CHAPTER SEVEN

Darwin’s Cousins

IN 1894, when the playwright George Bernard Shaw (1856–1950) needed to invent a character that captured the challenges faced by the young women of his age, he made her a mathematician. Vivian Warren, the central character of the play Mrs. Warren’s Profession, is a graduate of Newnham College, a women’s school at Cambridge. Such colleges were still new in the 1890s and were trying to find their way amidst the older and wealthier men’s schools. One measure of success for the women’s schools was the scores of their students on the Tripos, the Cambridge mathematical honors exam. In 1890, a Newnham student had drawn national attention by besting all of her male peers and achieving the top score on the Tripos, an achievement that would have made her First Wrangler but for her gender.¹ In Mrs. Warren’s Profession, Shaw has the fictional Vivian Warren achieve the third-highest score on the exam, a detail that was probably added in consideration of Shaw’s friend, the mathematician Karl Pearson (1857–1936). When Pearson was a student at Cambridge, he had been the Third Wrangler in the Tripos.² As a friendly jab at Pearson, who was somewhat sensitive about the fact that he did not get the top score on the exam, Shaw has Warren confess that she took the Tripos exam only because her mother agreed to pay her fifty pounds “to try for fourth wrangler or thereabouts.” Even though she bested her goal, Warren concludes that the Tripos “doesn’t pay. I wouldn’t do it again for the same money.”³

In Mrs. Warren’s Profession, Vivian Warren is identified as an actuary, but she does the work of a human computer. She describes her work as “calculations for engineers, electricians, insurance companies, and so on.” In one speech, she talks about how much she enjoys working in an actuarial office in the city of London. Her days are spent in calculations. “In the evenings we smoked and talked, and never dreamt of going out except for exercise. And I never enjoyed myself more in my life.”⁴

The play opens with the trappings of a domestic comedy: a young woman, a young man, a country house, a wise friend, and a mother, the Mrs. Warren of the title. As the plot unfolds, we learn that Mrs. Warren is not simply a wealthy landowner but also a former prostitute and the manager of a brothel. As Vivian Warren learns her mother’s story, she systematically rejects the other characters of the play and retreats into mathematics, as if it is the only thing that is pure and untainted. Her suitor is the easiest thing to reject, as he proves to be her half brother. She also declines a marriage with the brothel’s financier, rejects the conventional advice of the wise friend, and firmly expels her mother from her life.⁵

Like Vivian Warren, the new computers of the 1890s were college graduates, though none left a record quite so dramatic as the one described in Shaw’s play. Many were graduates of the new women’s colleges: Newnham and Girton at Cambridge, Bedford in London, Radcliffe and Bryn Mawr in the United States. Most of these colleges had been formed in the late 1870s or early 1880s. Though only a small fraction of their students studied science, the numbers were growing, as were the expectations that the graduates would find useful work. “If it had been wasteful in the 1870s for women to sit idly home,” wrote the historian Margaret Rossiter, “it was much more intolerable for college graduates to lack useful and respectable work.” Rossiter notes that women moved quickly into laboratories but that they were “introduced in ways that divided the ever-expanding labor but withheld most of the ever precious recognition.”⁶ For the women of the 1890s, the social and biological sciences offered new opportunities for employment. These fields were incorporating new methods of statistical analysis, methods that required not only the traditional measuring of samples and tabulating of data, but also the more sophisticated calculations of the new mathematical statistics.

The advance of statistical analysis was closely tied to Charles Darwin’s theory of evolution in much the same way that astronomical calculations were linked to Newton’s fundamental laws of motion. Darwin’s theory suggested that biological organizations were shaped by the force of natural selection, that natural selection was still operating in the nineteenth century, and that the effects of natural selection might be measured in both animals and people. If it could be measured, it might provide an explanation for a host of biological and social phenomena, just as Newton’s theory of gravitation provided an explanation for Halley’s comet. Darwin claimed that evolution could explain the size and shape of animals. His followers speculated that evolution might explain differences in intelligence, behavior, and even social standing. “Those whom we called brutes,” quipped George Bernard Shaw, “had their revenge when Darwin shewed us that they are our cousins.”⁷

