“On the Frontier of the Empire of Chance”

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?

The Empire of Chance

The Empire of Chance: How Probability Changed Science and Everyday Life, Gerd Gigerenzer, Zeno Swijtink, Theodore Porter, Lorrain Daston, John Beatty, and Lorenz Krüger

            In their collaborative work, authors Gerd Gigerenzer, Zeno Swijtink, Theodore Porter, Lorrain Daston, John Beatty, and Lorenz Krüger attempt a cohesive study of how the science of statistics “transformed our ideas of nature, mind, and society.” (xiv) The first three chapters present a timeline on which the intellectual development of the science of statistics — with some consideration of its particular applications — is situated, the middle three deal with statistics in particular fields, and the last two concern broader implications of statistical analyses, ideologies, and methodologies. A central theme of the book is the idea that the science of statistics was both shaped and shaped by the sciences that it aided and that helped to develop it for their own explanatory and predictive goals. Professing to be the first of its kind, the survey offers detailed technical descriptions and examples that flesh out the mathematics and theories with which its actors are working.

The passages dealing with mid-nineteenth century debates surrounding the viability of statistical methods for physicians reminded me of S. Lochlann Jain’s criticisms of the same methods in her work, Malignant. Jain and her unlikely intellectual compatriots cite similar issues with the “numerical method” in medicine; it denies the complexity and uniqueness of the individual patient, aiming “not to cure the disease, but to cure the most possible out of a certain number” (Risueño d’Amador, 1836, 46). This results in the emotions Jain so skillfully articulates in her first-hand account as a cancer patient. Reduced to numbers, cancer sufferers are identified by the statistical methods their doctors use to diagnose and treat them. Equally concerning is the reliance of pharmaceutical companies on results from statistical studies to produce drugs that will target cancer on a broader scale, to the detriment of patients who would have benefitted from more personalized treatments. Perhaps these nineteenth century critics were not off base in their hesitancy to adopt such a dehumanizing method of handling disease.

Another bit I found particularly interesting was section 3.5, “Hybridization: the Silent Solution.” Having taken statistics and seen it in what I am now realizing was a surprising amount of my undergraduate science classes, I was struck by the fact that the statistical methods we learn as absolute and established are in fact far from it. Integral tenets to the type of statistics I was taught are, in actuality, theoretically at odds with one another, and yet, as the authors contend, “Statistics is treated as abstract truth, a monolithic logic of inductive inference.” (107) Because statistical methods are so widespread, I find it both surprising and alarming that these obvious impediments to its image as a well-established and unproblematic method of analysis are kept more or less hidden. It lead me into thinking about how oftentimes, when scientific disciplines are “successfully” mathematized, we deem them somehow more intelligible; they become more solid, their results more trust-worthy. Is this a valid logical jump to make, especially if statistics, one of the mathematical sciences that is employed most often, rests on shaky ground?

The Whale and the Supercomputer

The Whale and the Supercomputer: On the Northern Front of Climate Change, Charles Wohlforth

I was interested in how the natives perceived scientific methods as lazy, in a way. After it was pointed out, I cannot unsee it now. While the Iñupiaq spend most of their time living in and experiencing Alaska and the changes it has undergone in recent years, scientists primarily only come in the summer. They take measurements or install gear to do so in the winter, when they will undoubtedly not be present to observe the data-gathering in action. Scientists take detailed data in an isolated manner; they search for “slices” of something far more complex, and they try and extrapolate about what they don’t know, given what they do know in detail. As evidenced by many failures — one being the gross underestimate of the Arctic whale population — this does not always work, and it can affect policy, people, and the earth itself.

This stands in sharp contrast to the way that the natives attempt to understand nature. Far more grounded and involved in the knowledge-gathering process, they work together as a community, bound by social conventions, common culture, and a need to survive in a harsh and rapidly changing environment. Their knowledge base is more practical; while they observe the changes taking place around them, they don’t necessarily seek the kind of explanations scientists would. They seek practical adaptations, ways of working with the cards that nature has dealt them. They have little interest in conquering nature and instead hope to work with her.

The way that these two groups interact is telling. The Iñupiaq seem to relatively readily have adopted many of the techniques white whalers employed in the 19th century, like brass pipe bombs, that made their work less dangerous and more fruitful. Because their way of knowledge-gathering and authentication is largely based on what works, rather than where that knowledge came from, there seems to be much less intellectual resistance to the adoption of alternative ways of doing and knowing. Scientists, on the other hand, seem to have a harder time incorporating traditional knowledge into their research. A good example can be found in the episode Wohlforth recounts of one of Matthew’s data-gathering expeditions in which an Iñupiaq elder is brought along. The scientists were worried about “translating the different frames of reference”, (90) and in the end, the elder ended up primarily being a guide. His knowledge was of a different language, inscrutable and irreducible, and unable to be communicated or translated into the numbers and statistics the scientists felt were the only way to understand what was happening to the climate in Alaska.

I think it all comes down to communication. Wohlforth spends a lot of time talking about how systems composed of many people operate; the Iñupiaq on a whale hunt, scientists in a conference room at IARC trying to understand why their models for climate change weren’t producing results. He discusses the difficulties in translating one person or culture’s knowledge to another, but emphasizes that it is in these connections that the whole, complicated truth lay. One way of knowing, even one as meticulous as the scientific method, cannot paint an entire, comprehensive picture of an actuality. The mechanical worldview’s track record with the “harder” sciences — chemistry, physics, some aspects of biology — have given scientists an unrealistic faith in it; climate change shows us that some things are simply too complicated to be broken down and must be viewed more holistically if we ever expect to understand them as they are.

When international and US lawmakers, concerned with the preservation of whale species, attempted to make hunting them illegal (despite the fact that the Iñupiaq way of life would be a casualty of such policy), scientific and traditional knowledge were forced into cooperation. Scientists had estimated the population of the bowheads to be far smaller than the natives believed to be the case. Political maneuvering on the part of the Iñupiaq made their voices heard, and the scientists were forced to listen. Having coexisted with the bowheads for as long as they could remember, the natives knew that the way the scientists were counting them was inefficient, missing huge numbers of animals — their migration band was much larger than scientists predicted, and the whales often swam under the ice where they could not be seen. In order to develop a more effective way of counting bowheads, the scientists were forced to collaborate with the natives. The result was that, unsurprisingly, the natives had been right all along. As the only place where “samples of large, freshly killed baleen whales” were present, Barrow drew many scientists who wished to study the mysterious animals. In close proximity, and because the scientists needed their expertise on ice navigation, a discourse between the natives and the scientists opened up. As Wohlforth so eloquently puts it, “Researchers… had to accept that there was another valid way of knowing complex facts about the environment.” (22)