Circulating Now welcomes guest blogger Dan Bouk, PhD who shares his insights on nineteenth century government data collection and analysis as part of our Revealing Data series. Dr. Bouk is Associate Professor of History at Colgate University.
By popular legend, although attributions are slippery, the American revolution brought with it the warning that soldiers ought not fire until they could see the white of the enemy’s eyes. But as a gorgeous book held in the history of medicine collections proves, by the time of the American Civil War doctors and surgeons concerned themselves not with the whites, but with the color of potential soldiers’ eyes. They looked at each set of brown, blue, black, gray, or hazel eyes and noted down what they found on a “blank” form.
That blank form demanded further observations that may have struck some of those making them as odd or beside the point: hair color, girth of chest, “nativity,” occupation. The point is not that these categories had nothing to do with health or medicine. Various nineteenth-century medical theories made the surface of the body (including eye color) a possible guide to its interior and made heredity or occupation into potential predictors of longevity or character. Still, doctors drawn into this nation-spanning project could be forgiven for wondering what such questions had to do with the most important question (number 17) on the blank: should the examined man be accepted or rejected for service in the union army?
One Pennsylvania surgeon groused about all the paperwork. He wrote: “the filling-up of the blanks for the examination of recruits, which has been recently required with each recruit, consumes so much time that, without assistance, the surgeon cannot examine a much greater number than of drafted men.” He may have been angling for clerical help, or he may have been pushing back against being made into a clerk himself—a fate feared in coming years by doctors who supplemented their incomes by conducting examinations for booming life insurance corporations.
The surgeon likely understood, as did many of the doctors and surgeons involved, why these blanks and their odd questions had so suddenly appeared. The blanks served the ambitions of Jedediah Hyde Baxter, the Chief Medical Officer of the Provost-Marshal-General Bureau, who saw an opportunity for science to benefit from the sprawling bureaucracy being built to direct one of the world’s first industrial wars. When the Belgian Adolphe Quetelet first reported in 1846 that measurements of chest girths of soldiers produced not only a national average but a bell curve or binomial distribution, his findings inspired statistical fever. Baxter burned with it, as did many doctors who joined him enthusiastically. One surgeon, for example, wrote Baxter not to complain about the length of the blanks, but instead to beg for more “specificness in the description of diseases.”
Having gathered data from a half million examinations, Baxter possessed the nineteenth century equivalent of “Big Data.” He did not, however, entirely trust it, because he knew how politics pulsed through his measurements. Historian Ted Porter has a good name for the way that the process of quantification can go awry when the stakes are high: “funny numbers.” Civil War data often proved to be funny. Surgeons—already peeved by the frequency with which boards of examiners ignored their recommendations on whether to take a man or not—fumed about on-going scams by which a “sound” individual would be allowed to disingenuously substitute himself during the examination in place of a volunteer plagued by some defect. They did not find the scam funny, but it could make their numbers hilarious.
No data were funnier, however, than hernia data. Baxter explained how President Lincoln’s efforts to round up fresh soldiers also gathered the herniated. The US government assigned recruiting quotas to each district according to the number of eligible men in each. Savvy politicians realized that the quickest way to fill a quota was to lower it, and they could lower the quota by declaring more citizens unfit for duty. Hernias became a favored excuse, and local officials and doctors rounded up all those with hernia to ensure their names were stricken from the rolls to a degree they did not for other diseases. Baxter stopped short of claiming that some of these hernias might have been dreamed up from whole cloth and yet that too seems at least possible—those doctors working for life insurers (with lower stakes) sometimes committed such frauds or much worse.
Baxter’s lithographer (who designed and printed the maps), Julius Bien, chose not to capture any humor in the hernia or other data. His breath-taking maps hint at no uncertainties, at no challenges. They evoke objectivity. They filled massive scientific volumes meant to express the American nation’s scientific capacity, destined for exchange among the world’s statistical experts and for popular viewing at then frequent global expositions, forerunners to the world’s fairs.
They represented, at a glance, the nation. Yet as is often the case in Big Data projects today too, these statistical depictions had their limits and blindspots. They were organized around congressional districts, a category with no obvious medical significance, but one dictated by the needs of the draft. They extended no farther south than Missouri and excluded all women and many men (who were either too old or too young). While the data included people of color and men born in many different countries, Baxter used that data to establish racial and national differences. In fact, to bring us back to where we began, it was Baxter’s desire to tease out the differences between “complexion” and race that made the reporting of superficial characteristics so important. Before he could assert the superiority of “blonde races,” (unsurprisingly for a moment when many were turning science to the project of justifying racism and exploitation) Baxter charged his small army of doctors and surgeons to inventory the colors of Americans’ eyes.
We hear about data every day. In historical medical collections, data abounds, both quantitative and qualitative. In its format, scope, and biases, data inherently contains more information than its face value. This series, Revealing Data, explores how, by preserving the research data of the past and making it publicly available, the National Library of Medicine (NLM) helps to ensure that generations of researchers can reexamine it, reveal new stories, and make new discoveries. As the NLM becomes the new home of data science at the National Institutes of Health (NIH), Circulating Now explores what researchers from a variety of disciplines are learning from centuries of preserved data, and how their work can help us think about the future preservation and uses of the data we collect today.
Dan Bouk is Associate Professor of History at Colgate University and author of How Our Days Became Numbered: Risk and the Rise of the Statistical Individual (University of Chicago Press, 2015). His article on the history and political economy of personal data over the last two hundred years, which inspired this post, will appear at the end of this year in the History of Science Society’s annual journal Osiris.