Quantification In History Research Paper

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‘Quantification’ refers to a specific method of historical research that departs from the prevalent practice of textual analysis by actually seeking to measure changes in the past. Due to the mass of data to be handled and the complexity of the calculations involved, the application of quantitative methods usually has to be computer-assisted. In contrast to a mere illustration of certain tendencies by tables or graphs, quantification tends to use analytical statistics in order to probe relationships between certain variables. Such statistical analysis also requires a high degree of formalization in the research design that formulates hypotheses to be tested and tries to combine them into models. The final aim of the quantitative approach is not just to explain a particular set of developments but to make a theoretical contribution to some facet of historical understanding.

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1. The Rise Of Quantification

Within historical research, the development of quantitative methods was a product of a particular constellation during the 1960s. Already during the Enlightenment some scholars had sought to describe socioeconomic developments by compiling time-series, and by the middle of the nineteenth century national governments took on the task of determining population trends through a series of censuses. But it took the shift to the ‘new social history’ a century later to direct historical interests away from affairs of state to mass politics, societal changes, demographic transformations, or economic growth. At the same time the arrival of mainframe computers, followed eventually by powerful PCs, made it possible to handle large amounts of data and to use complicated statistical procedures in customized form via statistical packages such as SPSS or SAS. In order to explore these exciting new subjects with novel techniques, historians became interested in the theoretical constructs of the social sciences, borrowing eclectically from political science, sociology, or demography and somewhat less so from economics. The result of this interaction was the rapid development of a new hybrid, combining elements of historical research with social scientific analysis.

During the 1970s, this ‘social science history’ or ‘historical social science’ was successfully institutionalized. In the United States the multitude of initiatives in history and the neighboring disciplines combined in founding the Social Science History Association in 1975, and made its annual meeting a showcase of the most innovative work. In France many of the long-term community studies, produced by the Annales School, turned quantitative, compiling detailed time-series of population, prices, or wages and probing their inter-relationship. In Germany, the quantifiers linked with the theory-oriented project of a Historische Sozialwissenschaft to create a vigorous organization, called QUANTUM. Within the decade, a spate of new journals emerged to provide publication outlets for the new work, such as the Journal of Social History, Journal of Interdisciplinary History, Historical Methods Newsletter, Social Science History, Histoire et Mesure, and Historical Social Research. New Textbooks (Dollar and Jensen 1971, Floud 1979) as well as influential anthologies (Aydelotte et al. 1972, Lorwin and Price 1972) provided a powerful platform for the propagation of quantitative research.




2. Research Contributions

The first field transformed by quantitatively-oriented work was the new political history that differed from its predecessor by its attention to collective phenomena (Bogue 1983). For instance, Michael Kater investigated the rise of the Nazi movement in Germany by analyzing its membership files, indicating precisely which social stratum, religious group, gender, region, etc. joined the bandwagon at what time. For democratic societies like the US, Lee Benson’s or Alan Bogue’s analysis of electoral behavior proved quite productive, since comparing returns over time made it possible to establish which polls were the ‘critical elections’ when party realignments were transformed by ‘ethno-cultural’ or other factors. For parliaments without party discipline, Thomas B. Alexander’s rollcall analysis also offered a powerful instrument for establishing who actually voted with whom, indicating what networks dominated legislative behavior. This retro-projection of political science methods gradually provided a firmer empirical basis for an analysis of the transformation of mass politics in the last two centuries.

The second area that was deeply affected by quantitative methods and conceptual borrowing from sociology was the new social history (Stearns 1985). As ‘history from the bottom up,’ this perspective examined previously untouched serial records, such as police files, employment registers, or draft books in order to infer from the behavior of ordinary people what they might have felt and thought. The appeal of this effort was the diffusion of its topics, since the labor history of the Tillys included subjects as different as proletarian living conditions and their collective efforts at protesting through strikes. Another question, treated e.g., by Hartmut Kaelble concerned the pattern of social mobility, comparing the relative openness of societies to upward or downward movement over time or across borders. A related issue was the societal impact of education that required an analysis of the enrollment and composition of schools or universities in order to get at changes in educational opportunities. These quantitative probes produced much new and sometimes conflicting information about the lower orders, the make-up of institutions, and basic trends in societal transformations.

