Lawrence Goldman's Victorians and Numbers: Statistics and Society in Nineteenth Century Britain will surely not be the last word on the subject—or so one hopes, of course—but this remarkable book provides by far the best and most expansive intellectual history of Victorian statistics to date, simultaneously revitalizing well-trodden ground while recovering a host of neglected figures, moments, and institutions. The story that Goldman tells is framed by two key developments and is assembled over the course of sixteen chapters organized into five parts, along with a prologue and an introduction. The first of these two developments is the “avalanche of printed numbers,” as Ian Hacking once put it (“Biopower and the Avalanche of Printed Numbers,” Humanities in Society, no. 5 [1982]: 279–95), that began to fall in the 1820s and 1830s and the work of a variety of private statistical associations, individual pioneers, and enthusiasts, and number-crunching government offices such as the Board of Trade and the General Register Office established in 1837 (parts one to three). The second is the advent of mathematical statistics from the 1880s and the refinement, led initially by Francis Galton and later by Karl Pearson, of a new set of statistical tools such as correlation and regression analysis, coupled with a more precise sense of the inferential possibilities and problems afforded by large data sets (part five).

Both of these developments are well known, and by and large Goldman leaves intact their chronology. What he does, however—and does so meticulously—is to rethink their nature and significance, and of all that emerged in between (part four). Put crudely, the argument made by Goldman works in two directions in this respect. On the one hand, he argues that the statistical movement of the 1830s–1870s was animated by a broadly liberal ethos of reform, which was environmentalist, ambitious, internationalist, and critical, if not structurally so, of urbanization and industrialization. One of the striking discoveries, first articulated with any force by Adolphe Quetelet, the Belgian social physicist (a contemporary term), in the 1830s, was the existence of statistical regularities relating to crime, marriage, and suicide (chapter 7). As Goldman argues, although for some this raised troubling questions about the nature of free will, for the leading statisticians of the time it was an invitation to wide-ranging reform: change the underlying conditions (or causes) and you thereby change the outcomes (or effects) (xxiv, 146–48). New vistas of reform were opened up, fueling optimism about the possibilities of evidence-based statecraft and premised on a sense that ultimately all humans could be improved, regardless of class or race. These liberal ideals were embodied not just in the growing interventionism of the British state at the time (as in the fields of public health and education), but above all in the staging of a series of mid-century international statistical congresses—the 1860 Congress took place in London—where the science of statistics was promoted with a near-religious enthusiasm: as the key to unlocking progress on a global scale.

Goldman's argument, however, also works in the other direction, in the sense that he argues that this broadly liberal amalgam of statistical fervor, humanitarian concern, and administrative zeal was composed of intellectual ingredients decidedly more eclectic and idiosyncratic than hitherto acknowledged. It is this aspect of the book that will be of most interest to those already familiar with the subject. Goldman puts back into the picture a number of individuals, groups, moments and texts that have been either obscured or overlooked entirely in the existing literature. The elite London (later Royal) and Manchester statistical societies are given due consideration, but so, too, is the short-lived working-class statistical association, the first so-called London Statistical Society, formed in 1825, led by the metropolitan radical John Powell (chapter 4). Quetelet is rightly accorded significance, but Goldman also gives attention to the ambitions and influence of the great German polymath Alexander von Humboldt (chapter 8). The inventive brilliance of Charles Babbage and Ada Lovelace is added to the mix, along with the fabled numerical fetishism of Prince Albert and Florence Nightingale (chapter 5). Goldman analyzes the work of William Farr, head of statistics at the General Register Office, but he considers it alongside the statistical labors of William Guy and John Simon (chapter 12). One might go on. The point for Goldman is that the liberalism of the Victorian statistical movement was a highly peculiar, contingent formation, made of diverse currents of reformist and scientific aspiration.

In execution and argument Victorians and Numbers recalls Goldman's earlier work on the National Association for the Promotion of Social Science (Science, Reform, and Politics in Victorian Britain: The Social Science Association, 1857–1886 [2002]). Both accounts are based on the same forensic attention to the printed and archival sources of key players among the governing and intellectual elites. But the stakes here are different, given the way the history of Victorian statistics has developed in recent decades and the influence of skeptical Foucauldian scholarship that has stressed the disciplinary ambitions of the urge to count and classify. Goldman's account, by contrast, is self-consciously more open. As he argues in the conclusion, statistics are not inherently ideological and lend themselves to various uses, depending on institutional context and the way that they intersect with all sorts of shifting intellectual, political, and social assumptions (316–20). The observation is surely correct, but it also brings into relief one of the few omissions of the book: Goldman's failure to probe more deeply into the ways that statistics were employed at mid-century by those organizations and individuals beyond the liberal elites and how they were appropriated in public debate by pressure groups, say, or put to work by lowly government officials. At the very least, this would have expanded the scope of the “Victorians” referred to in the title.

In the end, this liberal formation began to fall apart in the 1870s and 1880s, when Galton and more mathematically able statisticians entered the fray, bringing with them the eugenic assumption that (biological) nature was more important than (socio-environmental) nurture. Those of liberal sympathies were no longer at the cutting edge of the discipline, or in charge of what it meant. Yet, as Goldman stresses, eugenics never gained any administrative sway in Britain, unlike in the United States and Germany; more crucially still, statistics were put to work like never before in excavating socioeconomic questions (such as income inequality and labor relations) that had previously received only residual attention (chapter 15). The era of liberal statistics was over. Class and race were now firmly on the agenda. An account of what followed, in the late nineteenth and early twentieth centuries, that comes even close to matching the scale, sophistication, and richness of Goldman's would be hugely welcome.