\"Urban Service Access in Premodern Cities: An Exploratory Comparison\" (2016)

566969

research-article2015

JUHXXX10.1177/0096144214566969Journal of Urban HistoryStanley et al.

Article

Service Access in Premodern Cities: An Exploratory Comparison of Spatial Equity

Journal of Urban History 2016, Vol. 42(1) 121­–144 © 2015 SAGE Publications Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0096144214566969 juh.sagepub.com

Benjamin W. Stanley1, Timothy J. Dennehy2, Michael E. Smith2, Barbara L. Stark2, Abigail M. York2, George L. Cowgill2, Juliana Novic2, and Jerald Ek3

Abstract Spatial equity studies measuring urban service access have been conducted in variety of modern settings, but this research has not been extended to premodern cities. This article presents an exploratory, transdisciplinary pilot study of service access in six premodern urban environments to better understand the historical origins of inequality. Using archaeological and historical spatial data, neighborhood and household access to three types of service facility is studied across different urban traditions. Findings reveal that the size, shape, and spatial structure of cities may influence service accessibility as much as political influence over facility siting or residential choice. Most cities display a spatially concentric pattern of accessibility, and denser cities tend to display more equitable service access. Elite groups possess consistently better service access than nonelite groups. Although this exploratory study must be expanded to produce firmer results, it indicates the importance of interpreting modern urban inequalities from a long-term perspective, and points to the efficacy of comparative, spatially oriented, urban historical research for generating new insights into urban processes. Keywords spatial equity, urban services, urban history, comparative urbanism, service access

For decades, “socially relevant spatial science” has been probing the existence and drivers of socio-spatial inequity in the urban distribution of amenities and harms.1 Many studies have found that social disparities and differential access to essential services among neighborhoods are commonplace in contemporary world cities. The historical origins of such patterns lie beyond the gaze of most urban scholars, however, and there have been no comprehensive efforts to determine whether intraurban inequality has been universal or to seek the historical drivers of disparities among neighborhoods.

1School

of Sustainability, Arizona State University, Tempe, AZ, USA of Human Evolution and Social Change, Arizona State University, Tempe, AZ, USA 3Department of Anthropology, University at Albany, SUNY, Albany, NY, USA 2School

Corresponding Author: Benjamin W. Stanley, School of Sustainability, Arizona State University, PO Box 875502, Tempe, AZ 85287-5502, USA. Email: [email protected]

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To rectify this gap, we present an exploratory, comparative study of spatial urban service access across six premodern cities, based on an array of historical and archaeological data. Two research questions guide our approach in this pilot study: 1. To what extent does the spatial distribution of public facilities indicate inequality in access to services in premodern urban neighborhoods? 2. To what extent do spatial patterns of service inequality correlate positively with the spatial distribution of elite residents? Our research is part of a larger transdisciplinary research project (see Acknowledgments section) based on the notion that urban areas throughout world history share commonalities inviting comparative study, such as the ubiquitous nature of neighborhood organization, social clustering, and the uses of urban open spaces.2 Our project is rooted in the guiding principle that present-day urbanism is better understood in the context of deep urban history. This exploratory analysis of urban service access—a pilot study providing the foundation for a larger and more systematic comparative effort—was designed to further develop this approach. In this article, we provide preliminary answers to our research questions based on analysis of six initial urban case studies. In our broader comparative study of premodern service access, currently underway, we compare access patterns across a larger set of case studies (ca. twenty cities), introducing more detailed methods of calculating access patterns and inequality, and probing an array of contextual variables that may help explain the historical drivers of service equity patterns. The cities in our sample have been chosen based on the availability of spatial information related to service facility locations, neighborhood units, and class-based residential clustering—a strong constraint given the dearth of information available for premodern cities. While data availability limits the sample and prevents a more systematic comparison, we attempt to compare two or more cities within each of several urban cultural traditions to allow intracultural comparisons that better isolate variables such as city size and the peculiarities underlying the historical development of individual settlements. The larger study transcends this pilot study by addressing a set of contextual variables that may influence service access patterns, such as governance structures, levels of commercialization, and the independent power of religious hierarchies and voluntary associations. While the small sample size of the pilot study prevents consideration of these factors, the ultimate aim is not only to compare service access and equity patterns across a diverse set of cities but to understand better which contextual variables likely contribute to patterns of service access. Understanding how class mobility, ethnic diversity, and governance tend to affect urban service equity in premodern cities can help inform modern efforts to ensure service equity in different cultural contexts. Furthermore, as an interdisciplinary comparative study of premodern urbanism, this project has wider implications for academic research. By comparing a range of spatial and nonspatial data across a variety of urban traditions from numerous disciplinary perspectives, this study helps generate fresh insights about urban systems that can inspire future urban studies. Simply applying spatial perspectives to premodern cities represents a relatively novel form of historical analysis in line with modern emphases on space emanating from geography, planning, and other disciplines. Using diverse theoretical perspectives to understand a cross-cultural sample of ancient cities pushes forward our understanding of how the urban political economy generates and mediates inequality in public service access.

Spatial Equity and Service Accessibility in Premodern Cities The concept of equity describes an ideal of “fairness.” Spatial social scientists primarily focus on mapping distributive equity, studied in terms of both the distribution of harms (e.g., toxic

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facilities3) and benefits (e.g., parks4). Studies of sociospatial equity in residential access to public or private services have been conducted within a broad variety of disciplines. Most have arisen from social geography and urban planning,5 but spatial inequity has also been addressed in political science,6 anthropology,7 sociology,8 economics,9 leisure and recreation studies,10 and health.11 Like most spatial equity studies, we focus on the distribution of service benefits requiring travel to spatially fixed infrastructure. Equity is usually defined in terms of the accessibility of services, often equated with the spatial proximities between residents and service facilities.12 Talen summarizes the primary methodological approaches to measuring proximity; the “container” approach (a count of the number of facilities within a defined geographical area) and the “minimum distance” approach (the distance between origin and nearest facility) are most common.13 Often proximities are calculated by determining residential origin points (usually the approximate center of a neighborhood-like unit) and distance to facility locations, measured by Euclidean (straight line), Manhattan (travel on right-angled blocks), or street network distance. Four widely cited conceptions of equity are applied to accessibility measures: equality, need, demand, and market criteria.14 Certain socioeconomic characteristics for origin areas are then compared to accessibility to map spatial equity. There is no direct and objective way to measure equity, however. Scholars describe patterns of service distribution, and determinations of equity are always made in context. Our study addresses two deficiencies in the urban literature: (1) the absence of equity studies rooted in archaeological or historical approaches with a longer temporal scale and (2) scarce attention to non-Western cities in general. We agree with Tilly’s call to put “contemporary inequalities into historical perspective” not only because the historical origins of inequality are underexplored but also because premodern cities can shed light on the methodological and ontological assumptions undergirding the modern service equity literature.15 For example, most modern studies assume that services are typically provided by major institutions in a “top-down” fashion, whereas in some documented premodern cities many urban services were provided “bottom-up” by individual households or neighborhood-based groupings.16 Sometimes grassroots, neighborhood-based groups can provide services more equitably than major institutions.17 This change in emphasis opens the door to considering other variables affecting service distribution. McLafferty, for example, hypothesizes that service provision can be driven by “spatial structure” (e.g., city size/shape, natural geographical barriers) instead of deliberate siting decisions.18 Study of premodern urban service equity can contribute to a variety of historical and archaeological debates and help clarify the historical production of inequality.19 In an influential study, Sjoberg hypothesized that in many premodern settings elite groups tended to cluster in central city areas to remain close to the main governmental and religious facilities that enhance elite social and political control.20 A number of historical studies based on Western European cities report data that conform to Sjoberg’s model,21 but others have criticized its applicability in individual cases.22 Archaeologists have applied Sjoberg’s ideas to a few ancient cities.23 Mesoamerican Maya cities frequently have palatial residences close to temples or other public buildings as do “Standard Plan” layouts in south-central Veracruz.24 Other archaeological studies find varying but significant degrees of elite clustering in central city locations, such as in Teotihuacan25 and Iron Age Israelite cities.26 In many studies, elites are more favorably positioned in relation to services than the general population.