One of Darwin’s human cousins, Francis Galton (1822–1911), worked to find a mathematical way of verifying the presence of natural selection. Galton has been portrayed as “a romantic figure in the history of statistics, perhaps the last of the gentlemen scientists,”⁸ a characterization that describes his family background and captures the unorganized nature of the science he pursued. His father was a wealthy Birmingham banker, and his mother was the daughter of a wealthy physician and the aunt of Charles Darwin. He had enrolled in Cambridge with the intent of taking the Tripos and pursuing a career in mathematics. The strain of study broke his health and forced him to temporarily withdraw from school. “It would have been madness to continue the kind of studious life that I had been leading,”⁹ he concluded. After a year of rest, he returned to Cambridge and completed an ordinary degree, without taking the Tripos and without honors.¹⁰

Without an honors degree, it would have been difficult for Galton to find an academic appointment. Like Charles Babbage, Galton had inherited a substantial fortune, and again like Babbage, he used his funds to finance his interest in science. He spent several years traveling through the Middle East and recording his observations of the land and its inhabitants. At times, his travels seemed to be more a rite of passage for a wealthy young man than a genuine scientific expedition. The historian Daniel Kelves reported that Galton sailed down the Nile River “lazing the days away half dressed and barefoot.”¹¹ The trip was not entirely an adventure, for Galton brought a modicum of rigor to his work. Writing his brother from East Africa, he reported, “I have been working hard to make a good map of the country and am quite pleased with my success. I can now calculate upon getting the latitude of any place, on a clear night to three hundred yards.”¹² He did not suggest that he had mastered the more difficult calculation of longitude.

In his records of the trip, Galton shows that his ideas on quantification were crude and often uncertain. In one episode, often retold, his work could have been lifted directly from Jonathan Swift’s description of Laputa. In East Africa, Galton reported to his brother that he had found a community in which the women “are really endowed with that shape which European milliners so vainly attempt to imitate,” adding that they had “figures that would drive the females of our native land desperate—figures that afford to scoff at Crinoline.” To quantify the shape of these women, Galton had measured the dimensions of their bodies as the Laputan tailor had measured Gulliver. “I sat at a distance with my sextant, and as the ladies turned themselves about, as women always do to be admired, I surveyed them in every way.” Once he had recorded the angles, he “subsequently measured the distance of the spot where they stood—worked out and tabulated the results at my leisure.”¹³ If Francis Galton had moved in literary circles and had been as familiar with Charles Dickens as he was with Charles Darwin, this letter might be considered a joke, a satire on scientific practice, a sly way of telling his brother that he had spent the day studying half-naked women with a telescope.¹⁴

Upon his return to England, Galton found a position at the Kew Observatory, a government-funded weather research station. He spent most of his time testing new meteorological instruments, but he found some time to consider problems that were suggested by the different sizes and shapes of the Africans.¹⁵ He tried to put his investigations in the context of Darwin’s theories and tried to derive mathematical methods that would verify the action of natural selection. At first, he attempted to find a way of measuring economic and social success across the generations of a single family. “As a statistical investigation, it was naive and flawed,” wrote historian Steven Stigler, “and Galton seems to have realized this.”¹⁶ In his second approach to this subject, he considered physical traits, such as those he had measured with his sextant in East Africa. The standard methods of statistics were largely confined to the tabulation of data and gave him no obvious way to approach the problem.

Galton was more comfortable with graphical techniques than with computations or formulas. In one problem, he used a graph to find a mathematical relationship between the heights of parents and the heights of their fully grown sons. His set of data included measurements on 928 people, 205 pairs of parents and 518 sons. His first step was to reduce the heights of the two parents to a single value, a value that he called the “mid-parent.” The mid-parent was an average of the values with a slight adjustment to place the mother’s height on the same scale as the father’s. Once he had computed the mid-parent value, he paired this value with the height of the son and created a graph. “I began with a sheet of paper, ruled crossways, with a scale across the top to refer to the statures of the sons,” he explained.¹⁷ The scale down the side referred to the mid-parents. For each pair of data, he drew a small pencil mark on the grid.

