Quantitative Methods in the Humanities: An Introduction

By Claire Lemercier, Claire Zalc and Arthur Goldhammer

This timely and lucid guide is intended for students and scholars working on all historical periods and topics in the humanities and social sciences--especially for those who do not think of themselves as experts in quantification, "big data," or "digital humanities."

The authors reveal quantification to be a powerful and versatile tool, applicable to a myriad of materials from the past. Their book, accessible to complete beginners, offers detailed advice and practical tips on how to build a dataset from historical sources and how to categorize it according to specific research questions. Drawing on examples from works in social, political, economic, and cultural history, the book guides readers through a wide range of methods, including sampling, cross-tabulations, statistical tests, regression, factor analysis, network analysis, sequence analysis, event history analysis, geographical information systems, text analysis, and visualization. The requirements, advantages, and pitfalls of these techniques are presented in layperson’s terms, avoiding mathematical terminology.

Conceived primarily for historians, the book will prove invaluable to other humanists, as well as to social scientists looking for a nontechnical introduction to quantitative methods. Covering the most recent techniques, in addition to others not often enough discussed, the book will also have much to offer to the most seasoned practitioners of quantification.

• Language: English
• Publisher: University of Virginia Press
• Release date: Mar 13, 2019
• ISBN: 9780813942704

Book preview

Quantitative Methods in the Humanities

Quantitative Methods in the Humanities

AN INTRODUCTION

Claire Lemercier and Claire Zalc

Translated by Arthur Goldhammer

UNIVERSITY OF VIRGINIA PRESS

CHARLOTTESVILLE AND LONDON

University of Virginia Press

© 2019 by the Rector and Visitors of the University of Virginia

All rights reserved

First published 2019

Library of Congress Cataloging-in-Publication Data

Names: Lemercier, Claire, author. | Zalc, Claire, author. | Goldhammer, Arthur, translator.

Title: Quantitative methods in the humanities : an introduction / Claire Lemercier and Claire Zalc ; translated by Arthur Goldhammer.

Other titles: Methodes quantitatives pour l’historien. English

Description: Charlottesville : University of Virginia Press, 2019. | Includes bibliographical references and index.

Identifiers: LCCN 2018049781 | ISBN 9780813942681 (cloth : alk. paper) | ISBN 9780813942698 (pbk. : alk. paper) | ISBN 9780813942704 (e-book)

Subjects: LCSH: History—Methodology. | History—Statistical methods.

Classification: LCC D16.17 .L4613 2019 | DDC 907.2/1—dc23

LC record available at https://lccn.loc.gov/2018049781

Cover art: iStock/-strizh-

CONTENTS

Acknowledgments

Introduction

1 Quantitative History from Peak to Crisis

2 Sources and Samples

3 From Source to Data

4 From Correlation to Causality?

5 Quantification, Networks, and Trajectories

6 Visualizing History

7 Counting Words, Exploring Texts

Conclusion

Bibliography

Index

ACKNOWLEDGMENTS

Christian Baudelot, Noël Bonneuil, Pascal Cristofoli, Gilles Lemercier, Lise Mounier, Paul-André Rosental, Anne Strauss, and Anne Varet-Vitu opened important doors to quantification for us. This book is the result of more than fifteen years of workshops, courses, and summer schools, where we learned enormously while we taught: our warmest thanks to all the participants. An initial, quite different French version was published in 2008, thanks to the excellent Pascal Combemale and Marieke Joly; La Découverte kindly reverted the English rights to us. Fellow quantifiers, especially Fabien Accominotti, Pierre François, Pierre Mercklé, and Carine Ollivier regularly reminded us that some sociologists were interested in history, weird data, and nonstandard methods. Clare H. Crowston and Steven L. Kaplan heartily encouraged us to advance this English version, and made important suggestions on a first draft. We thank the four anonymous reviewers who encouraged us to clarify our ideas and contributed in expanding our references, especially in US history. Danièle Fraboulet and Jérôme Krop let us use their datasets for two of our examples; we discussed some of the mysteries of R-generated figures with Anton Perdoncin and Nicolas Robette. We acknowledge the financial support for translation provided by the Center for the Sociology of Organizations, the Institute for Early Modern and Modern History, Labex TransferS, and Sciences Po. We thank our employer, CNRS, for freedom in research, and the French scientific community for mostly ignoring the divide between the humanities and social sciences. Finally, this book would not have existed without the enthusiasm and professionalism of our colleague and friend Nicolas Barreyre, our translator Arthur Goldhammer, and our editor Dick Holway and the rest of the team at the University of Virginia Press.