Sample of Cities and Methods Our exploratory study compares the spatial distribution of neighborhoods and services in six premodern cities—drawn from a variety of regions, cultures, and histories—to test the feasibility

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of a larger, more systematic comparative analysis of premodern cities. We used a diverse-case sampling strategy to incorporate three kinds of variability: diversity in urban traditions; city size; and type of documentation (archaeological and historical). Our sample includes two very large archaeological cities from ancient Mesoamerica (Teotihuacan, Mexico; and Tikal, Guatemala) and four smaller cities from the Old World with a combination of historical and archaeological documentation (Bhaktapur, Nepal; Lamu, Kenya; Chester, England; and Empuries, Spain). Service facility locations and neighborhood boundaries were based on published maps, when available, or identified based on published information describing the built environment. In archaeological cases, neighborhoods were determined by spatial estimation. Maps of service distributions analyzed in these cities are provided in Figures 1 and 2. The specific urban services offered in any city depend on its urban tradition as well as on idiosyncratic factors. We selected three common services for our comparisons: religious or ritual facilities, commercial/market facilities, and spaces for general assembly. These services were chosen based on their importance and our ability to define and locate the service facilities in drastically different urban cultures. While the quantity and quality of services available at a given location may be more important for service equity than facility location alone,27 these variables are not considered in this study because of lack of data. For archaeological cases lacking historical documentation, we base our interpretations of architecture and services on morphological characteristics and excavations of similar categories of buildings and spaces, both at the individual cities analyzed and at others in the same urban tradition. Each category of service facility can vary by spatial or demographic scale. For example, many premodern cities had three levels of religious facility: a small number of high-order facilities (e.g., large, central temples), a larger number of intermediate-order facilities (e.g., neighborhood shrines), and a still larger number of low-order shrines that served individual residences. For assembly facilities, our analysis derived inspiration from a previous classification of “citywide” and “intermediate” scales of open space in urban history.28 In this pilot study, we include only the high-order and intermediate-order facilities, since they have broader urban roles, and we combine them in our analyses here; in the future, we may analyze them separately. In order to compile the most reliable information about facility locations, neighborhoods, and contextual variables, we synthesized data from a broad variety of sources. We include both urban archaeological and historical data, as well as sources from anthropology, architectural history, and geography. Our research proceeded in two steps. First we investigated the historical, archaeological, and cartographic sources for a number of cities. Those that lacked sufficient data were dropped from the study. Our second step involved detailed research on the remaining cities that compared available sources of textual and archaeological data. Specific sources deemed questionable by peer researchers were used critically. For example, whereas El Zein’s (1974) claims about Lamu’s historical and cultural development are questioned by Middleton (1992) and others, his more general observations about Lamu’s urban form, neighborhood delineation, and assembly patterns agree with other sources. We therefore included the latter but not the former in our research. The sizes and population densities of cities in our sample vary greatly. Table 1 provides basic metric data, and more complete measurements are found in Table A1 of the Appendix. The following sections briefly summarize the historical and geographical context of each case study as well as processes of data collection and preparation.

Lamu, Kenya The Swahili port town of Lamu, an island site just off the present-day Kenyan coast, was economically dependent on seasonal maritime trade; the government was influenced by, but functionally independent from, a series of colonial rulers, including Portuguese, Omani, Zanzibari,

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Figure 1.  Service distribution in large cities. Only the central, mapped portion of Tikal is included.

and British. Lamu’s deeply conservative Islamic tradition dictated its political structure—a citystate ruled by a patrician religious oligarchy drawing power from lineage-based social classes— as well as an urban form of densely packed stone houses accessed by a hierarchy of narrow streets similar to other Arab-Islamic cities with filtered access.29 During our mid-nineteenthcentury focal period, the town was roughly divided into twenty-seven neighborhoods defined as

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Figure 2.  Service distribution in small cities. Note that the scale differs from that used in Figure 1.

much by shifting kinship/lineage relations as by urban space itself.30 Lamu’s services are closely related to religion: local, community-maintained mosques provided daily religious services (intermediate-order) as well as school and social interaction space;31 the Friday (Jumaa) mosque represented the main, high-order congregational space.32 An array of local shops along the main thoroughfare provided market services.33 Modern Google Maps aerial imagery of Lamu was used to construct KML files indicating the locations of major landmarks (the Fort, main street, and coastline), which were imported into ArcView10 as a spatially relative drawing. The positions of these landmarks were used to georeference text-based maps and create neighborhood and service shapefiles: neighborhood boundaries;34 neighborhood mosques and Jumaa Mosque;35 and shops, approximated by the position of

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Stanley et al. Table 1.  City Size and Density. Areaa Small cities  Lamu  Empuries  Bhaktapur  Chester Large cities   Tikal (entire city)   Tikal (analyzed portion)  Teotihuacan

Population

Densityb

Max dimc

0.4 0.5 1.1 2.1

6,000 3,500 40,000 4,000

14,600 6,900 35,800 1,900

1.54 1.16 1.96 2.42

120.0 16.0 22.0

60,000 15,000 100,000

500 900 4,500

15.50 5.11 9.08

a. Square km. b. Persons per square kilometer. c. Greatest distance across the city (km.) For Tikal (entire city), city boundaries are hard to determine because of its low-density character, and max dim. is an approximation.

the main street.36 The three available hand-drawn maps of mosque positions mostly aligned when cross-referenced, but there were some notable differences; Ghaidan’s map was chosen as the representation with the most detail and fewest discrepancies.37

Empuries, Spain Empuries was a binucleate colonial city in Iberia. Although its origins stretch back to the Iron Age, both the Greeks and the Romans created colonies at this coastal site. Both Neapolis (the older Greek colony) and the Roman city (located several hundred meters west of Neapolis) were occupied during the Late Republican and Early Imperial era (ca. 200 BC to AD 200), our focal period. The city had a distinctly multicultural composition, with Greek traders and their descendants living in Neapolis, Roman citizens enjoying favored status in the southern sector of the Roman city, and native Iberians dwelling in the more remote northern sector, separated by a wall cutting the Roman city in half.38 Digitization utilized maps from Kaiser’s study of urban spatial relations at Empuries.39 Shapefiles corresponding to Kaiser’s administrative, religious, and commercial categorization of space were digitized for the thoroughly excavated portion of the site. Despite nearly 100 percent coverage of Neapolis, only 20 percent of the Roman city has been excavated. Neapolis contained several typical Greek structures and their associated services; the highest order included an agora and public marketplace, as well as several large temples dedicated to Greek gods, while individual household shops (tabernae) represent a finer scale of services than other cases. Similarly, the Roman city included a forum and temples to Roman gods (high-order), as well as many intermediate-level shops.