The final picture looked like an oval. Tall parents tended to have tall sons, and short parents seemed to produce short sons. He summarized that relationship by drawing a line from one of the narrow ends of the oval to the other, a line that split the oval in half. The slope of that line, when adjusted for scale, would be known as the correlation coefficient.¹⁸ A correlation value close to 1 indicated that the quantities would be highly related. A value close to zero indicated that they had no relation. Unsure of the underlying mathematics, he turned to a Cambridge mathematician, who confirmed the “various and laborious statistical conclusions with far more minuteness than I had dared to hope.”¹⁹ In confirming the work, the Cambridge mathematician could produce no simple formula for the correlation coefficient. The only way that Galton could compute a correlation was to draw the picture with its ovals and lines. That restriction did not seem to bother him, as Galton at first believed that he had solved a special problem with limited application. It took him about five years to appreciate that he had created a general method for studying any statistical data that shared the same mathematical properties as his height data. “Few intellectual pleasures are more keen,” he wrote, “than those enjoyed by a person who … suddenly perceives … that his results hold good in previously-unsuspected directions.” Still, he was embarrassed that he had not recognized the importance of his discovery and confessed fear that “I should be justly reproached for having overlooked it.”²⁰

Galton’s influence on organized computation began in December 1893, when he established the “Committee for Conducting Statistical Inquiries into the Measurable Characteristics of Plants and Animals.” This committee, which reported to the Royal Society, was a test of organized scientific research. It was a time of “trial and experiment,” wrote one observer. “The statistical calculus itself was not then even partially completed,” and “biometric computations were not reduced to routine methods.” The first work of the committee was to support the research of the biologist W. F. Raphael Weldon (1860–1906). Weldon had discovered the methods of Galton in the late 1880s and applied them to the study of shrimp and crabs. He “was on the look-out for a numerical measure of species,” wrote one biographer, and sought in his measurements evidence that one type of animal was evolving into two species. He was an energetic researcher and pushed the committee beyond its ability to support his work. None of the members could provide the mathematical advice he needed, though they did “ask for a grant of money to obtain materials and assistance in measurement and computation.”²¹

Through most of his early research, Weldon’s chief computer was his wife, Florence Tebb Weldon (1858–1936). Florence Weldon was one of the first college-educated human computers. She had graduated from Girton College at Cambridge, a companion to Newnham. By working for her husband, Florence Weldon received little recognition but probably found a substantial scope in her scientific work. She did the same tasks that her husband handled. The two of them spent their summers traveling around England and visiting Italy. Typically, they would collect about a thousand specimens, clean the animals, and measure them. In an early study, they took twenty-three measurements on each specimen. Wife and husband shared the labor of research, tabulated the results, and calculated averages, “doing all in duplicate.” They “were strenuous years in calculating,” recorded a friend. “The Brunsviga [calculator] was yet unknown to the youthful biometric school.” The Brunsviga, a favorite of English statisticians, was similar in design to the machine invented by Frank Baldwin in St. Louis. It was small and light and used sliding levers, rather than keys, to record data. Having no calculating machine of any kind, the Weldons “trusted for multiplication to logarithms and [the tables of] Crelle.”²²

Florence Weldon proved to be a greater help to her husband than Galton’s committee. “The committee did not possess a mathematician to put on the break,” claimed Shaw’s friend Karl Pearson, “and Weldon attempted too much in too short a time.” As W. F. Raphael Weldon began to publish his results, he was met by the same kind of hostility that had greeted the calculations of Halley and Clairaut. W. F. Raphael Weldon’s work was far from perfect, and his mathematical formulas did not always demonstrate the properties he had hoped to illustrate; but the response to his work was not in proportion to its flaws. “The very notion that the Darwinian theory might, after all, be capable of statistical demonstration seemed to excite all sorts and conditions of men to hostility,” observed Pearson. W. F. Raphael Weldon worked with the committee through the mid-1890s and then took a position at Oxford University.²³

The methods of organized statistical calculation, especially the calculation of correlation values, developed in the laboratory of Karl Pearson at the University of London. Pearson was a professor of mathematics, but he had broad interests that ranged from history and politics to religious faith and the relations between the sexes.²⁴ Born Carl Pearson, he was the son of a London attorney and the product of a traditional Cambridge mathematics education, including the third-place finish on the Tripos. As a young man, he had a crisis of faith that caused him to abandon conventional Christianity and embrace socialism. After two years of study in Germany he adopted the German spelling of his first name, Karl.²⁵ Pearson was a radical but not a bomb thrower. George Bernard Shaw described such people as Pearson as “unconventional in a conventional way.” “[He] was in many ways poorly socialized,” observed his biographer, Ted Porter, “a thoroughly original character who, while drawing deeply and repeatedly from the cultural resources of his time, rejected many of the conventions of his class and profession.”²⁶ Before turning his attention to statistical theory, he wrote books on the philosophy of science and organized a selection of his friends into a Men and Women’s Club. According to a historian of the club, “discussions ranged from sexual relations in Periclean Athens to the position of Buddhist nuns, to more contemporary discussions of the organization and regulation of sexuality, particularly in relation to marriage, prostitution, and friendship.” Pearson’s presentations were highly intellectual, often laced with Darwinian ideas, and were occasionally beyond the grasp of other club members.²⁷