Quantitative Methods in the Humanities

Introduction

We came to quantitative methods not out of ideological conviction but out of necessity: our sources led us to them, and our arguments relied on them. For us, quantification is not an end in itself but a useful and sometimes necessary tool.

In that spirit, the purpose of this guide is not only to familiarize readers with the various possible uses of quantification in historical practice but also to describe the power and limits of quantitative methods. We hope that our readers will become critical consumers of quantitative research who neither fetishize numbers nor fear them.

This guide is also addressed to anyone who is grappling with historical sources: historians, nonhistorians, students, apprentice researchers, and experienced veterans. We mostly cite historical works, but we are confident that our main arguments are no less applicable to other humanistic disciplines (qualitative social scientists, and even quantifiers, might also be interested). Our ambition is to enable anyone to understand quantitative methods, even if that means deciding eventually, with full understanding, that it is better to do without them. Above all we hope that no one who reads this book will avoid quantitative methods out of ignorance, fear, or denial.

Why Count?

Although history is not an exact science, counting, comparing, classifying, and modeling are nevertheless useful methods for measuring our degree of doubt or certainty, making our hypotheses explicit, and evaluating the influence of a phenomenon. Thanks primarily to advances in microcomputing, every student now has at her disposal calculating capabilities of which researchers could only dream in the 1970s. Yet the learning curve remains steep. Historians are commonly trained as humanists, and many are ambivalent about numbers. Some respect the authority of numbers, but as something alien, without much interest for their own work. Many others disdain measurement as a trivial concern irrelevant to interpretation, or a product of the tyranny of the state or the market. For them, numbers cannot address what matters, namely, people and interpretations, and they may even harm their mission. Articles and books featuring tables and graphs are either rejected outright or accepted without verification: quantification, whether seen as a blemish or a mark of seriousness, is never just a tool like any other.

Furthermore, although new methods appear regularly, these often remain confined within certain disciplines such as sociology or demography. Others are used only in medieval or contemporary history or by followers of Pierre Bourdieu or by colleagues trained in political science even though they might well be applied to sources and problems in other fields. There are, for example, many surprising applications of quantification not just to economic and social history but also to political and cultural history, not just to classes and nations but also to individuals and small groups. A common prejudice, to be sure, divides the social world into phenomena that are suitable for quantification (population distributions, social mobility, etc.) and those that are irreducibly qualitative: conversation, narratives, biography, ethnography, and history often serve as examples. Formalisms clearly can and do apply, however, to these phenomena as well (Tilly 2004). To make these methods accessible, we believe that disciplinary isolation and the compartmentalization of research must be overcome.

We also believe in the circulation of methods between countries and continents. A first version of this book was published in French in 2008. It was written mainly for a French audience, so our discussions often made reference to French works, especially when we walked readers through our own research. In this completely revised English edition, we provide numerous examples of the application of quantitative methods to the history of other parts of the world, especially the United States. Our goal is to encourage debate that transcends specific historical literatures. Quantification is indeed useful in the study of East Asian and West African history as well as West European and North American history; of art and gender history as well as demographic and economic history. We emphasize diversity because we advocate nonstandard approaches to quantification. The risk of standardization has always plagued quantitative history. By contrast, we take the view that different historical literatures rely on different sources and pose different questions, which we regard as opportunities for methodological innovation. Accordingly, we have kept some French references, especially when they were useful to document approaches that are uncommon in the English-speaking literature (such as the historical use of factor analysis). We will use the companion website to this book to gradually expand our list of references to other languages and other parts of the world (https://quanthum.hypotheses.org).

Why This Guide?

This book emerged from several years of teaching experience, which persuaded us of the need for a text that would not only present a range of techniques applicable to historical data but also discuss critiques of those methods. Indeed, after an initial period of enthusiasm, quantitative history has been subjected to numerous critiques, and these must be addressed (as we do in chapter 1). Some of these critiques stemmed from intrinsic difficulties of quantification in the humanities; others, however, were rather the product of historians’ poor understanding of quantitative methods, which is itself a consequence of the aridity of much quantitative history.