Bhaktapur, Nepal Described as an exemplar of Newar urbanism in premodern times,40 Bhaktapur featured a distinctive Hindu-Buddhist culture and corresponding urban form of narrow streets, public squares, and various shrines during the “Three Kingdoms” period (AD 1520–1768), our focal period.41 Bhaktapur’s predominantly Hindu “caste” or “macrostatus” system directed the city’s division of labor and complex calendar of ritual events that holistically incorporated all residents.42 Bhaktapur is traditionally divided into twenty-four neighborhoods, each oriented around a local square used for agricultural, commercial, ritual, and social purposes, and each assigned to a specific shrine— an unhewn stone (pitha) marking the site for public rituals.43 Citywide assembly is provided by

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three major squares (high- to intermediate-order)—Darbar, Tacapah, and Taumadhi—all of which are home to numerous temples and religious/recreational events. Intermediate-level market services include small shops and bazaar spaces lining virtually the entire length of the main city road. GIS maps of neighborhoods and services used a basemap of present-day Bhaktapur, derived from Bing Maps aerial imagery. Although this is a modern image, the historic core of the city is largely intact. A series of district and service maps from textual sources were scanned and georeferenced to align with the basemap using key visible monuments (e.g., reservoirs, temples, and squares). A series of shapefiles were manually constructed from a variety of sources to represent neighborhood and city boundaries; Darbar Square; Tacapah/Taumadhi Squares; main road; Ganesa (pitha) shrines; and household locations of the six major caste groups.44

Chester, England Chester, founded as a gridplanned military fortification during Roman rule, served as an ecclesiastical, administrative, and economic center in the Middle Ages (focal period AD 1250–1500). Like other medieval European towns, guild-based craft production was economically crucial and triggered occupational clustering.45 Chester’s residents were granted the legal freedoms of “burgage tenure,” which allowed land ownership if residents paid taxes and followed other civic requirements. Urban citizenship could be inherited, purchased, or bestowed by the local government, leading to a social hierarchy in which an elite merchant oligarchy received key governmental positions while the social mobility of noncitizen craftsmen, servants, and temporary laborers was limited.46 Urban form and density varied between areas of dense housing and scattered agricultural lands. Chester was divided into four administrative wards (four quadrants), as well as nine parishes surrounding Christian neighborhood churches;47 extramural suburbs to the north, south, and east represented socioeconomically important yet nonofficial neighborhoods, home to many of the poorest residents. Chester’s services included parish churches (intermediate-order), important hubs of religious and social activities; shopping in the “Rows,” a unique form of urban storefront; and the Common Hall (high-order), which hosted a range of civic assemblies, courts, and meetings.48 The Mapping Medieval Chester Project (MMCP) provided GIS information regarding administrative neighborhood boundaries, parish neighborhood boundaries (Chester Parishes, c. 1500; cut by urban extent); the “Rows”; and parish churches.49 The Common Hall’s location was mapped based on textual description of its street address and an MMCP map (Chester Streets, c. 1500).50

Tikal, Guatemala Tikal was an independent capital from ca. 900 BC to AD 900.51 The Late Classic period of growth includes our focal period (AD 692–800). An example of low-density tropical urbanism,52 Tikal contained palaces, temples, a ball court, plazas, municipal reservoirs, plaza groups, and a likely marketplace connected by elevated paved roads in the urban core.53 Residences were dispersed over an area of approximately 120 km2 bounded by swamps and an embankment system.54 A residence unit comprises a set of buildings around a courtyard. Our analysis focuses on the innermost 16 km2 known as “Central Tikal” for which maps are available.55 Nine detailed 1-km2 map quads of central Tikal56 were scanned and georeferenced prior to this project by Jerald Ek and Juliana Novic, who digitized structural information . We also digitized groups located outside the central 9-km2 maps, but within the bounds of a less exact 16-km2 map. This enabled us to eliminate residences closer to the outer boundary than to each other, allowing a cluster analysis of nearest-neighbor distances using K-means. A solution involving 15 clusters was chosen based on neighborhood size at Mesoamerican cities

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(Aztec calpulli57 and Maya neighborhood clusters58). These 15 clusters helped us create 18 neighborhood polygons that also took into account natural topographic separations such as lowlying, flood-prone areas. After ranking residences by size of architectural footprints (which correlate with total labor investment59), we noted a break in the distribution that separated a long “upper tail” of larger footprints from the rest. We defined this top echelon, equaling 4.6 percent of all residences, as “elite.” Five additional structures classified as “palaces” by Tikal’s excavators were included in the elite census even though their footprints were below the cut-off. Higher-order facilities analyzed include formal plazas and causeways likely used for large public gatherings and processions; massive temple-pyramids for ritual activity, and smaller twinpyramid complexes likely used in calendric ceremonies; and a section of the East Plaza tentatively identified as a marketplace.60

Teotihuacan, Mexico In the highlands of central Mexico near Mexico City, 1,100 km from Tikal and ethnically very different, Teotihuacan grew to cover ca. 20 km2 by AD 150, with a population near 100,000.61 The city was the capital of a large regional state before decline in the 500s and catastrophic collapse in the 600s. Temple pyramids, elite residences, and other civic-ceremonial structures lined a broad central avenue for 2.15 km. Outside those structures, most people lived in architecturally substantial walled compounds, each with multiple apartments and shrines, separated by straight narrow streets near the center and more widely spaced toward the outskirts. Possibly as many as 15 percent of the population lived in insubstantial structures interspersed among the compounds. Several neighborhoods of craft workers have been identified in scattered districts. A large enclosure near the central avenue may have been a major marketplace. We used Millon et al.’s 1:2,000 site map to digitize structures, which were categorized using the functional description assigned by surveyors of the Teotihuacan Mapping Project (TMP).62 The Project personnel characterized apartment compounds as having high, intermediate, uncertain, or low status. Neighborhoods were created using Robertson’s N-clusters, which grouped apartment compounds based on statistically derived similarities in the mix of ceramic assemblages for the Tlamimilolpa phase, our focal period (AD 170–350).63 The ceramic assemblages were used as proxies for status. These N-clusters were subdivided, using natural- and proximity-based boundaries to create twenty-two large spatial areas (districts or large neighborhoods). Services analyzed include large formal plazas and the Avenue of the Dead, which likely functioned as high-order places of assembly; the monumental pyramids (high-order) as well as smaller temple-platforms (intermediate-order) that served as foci for religious ritual; and the probable high-order marketplace known as the Great Compound as well as structures tentatively identified as intermediate-order neighborhood marketplaces by TMP surveyors.

Analyses of Service Access Each case study was analyzed using ESRI ArcView10 GIS mapping software. In most analyses, center (centroid) points of neighborhood polygons were used to approximate the origin locations of all local residences, a simplifying procedure widely shared in equity studies64 despite potential aggregation error.65 Proximity to services was measured using the Euclidean minimum distance between origin points and the nearest service; minimum distance is considered the most effective measure of neighborhood-based service provision by some authors.66 Euclidean distance was used instead of road networks, because in some case studies it is impossible to map thoroughfares and determine which were publically accessible. Services were only chosen for analysis if they were likely publically accessible; in many historical cases, details about public accessibility are

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Table 2.  Neighborhood Distance to Facilities. Distance to All Facilitiesa   Small cities  Lamu  Empuries  Bhaktapur  Chester Large cities  Tikal  Teotihuacan

Mean Distance to Facilitiesa

% of Neighborhoods >800 mb

Mean

Median

Market

Assembly

Religious

Market

Assembly

Religious

194 308 170 354

146 330 139 279

146 248 139 279

367 346 262 533

68 330 108 250

0 0 0 0

11 0 0 23

0 0 0 0

969 963

796 1,043

1,356 1,043

756 1,521

796 326

89 41

44 68

44 9

a. Mean distance (in meters) from neighborhood centroid to the closest facility. b. Percentage of neighborhoods over 800 m from the closest facility.

available, but in archaeological cases, access was often assumed because of lack of contextual data. When judging equity in access to facilities, we focus on both absolute and relative distances between neighborhoods and services. Finally the positions of elite households, available in three of six cases, were used to determine whether service access correlates with social or economic status.