A third area propelled by computer-assisted source collection and statistical analysis was the field of historical demography (Hareven and Vinovskis 1978). For time-periods before national censuses, the demographers faced the challenge of reaggregating vital statistics from the ground up by converting parish registers into reliable measures of natality, nuptiality, or mortality. Under the direction of Anthony Wrigley the Cambridge population project established the outlines of a population history for England, while the demography center in Umea undertook a national project of quantifying church records so as to explain demographic changes in Sweden. American demographers like John Demos and Tamara Hareven instead combined individual life-event data to scrutinize the development of family structures from extended via stem to nuclear families and the like. Other scholars such as Roderick Floud and Richard Steckel studied changes in the height of military recruits or slaves in order to develop more accurate measures of social deprivation. This historical demography amassed a source base for the prestatistical area and produced interesting interpretative concepts for explaining the population transition.

The final area in which quantification transformed research priorities and methods was the new economic history (Davis and Engerman 1987). Redirecting attention away from entrepreneurship, ‘cliometrics’ as it was also called, inspired efforts to establish indicators of national production and income for the prestatistical age as well as to transform information from manuscript censuses into published form. In the US, a heated debate revolved around the profitability of slavery, with Robert Fogel’s and Stanley Engerman’s claims producing much controversy, due to their combination of economic and moral argumentation. Much attention also focused on the key factors of economic development, such as railroads, with some scholars actually arguing that their impact had been exaggerated. In Europe discussions revolved around the pattern of industrialization instead, with some specialists like Sidney Pollard proposing a more complex regional diffusion model. On the whole, the quantitative impulse made economic history more rigorous and theoretical, but removed it at the same time further from the mainstream of historical debate.

By the 1980s these signal contributions had managed to overcome traditionalist skepticism and to establish quantification as a new and growing subfield within the historical discipline. Though they were sometimes difficult to read for laymen, high-quality monographs convinced reluctant granting agencies to fund major collective initiatives, such as the Philadelphia Social History Project, directed by Theodore Hershberg. The number of articles with graphs and tables in respected historical journals began to reach almost one-quarter (Kousser 1989). Opinion surveys of the profession suggested that most scholars expected quantification to be here to stay. Even if some critics still bemoaned the spottiness of graduate training in this area, the rapid rise of quantitative methods in historical research had been impressive and their future prospects seemed secure.

3. The Culturalist Challenge

During the decade of the 1980s, however, the seemingly unstoppable progress of the quantitative history ‘project’ began to stall. By the middle of the decade, the number of quantitative journal articles and the frequency of graduate courses in quantitative techniques suddenly began to drop (Reynolds 1998). It seems that over the past 10 years ( plus or minus five!) quantitative history has become increasingly marginalized, since a variety of other methods have risen to prominence, making so-called ‘quants’ seem rather quaint. Ironically, the demise of quantitative history has occurred simultaneously with the development of enhanced technology, more complete datasets, and increasingly sophisticated models and methods, which, taken together, have rendered quantitative history potentially more useful than ever before.

The factors responsible for this loss of attention are still being debated vigorously. Some scholars attribute the problems afflicting quantitative history to the initial overselling of the method by insufferable practitioners who promised more insights than their research was able to deliver. These critics, comprised largely of traditionalists, have always been suspicious of the proposition that history had anything to learn from the social sciences and have long bristled at heady sentiments such as that expressed by Emmanuel Le Roy Ladurie who predicted in 1967 that in the future ‘the historian will be a programmer or he will be nothing’ (Rabb 1983). No wonder that such skeptics gladly seized upon Bernard Bailyn’s and Lawrence Stone’s calls for a revival of the narrative.

Another reason was the cultural turn of many younger historians who rejected both the materialist premises and positivist vision of most practitioners of quantitative history. To these critics, quantitative representations of the past were at once too cold, too remote, too impersonal, and too abstract. Large datasets were said to dehumanize, and ‘soulless’ quantifiers were assumed to be ready, like Marx’s bourgeoisie, to drown all human sentiment ‘in the icy water of egotistical calculation’ (Coclanis 1992). Moreover, in making fetishes of rigor and precision, quantitative historians purportedly attempted to exact more from the vast, vague, largely unknowable past than historians had any right to claim. Instead, the past was reconfigured as a ‘foreign country,’ to invoke the title of historian David Lowenthal’s influential 1985 book.

The changing demographics of the historical profession, particularly in the United States, also served to reinforce the trend towards qualitative approaches. As history opened up to women and minorities— groups, generally speaking, less inclined to pursue quantitative approaches to the past—quantitative history could be expected to decline in a relative sense. Just as women and minorities have been under-represented in the hard sciences over the years, they have proven less interested in the more social scientific sides of history. Though both groups have embraced social history as a vehicle for their identity politics, relatively few of their members can be found in fields such as economic history, historical demography, or quantitative political history.