We therefore adopt a basically practical approach. We begin with questions that historians, including both beginners and more advanced researchers, encounter in the course of their work: how to build a corpus or sample (chapter 2), how to record and categorize information from sources (chapter 3), and so on. Most textbooks overlook such problems as mere contingencies of research that each investigator must face on her own. Nevertheless, the questions we raise pertain both to the historian’s craft and to the nature of history itself: What is the investigator trying to show—to describe, understand, or explain? How can an argument be crafted in such a way as to respect the language and lacunae of the sources? How can one avoid the perils of simplistic and anachronistic positivism and pessimistic disdain of the need for proof? How can one get beyond the utopian longing for an exhaustive reconstruction of the past?

What this guide proposes is a dialogue between concrete problems and general questions. It is motivated by our belief that acquiring a general familiarity with problems of quantification can help to sharpen one’s critical faculties and lead to better exploitation of certain sources. Using numbers and spreadsheets and borrowing techniques from the social sciences did not divert us from the fundamental tenets of the historical profession—source criticism and attention to specific contexts and to human agency. What we offer here is a discussion of how quantitative methods can support the traditional tools of the historian and vice versa.

Choosing a Method

Preconceived ideas about the comparative virtues of this or that method are commonplace. In practice, however, it turns out that a priori methodological choices (of, say, network analysis or factor analysis) are not necessarily well adapted to the available sources or to the questions one wants to answer.

It is therefore useful to gain an overview of the main quantitative methods that historians have found useful, focusing on the methods’ basic principles, scope of applicability, and necessary precautions (chapters 4 to 7). Each technique has a different purpose and is better or worse suited to certain types of sources and questions. In this book we do not explore the mathematical principles underlying each method. These can be found in longer, more specialized texts—and we provide references for the interested reader. We have even less to say about the use of different software packages. As a supplement to this book, we have set up a website with a guide to further reading as well as software and practical advice, and we encourage readers to have a look. What we discuss here is rather the purpose of each approach, the types of sources for which it is suitable, necessary methodological precautions, and common pitfalls.

Despite our optimistic vision of the possible uses of quantification, we are mindful of the ideological issues underlying the history of methodology. Any relapse into numerical fetishism is to be avoided, where by numerical fetishism we mean the belief that reality is best summed up by numbers, regardless of how those numbers were arrived at. Conversely, there are other simplifications that must also be avoided, such as the belief that reality exists only in the individual or the uncategorized. Behind the choices of scales and models, there are assumptions about the historical and social roles of institutions, norms, individuals, classes, and families. Learning about a method requires knowing what assumptions the pioneers of that method made and what assumptions are maintained by the majority of its adepts. We are nevertheless confident that once those assumptions, not to say biases, are known, a method can be employed in different ways, better suited to the current historical agenda, as long as it was chosen appropriately in view of the available sources and the questions to be asked.

Although these methods are presented separately here for reasons of clarity, they are in fact complementary. In this book we devote an equal amount of space to each, even though some are more common than others in current historical practice: we deem it useful to open the historical imagination to a more diverse set of tools. Other textbooks give more details than ours about techniques that are particularly well suited to questions in economic history, or to historical material that already consists of numbers (Feinstein and Thomas 2002; Hudson and Ishizu 2017). We present a wider range of methods, with examples drawn from more diverse topics and sources. In practice, it is often possible and fruitful to apply several quantitative treatments, descriptive as well as explanatory, to the same corpus, so as to approach the subject from several angles. In the humanities, the techniques presented in chapters 2 and 3—producing cross-tabulations from soundly sampled sources—are sufficient to yield compelling conclusions. It is important to know, however, which other methods might offer added value in specific cases. Learning them is in fact relatively easy, once one has grasped their basic principles, which we present here. The most vexing and time-consuming task in quantitative history is always the upstream work of systematically abstracting information from sources. It is also arguably the most interesting task, the one that makes use of the historian’s specific skills.

ONE

Quantitative History from Peak to Crisis

In 1903, the young French sociologist François Simiand publicly attacked Charles-Victor Langlois and Charles Seignobos, the proponents of what was then a still new historical method of source criticism, and who are still today considered to be the inventors of scientific history (Simiand 1985). Simiand alleged that their method was subjective and lacked conceptual discipline and contrasted this with the rigor of statistics (such as those Emile Durkheim, one of the founders of sociology, had assembled on suicide). This episode marked the beginning of quantitative history and set the tone for relations between the disciplines of history and sociology.