Absolute Distances to Services Our analysis of absolute travel distances between residences and service facilities reveals great variation among cities. Not surprisingly, much of this variation is explainable by scalar differences between the large and small cities. The data also suggest a possible relationship between urban population density and service access. In modern planning literature, “walkability” thresholds for transit-oriented or other urban developments are usually set at ¼ to ½ mile (about 400– 800 meters).67 Before the modern era, when walking was the primary form of movement for urban residents, walkability ranges were surely much wider than in contemporary cities. The most significant differences in our sample appear between small and large cities (see Table 1). The magnitude of travel distances between residences and service facilities is determined in part by the size and shape of a city. Although travel distances can be greater in cities with an elongated shape, in general small cities cannot have large travel distances within the settlement because of their size. Although large cities can have much higher travel distances, actual distances to services do not have to be higher than in small cities. If most facilities exist at the neighborhood scale (i.e., if intermediate-order facilities are widely distributed), then travel distances to services can be similar to those in smaller cities. We calculated distances between service facilities and the centroids of individual neighborhoods, examining travel distance between neighborhoods and facilities in two ways. First, we calculate the mean distance between each neighborhood centroid and each of the three types of service facility. Second, we consider the distance data with respect to the contemporary planning thresholds of 400 and 800 meters. In our sample, the mean facility distance (for all service types) among the four small cities (Lamu, Empuries, Bhaktapur, and Chester) is 256 meters, well within the 400-meter threshold used by modern planners. In these cases, the mean absolute distances to the three types of services do not vary greatly (Table 2 and Figure 4). Only one of the twelve mean distances for small cities (assembly facility distance in Chester) is larger than 400 meters (Table 2). While some of

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Mean neighborhood distance (m)

1600 1400 1200 1000 800

Market

600

Assembly

Religious

400 200 0 Lamu

Empuries

Bhaktapur

Chester

Tikal

Teohuacan

Figure 3.  Mean travel distance to market, religious, and assembly services. Cities are arranged from smallest to largest spatial area, counting only central Tikal.

Mean travel distance (m)

1,200 1,000

Tikal Teohuacan

800 600

Chester

400

Empuries

200

Lamu Bhaktapur

0 0

10,000

20,000

30,000

40,000

Populaon density Figure 4.  Graph of travel distance and density. The two large cities are separated at the top of the chart by their larger travel distances. Density is portrayed in persons per square kilometer.

these cities do exhibit unequal access to services, the magnitude of those differences is not great. All of the four small cities have good access to urban services. In contrast, the two large cities (Tikal and Teotihuacan) exhibit greater distances to the three types of service. Mean travel distances are around 1,000 meters, four times the mean for the smaller cities (Table 2). These cities have quite different profiles in their distances to the three types of service facility (Figure 3). Most neighborhoods have mean facility distances over 400 meters, and many have distances greater than 800 meters (Table 2). Two categories—marketplaces at Tikal and assembly

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spaces at Teotihuacan—have distances close to 1,500 meters. For marketplace distances at Tikal, however, the high figure may reflect the difficulty of recognizing intermediate-level facilities. Our cases suggest the possible role of population density in generating patterns of urban service provision in premodern cities. The six cities in our sample vary tremendously in density (Table 1). A plot of mean service distance by density reveals separate but parallel patterns for the large and small cities (Figure 4). Within each group, service distance declines slightly with increasing density. Ladd showed that the number of services in contemporary U.S. cities is correlated with both population size and density, and Rasterhoff found similar patterns in seventeenth-century Dutch cities.68 The results for our small sample suggest possible regularities that can be tested in our larger study. With increasing density, there is potentially a greater concentration of economic and social resources to support local services or to create sufficient demand for them (or both).

Relative Measures of Access Like absolute measures, relative measures of access allow both intra- and interurban comparisons among neighborhoods. Relative measures, however, control for city size and absolute distance by creating a city-specific ranking of neighborhood accessibility to service facilities. The case studies indicate that relative access is largely shaped in a concentric pattern radiating from well-serviced central city areas, with the exception of Bhaktapur. The intraurban range between high- and low-access neighborhoods remains sizeable for both large and small cities, but the range is smallest for the densest cities, pointing again to a possible correlation between urban density and access. Overall, there is considerable variation in relative service access among our six case studies, possibly driven by both spatial structure and sociopolitical factors. The calculation of relative access scores (RAS) indicates above- or below-average service accessibility per neighborhood in comparison to all other neighborhoods in the city. RAS is determined by finding the difference between a neighborhood’s absolute distance and the citywide mean neighborhood distance to a service, and dividing the difference by the standard deviation of all distances to that service (a Z score). For each city, RAS was calculated per neighborhood for each service (religious, assembly, and market). Composite relative access scores measuring generalized service accessibility represent an average of the three RAS for each neighborhood. Composite RAS were then divided into six groupings (less than –1, –1 to –0.5, –0.5 to 0, 0 to 0.5, 0.5 to 1, and more than 1) to yield six composite access ranks (from 1, highest access, to 6, lowest access). Comparing the composite access ranks for all neighborhoods within a city provides a measure of intracity equity. Composite access ranks are mapped and compared across all six cities in Figures 5 and 6. The spectrum from light to dark shading indicates decreasing levels of neighborhood service accessibility. Table 3 shows the range of composite RAS for each city, indicating the extremity of difference between the most and least service accessible neighborhoods (based on how far the RAS extends beyond –1 and +1). When access rank maps of different cities are compared, they illustrate comparative differences in equity. Five of the six cities display a spatially concentric “bull’s-eye” pattern of relative service access (Figures 5 and 6), where core neighborhoods tend to have above-average access while peripheral areas have below-average access. This pattern can be attributed in part to the predominance of centrally located, higher-order services in certain cities. While the political influence of centrally located elites may be a factor, concentric access patterns are not solely determined by social status, as we address in the next section. The exception to this pattern is Bhaktapur, which exhibits a more scattered pattern of relative service access, including some high-access

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Figure 5.  Relative service access in large cities. Darker shading indicates worse service access. As in Figure 1, the map only portrays the central city area.

neighborhoods positioned peripherally. Many variables differentiate Bhaktapur from other case study cities, including higher population density,69 an exceptionally long commercial thoroughfare,70 and a cultural tradition stressing ritual unity among social classes and certain checks upon political power.71 One of the strongest physical factors derives from Bhaktapur’s urban history as two separate towns that grew together into one city; as a result, the city contains three dispersed city-scale plaza spaces used for general assembly.

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Figure 6.  Relative service access in small cities. Darker shading indicates worse service access. As in Figure 2, the scale differs from that used in Figure 5.

Four of the six cases (Teotihuacan, Tikal, Empuries, and Chester) exhibit intracity distributions of relative service access showing greater proportions of neighborhoods with both extremely high and extremely low composite access ranks. The most privileged neighborhoods in these cities often display an RAS well below –1, while disadvantaged neighborhoods score well above +1, and sometimes above +2 (Table 3). These patterns indicate significant intraurban inequity in access to services. For example, Chester’s central neighborhood has relatively high access while peripheral suburbs have extremely low access, and these disparities are magnified when considering that city walls divided central from peripheral neighborhoods. Textual evidence suggests

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Stanley et al. Table 3.  Maximum and Minimum Relative Access Scores.

Small cities  Lamu  Empuries  Bhaktapur  Chester Large cities  Tikal  Teotihuacan

Minimum

Maximum

Range

−0.81 −1.28 −0.91 −1.15

2.06 1.82 1.38 2.17

2.87 3.10 2.29 3.32

−1.75 −1.10

2.03 1.66

3.78 2.76

Note: Negative values indicate the most service accessible neighborhood, and positive values, the least service accessible.

that many of the city’s poorest residents lived in these peripheral neighborhoods,72 indicating that access may have correlated with income- and status-based groups. Lamu, like the four cities above, displays a relatively concentric pattern of service access and contains peripheral neighborhoods with extremely low service access. The city does not include core neighborhoods with the highest composite access ranks, however, indicating some degree of higher equity. Bhaktapur neighborhoods also display a large number of mid-range ranks and no highest ranks, while in addition exhibiting the smallest citywide range of access scores (Table 3). Despite intraurban inequality in Lamu’s and Bhaktapur’s service access, they exhibit a more constrained distribution of relative access that contrasts with the other cities. It is hard to posit specific factors contributing to this difference, but it is notable that they possess the highest two population densities among the case studies, pointing to the importance of investigating density effects more closely in the expanded study.

