This book seeks to contribute an archaeological deep time perspective to the burgeoning discussions and literature on increasing inequality in the modern world: How can we evaluate claims of growing inequality without knowledge of its long-term history? The book grew from a symposium at the 2016 Society for American Archaeology meeting in Orlando, Florida, and an Amerind Foundation seminar in Dragoon, Arizona, later that year (full disclosure: I was invited to the Society for American Archaeology session but had to decline). The book advocates for and is a primer on using the Lorenz curve and the Gini coefficient; the former graphically encapsulates wealth inequalities in a sampled population, and the latter is a coefficient summarizing the graph's information. The Gini coefficient fills the need for a standard index of inequality for making consistent comparisons across great distances in time and space. This technique has been widely used in social science disciplines for comparing income and wealth differences, and it has been applied sporadically by archaeologists since the 1980s. The Gini coefficient focuses the book on material wealth inequalities, which, while easier to measure archaeologically than differences in prestige or power, still requires an archaeological proxy. House size as measured by area is that proxy. While not a perfect measure, it crosscuts the great diversity of forms of wealth in the ethnographic and archaeological record.

The book has 11 chapters. The first (Smith, Kohler, and Feinman) is a useful, concise introduction to theoretical and methodological issues surrounding wealth inequality and to the purpose of and justification for the book and its methodology. The next two chapters are methodological. Chapter 2 (Peterson and Drennan) is a primer on using Gini coefficients and Lorenz curves. Chapter 3 (Oka, N. Ames [no relation], Chesson, Kuijt, Kusim, Gogte, and Dandekar) proposes a “composite archaeology inequality index,” which is the geometric mean of multiple Gini coefficients calculated on different forms of wealth. Chapters 4 through 10 are case studies that include the Pacific Northwest of North America (Prentiss, Foor, and Murphy), the American Southwest (Kohler and Ellyson; Pailes), the Mississippian societies of the southeastern United States (Betzenhauser), northern Mesopotamia compared with southwestern Germany (Bogard, Styring, Whitlam, Fochesato, and Bowles), Mesopotamia (Stone), and prehispanic Oaxaca (Feinman, Faulseit, and Nicholas).

The final chapter, entitled “Deep Inequality” (Kohler, Smith, Bogard, Peterson, Betzenhauser, Feinman, Oka, Pailes, Prentiss, Stone, Denney, and Ellyson), uses data from the case studies and other sources to ambitiously examine inequality across large spatial and temporal scales to test a number of expectations along several dimensions, including adaptation (subsistence), site (settlement) type, and demographic scale. The authors compare inequality between the New and Old Worlds, finding it generally more strongly expressed in Old World states, which they attribute to the presence of large domestic animals in the Old World. One counterintuitive result of the analysis is that Teotihuacán's Gini coefficient suggests that it was egalitarian. An earlier version of this chapter published in 2017, using a slightly different dataset, argues that this surprising finding indicates that Teotihuacán was a collective rather than an autocratic polity and, furthermore, that the Gini coefficient for Teotihuacán is related to urban planning, the lack of large palaces at the site, and a residential pattern dominated by intermediate-sized houses (Kohler et al., Nature 551:619–623). Regardless of the explanation, this is the sort of counterintuitive result on which science thrives.

The case studies do not rely solely on house size. Prentiss and colleagues base Gini coefficients on six other lines of material evidence from the Bridge River site in south-central British Columbia; some essays touch on storage as a measure of wealth or income; Bogard and colleagues propose an aggregation function to deal with various forms of wealth contributing differentially to a standard of living. Methodological issues addressed include Gini coefficients requiring representative samples of the population and the difficulties achieving that with archaeological samples, the effects of constraints on house size variations, how to partition structures in complex residual patterns into houses, and so on.

Some will reject the reductionism of summarizing a complex phenomenon such as inequality with a single number, while others will find it appealing. It does allow the kind of “big data” comparison and hypothesis testing undertaken in Chapter 11. It also encourages working across disciplines, phenomenological scales, and lines of evidence. Fully understanding the method and results, including surprising results such as Teotihuacán's, requires nuanced analysis of these multiple lines of evidence, some more qualitative than a Gini coefficient.

The book is a significant contribution. It is well crafted and well executed; the essays are tight; and the overall quality is high. It is stimulating whether you agree with its methodological premise or not. Few of us will disagree with archaeological data and insights contributing to current policy debates. This book makes an excellent case for the importance of studying patterns in deep time.