Pearson’s influence over the practical issues of computation began in 1895, when the Royal Society added Pearson to the Committee for Conducting Statistical Inquiries into the Measurable Characteristics of Plants and Animals. Pearson was not particularly impressed by the organization of the group or its method of operation. He later recalled that “Weldon’s work was hampered by the committee” and suggested that the members had neither the inclination nor the ability to help him.²⁸ Pearson’s contribution to the group was a mathematical formula for correlation, a formula that turned correlation analyses from a lengthy graphical procedure requiring a certain judgment to a straightforward equation. This formula required the computers to summarize the data in five quantities. In Galton’s example, two of the quantities were computed from the children’s heights, two more came from the mid-parent heights, and the last was calculated from products of the two sets of data. A final computation of four multiplications, three subtractions, one square root extraction, and a long division produced the correlation value.²⁹

The formula for correlation became one of the first mathematical tools for a small computing group that Pearson formed at the University of London in an organization he would call the “Biometrics Laboratory.” “All the work of computing undertaken in my Department,” Pearson explained, “[was] entirely done by volunteer workers,” a group of computers that included students, friends, relatives, and his wife.³⁰ Though Pearson dominated the group, he liked to think that they were all collaborating as equals. The first large project of this group began in the summer of 1899. At “Hampden Farm House in the Chilterns,” he reported, “we had at our disposal a considerable strip of garden covered with Shirley poppies.” The poppies, with their distinctive seed pods, provided the basic material for a study of inheritance. Pearson recruited fifteen friends to help with the research, a collection of eight men and seven women that included the Weldons. Several of this group had been members of the Men and Women’s Club. Pearson treated this project as a socialistic endeavor, an effort in which all contributed equally. Though he was directing the work, he took his turn with the more mundane tasks, such as tending the plants, measuring specimens, and harvesting the seed.³¹

Pearson’s socialism did not prevent the summer from having an informal elegance, the air of a comfortable English country house during the last summer of Queen Victoria’s reign. The group would meet on Fridays, at what Pearson called the “biometric teas,” a term that invoked men with high collars, women in long dresses, and an attentive servant pouring tea and offering cucumber sandwiches. In the leisure of a long summer afternoon, they would review their progress, discuss new ideas, and make plans for the weekend. Pearson reported that “Saturday and Sunday … were given to calculation and reducing weekly work.”³² In this case, the term “reduction” meant not the processing of astronomical data but the calculation of the five basic terms for correlation analyses. The results of this experiment were published in a paper without an author, though a footnote acknowledged that Pearson had drafted the report. The paper listed the contributions of all sixteen workers, including the women. It also invited interested parties to join the research. “To any of our readers willing to assist in further observations on ‘first flower,’ the Editors will most gladly send seed of pedigree poppies with suggestions for further work.”³³

17. Karl Pearson with Brunsviga calculator

The cooperative spirit of Hampden Farm would quickly dissipate, but at least a few of the workers would have a long relationship with Karl Pearson and the Biometrics Lab. One of the summer workers, Alice Lee (1859–1939), became a student of Pearson’s. She held a bachelor’s degree from Bedford College, a women’s college at the University of London. She supported herself by teaching mathematics and physics at the college, occasionally covering Greek and Latin courses whenever there was a need. To supplement her income, she lived in the college rooms and oversaw the students. This assignment gave her little time to herself, but it paid for her room and board.³⁴