Elites and Service Access Although political or economic status in premodern cities can be difficult to study, we found data for the spatial distribution of elite households in three of six case studies (Bhaktapur, Tikal, and Teotihuacan) and compared these distributions with absolute and relative measures of service accessibility. Our results suggest several interesting patterns to guide future research. First, the percentage of neighborhoods with elite residences—a measure of elite clustering—seems to be positively associated with the citywide proportion of elite households in two of three cases. Second, elites in all three cities have better access to services than nonelites based on household-distance measurements. Nevertheless, elite presence in a particular neighborhood does not automatically translate into better service access for the nonelite population. Comparing elite abundance with elite distribution throughout the city provides a simple, preliminary measure of equity (Table 4). The city with the highest proportion of elite households to nonelites across the total population of residential units, Bhaktapur, also maintains the highest percentage of neighborhoods with elite presence. This implies that the difference in service access between elites and nonelites in Bhaktapur should be relatively constrained. A comparison of elite abundance and distribution in our two large cities helps illustrate these effects. Although Teotihuacan has twice as many elite residences as Tikal, it has fewer neighborhoods with elite presence than Tikal (Table 4). The implication here is that Teotihuacan’s elites are more clustered and separated from the general population, possibly contributing to inequity in service access—a hypothesis supported by comparing elite and nonelite household distance to services (Table 5).

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Table 4.  Elite Distribution and Composite Service Access. Elite Households

City

Number

Bhaktapur Tikal Teotihuacan

551 35 286

Percentage

Neighborhoods with Elite Households (%)

Regression (r2)a

Moran’s I: Elitesb

Moran’s I: Accessc

16.0 4.6 9.0

91.7 77.8 54.5

0.23 0.16 0.34

0.38 −0.01 0.28

0.18 0.20 0.45

a. Linear regression comparing the percentage of elites and composite access score, by neighborhood. b. Spatial structuring of elite household locations (r2). c. Spatial structuring of composite relative access scores, by neighborhood (r2).

Table 5.  Elite and Nonelite Service Access. Mean   Religious facilities  Bhaktapur  Tikal  Teotihuacan Assembly spaces  Bhaktapur  Tikal  Teotihuacan Market facilities  Bhaktapur  Tikal  Teotihuacan

Median

Range

Elite

Nonelite

Elite

Nonelite

Elite

Nonelite

103 498 74

122 723 400

92 370 48

114 650 299

395 1,560 551

433 2,176 1,697

230 477 310

281 717 1,511

224 300 215

274 662 1,359

823 1,643 2,570

633 2,241 4,314

90 917 369

154 1,331 996

67 656 361

137 1,320 732

540 2,001 1,976

561 2,485 3,565

a. Distance from neighborhoods to the nearest service, in meters.

Before exploring the relationship between elites and services, however, we needed to understand whether spatial clustering among elites and among services alone could account for any correlative patterns. “Moran’s I” is a measure used to quantify spatial autocorrelation.73 Spatial autocorrelation refers to the condition in which nearby cases have attributes that are more similar than those of cases located farther apart. Such spatial clustering causes problems for statistical comparisons of cases, since most statistical methods are based on the assumption that the cases are independent of one another. Spatial autocorrelation introduces the danger of positing a false relationship between sets of geographic data. If the value of Moran’s I is high, then many formal statistical methods are inapplicable.74 We calculated Moran’s I for the spatial arrangements of elite households and composite neighborhood service access in the three cities. While the values vary considerably (Table 4), they reveal low levels of spatial autocorrelation. The highest value (r2 = 0.45) points to low to moderate spatial structure among neighborhood service access in Teotihuacan. These Moran’s I values indicate that we are warranted to use statistical methods to examine quantitative patterns among the elite residences and service facilities at our sites.

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We evaluated whether elites disproportionately reside in neighborhoods with more favorable service access, using linear regression to compare the composite access ranks for city neighborhoods with the percentage of elite households in each neighborhood (Table 4). This analysis focused upon relative measures of access and elite data aggregated at the neighborhood scale. Neighborhood service access and elite presence are not strongly correlated at the neighborhood level. To provide a finer scale of equity analysis, we mapped the household locations of elites and nonelites in our three case studies and calculated the distances between these locations and the nearest services (Table 5). This calculation helps avoid aggregation errors while focusing on absolute, not relative, measures of access. We found that elites consistently enjoyed better access to services in all three samples with individual residence data. The difference between elites and nonelites is most pronounced in Teotihuacan, where mean distance for nonelites to the nearest religious service, for instance, is more than four times that for elites. The predominance of higherorder, centralized service clustering in Teotihuacan (most pyramids and temple-platforms line the Avenue of the Dead in the city center) combined with central elite clustering produces these patterns, but it is hard to determine whether elite manipulation of service locations or elite residential choices are primarily responsible. Since elites have shorter distances to services than nonelites in all three cities, it might be anticipated that neighborhoods containing more elites will have better service access. The lack of a strong predictive relationship between the percentage of neighborhood elites and that neighborhood’s composite access rank, as shown by small r-squared values for the linear regression, indicates otherwise (Table 4). Thus, the absence of elites does not relegate a neighborhood to lowered service access, and the individual residential advantages of elites are not extended strongly to the surrounding neighborhood residents.

Discussion and Conclusions One goal of our research was to establish a set of methods and procedures that could be applied to a larger and more systematic sample of cities in the future. Although our sample is too small to generate reliable findings on service access in premodern cities, this exploratory pilot study shows that such a comparative analysis is feasible: we were able to obtain, map, and analyze data on neighborhoods, elites, and service facilities from historical and archaeological sources. We identified three types of service common to a variety of urban traditions (religious, assembly, and market services) and adapted methods from geography and planning for measuring and comparing equity of service access. We hope that these methods can be used and refined by others to further the rigorous spatial analysis of past cities. Our data suggest that service access in premodern cities was influenced primarily by spatial distribution patterns (e.g., centrally located vs. dispersed facilities; geographical barriers) and elite effects (e.g., political influences on service provision; residential choices). In line with research linking spatial urban structure to service access, our findings suggest that the pathdependent nature of historical settlement and development patterns should be studied more closely as an explanatory variable in the larger study; for the pilot study, the small sample size and lack of historical development data for many cities restricts our conclusions in this regard. While most modern equity studies do not specifically address purely spatial variables like urban density, academic debate over a study that does investigate spatial structure indicates the value of studying it in more detail.75 This debate also indicates that urban structural factors could provide an effective conduit for comparing ancient and modern service access patterns, which represents a future goal of our project. In our larger comparative study, we will also explore a range of other variables, including sociocultural urban traditions, regional political factors, and the path