During the 1980s, many historians turned instead to cultural anthropology for methodological inspiration. Rejecting the rigorous, formal and remote, datadriven ‘truths’ sought by quantifiers, scholars interested in experience and meaning preferred in-depth microstudies, whether of single villages, small groups, or even well-documented individuals. Gradually, ‘thick description’ came to trump ecological regression, crude death rates, and multiple R-squares, no matter how robust! The philosophical basis of this shift to anthropology was the rise of postmodernism, which deprecated the rationalism, universalism, and empiricism of historical social science. By the late 1990s the ascendancy of cultural studies left quantifiers off in a corner silently counting all by themselves.

4. The Continued Importance Of Quantification

The current disregard of quantitative methods in the discipline is unfortunate, since quantification continues to be an essential technique for historical research. Some questions can best be answered through recourse to what Sir William Petty referred to in the seventeenth century as ‘Number, Weight, or Measure,’ and it is more than ‘physics envy’ that has drawn scholars to quantitative analyses of the past. Even after conceding that many early practitioners were a bit overly zealous in their claims, it seems fair to suggest that quantitative history can provide the methodological discipline, intellectual rigor, and moral purpose that subjectivist forms of history often lack. With all due respect to such influential postmodernist thinkers such as Baudrillard and Lyotard not every aspect of the past is positional, free-floating, and contextual.

The utility, indeed, the necessity of quantitative history seems more compelling in light of important new developments in the field. Technological constraints have eased considerably, for example, as miniaturization and digitalization in the electronics industry have advanced. Today’s personal computers, programmable calculators, and other platforms offer tremendous power and, thus, computational possibilities to quantitative historians. Similarly new developments in statistical packages, spreadsheets, CD-ROM technology, GIS (geographic information systems), and the like have vastly expanded the analytical reach of software that can be applied to historical questions.

The increasing availability of new and/or enhanced sources and datasets also presents unprecedented research opportunities. Materials readily retrievable from established institutions such as the ICPSR (Interuniversity Consortium for Political and Social Research) in Ann Arbor, Michigan, and data available on-line from the World Bank, the IMF, and other governmental, quasigovernmental, and nongovernmental organizations and agencies are transforming the nature (and sites) of scholarly production. The new CD-ROM version of the Historical Statistics of the United States, datasets assembled by Yale’s Cambodia Genocide Project, the University of Minnesota’s IPUMS (Integrated Public Use Micro Sample) Project, drawn from US census records, and the East German central cadre files—to cite but four examples—are of similar scholarly importance, and have tremendous potential as teaching tools. Various research projects undertaken under the auspices of, or promoted by the Association for History and Computing, founded in England in 1987, have proven extremely useful as well.

At the same time, quantitative historians have in recent years developed more sophisticated methods, allowing them to analyze and interpret historical questions with greater sensitivity and precision. Economic historians, for example, have utilized both game- theoretical approaches and advanced econometric techniques to excellent effect, and anthropometric historians have employed important new procedures from auxology and biostatistics to facilitate their reconstruction of our biological past (Steckel 1995). Economic and social historians, along with historical sociologists, have also begun to employ regression analysis in more subtle and refined ways, using temporally recursive regression procedures, when appropriate, instead of standard time-series regression techniques.

Other quantitative historians have begun to ‘push the envelope’ in different ways, in so doing, often trespassing on the territory of scholars in other social sciences or even in the humanities. Thus, as procedures such as social network analysis (SNA), event-structure analysis, and quantitative language analysis are successfully employed in answering historical questions—quantitative analyses of major ‘texts’ in order to produce so-called semantic grammars, for example—non and anti-quantifiers ignore the results at their peril. In addition, quantitative historians’ recent incorporation of spatial relationships into historical analysis through spatial-effects regression models and the like has produced similarly impressive results (Griffin and van der Linden 1998).

At the beginning of the twenty-first century, the future prospects of quantification in history are therefore indistinct. Clearly, individual quantitative historians, among the profession’s most avid proponents of scientific rationalism, universalism, and empiricism, are continuing to expand the frontiers of their research and are still making important contributions. But whether or not the interest of mainstream historians will return to quantification and the subfield as such will ever again recapture the excitement and energy it possessed in the 1970s remains an open question. The relative popularity of various approaches does not just depend on the quality of their monographic work but on the larger tides of intellectual fashion. However, one unexpected development offers some cause for optimism: though quantitative historians hang on for their professional lives, historically-inclined political scientists, economists, and sociologists are winning kudos in their respective disciplines by bringing quantitative methods to bear on the past.

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