What We Are Reading Today: Genetics in the Madhouse

Updated 30 July 2018

What We Are Reading Today: Genetics in the Madhouse

In this compelling book, Genetics in the Madhouse, author Theodore Porter draws on untapped archival evidence from across Europe and North America to bring to light the hidden history behind modern genetics.

“Porter’s masterful book casts the fresh light of sanity over a previously uncharted sea of data on madness,” Stephen M. Stigler, author of The Seven Pillars of Statistical Wisdom, said in remarks published in the Princeton University Press website.

“Porter brings analytical order to an intriguingly chaotic subject, illuminating the challenges of ‘big data’ from a past era when the plasticity of categorization resulted in data being deduced from conclusions, a problem with uncanny similarities to those we face today,” added Stigler.

Porter is Distinguished Professor of History and holds the Peter Reill Chair at the University of California, Los Angeles.  His books include Karl Pearson: The Scientific Life in a Statistical Age, Trust in Numbers: The Pursuit of Objectivity in Science and Public Life, and The Rise of Statistical Thinking, 1820–1900 (all Princeton). 

Carl Zimmer, author of She Has Her Mother’s Laugh: The Powers, Perversions, and Potential of Heredity, commented: “The book is a fascinating exploration of the long-running conviction that madness, criminality, and other mental traits can be passed down from parent to child.”


What We Are Reading Today: Generative Social Science

Updated 05 August 2020

What We Are Reading Today: Generative Social Science

Author: Joshua M. Epstein

Agent-based computational modeling is changing the face of social science. In Generative Social Science, Joshua Epstein argues that this powerful, novel technique permits the social sciences to meet a fundamentally new standard of explanation, in which one “grows” the phenomenon of interest in an artificial society of interacting agents: heterogeneous, boundedly rational actors, represented as mathematical or software objects.
After elaborating this notion of generative explanation in a pair of overarching foundational chapters, Epstein illustrates it with examples chosen from such far-flung fields as archaeology, civil conflict, the evolution of norms, epidemiology, retirement economics, spatial games, and organizational adaptation.
In elegant chapter preludes, he explains how these widely diverse modeling studies support his sweeping case for generative explanation.
This book represents a powerful consolidation of Epstein’s interdisciplinary research activities in the decade since the publication of his and Robert Axtell’s landmark volume, Growing Artificial Societies.