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dependencies of city population growth. Immigrants frequently settled at the city margins and had to adapt to the established built environment and cultural privileges of residents (e.g., specific rights to land or resources in Chester). Sociopolitical conceptions of citizenship may emerge as a revealing line of inquiry, given the drastically different ways in which urban citizenship can be culturally codified (e.g., holistic metaphysics in Bhaktapur; legal definitions in Chester; religious lineage in Lamu). The relationship between population density, city size, and distribution of services proved particularly intriguing despite the small sample of cases. Smaller cities enjoyed favorable access to higher-order services compared to large cities. Urban density affected both absolute and relative access measures, which is particularly noteworthy given contemporary debates over dense planning in modern cities.76 Increasing urban density not only generates better absolute access per capita to existing services by definition, but it may possibly create multiplier effects related to sociopolitical organization that better proliferate services across a city. One of the most striking patterns to emerge from our study is a concentric tendency of neighborhood service access in five of the six cities. This configuration is in line with Sjoberg’s descriptive model,77 although he focused on elite residence locations while our data measure access to services. Our study uncovers a more nuanced relationship; most notably, elites have better access than nonelites, but neighborhoods with elite residences do not consistently have better access than neighborhoods without elites. In line with Sampson’s argument that the neighborhood is a crucial institution with its own effects and consequences,78 our results suggest that the neighborhood itself plays a role as service provider, either via local provision or by demanding services from a higher level of government. In classifying service facilities as high-order, intermediate-order, and low-order, we employ the terminology of economic geography.79 Urban service facilities can be viewed as having threshold values related to the minimum level of “demand” for their services, as well as ranges indicating the maximum spatial extent of individual services. The proliferation of urban services through more widely distributed intermediate-order facilities, which yield better access, may indicate that some neighborhoods or districts reached a critical mass of demand for self-provision of services. This pilot study demonstrates both an opportunity and the need to conduct comparative urban research to better understand the roles of neighborhoods and elites in equitable distribution of service provision. Although our small study demonstrates that size and density clearly affect patterns of service provision, it also illustrates considerable variability in neighborhood access within and across cities, which is not simply a function of elite clustering. Ultimately, we are working toward a better understanding of urban traditions, historical experiences, and governance in premodern and modern neighborhood contexts in order to push research beyond a contemporary Western focus. Our study responds to growing calls for broader understanding of urban experiences and extends it into the premodern world. Comparative studies incorporating a spatial perspective on historical urban functioning are relatively underexplored, and, regardless of this project’s ultimate findings, this interdisciplinary exercise promises to yield many new insights about urban processes more generally. Our continuing research highlights the importance of neighborhoods, the role of urban citizenship, and impact of population density on public service provision. These preliminary findings demonstrate the potential for the approach to be expanded and replicated. This study of urban service access is but one example of the ways in which modern scholarship can benefit from a transdisciplinary, long-term perspective on urban dynamics.

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Appendix Table A1.  Descriptive Data on the Six Cities.

Descriptive data   Size (km2)  Population   Density (persons/km2)   No. of neighborhoods Neighborhood size   Mean (km2)   Median (km2)   Range (km2) Religious facilities   No. of facilities   Facility scalea Neighborhood distances   Mean (m)   Median (m)   Range (m) Assembly spaces   No. of facilities   Facility scalea Neighborhood distances   Mean (m)   Median (m)   Range (m) Market facilities   No. of facilities   Facility scalea Neighborhood distances   Mean (m)   Median (m)   Range (m)

Lamu

Empuries

Bhaktapur

Chester

Tikal

Teotihuacan

0.41 6,000 14,634 27

0.51 3,500 6,863 36

1.12 40,000 35,812 24

2.07 4,000 1,935 13

16 15,000 938 18

22 100,000 4,545 22

0.015 0.013 0.054

0.012 0.013 0.010

0.047 0.044 0.077

0.156 0.096 0.425

0.578 0.541 0.783

0.970 0.890 1.800

23 2

3 1

24 2

9 1, 2

18 1, 2

239 1, 2

68 64 161

330 265 570

108 105 272

250 143 711

797 743 1,762

326 228 1,056

1 1

3 1

3 1, 2

1 1

18 1, 2

9 1

367 308 1,022

346 269 648

262 235 586

533 479 970

756 760 1,820

1,521 1,245 3,543

Many 2

37 2

Many 2

Many 2

1 1

14 1, 2

146 124 363

248 180 581

139 114 330

279 229 791

1,356 1,418 2,141

1,043 752 2,927

a. Facility scale: 1: high-order facility; 2: intermediate-order facility.

Acknowledgments We thank Robert Fry, Niels Gutschow, Alan Kaiser, and Keith Lilley for help with sources and data. Daniel Shaevitz and Scott B. Kelley provided technical assistance, and Kristina Calderon and Chelsea Ferguson helped with digitizing and documentary research. Fellow project members Christopher Boone and Sharon Harlan contributed ideas and perspectives.

Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Our research was carried out as part of the project “Urban Organization through the

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Ages: Neighborhoods, Open Spaces, and Urban Life,” funded by the President’s Strategic Fund at Arizona State University (http://cities.asu.edu/). It is part of the umbrella project “Late Lessons from Early History” in the School of Human Evolution and Social Change (ASU).

Notes  1. V. J. Del Casino Jr. and J. P. Jones III, “Space for Social Inequality Researchers: A View from Geography,” in The Sociology of Spatial Inequality, ed. L. M. Lobao, G. Hooks, and A. R. Tickamyer (Albany: State University of New York Press, 2007), 233–51.   2. M. E. Smith, “The Archaeological Study of Neighborhoods and Districts in Ancient Cities,” Journal of Anthropological Archaeology 29 (2010): 137–54; A. M. York, M. E. Smith, B. W. Stanley, B. L. Stark, J. Novic, S. L. Harlan, G. L. Cowgill, and C. G. Boone, “Ethnic and Class-Based Clustering through the Ages: A Transdisciplinary Approach to Urban Social Patterns,” Urban Studies 48, no. 11 (2011): 2399–415; B. W. Stanley, B. L. Stark, K. L. Johnston, M. E. Smith, “Urban Open Spaces in Historical Perspective: A Transdisciplinary Typology and Analysis,” Urban Geography 33, no. 8 (2012): 1089–117.   3. See B. Bolin, A. Nelson, E. J. Hackett, K. D. Pijawka, C. S. Smith, D. Sicotte, E. K. Sadalla, E. Matran, and M. O’Donnell, “The Ecology of Technological Risk in a Sunbelt City,” Environment and Planning A 34, no. 2 (2002): 317–39.   4. See E. Talen and L. Anselin, “Assessing Spatial Equity: An Evaluation of Measures of Accessibility to Public Playgrounds,” Environment and Planning A 30 (1998): 595–613.   5. Talen and Anselin, “Assessing Spatial Equity”; J. Wolch, J. P. Wilson, and J. Fehrenbach, “Parks and Park Funding in Los Angeles: An Equity-Mapping Analysis,” Urban Geography 26, no. 1 (2005): 4–35.  6. D. L. Cingranelli, “Race, Politics and Elites: Testing Alternative Models of Municipal Service Distribution,” American Journal of Political Science 25, no. 4 (1981): 664–92.   7. S. M. Low, “Claiming Space for an Engaged Anthropology: Spatial Inequality and Social Exclusion,” American Anthropologist 113, no. 3 (2011): 389–407.   8. L. M. Lobao, G. Hooks, and A. M. Tickamyer, “Introduction: Advancing the sociology of spatial inequality,” in Lobao et al., eds., The Sociology of Spatial Inequality, 1–25.   9. M. T. Marsh and D. A. Schilling, “Equity Measurement in Facility Location Analysis: A Review and Framework,” European Journal of Operational Research 74, no. 1 (1994): 1–17. 10. J. L. Crompton and B. E. Wicks, “Implementing a Preferred Equity Model for the Delivery of Leisure Services in the U.S. Context,” Leisure Studies 7 (1988): 287–303. 11. S. N. Zenk, A. J. Schulz, B. A. Israel, S. A. James, S. Bao, and M. L. Wilson, “Neighborhood Racial Composition, Neighborhood Poverty, and the Spatial Accessibility of Supermarkets in Metropolitan Detroit,” American Journal of Public Health 95 (2005): 660–67. 12. E. Talen, “Neighborhoods as Service Providers: A Methodology for Evaluating Pedestrian Access,” Environment and Planning B: Planning and Design 30 (2003): 181–200; E. Talen, “Geovisualization of Spatial Equity,” in The SAGE Handbook of GIS and Society, ed. T. L. Nyerges, H. Couclelis, and R. McMaster (Los Angeles: Sage, 2011), 458–79. 13. Talen, “Neighborhoods as Service Providers,” 183. 14. W. Lucy, “Equity and Planning for Local Services,” Journal of the American Planning Association 47 (1981): 447–57; E. Talen, “Visualizing Fairness: Equity Maps for Planners,” Journal of the American Planning Association 64 (1998), 22–38; Talen, “Neighborhoods as Service Providers.” 15. C. Tilly, “Historical Perspectives on Inequality,” in The Blackwell Companion to Social Inequalities, ed. M. Romero and E. Margolis (Malden, MA: Blackwell, 2005), 15–30. 16. M. van der Heijden, E. van Nederveen Meerkerk, G. Vermeesch, and M. van der Burg, eds., Serving the Urban Community: Public Facilities in the Low Countries (Amsterdam: Aksant Amsterdam University Press, 2010). 17. D. A. Oakley and J. R. Logan, “A Spatial Analysis of the Urban Landscape: What Accounts for Differences across Neighborhoods?” in Lobao et al., eds., The Sociology of Spatial Inequality, 215– 31; R. J. Sampson, Great American City: Chicago and the Enduring Neighborhood Effect (Chicago: University of Chicago Press, 2012). 18. S. McLafferty, “Urban Structure and Geographical Access to Public Services,” Annals of the Association of American Geographers 72 (1982): 347–54, 351.

