative poems, and novels about people struggling to understand their world and themselves.

Stanford Writing Intensive Seminar in English: Average Americans

Perennially invoked by politicians and pundits, declared “divine” by Walt Whitman, the “average American” has been one of the United States’ most important fictional characters for well over a century.  But do averages tell us anything about the individuals from whom they are derived? And who benefits when we use the “average American” as a way of saying who represents the U.S.? The logic of the average resonates with American self-concepts of democracy, equality, and scientific rationalism, yet the same data can be used to suppress difference and dissent. How does the novel propagate and problematize this idea of the representative individual? As we move between close and distant scales of reading, we will ask how numbers and texts attempt to represent American personhood.