Urban Scaling

I describe a new approach to understanding processes of village aggregation and urbanization in the past. The key concept—energized crowding—refers to the social effects of large numbers of social interactions that take place within settlements. Demographic processes of population growth and settlement nucleation (aggregation and urbanization) lead to increased energized crowding, which in turn generates a variety of social outcomes. I discuss those outcomes under three headings: scalar stress, community formation, and economic growth. In this model, aggregation and urbanization are crucial processes that lead—by way of energized crowding—to many documented social outputs in both contemporary and past settlement systems. Because this is a new approach for archaeology, conceptual tools for understanding these processes must be borrowed from other social sciences. In particular, recent research on settlement scaling provides empirical and theoretical support for the notion that aggregation and urbanization were of fundamental importance in generating social change in the past. Population aggregation—the concentration of formerly dispersed people into villages, towns, and cities—is one of the most consequential processes in the history of human society. When people come together in a settlement, the number and level of interactions among individuals increases exponentially, and these interactions have generative power. That is, they bring about a variety of social changes, both positive and negative. Research by sociologists and anthropologists has tended to focus on the negative consequences of urbanization—increased levels of stress, crime, poverty, and alienation. Research by economists and geographers, on the other hand, emphasize the positive consequences of aggregation. The acceleration of face-to-face social interaction in larger and denser settlements stimulates knowledge transfer, technological innovation, and economic growth. One well-documented finding for contemporary cities is that as cities grow larger, their per-capital productivity increases; individuals are more productive in larger cities (Bettencourt 2013; Pumain 2012). These positive and negative consequences of aggregation and urbanization are two sides of the same coin. Whether talking about the aggregation of small early farming groups into villages or the processes of rural-to-urban migration that lead to urbanization in the developing world today, the results are similar. Increased numbers of people living in close contact activates a process that architectural historian Spiro Kostof (1991:37) called energized crowding: " Cities are places where a certain energized crowding of people takes place. This has nothing to do with absolute size or with absolute numbers; it has to do with settlement density. " While research suggests that the magnitude of the social effects of energized crowding does in fact depend on

In recent decades researchers in a variety of disciplines have developed a new "urban science," the central goal of which is to build general theory regarding the social processes underlying urbanization. Much work in urban science is animated by the notion that cities are complex systems. What does it mean to make this claim? Here we adopt the view that complex systems entail both variation and structure, and that their properties vary with system size and with respect to where and how they are measured. Given this, a general framework regarding the social processes behind urbanization needs to account for empirical regularities that are common to both contemporary cities and past settlements known through archaeology and history. Only by adopting an explicitly historical perspective can such fundamental structure be revealed. The identification of shared properties in past and present systems has been facilitated by research traditions that define cities (and settlements more broadly) as networks of social interaction embedded in physical space. Settlement Scaling Theory (SST) builds from these insights to generate predictions regarding how measurable properties of cities and settlements are related to their population size. Here, we focus on relationships between population and area across past settlement systems and present-day world cities. We show that both patterns and variations in these measures are explicable in terms of SST, and that the framework identifies baseline infrastructural area as an important system-level property of urban systems that warrants further study. We also show that predictive theory is helpful even in cases where the data do not conform to model predictions.

In a recent critique on the correlation between urbanization and economic development in the Roman world, it was stressed that ‘we need a theory of (ancient) urbanization and of the nature of the processes that supported the development of urban centres before we can attempt to delineate and quantify the parameters of this development, let alone begin to discuss the implications of this for the economy’ (Morley 2011: 153). Yet this is no easy task, as urban planners, economists, geographers, sociologists, and land use analysts still struggle to quantitatively and qualitatively understand the growth and sustainability of modern cities and complex urban systems. That said, progressive work in the field of urban scaling has finally allowed for a more scientific approach to the evolution of cities by identifying a set of basic principles by which all urban systems abide (Bettencourt et al. 2007). Developed by researchers at the Santa Fe Institute (SFI), urban scaling is used ‘to predict the average social, spatial, and infrastructural properties of cities as a set of scaling relations that apply to all urban systems’ (Bettencourt 2013a). While confirmed scaling relationships have been observed in thousands of modern cities worldwide (Bettencourt et al. 2007), only preliminary studies have been conducted for the ancient world, and solely in a Mesoamerican context (Ortman et al. 2015). As the theoretical framework of urban scaling is designed to better examine and interpret the (often elusive) empirical and theoretical processes behind urbanization and demographic and economic growth, it has the potential to be extremely useful for Roman contexts, as will be discussed. This paper will begin by outlining some of the fundamentals of urban scaling, how it can be used to assess and quantify growth, and how scaling relationships have been observed in ancient contexts to date. This will then be followed by a more theoretical discussion in which I will use the tenets of urban scaling theory to explore the demographic and economic growth of Rome from the mid-Republic to the early Augustan period (c. 225 – 2 B.C.), and provide two competing scenarios for the overall growth (and decline) of the City, and by proxy, Empire.