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19. C. Tilly, Durable Inequality (Berkeley: University of California Press, 1998); Tilly, “Historical Perspectives on Inequality.” 20. G. Sjoberg, The Preindustrial City: Past and Present (New York: Free Press, 1960). 21. W. F. Abbott, “Moscow in 1897 as a Preindustrial City: A Test of the Inverse Burgess Zonal Hypothesis,” American Sociological Review 39, no. 4 (1974): 542–50; H. Carter, An Introduction to Urban Historical Geography (London: Edward Arnold, 1983). 22. J. Langton, “Residential Patterns in Pre-industrial Cities: Some Case Studies from Seventeenth Century Britain,” Transactions of the Institute of British Geographers 65 (1975): 1–27. 23. E.g., J. E. Arnold and A. Ford, “A Statistical Examination of Settlement Patterns at Tikal, Guatemala,” American Antiquity 45 (1980): 713–26; W. J. Folan, A. A. Hernández, E. R. Kintz, L. A. Fletcher, R. G. Heredia, J. M. Hau, and N. C. Canche, “Coba, Quintana Roo, Mexico: A Recent Analysis of the Social, Economic and Political Organization of a Major Maya Urban Center,” Ancient Mesoamerica 20 (2009): 59–70. 24. A. J. E. Daneels Vierriest and J. E. Annick, “El Patrón de Asentamiento del Periodo Clásico en la Cuenca Baja del Río Cotaxtla, Centro de Veracruz: Un Estudio de Caso de Desarrollo de Sociedades Complejas en Tierras Bajas Tropicales” (PhD thesis, Instituto de Investigaciones Antropológicas, Universidad Nacional Autónoma de México, 2002). 25. R. Millon, “Social Relations in Ancient Teotihuacan,” in The Valley of Mexico, ed. E. R. Wolf (Albuquerque: University of New Mexico Press, 1976); I. G. Robertson, “Mapping the Social Landscape of an Early Urban Center: Socio-spatial Variation in Teotihuacan” (PhD thesis, Department of Anthropology, Arizona State University, 2001). 26. A. Faust, “Residential Patterns in the Ancient Israelite City,” Levant 35 (2003): 123–38. 27. A. Kirby, “Neglected Factors in Public Services Research: A Comment on ‘Urban Structure and Geographical Access to Public Services,’” Annals of the Association of American Geographers 73 (1983): 289–95; C. Lesger, “Patterns of Retail Location and Urban Form in Amsterdam in the MidEighteenth Century,” Urban History 38 (2011): 24–47. 28. Stanley et al., “Urban Open Spaces in Historical Perspective.” 29. A. H. J. Prins, Didemic Lamu: Social Stratification and Spatial Structure in a Muslim Maritime Town (Groningen, Netherlands: Instituut voor Culturele Antropologie der Rijksuniversiteit, 1971); U. Ghaidan, Lamu: A Study of the Swahili Town (Nairobi: Kenya Literature Bureau, 1975/1992); J. Middleton, The World of the Swahili: An African Mercantile Civilization (New Haven, CT: Yale University Press, 1992). 30. A. H. M. El Zein, The Sacred Meadows: A Structural Analysis of Religious Symbolism in an East African Town (Chicago: Northwestern University Press, 1974); Middleton, The World of the Swahili. 31. Prins, Didemic Lamu. 32. El Zein, The Sacred Meadows. 33. Ghaidan, Lamu. 34. El Zein, The Sacred Meadows, 16. 35. Ghaidan, Lamu, xiii–ix. 36. Ibid. 37. Ibid.; El Zein, The Sacred Meadows, 16; Prins, Didemic Lamu, appendix. 38. A. E. Kaiser, “The Urban Dialogue: An Analysis of the Use of Space in the Roman City of Empúries, Spain,” 2000, Vol. S901, British Archaeological Reports International Series, Archaeopress, Oxford. 39. Ibid. 40. R. I. Levy, with K. R. Rajopadhyaya, Mesocosm: Hinduism and the Organization of a Traditional Newar City in Nepal (Berkeley: University of California Press, 1990), 2. 41. D. R. Regmi, Medieval Nepal (Kathmandu: Firma K.L. Mukhopadhyay, 1966); N. Gutschow, “Bhaktapur: Sacred Patterns of a Living Urban Tradition,” in Urban Form and Meaning in South Asia: The Shaping of Cities from Prehistoric to Precolonial Times, ed. H. Spodek and D. M. Srinivasan (Washington, DC: National Gallery of Art; London: University Press of New England, 1993), 163–83; N. Gutschow, Architecture of the Newars: A History of Building Typologies and Details in Nepal, Vol. I and II (Chicago: Serindia, 2011). 42. Levy, Mesocosm; D. N. Gellner, “Introduction,” in Contested Hierarchies: A Collaborative Ethnography of Caste among the Newars of the Kathmandu Valley, Nepal (Oxford: Clarendon Press, 1995), 1–37.