Initially, Lee worked as a volunteer in the Biometrics Lab. Her relationship to Pearson was awkward at best. At times she was his student and at times a staff member. Occasionally, he thought of her as a peer but never as an equal. Twice she declined to be listed as the coauthor of a paper with Pearson. She wrote Pearson, “I have done nothing but the Arithmetic, and I suppose a machine could do most of that.”³⁵ She may have been modest about her accomplishments or scrupulously honest in her dealings with Pearson, but she may also have suspected that indiscriminate credit might hurt her reputation as a scholar. If her name appeared on a paper for simply doing arithmetic, then other scientists could conclude that she was nothing more than a computer. She was attempting to establish a reputation in the field of craniometry, the measurement of skulls. The task is hard enough if the subject is dead but considerably more difficult if the object of measurement remains alive. She developed a statistical model that estimated the cranial volume of living subjects from external skull measurements. When she presented the results of her study, some faculty claimed that the work was a simple elaboration of Pearson’s ideas. Pearson intervened in the evaluation of her work, defended the merits of her approach before his colleagues, and argued that he had no claim to her results. Based upon his presentation, the faculty reconsidered the case and awarded the degree.³⁶

Pearson’s treatment of Alice Lee and his other computers vacillated between radical ideas and common stereotypes. He could defend the contributions of women to Francis Galton, writing that “their work is equal at the very least to that of the men. They are women who in many cases have taken higher academic honours than the men and are intellectually their peers.”³⁷ Yet in private he could express doubts about the quality of their work and was not always able to treat women as equals. He once complained of Lee, “I am here, as on other occasions, apt to be vexed by her want of power of expression.” Rather than blame her education or even her upbringing, he found the cause in her gender. “On the whole I think it is characteristic of most women’s work.”³⁸

Through 1903, Pearson had no regular source of funds to support the Biometrics Laboratory. “I live on students fees practically,” he wrote to a colleague, “and any step which leaves my department under incomplete supervision tends to impair its efficiency [and] affect my income.”³⁹ That year, he received a grant of £500 from a civic organization that had been established by the businessmen that manufactured and traded cloth, an organization known as the Worshipful Company of Drapers.⁴⁰ The funds brought some measure of order to the laboratory and a salary to Alice Lee. She received £90 a year, about half the salary given to an assistant professor. For this money, she worked three days a week, arriving at 9:30 AM and leaving at 5:00 PM. Pearson allowed her half an hour for lunch, which was presumably taken at her desk or, when the weather allowed, in the courtyard of the school. Her duties included reducing data, computing correlation coefficients, creating bar charts—charts that Pearson was now calling “histograms”—and calculating a new kind of statistic, which Pearson had denoted χ² (usually pronounced chi-squared). The χ² statistic promised to be just as important as the correlation statistic. It allowed researchers to test scientific theories in a formal, mathematical way.⁴¹

In addition to her computational work, Lee did “all the hundred and one things that need doing here.” She acted “more or less” as the laboratory secretary, excerpted books in the library, formed indexes, and organized catalogs of data. By the standards of office work, the job was not well paid, a fact that slightly embarrassed Pearson. A young female typist or stenographer was usually able to feed a mother or a child on an office worker’s salary. He confessed, “It is a post well suited to a woman living with her family in London and keen on scientific work.”⁴² Even with all of this clerical work, Lee continued to pursue her own research projects, which led to four papers published in her own name and contributions to twenty-six others.

The Draper grant allowed Pearson to hire the sisters Cave-Browne-Cave as part-time computers. Beatrice and Frances Cave-Browne-Cave were the daughters of a senior civil servant and graduates of Girton College. They met both Pearson and Francis Galton at a “reading party,” a meeting that was probably a public discussion of natural inheritance or statistical methods.⁴³ The elder, Beatrice Cave-Browne-Cave (1874–1947), taught mathematics in a girls’ school located in south London. She worked as a part-time employee of the Biometrics Lab, doing calculations in her home. Before the Draper grant gave her a small stipend, she did Pearson’s calculations without compensation. The only reward she received was to be listed as a joint author on two papers, one published jointly with Pearson, the other as a collaborative effort of five authors.⁴⁴

The younger sister, Frances Cave-Browne-Cave (1876–1965), remained at Girton College as a teacher. She had been the top student in her class and had tied the Fifth Wrangler in the Cambridge Tripos exam.⁴⁵ Like Alice Lee, she had a research program of her own. She was performing a correlation analysis of weather data that had been collected from the east and west sides of the Atlantic Ocean. Pearson guided the work and outlined the basic mathematics but let Cave-Browne-Cave work at her own pace. She was a popular teacher at Girton and enjoyed socializing with the young women at the college. She devoted many of her evenings to her students, talking with them and helping them with their studies.⁴⁶ Only on those rare occasions when she was left alone in her room did she find time for her research. “The magnitude of the computations,” she recorded, “almost precluded the idea that any individual worker or workers can hope to complete such a task within a reasonable period.”⁴⁷ The project required her to calculate hundreds of correlations with Pearson’s formula. Even though she worked on her own, she was able to complete two substantial projects that demonstrated patterns in the weather as it moved across the ocean.⁴⁸

