Bouk 2022

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Bouk, Dan. Democracy's Data: The Hidden Stories in the U.S. Census. MCD, 2022.

0. Stories in the Data

Page 3 · Location 68 To find the stories in the data, we must widen our lens to take in not only the numbers but also the processes that generated those numbers.

Page 10 · Location 196 We too easily forget that counting “the people” required first defining who “the people” were and what mattered about each person.

Page 10 · Location 197 We have forgotten the history that birthed “appropriate” census questions. We forget that those questions and the categories created to generate data might even inspire new ways of thinking about ourselves and our neighbors. In every boring bureaucratic form, there lurks drama, conflict, and the quintessentially modern struggle to fit messy lives into standardized categories.

Page 13 · Location 245 Data are not exclusively

Page 13 · Location 245 the province of computer coders, hackers, and quants. Data belong to a particular time and place, and they carry the imprint of that time and place. What my family’s story helps make clear is that to read census data, or any similar data, is to encounter a complicated, multilayered cultural object, a deep, often tangled text.

Page 14 · Location 258 Like other texts, data sets belong to old, though not necessarily exalted, traditions and genres. The forms we now fill out daily to make a doctor’s appointment or to order dinner online belong, for instance, to a tradition of “blank” forms that reaches back at least to Johannes Gutenberg, who used his printing press to produce big batches of indulgences for the Catholic Church, each leaving a space for a name to

Page 14 · Location 261 be written identifying the sinner seeking absolution.

Page 15 · Location 277 Even in the cloud, data sets remain materially instantiated texts.

Page 15 · Location 277 Like any other texts, data sets will bear the imprint of their times, revealing the values of their authors and perhaps of the wider society, with its patterns of power

Page 15 · Location 279 and wealth and domination, with its ideals of truth and beauty and justice. Data makers decide what counts and who counts. The questions they ask, the categories they attend to, and the labels they apply all hail from their way of seeing the world and judging what matters.

Page 16 · Location 305 Some people fall in love with the appearance of data as a thing more or less certain, simple, and precise. I think there is more beauty and also more truth in acknowledging and even appreciating the roots of data in the uncertain, complicated, and often hazy spaces of life.

1. The Question Men

Page 27 · Location 426 To really understand a data set we need to learn as much as we can about its designers: Where did they come from? What did they dream and desire? And who wasn’t invited to help frame the data? Whose experiences and values were simply brushed aside?

Page 32 · Location 529 Under his hand, the Metropolitan Statistical Bureau blossomed into one of the most trusted sources for American statistics, second only to the Census Bureau. Reformers looked in vain in the census to discover how many people died in car crashes or lost limbs to industrial accidents. But Dublin had access to reliable figures in his employer’s private statistical stash, and through the Metropolitan Life’s Statistical Bulletin he made them widely available.

Page 35 · Location 578 One of those American students who made the Atlantic crossing was W.E.B. Du Bois, whose 1899 social survey The Philadelphia Negro introduced the German style of social science to the study of race in the United States and whose masterpiece The Souls of Black Folk was cousin to the sort of fieldwork done by the Brothers Grimm to capture the spirit/ soul (Geist) of many European nations (Volk).

Page 39 · Location 662 Census officials thought 32 numbered columns, the count in 1930, was the most that could be squeezed into that space. Asking a new question meant adding a new column, which meant that some other question, some other column, had to go.

2. Names and Negotiations

Page 57 · Location 952 In the late 1930s, a Works Progress Administration project aided the census in this arduous task by building a new kind of name index, called Soundex. 10 The bureau knew as well as anybody that its records didn’t always spell names

Page 57 · Location 955 properly and that spellings shifted over time, and so it built an alphabetized index based on phonetics that allowed bureau officials to find any record based on the sound of a name and so provide people with the evidence they needed to get along in a document-hungry world.

Page 58 · Location 988 Though people quickly came to rely on numerical addresses to find one another, send letters, or navigate strange and growing cities, those uses were accidental benefits of an apparatus

Page 58 · Location 990 meant to serve the data makers in imperial or national bureaucracies.

3. Partners

Page 77 · Location 1296 To count a person in 1940, the Census Bureau demanded that there be a “head” of that person’s household. It struggled to make sense of people who lived in arrangements that defied the bureau’s expectations.

Page 94 · Location 1629 The “partner” label made it possible for a household census to count at the margins of society. It created a big tent filled with an enormous variety of arrangements for living together.

Page 97 · Location 1687 That “Par” is tantalizing, but isn’t for “partner.” Scattergood, as a partner, would have been punched in and tabulated as “Lod,” as a “lodger.” When it came to making statistics, all the partners of this chapter simply disappeared. That is why their stories cannot be found in the published numbers.

