AHA Annual Meeting

Abstract of the Presidential Address at the Annual Meeting: “Inequality: Historical and Disciplinary Approaches”

Patrick Manning, November 2016

In Rio de Janeiro, high-rise buildings loom in front of Rocinha, one of the largest favelas in Brazil. Wikimedia CommonsInequality is a contemporary social dilemma of growing concern. Has it been constructed through human agency, or is it a simple fact of nature? In their debates, ancient philosophers and modern analysts have been critical of inequality without being able to resolve it. For the past two centuries, human thought has pursued social equality and democratic governance, while the realities of social change have brought new economic and social inequalities.

Understanding inequality in society will require a large-scale research project. The hypotheses articulated and tested must be the strongest and most relevant. What is the social function of inequality? Can regulation limit inequality? Do patterns of inequality connect worldwide? Is social prejudice more basic than economic inequality? Does inequality come from the top or bottom ranks of society? Have there been cycles of inequality? We need to explore such questions with data on the full range of human activities, at levels from the family to big regions (for example, the Caribbean, Southeast Asia, Europe, Africa) to the planet.

This presentation will survey recent research on inequality and propose a design for an interdisciplinary campaign to clarify the history, trajectory, and influence of inequality. While economic analysts have shown that the top 1 percent of individuals hold the majority of today’s wealth, how does that relate to hierarchies of gender, race, nationality, health, and nutrition? Historians, to guide this work, must build on the growing comprehensiveness of historical studies—in narrative, collaboration, theory, and disciplinary alliances. Researchers must assemble archival data, conduct field research, simulate missing data, and reach for the great new potential of information science to locate relationships within both data-rich and data-poor domains. The outcome will not end the debate on inequality, but will raise it to a new and evidence-based level.


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