Even with the Draper grant, Pearson’s largest projects retained the collaborative aspects of the Hampden Farm experiment. In 1903, he oversaw a large study of child development, “a cooperative investigation extending over a number of years, and depending upon a body of collaborators.” The project collected physical measurements and character assessments from 4,000 children and their parents in order to establish evidence of the inheritance of what Pearson called “moral qualities,” attributes that we would now identify as aspects of intelligence or personality. Both sisters Cave-Browne-Cave were among the six collaborators who worked on the project. Unlike the Hampden Farm experiment, this project seemed firmly in the control of Pearson. He was the one setting the scale of the project and posing the questions to answer. His collaborators gathered the data by measuring and observing the children. Beatrice Cave-Browne-Cave collected data from her high school students. Only a few of the assistants, including both Frances and Beatrice Cave-Browne-Cave, processed the data, created tables, and computed the correlations.⁴⁹

In 1904, the Worshipful Company of Drapers pledged an annual grant to the Biometrics Laboratory, giving Pearson a measure of financial security.⁵⁰ With this money, the laboratory slowly lost its collaborative feel and acquired the more conventional feel of a university office. The lab workers split into three distinct strata: professors, students, and staff. Most of the staff worked as computers, and most, though not all, of the computers were women. These women occupied an isolated corner of academic life. They tended to interact either with Pearson or with other women. Lee taught women at Bedford; Frances Cave-Browne-Cave was a professor to women at Girton; her sister Beatrice worked at a girls’ high school. Their experience was not that different from the life of other female computers. At Harvard, the observatory computing staff had been augmented by women who measured photographs and conducted research of their own. Most of these women were aware that their positions were quite different from those of the men. “I have to see to all the changes of household linen, etc. and gather together the family wash,” wrote a member of the Harvard Observatory staff. “Alas! How matter of fact and different from the Sunday morning duties of other officers of the University.”⁵¹

The increasing stratification of labor in the 1890s made the computing laboratories vulnerable to the labor troubles of the age, though none of them faced anything as severe as the strike at the Homestead steel mill in Pennsylvania or the riots in Chicago’s Haymarket Square. The most dramatic incident occurred when the Greenwich Observatory was bombed by a French anarchist. The explosion shook the building, though it left the structure undamaged and the computing staff untouched.⁵² Investigators looked for a motivation for the explosion among the observatory employees and found only minor complaints. Among the human computers, the most pressing concern was the policy, established by George Airy, of dismissing any computer once he or she reached the age of twenty-three. “The mathematics and kindred subjects which have been acquired [at the observatory] become absolutely useless,” complained one former computer, “as men are not wanted in the market unless having had a good business experience. So they swell the already overcrowded unskilled labour multitude. This rotten system seems to be maintained by the Government solely to save money.”⁵³ Investigators found it difficult to connect such sentiments to the group that prepared the bomb. They eventually concluded that the explosion was detonated accidentally and that the observatory was probably not the target. The writer Joseph Conrad fictionalized the incident in his novel The Secret Agent. He suggested that the bomber was targeting the institutions of capitalism and the British government, not the observatory itself.⁵⁴ In the story, the bomb was thrown “into pure mathematics,” and it had “all the shocking senselessness of gratuitous blasphemy.”⁵⁵

Most of the labor problems among computers were the ordinary conflicts between labor and management and hence were more irritating than dramatic. At the American Nautical Almanac, the “gentlemen of liberal education” had been replaced long ago by computers drawn from the civil service rolls. Computers had to pass a special exam to gain a place on the almanac staff. This exam was difficult, and it regularly failed to identify enough qualified applicants to fill the vacancies in the computing room.⁵⁶ The director of the almanac office was Simon Newcomb (1835–1909), who had begun his career as a computer under the direction of Charles Henry Davis. Through his work at the almanac, he had achieved a certain measure of fame and was probably the best-known American scientist of his day. He had a conservative nature and had little sympathy for the complaints of workers, labor movements, and strikers. When he was asked his opinion on the growing use of machines in manufacture and their impact upon workers, he replied that “the laboring man is earning higher wages now than he did … before the introduction of labor saving machinery.” He watched the labor unrest of the 1890s with a sense of alarm and concern. He placed the blame for such discontent directly on the workers. “Too many men will not do more than they are compelled to do,” he said; “they do not work cheerfully and become malcontents ready to destroy.”⁵⁷