Medieval European urbanization presents a line of continuity between earlier cities and modern European urban systems. Yet, many of the spatial, political and economic features of medieval European cities were particular to the Middle Ages, and subsequently changed over the Early Modern Period and Industrial Revolution. There is a long tradition of demographic studies estimating the population sizes of medieval European cities, and comparative analyses of these data have shed much light on the long-term evolution of urban systems. However, the next step—to systematically relate the population size of these cities to their spatial and socioeconomic characteristics—has seldom been taken. This raises a series of interesting questions, as both modern and ancient cities have been observed to obey area-population relationships predicted by settlement scaling theory. To address these questions, we analyze a new dataset for the settled area and population of 173 Euro-pean cities from the early fourteenth century to determine the relationship between population and settled area. To interpret this data, we develop two related models that lead to differing predictions regarding the quantitative form of the population-area relationship, depending on the level of social mixing present in these cities. Our empirical estimates of model parameters show a strong densification of cities with city population size, consistent with patterns in contemporary cities. Although social life in medieval Europe was orchestrated by hierarchical institutions (e.g., guilds, church, municipal organizations), our results show no statistically significant influence of these institutions on agglomeration effects. The similarities between the empirical patterns of settlement relating area to population observed here support the hypothesis that cities throughout history share common principles of organization that self-consistently relate their socioeconomic networks to structured urban spaces.

This thesis explores the question of whether correlations between socioeconomic indicators and health and environmental indicators can be observed at the metropolitan level of analysis. Indicators are considered both in terms of per capita values and scale-adjusted values. Scale-adjusted values are a concept based on research on urban scaling which account for the agglomeration effect of population on socioeconomic output and describe a city’s performance in terms of how it compares with expected performance on an indicator for its population size based on the power law scaling of that indicator to population. These indicators provide an alternative baseline for comparing the relative economic performance of cities of different sizes. Considering these scale-adjusted indicators a potentially more meaningful measure of socioeconomic performance, they were expected to correlate with health and environmental outcomes better than per capita values, although this was only true for median household income.

One of the questions driving this inquiry was whether the theory of urban scaling might be useful in explaining the variation in indicators which do not scale with population, but which have been shown in other research to relate to socioeconomic factors. In this study, those factors are air quality, tree cover and twelve health outcomes and risk factors collected by the CDC. In all but a few cases, stronger correlations could be seen with per capita socioeconomic values than with scale-adjusted values.

Data for metropolitan and micropolitan statistical areas were gathered on a wide range of socioeconomic indicators and tested for correlations with health and environmental outcomes. Socioeconomic data that scaled with population were also calculated as a scale-adjusted metropolitan indicator (SAMI) value and tested for correlations with health and environmental outcomes. The expectation was that SAMI values would help explain health and environmental outcomes, which was found generally not to be true. From the data, however, some correlations between socioeconomic and health indicators could be observed, while tree canopy and impervious surface showed inconsistent correlations with health and economic indicators in different ecoregions.

In a recent critique on the correlation between urbanization and economic development in the Roman world it was stressed that ‘we need a theory of (ancient) urbanization and of the nature of the processes that supported the development of urban centres before we can attempt to delineate and quantify the parameters of this development, let alone begin to discuss the implications of this for the economy’ (Morley 2011: 153). Yet this is no easy task, as urban planners, economists, geographers, sociologists, and land use analysts still struggle to quantitatively and qualitatively understand the growth and sustainability of modern cities and urban systems. That said, progressive work in the field of urban scaling (see Bettencourt 2013) has finally allowed for a more scientific approach to the evolution of cities by identifying a set of basic principles by which urban systems abide. While these confirmed scaling relations have been observed in thousands of modern cities worldwide, recent archaeological work in Pre-Hispanic Mexico suggests that ‘the fundamental processes behind contemporary urban scaling operated in the ancient world just as they do today’ (Ortman et al. 2014). This paper will then examine how the theoretical framework and principles of urban scaling may be applied to assess the growth and evolution of ancient Rome. By taking a diachronic approach, and examining specific phases of Rome’s urban growth (and the sustainability of such growth) we may achieve a better understanding of the underlying motivating factors behind the City’s expansion and ultimate decline. These conclusions may then be extrapolated in ways that arguably push us closer to a more acceptable theory on ancient urbanization and how it relates to the Roman economy.