When the New Histories Were Quantitative

For many years thereafter, the Simiand-Seignobos debate set the terms of a confrontation that was often replayed, not just in France but in the United Kingdom, the United States, and elsewhere. On one side were the three idols of the historians’ tribe, the political idol, the individual idol, and the chronological idol, and the historical method, which lacked a priori concepts and a scientific notion of causality. On the other side stood sociology, which treated social facts as things and, in particular, used statistics to reveal persistent basic phenomena. In 1929, a new journal was created: Annales, which at the time opposed the historical establishment but came to set the tone of mainstream history after World War II, in particular in the 1960s in the United States (Burke 2015). The new journal proposed to make room in history for economic and social as well as comparative methods, and for groups rather than individuals, in particular, groups that did not write their own history. This implied using new sources, archaeological remains as well as marriage and death records, and new methods, often borrowed from sociology, geography, demography, or economics.

Similar self-styled revolutions in favor of a new social history took place in many countries in the 1960s, building an international effort (Sewell 2005). At that time, the Annales school had become prominent in France (Revel and Hunt 1996). Like Simiand in 1903 and the founders of Annales in the 1930s, American new social historians thought of themselves as rebels against traditions in the historical discipline. Political science and sociology were so important a source to borrow from that they ultimately called their new specialty social science history. The Social Science History Association (SSHA) was founded in 1974 (Graff 2001). It included political and economic historians as well and succeeded the Quantitative Data Committee of the American Historical Association, which was established in 1963.

New social historians focused on people, themes, and sources that had previously been mostly dismissed by mainstream historians: they used tax registers, wills, popular songs, records of marriages, and so forth to capture the whole range of ordinary people’s life experiences. Many of them, particularly in England, analyzed these new sources by way of standard close reading and note-taking, and saw no reason to abandon narrative as a way to present their conclusions. The 1960s issues of Annales are not as full of tables, graphs, or sociological phrasing as many social science history pioneers would have liked. In 1977, the main English-speaking general journals in history (arguably including the most quantitatively oriented) published 20 percent of quantitative papers, as opposed to 10 percent in 1967 (Sprague 1978). In the United States of the late 1960s, new methods were mostly developed outside Ivy League campuses, and in area studies rather than American history departments (Landes and Tilly 1971). Yet a significant minority of historians had adopted new ways to store information (on punch cards), analyze it (often through cross-tabulations), and, more generally, ask questions that required quantitative answers. These historians considered ordinary people in the aggregate, as constrained by objective social structures of which they were incompletely aware and that could only be revealed by a systematic reading of the evidence (Sewell 2005).

Quantitative history is fashionable just now both in Europe and in the United States, François Furet wrote in a special issue of Daedalus on Historical Studies Today (1971). A new way of writing history took hold, and as a result the physical appearance of history journals and books changed as well: they began to include tables, figures, maps, and even columns and columns of raw numbers. This fashion was not limited to social history. In the United States, a new generation of scholars, borrowing techniques from geography, political science, and economics, promoted new political history and new economic history. They claimed to offer a more rigorous way to decide on the old, fundamental questions of the discipline.

New political historians such as Lee Benson and Allan Bogue advocated for behavioral history—a program they had developed with Paul Lazarsfeld, a pioneer in opinion polling studies (scholarly as well as applied to market research and voter surveys). They were not satisfied with a narrative of successive presidents. Instead, they defined a sequence of party systems and critical elections, based on yearly series of electoral results. Benson also pioneered studies of attributes correlated with votes, such as class or religious affiliation, showing that the people had not been populist Andrew Jackson’s source of support, at least in New York State (Benson 1961). Other early studies similarly found that religion played a more important role than expected, as opposed to class (e.g., Hammarberg 1983). Systematic, quantitative studies of votes in Congress showed them to be much more determined by party affiliation than sectionalism (and much more than was believed before), opening the way for a study of deviations from this standard (Silbey 1983).

New economic historians called their specialty cliometrics: the application of econometrics to historical data. In the United States, they were probably the most visible new historians outside the universities, thanks to two books: Robert Fogel’s demonstration that railroads, contrary to conventional wisdom, had not been necessary for American economic growth (Fogel 1964), and his and Stanley Engerman’s controversial revision of the historiography of slavery, Time on the Cross (Fogel and Engerman 1974). Fogel presented regression models, with their all other things being equal motto (see chapter 4), in an attractive way: he called his work counterfactual history, a history of alternative futures. In his book on railroads, he devised a simple, abstract model of the American economy in a way that would allow him to discuss what would have happened if there had been more canals and roads, but no railroads (growth would have been only slightly lower).

Such a model cannot be derived solely from data, however quantitative: it relies on many hypotheses drawn from economic theory (here, the general equilibrium) or that just suit the author or the data or that make computation easier. The most significant limitation of the book is probably the fact that