For the most part, Newcomb’s computers were German immigrants from Foggy Bottom, the working-class neighborhood of Washington that served as a home to the almanac office. His most promising computer was a Swiss-German named John Meier. Meier “was the most perfect example of a mathematical machine that I ever had at my command,” Newcomb reported. Meier was hardworking and skilled at arithmetic. Newcomb also observed that, “Happily for his peace of mind, he was totally devoid of worldly ambition.” Meier lived the turbulent life of urban working classes and regularly needed Newcomb’s assistance “as an arbitrator of family dissensions.”⁵⁸ Meier suffered from an illness that he called “nervosity.” Newcomb gave no name to the disease, though he clearly believed it to be alcoholism. Meier, who had been able to limit the problems caused by his “nervosity,” began to lose control of his life when his wife left him. His children, a boy and a girl, proved more than he could handle alone. His son, testy and combative, showed that he was more than ready to pick fights with his father. The daughter, seventeen years old, had no one who could discipline her and was often found “in company with young men.”⁵⁹ Newcomb avoided intervening in the failing marriage, but he advised Meier’s son, counseled the daughter, and sought support from the family’s pastor, the minister of the neighborhood German church. After several months, Newcomb tired of the demands upon his time and concluded that Meier simply was not capable of working for the almanac. He relieved Meier from service and requested the return of all books belonging to the almanac office. Using the popular notions of inheritance to justify his actions, he wrote that Meier “illustrates the maxim that ‘blood will tell’” and then added, “which I fear is as true in scientific work as in any other field of human activity.”⁶⁰

Newcomb faced a second labor conflict that was resolved only after a hearing by the secretary of the navy. In this incident, Newcomb accused a senior staff member of being “incapacitated for effective work,” a phrase that probably implied that the worker arrived at the office drunk, and of taking “one week to do what a skilled computer should do in one or two days.” The staff member defended himself by claiming that Newcomb had showed favoritism to incompetent computers, that he was only concerned with “advancing his personal reputation,” and that he had “diverted practically three-fourths of the appropriation made for the support of the Almanac Office for years past to a purpose for which it was not intended.”⁶¹ The hearing was reported in embarrassing detail by the local papers, but the issue was ultimately resolved in Newcomb’s favor.⁶² However, the departure of the troublesome employee provoked the secretary of the navy to impose a little more control over almanac operations. “To avoid further trouble,” he wrote, he would “remove the almanac office from the Navy Department Building to the Naval Observatory, where it naturally belongs.”⁶³

18. Simon Newcomb

Simon Newcomb was an astronomer, but like Pearson, he had a wide range of interests. He met Pearson during a trip to Europe in 1899.⁶⁴ There was probably no way the two could have been friends, as their political values seemed to have little in common. Pearson, who was just starting the Hampden Farm experiments, seems to have treated Newcomb with respect, but there is no evidence that the two men corresponded after Newcomb’s visit. The two came into contact again only after four years had passed and Newcomb had become the director of the Congresses that were planned for the 1904 World’s Fair in St. Louis. Newcomb wrote to Pearson and asked if he would come to the United States to discuss the methods of statistics at one of the Congresses. Pearson had no interest in such an event and brusquely declined, stating that “I see no possibility of my being able to afford a visit to America from either standpoint of time or money”⁶⁵

By then, Newcomb had retired from the Nautical Almanac Office and had turned to promoting the use of mathematics in “other branches of science than astronomy,” especially in the “examinations and discussions of social phenomena.”⁶⁶ As this concept seemed to be related to the goals of Pearson, Newcomb wrote to the English statistician and asked him to help found an “Institute for the Exact Sciences.” “The nineteenth century has been industriously piling up a vast mass of astronomical, meteorological, magnetical, and sociological observations and data,” he explained to Pearson. “This accumulation is going on without end, and at great expense, in every civilized country.” His proposed institute would collect and process this data. One division of the organization would concentrate on data from experiments. A second group would assemble data that had been collected by observing social phenomena. The third division of the institute would be a large computing laboratory. The computers would process the data gathered by the other two divisions and would develop new mathematical methods that could be applied “to the great mass of existing observations.”⁶⁷

