Overview

Scholarly Borderlands is a new initiative devoted to exploring the space between fields—or the “borderlands” between disciplines—as uniquely productive for social inquiry. Through establishing working groups on a variety of emergent issues, the Council encourages dialogue, collaboration, and innovation that may cross analytical, methodological, and epistemological boundaries. The goal is to shape the craft of social science through asking new questions and developing new frameworks and tools for addressing them. These efforts aim to build fresh ties within the social sciences and to more robustly link the social sciences to work in science and the humanities. The initiative has selected an initial group of project areas, some already underway and others in formation, that are simultaneously intellectual puzzles and opportunities for scholarly collaboration and innovation.

Big Data and Historical Social Science

While “big data” often connotes new opportunities for understanding the present, largely through the analysis of social media and search engine data, other newly available kinds of rich data sources create huge possibilities for reimagining the past. In recent years, millions of previously difficult-to-access documents and massive archival data structures have become widely available to scholars of human history and the general public. The project on Big Data and Historical Social Science, led by Peter Bearman and Chris Muller, brings together researchers across a range of disciplines, methods, and research strategies to explore the intersection of classical historical and social science problems and big data. How can access to new kinds of historical data, and new capacities to manipulate and analyze them, allow scholars to address historical questions in new ways?

At an initial planning meeting for the project in November 2015, participants agreed that demonstration projects on particular historical eras and questions would be the first step in exploring how scholars working on different aspects of a historical puzzle could collaboratively mobilize diverse data sets and data structures. The first project is on “race” in the Americas in the period between the Reconstruction era and the Civil Rights movement (1877–1965). For this and future demonstration projects, the group will deploy techniques for “nesting” data—that is, utilizing temporal and spatial tools to understand changing data structures across time and levels of analysis—and for “linking” data—networking different kinds of data to provide a comprehensive picture and moroe thorough explanations of historical continuities and changes.

History, Networks, and Evolution

“In the short run, actors make relations, but in the long run, relations make actors” is a compelling assertion from John Padgett and Walter Powell’s The Emergence of Organizations and Markets (2012). The Scholarly Borderlands project History, Evolution and Networks, led by Padgett, takes this insight about the “long run” to reimagine how scholars understand macrohistorical change. Focusing on novelty and the question “Where do new types of people, organizations, social movements, states, and markets come from?” the project conceives of history as interacting sets of dynamically evolving networks of people and practices. This core question is the basis for developing theoretical and empirical bridges between fields and approaches not usually in close conversation: history, social network analysis, evolutionary biology, and biochemistry. Scholars in these latter fields are increasingly concerned with the coevolution (as juxtaposed to the natural selection) of species, which creates the potential for exchange with social scientists looking at the interactions across networks and the emergences of new social actors and institutions.

The project is a partnership of the SSRC, the Center for Advanced Study in the Behavioral Sciences at Stanford, and the Santa Fe Institute. A core working group began meeting in 2015. Participants are currently developing case studies and collaborations from evolutionary biology and history that are linked by a common set of questions and analytical tools.