4. Counting with Friends

Page 114 · Location 1952 Complex political negotiations like these have shaped, in one way or another, every census and probably every big data set. 5. Silences and White Supremacy

Page 129 · Location 2263 One way to uncover the political forces that shaped a data set is to look to that set’s silences. Those silences often have political implications, and those silences themselves are often the product of politics.

Page 141 · Location 2513 Marking a subpopulation and making it visible can lead to policies that aid oppressed groups and support the systematically marginalized—the Civil Rights movement made that possibility clear. But without the political will for equality, marking a subpopulation as racially other can—and in the 1930s

Page 142 · Location 2516 did—justify continued inequality, neglect, and discrimination. 41

6. Uncle Sam v. Senator Tobey

Page 178 · Location 3195 “The census law to start with was an insult to the American people; an invasion of their homes and private lives; and has every appearance of being intended to card-index the people on behalf of would-be dictators.” 47 Here was a forerunner to today’s database politics. Before the advent of the digital computer, card indices allowed governments and businesses to keep track of thousands or even millions of individuals.

Page 179 · Location 3213 U.S. government built card indices because it modeled its chief welfare program on private insurance practices and borrowed technologies from private insurance corporations. It was not a coincidence that the rows of file cabinets in the Social Security offices so closely resembled those in the Metropolitan Life or New York Life towers. In the end, Roosevelt’s preferred model for old-age insurance depended on the U.S. government keeping track of each worker’s wages over the course of their entire life—an extraordinary data project.

7. The Inventory and the Arsenal

Page 202 · Location 3581 A Census Bureau press release announced the installation of a “huge battery of mechanical robots which will tabulate the returns of the 1940 census.”

Page 203 · Location 3600 This enthusiasm for the most up-to-date calculating capacity would make the Census Bureau the first civilian purchaser of an electronic

Page 203 · Location 3601 computer (the room-size UNIVAC), which it used to process the 1950 census.

Page 204 · Location 3634 The captions never reference the (mainly women) workers who appear with the machines. The only nod to the labor of those workers comes through passive-voice constructions such as “Holes are punched” or “The electric machine tabulator is fed statistics.”

Page 206 · Location 3664 Black workers could get jobs only

Page 206 · Location 3664 as “card punchers” or census data “editors” (those who fixed errors in census sheets and prepared them to be punched into cards)—and on those lowest rungs of the ladder, nearly a thousand African Americans languished.

Page 206 · Location 3677 Although tabulating machine operators made more money and enjoyed greater prestige than punchers or editors, arguably the most important job in Census Building was done by hand. As each enumerator’s portfolio of work arrived in D.C., a clerk combed through each and every census sheet to make sure the right ones had been included, that all the right places had been enumerated, and that all the blank lines or lines filled in accidentally had been “canceled.”

Page 212 · Location 3780 The bureau’s staff received a request with a person’s name (and, ideally, at least a rough address) and consulted a special index, called a “Soundex” because it was organized phonetically. The

Page 212 · Location 3782 Soundex had been a Depression-era WPA project and seemed like it would come in handy with the advent of Social Security and other retirement programs. 45 No one realized just how essential the Soundex would become.

Page 217 · Location 3887 The Government Printing Office (GPO) had other priorities, war work got first dibs, and when paper and presses became available, they cost much more to operate in wartime.

8. The Data’s Depths

Page 234 · Location 4138 Democracy in the completed census sheets looks diverse and unruly.

Page 238 · Location 4219 And the more we read data, the more we play in the muck from which all good data is made, the more resilient we will be to looking squarely at complicated data-making processes, to seeing them clearly without shrinking away or overreacting. And looking squarely at complicated data-making processes is becoming an essential activity for all those who wish to have a say in

Page 238 · Location 4222 shaping our world, from activists to policy makers, and for every person striving to remain an informed citizen.

Page 238 · Location 4223 The exuberant embrace in recent days of Big Data and new analytical tools like machine learning too often point in a different direction. The cry of the innovator is, Don’t worry about where the data came from, just mine it algorithmically for potent predictions. This book has made clear how foolish, even dangerous, a cry like that is.

Page 238 · Location 4225 We need more investigations into data histories, not fewer, and more people willing and able to read the stories behind the numbers.


Page 277 · Location 4937 This debate misunderstands data by missing out on its depth. It focuses on just the numbers at the expense of the processes and systems and people behind them.

Page 277 · Location 4938 The fact is that every data set has a doorstep, a place where plans and dreams of order meet the throbbing tumult of experience, and from such encounters, via eruptions of ingenuity, we get these strange texts that bear the label “data.” They are texts with power in the world, texts that indeed should be treated carefully,

Page 277 · Location 4941 debated in public, and sometimes

Page 277 · Location 4941 regulated by governments. They are texts, too, that we can use to better understand ourselves, our political systems, and our societies. We just have to learn how to read them.