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We address three basic issues regarding the long-term dynamics of inequality in society. First, we consider the interpretation of residence sizes in socioeconomic terms by comparing statistical patterns extracted from the Global Dynamics of Inequality (GINI) Project database with those from the 21st-century United States. Second, we examine the degree to which the size and productivity of human networks is systematically related to inequality. Finally, we investigate relationships between productivity and productivity growth distributions for patterns of inequality and development across preindustrial societies. We find that across preindustrial societies residence size distributions provide a reasonable proxy for the distribution of productivity (income, a flow of physical and social resources to the group) and a minimum estimator for the distribution of wealth (a stock of such resources accumulated over time); that scale and productivity affect levels of inequality but account for only a small fraction of the observed variance across societies; and that inequality growth is independent of productivity growth, on average and over time. These findings have important implications for efforts to promote more equitable economic development in the present. 

Abstract The GINI project investigates the dynamics of inequality among populations over the long term by synthesising global archaeological housing data. This project brings archaeologists together from around the world to assess hypotheses concerning the causes and consequences of inequality that are of relevance to contemporary societies globally. 

Inequality is an intrinsic element of contemporary societies, with high income disparity impacting everything from life expectancy to violent crime. While inequality in today’s society is complex and multifaceted, the prominence and persistence of inequality that existed throughout human history raise important questions about its broader impacts in the past. In this paper, we discuss the concept of quality of life (QOL) for archaeology and introduce methods for studying multiple dimensions of wealth and well-being in past societies. Using previously published burial data from the ancient Maya site of Altar de Sacrificios, we illustrate this approach employing notions of personhood that treat individuals embedded in complex socio-material relations. These data enable diachronic analyses in the degree and kinds of inequality that characterized this Maya community over a span of nearly 2000 years. We further discuss how these techniques can apply to other units of archaeological analysis and comparative case studies. Tracing the disparities in material wealth, social well-being, and health through time enables a more detailed analysis of the specific contexts and historical processes that gave rise to varying degrees of inequality in the past. 

Many humans live in large, complex political centers, composed of multi-scalar communities including neighborhoods and districts. Both today and in the past, neighborhoods form a fundamental part of cities and are defined by their spatial, architectural, and material elements. Neighborhoods existed in ancient centers of various scales, and multiple methods have been employed to identify ancient neighborhoods in archaeological contexts. However, the use of different methods for neighborhood identification within the same spatiotemporal setting results in challenges for comparisons within and between ancient societies. Here, we focus on using a single method—combining Average Nearest Neighbor (ANN) and Kernel Density (KD) analyses of household groups—to identify potential neighborhoods based on clusters of households at 23 ancient centers across the Maya Lowlands. While a one-size-fits all model does not work for neighborhood identification everywhere, the ANN/KD method provides quantifiable data on the clustering of ancient households, which can be linked to environmental zones and urban scale. We found that centers in river valleys exhibited greater household clustering compared to centers in upland and escarpment environments. Settlement patterns on flat plains were more dispersed, with little discrete spatial clustering of households. Furthermore, we categorized the ancient Maya centers into discrete urban scales, finding that larger centers had greater variation in household spacing compared to medium-sized and smaller centers. Many larger political centers possess heterogeneity in household clustering between their civic-ceremonial cores, immediate hinterlands, and far peripheries. Smaller centers exhibit greater household clustering compared to larger ones. This paper quantitatively assesses household clustering among nearly two dozen centers across the Maya Lowlands, linking environment and urban scale to settlement patterns. The findings are applicable to ancient societies and modern cities alike; understanding how humans form multi-scalar social groupings, such as neighborhoods, is fundamental to human experience and social organization.