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43. Gutschow, “Bhaktapur.” 44. N. Gutschow, Stadtraum und ritual der Newarischen städte im Kathmandu-tal: eine architekturanthropologische untersuchung (Stuttgart, Germany: Verlag W. Kohlhammer, 1982), 32; Gutschow, Architecture of the Newars, 85, 633; N. Gutschow and B. Kolver, Ordered Space Concepts and Functions in a Town of Nepal (Wiesbaden, Germany: Kommissionsverlag Franz Steiner GMBH, 1975), 19; N. Gutschow, B. Kolver, and I. Shresthacarya, Newar Towns and Buildings: An Illustrated Dictionary (Sankt Augustin, Germany: VGH Wissenschaftsverlag, 1987), 85; Levy, Mesocosm, 164–84. 45. J. Laughton, Life in a Late Medieval City: Chester 1275-1520 (Oxford: Oxbow, 2008). 46. Ibid. 47. C. P. Lewis, “Framing Medieval Chester: The Landscape of Urban Boundaries,” in Mapping the Medieval City: Space, Place and Identity in Chester, c. 1200-1600, ed. C. A. M. Clarke (Cardiff: University of Wales Press, 2011), 42–56. 48. Laughton, Life in a Late Medieval City; A. T. Thacker, “Municipal Buildings,” in A History of the County of Chester, Vol V, Part 2, ed. C. P. Lewis and A. T. Thacker (Suffolk: Institute of Historical Research, University of London; Victoria County History, Boydell and Brewer, 2005), 15–20. 49. Mapping Medieval Chester Project (MMCP), Chester c. 1500, Civic Chester c. 1500, Chester Parishes c. 1500, Chester Streets c. 1500 (Swindon, UK: Arts and Humanities Research Council, 2009), accessed April 16, 2013, http://www.medievalchester.ac.uk. 50. Thacker, “Municipal Buildings”; MMCP, Chester Streets c. 1500. 51. T. P. Culbert, “The Ceramics of Tikal,” 1993, University Museum Monograph, Vol. 81, University of Pennsylvania Press, Philadelphia; T. P. Culbert, “The Ceramics of Tikal,” in Tikal: Dynasties, Foreigners, and Affairs of the State, ed. J. A. Sabloff (Santa Fe, NM: School of American Research Press, 2003), 47–82. 52. R. Fletcher, “Low-Density, Agrarian-Based Urbanism: A Comparative View,” Insights (Institute of Advanced Study, Durham University) 2, no. 4 (2009), https://www.dur.ac.uk/resources/ias/insights/ Fletcher16Jan.pdf (accessed April 12, 2013). 53. R. F. Carr and J. E. Hazard, “Map of the Ruins of Tikal, El Peten, Guatemala” (University Museum, University of Pennsylvania, Philadelphia, 1961, Vol. 11); W. A. Haviland, “Prehistoric Settlement at Tikal, Guatemala,” Expedition 7, no. 3 (1965): 14–23; W. A. Haviland, “Tikal, Guatamala and Mesoamerican Urbanism,” World Archaeology 2 (1970): 186–97; J. A. Sabloff, ed., Tikal: Dynasties, Foreigners, and Affairs of the State (Santa Fe, NM: School of American Research Press, 2003). 54. D. L. Webster, J. E. Silverstein, T. Murtha, H. Martínez, and K. Straight, “The Tikal Earthworks Revisited,” 2004, Department of Anthropology, Pennsylvania State University, State College; D. L. Webster, T. Murtha, K. D. Straight, J. E. Silverstein, H. Martinez, R. E. Terry, and R. Burnett, “The Great Tikal Earthwork Revisited,” Journal of Field Archaeology 32 (2007): 41–64; J. E. Silverstein, D. L. Webster, H. Martinez, and A. Soto, “Rethinking the Great Earthwork of Tikal: A Hydraulic Hypothesis for the Classic Maya Polity,” Ancient Mesoamerica 20 (2009): 45–58. 55. P. T. Culbert, L. J. Kosakowsky, R. E. Fry, and W. A. Haviland, “The Population of Tikal, Guatemala,” in Precolumbian Population History in the Maya Lowlands, ed. P. T. Culbert and D. S. Rice (Albuquerque: University of New Mexico Press, 1990), 103–22. 56. Carr and Hazard, “Map of the Ruins of Tikal.” 57. M. E. Smith, “Houses and the Settlement Hierarchy in Late Postclassic Morelos: A Comparison of Archaeology and Ethnohistory,” in Prehispanic Domestic Units in Western Mesoamerica: Studies of the Household, Compound, and Residence, ed. R. S. Santley and K. G. Hirth (Boca Raton, FL: CRC Press, 1993), 191–206. 58. W. R. Bullard Jr., “Maya Settlement Pattern in Northeastern Peten, Guatemala,” American Antiquity 25 (1960): 355–72; W. L. Fash Jr., “Deducing Social Organization from Classic Maya Settlement Patterns: A Case Study from the Copan Valley,” in Civilization in the Ancient Americas: Essays in Honor of Gordon R. Willey, ed. R. M. Leventhal and A. L. Kolata (Albuquerque: University of New Mexico Press, 1983), 261–88. 59. J. E. Arnold and A. Ford, “A Statistical Examination of Settlement Patterns at Tikal, Guatemala,” American Antiquity 45 (1980): 713–26. 60. C. Jones, “Excavations in the East Plaza of Tikal,” 1996, Tikal Report No. 16, University Museum, University of Pennsylvania, Philadelphia.

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Author Biographies Benjamin W. Stanley received a PhD from the School of Sustainability, and works as a postdoctoral researcher in the School of Human Evolution and Social Change, at Arizona State University. A geographer by training, he applies an interdisciplinary lens to the study of ancient and modern cities. His urban historical work has focused on comparative studies of ethnic and class clustering, urban open space, and group identity, while his work on modern cities emphasizes sustainability perspectives on the political economy of urban development. Recent publications include “Urban Open Spaces in Historical Perspective: A Transdisciplinary Typology and Analysis,” with B. L. Stark, K. L. Johnston, and M. E. Smith, Urban Geography 33, no. 8 (2012): 1089–1117; and “An Historical Perspective on the Viability of Urban Diversity: Lessons from Socio-spatial Identity Construction in Nineteenth-Century Algiers and Cape Town,” Journal of Urbanism 5, no. 1 (2012): 67–86. Timothy J. Dennehy is a PhD student in the School of Human Evolution and Social Change at Arizona State University. His research interests include the evolution and reproduction of social inequality; complex adaptive systems; egalitarianism; GIS and agent-based modeling; and Late Archaic and Early Formative Mesoamerica. His recent work has come from his involvement in the Late Lessons in Early History project at ASU, and includes a talk about service access in premodern cities given at the 2013 Society of American Archaeologists (SAA) Annual Meeting, as well as a personal essay for the November 2013 issue of the SAA Record.

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Michael E. Smith is professor of anthropology in the School of Human Evolution and Social Change at Arizona State University. He is an archaeologist who has directed excavations at numerous Aztec sites in central Mexico, where he studies houses and domestic contexts. He also publishes on comparative urbanism. Recent publications include The Comparative Archaeology of Complex Societies, ed. M. E. Smith (Cambridge University Press, 2012); and “Archaeology as a Social Science,” by M. E. Smith., G. M. Feinman, R. D. Drennan, T. Earle, and I. Morris Proceedings of the National Academy of Sciences 109 (2012): 7617–21. Barbara L. Stark is a professor emerita at Arizona State University. She specializes in Mesoamerican archaeology, ancient economies, settlement pattern and urbanism, and sociopolitical organization. Recent publications include “Ancient Open Space, Gardens, and Parks: A Comparative Discussion for Mesoamerican Urbanism,” in Making Ancient Cities, ed. K. D. Fisher and A. Creekmore (Cambridge University Press, 2014); “Urban Gardens and Parks in Pre-modern States and Empires,” Cambridge Journal of Archaeology 24, no. 1 (2012); with J. K. Chance, “The Strategies of Provincials in Empires,” in The Comparative Archaeology of Complex Societies, ed. M. E. Smith (Cambridge University Press, 2012). Abigail M. York is an associate professor of public policy and governance in the School of Human Evolution and Social Change and the Center for the Study of Institutional Diversity at Arizona State University. She has a PhD in public policy from Indiana University. Her work examines the dynamics of institutions, communities, and the environment with a focus on land use, urbanization, environmental justice, and economic development. Recent publications have appeared in Landscape and Urban Planning, Ecology & Society, and Journal of Urban Affairs. George L. Cowgill is an emeritus professor of anthropology at Arizona State University. His major research is on social and cultural aspects of ancient states and cities, especially in central Mexico. Recent publications include “Concepts of Collapse and Regeneration in Human History,” in The Oxford Handbook of Mesoamerican Archaeology, ed. D. L. Nichols and C. A. Pool (Oxford University Press, 2012); and “Cerro Portezuelo: States and Hinterlands in the Pre-Hispanic Basin of Mexico,” with D. L. Nichols and H. Neff, Ancient Mesoamerica 24, no. 1 (2013): 47-71. Juliana Novic is a PhD candidate at the School of Human Evolution and Social Change at Arizona State University. Her research focuses on the intersection of identity, economics, and urban relations. Her most recent publication, with M. E. Smith, is “Neighborhoods and Districts in Ancient Mesoamerica,” in The Neighborhood as a Social and Spatial Unit in Mesoamerican Cities, 2012. Jerald Ek is an archaeologist specializing in Classic Maya society. He has supervised excavations and archaeological survey in Campeche, Mexico. He is interested in socioecological systems and applications of resilience theory to archaeology.

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