Arwen Mohun, “On the Frontier of The Empire of Chance: Statistics, Accidents, and Risk in Industrializing America.” Science in Context 3 (2005): 337-357.
In “On the Frontier of The Empire of Chance,” author Arwen Mohun examines the rise in statistics and probabilistic thinking in the American vernacular context from the late nineteenth through the early twentieth centuries. Through the lens of a cultural historian of technology, Mohun takes a closer look at how the industrial-era quantification of risk altered the way people understood it; she asks why and how this transformation took place, and then delves into how these understandings were shaped and used in order to mold individual behavior and enact widespread change. Mohun argues that the actors in her narrative existed on the periphery of the Empire of Chance. While experts, primarily located in European centers of statistical theorizing, formed the “epicenter” of the empire, those on the frontier employed statistics as a tool in social manipulation. Far from relegating popular audiences to a primarily observational, inert role, however, the author also acknowledges their agency in the story by explaining how their motivations affected their choices regarding risk and reward.
Obviously, Mohun’s work builds off of the book she references in her title — The Empire of Chance. Her piece is different from that of Gigerenzer et al., however, in that it addresses how the methodological and intellectual developments of professional statisticians found their way into popular understandings of variability and the risks associated with it. This is reminiscent of Dr. Pandora’s assigned reading for her two weeks of 5990 at the beginning of the semester — Spectacular Nature and The Whale and the Supercomputer. Like Mohun’s work, Susan G. Davis looks at how ideas from the “top,” the professional scientists, filter down into the vernacular through institutions like SeaWorld. Mohun also looks at how institutions influence the way that popular audiences understand scientific theories, their consequences, and their uses. In contrast, Charles Wohlforth focuses on how non-professional ways of knowing had a major impact on the way scientists looked at and understood climate change in the arctic. Mohun mimics this approach when she includes in her analysis how the importance of individual experience affects the way that the average American understood and behaved in regards to risk-taking. When the approach involves popular science, both perspectives — top-down and bottom-up — are important for a holistic understanding of how science and vernacular audiences interact and influence one another, and in this regard, Mohun as clearly covered all of her bases.
Something I found particularly interesting in this piece was the discussion of the “pragmatic approach” to science that Mohun discusses primarily on pages 339 and 340. She argues that it was especially characteristic of American statisticians in the time period she covers, and cites as evidence their absence from histories of statistics. American statisticians worried less about developing sound theories and methods and more about applying their knowledge (no matter how unsound or theoretically dubious) to real-world problems. This embodied what I have come to understand as being a very Industrial-American ideal; the self-made, self-trained practitioner unconcerned with the useless, bookish knowledge so characteristic of their less hard-working, impractical European counterparts. I wonder if the different approaches caused animosity between American and European statisticians; they were obviously sharing ideas. What did these conversations look like, and how did they take place? Was it common for Americans to train abroad, or were universities in America training these frontiersmen of the Empire of Chance?