The new institute would be expensive to organize and to operate, but Newcomb believed that he could find funds at the Carnegie Institution of Washington, a philanthropy founded by U.S. Steel president Andrew Carnegie (1835–1919). As it operated in 1904, the Carnegie Institution was a granting agency that provided small amounts of money to researchers scattered across the country. Newcomb believed that this strategy was misguided. “We find that centralization is the rule of the day in every department of human activity,” he argued. “Two men anywhere will do more when working together than they will when working singly.”⁶⁸ He argued that a transformed Carnegie Institution, one that followed his model for an institute of exact sciences, would make better use of Carnegie’s money and would be “in the true spirit and intent of its founder.”⁶⁹

Pearson showed no enthusiasm for Newcomb’s plan. Unlike Newcomb, who had spent all of his career working for a military agency, Pearson knew what it was like to ask for research funds with cap in hand and suspected that it would be difficult to extract money from the Carnegie Institution and nearly impossible to transform the organization, as Newcomb envisioned. He also may have felt threatened by the proposed organization, as the proposed Institute for the Exact Sciences would do work similar to that done at the Biometrics Laboratory. Newcomb was not easily dissuaded by Pearson’s objections, and he pushed the statistician to support the idea.⁷⁰ It was a simple plan, he told Pearson, and it was important to avoid “thinking that I have in view something more comprehensive than I really have.”⁷¹ However, Pearson would not be moved and replied through a secretary that “Professor Karl Pearson is very much obliged for your letter re: Carnegie Institution proposals. He still considers the matter extremely difficult of execution.”⁷²

By 1906, Pearson’s Biometrics Laboratory could handle most of the tasks that Newcomb outlined for his Institute for the Exact Sciences. To be sure, it was smaller than Newcomb’s proposed institute, and its mathematical methods had taken a circuitous route from the observatory and almanac before they reached the problems of evolution and human behavior. With each passing year, the computing staff was gaining skill and experience with different forms of calculation. By 1906, Pearson could report that the group had mastered the art of mathematical table making. He had set his staff to work evaluating the functions that described the average behavior of random quantities. A typical function was the bell curve, sometimes called the normal curve. This curve described how certain quantities, such as the heights of people or the width of a crab’s body, clustered around a central average value. Statisticians need to know the area underneath the bell curve, a value that is tedious and time-consuming to compute. Pearson had his computers tabulate these values as a service to the general scientific community. “It is needless to say that no anticipation of profit was ever made,” wrote Pearson; the computers “worked for the sake of science, and the aim was to provide what was possible at the lowest rate we could.” When he published a book of these tables, he apologized for having to set a price on the work but claimed “That to pay its way with our existing public, double or treble the present price would not have availed.”⁷³

The statistical tables were only a small part of the computations at the Biometrics Laboratory. The bulk of the computations summarized large sets of data and were difficult to undertake without an adding machine or other calculating device. Indeed, Pearson often referred to the work of calculation as “cranking a Brunsviga,” a phrase that understated the role of computation at the Biometrics Laboratory. Through the first decades of the twentieth century, every member of the laboratory undertook at least a little calculation each day. In 1908, one visitor complained “that preoccupation with mastery of details of calculation and technique obscured, to some extent, the full meaning and scope of the new science.”⁷⁴

This new science, the science of mathematical statistics, offered a new way of studying a vast range of human problems, including those found in medicine, anthropology, economics, sociology, and even psychology, a field that was not quite separated from the discipline of philosophy. However, in the first decade of the twentieth century, Pearson’s new science was still linked, at least partially, to the study of human inheritance, a field that had acquired the name of eugenics. Francis Galton had been an early proponent of eugenics and had established a laboratory that collected family trees and looked for patterns of human inheritance. In his eighty-eighth year, Galton proposed to donate his laboratory and his fortune to University College London. The money would be used to support a professor of eugenics, a position that was given to Karl Pearson. Pearson’s interest in eugenics is well documented and has been the subject of several scholarly studies. “When it came to biometry, eugenics, and statistics,” wrote historian Daniel Kevles, “[Pearson] was the besieged defender of an emotionally charged faith.”⁷⁵ Grateful for the financial support, Pearson accepted the position, which put him in charge of two laboratories. “There is undoubtedly work enough for two professors,” he wrote, “but it is an ideal of a distant future.”⁷⁶