Seth E Spielman
Biographic Data
| ID | 1340314 |
|---|---|
| NAME | Seth E Spielman |
| GIVEN NAMES | Seth E |
| FAMILY NAME | Spielman |
| SIGNATURE | SPIELMAN S E |
| AFFILIATIONS | University of Colorado Boulder |
| ORCID | 0000-0002-5089-7632 |
| VERIFIED | Yes |
| TOTAL WORKS | 16 |
| TOTAL CITATIONS | 151 |
| AUTHOR COUNT | 16 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2006 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 6 |
Geodemographics and residential differentiation: A methodological review and future directions for learned representations of the social landscape
Residential differentiation reflects the complex patterns by which social groups distribute themselves across urban spaces, fundamentally shaping social, economic, and spatial structures. This paper reviews the methodological development of geodemographic classification, tracing its evolution from early social area analysis and factorial ecology through to contemporary approaches. We critically evaluate this lineage of methods for quantifying res…
The Impact of Covariance on American Community Survey Margins of Error: Computational Alternatives
A Generalized Model of Activity Space
This article introduces the concept of a generalized activity space to bridge area-based and activity-based representations of geographic context. We argue that microscale space–time paths fail to account for contextual determinants of behavior, because they emphasize “contacts” over “contexts,” a problem that could be solved, in part, by using a broader “generalized” representation of geographic context. This article develops the idea of a gener…
A Method for Measuring Coupled Individual and Social Vulnerability to Environmental Hazards
Although models of social vulnerability to environmental hazards are commonly developed to support policy interventions in emergencies and disasters, their utility is hindered by a lack of contextual information on individuals exposed to and affected by hazards. We develop a novel approach to model social vulnerability that couples individuals and their varying forms of protective capacity with the social fabric of the communities in which they r…
Evaluating social vulnerability indicators: Criteria and their application to the Social Vulnerability Index
Point Pattern Analysis
Point pattern analysis is a set of methods for the detection of patterns in maps that contain a set of locations. Typically, these locations are points where some sort of event has occurred – the location of a car crash, a crime, a seed germinating. Point pattern analysis is used to determine the presence or absence of structure in a map of locations. Point pattern analysis is a statistical enterprise involving formal statistical tests of null hy…
Migration in the 1930s: Beyond the Dust Bowl
This paper analyzes in detail the role of environmental and economic shocks in the migration of the 1930s. The 1940 US Census of Population asked every inhabitant where they lived five years earlier, a unique source for understanding migration flows and networks. Earlier research documented migrant origins and destinations, but we will show how short-term and annual weather conditions at sending locations in the 1930s explain those flows, and how…
Spatial Variation in the Quality of American Community Survey Estimates
Social science research, public and private sector decisions, and allocations of federal resources often rely on data from the American Community Survey (ACS). However, this critical data source has high uncertainty in some of its most frequently used estimates. Using 2006–2010 ACS median household income estimates at the census tract scale as a test case, we explore spatial and nonspatial patterns in ACS estimate quality. We find that spatial pa…
Studying Neighborhoods Using Uncertain Data from the American Community Survey: A Contextual Approach
In 2010 the American Community Survey (ACS) replaced the long form of the decennial census as the sole national source of demographic and economic data for small geographic areas such as census tracts. These small area estimates suffer from large margins of error, however, which makes the data difficult to use for many purposes. The value of a large and comprehensive survey like the ACS is that it provides a richly detailed, multivariate, composi…
Patterns and causes of uncertainty in the American Community Survey
Spatial collective intelligence? Credibility, accuracy, and volunteered geographic information
Collective intelligence is the idea that under the right circumstances collections of individuals are smarter than even the smartest individuals in the group (Suroweiki 2004), that is a group has an "intelligence" that is independent of the intelligence of its members. The ideology of collective intelligence undergirds much of the enthusiasm about the use of "volunteered" or crowdsourced geographic information. Literature from a variety of fields…
Dasymetric Modeling and Uncertainty
Dasymetric models increase the spatial resolution of population data by incorporating related ancillary data layers. The role of uncertainty in dasymetric modeling has not been fully addressed as of yet. Uncertainty is usually present because most population data are themselves uncertain, and/or the geographic processes that connect population and the ancillary data layers are not precisely known. A new dasymetric methodology - the Penalized Maxi…
Using High-Resolution Population Data to Identify Neighborhoods and Establish Their Boundaries
Neighborhoods are about local territory, but what territory? This paper offers one approach to this question through a novel application of "local" spatial statistics. We conceptualize a neighborhood in terms of both space and social composition; it is a contiguous territory defined by a bundle of social attributes that distinguish it from surrounding areas. Our method does not impose either a specific social characteristic or a predetermined spa…
Identifying and Bounding Ethnic Neighborhoods
This study presents three novel approaches to the question of how best to identify ethnic neighborhoods (or more generally, neighborhoods defined any aspect of their population composition) and to define their boundaries. It takes advantage of unusual data on the residential locations of all residents of Newark, NJ, in 1880 to avoid having to accept arbitrary administrative units (like census tracts) as the building blocks of neighborhoods. For t…
The spatial dimensions of neighborhood effects
Appropriate Use of the K Function in Urban Environments
There is clearly a need to understand neighborhood food environments and how they contribute to behavior. “Clustering of Fast-Food Restaurants Around Schools: A Novel Application of Spatial Statistics to the Study of Food Environments”1 is an interesting approach to understanding this important need. However, the article raises a number of methodological concerns about the use of spatial statistics in urban environments. First and foremost is tha…
The spatial dimensions of neighborhood effects
Using High-Resolution Population Data to Identify Neighborhoods and Establish Their Boundaries
Neighborhoods are about local territory, but what territory? This paper offers one approach to this question through a novel application of "local" spatial statistics. We conceptualize a neighborhood in terms of both space and social composition; it is a contiguous territory defined by a bundle of social attributes that distinguish it from surrounding areas. Our method does not impose either a specific social characteristic or a predetermined spa…
Spatial Variation in the Quality of American Community Survey Estimates
Social science research, public and private sector decisions, and allocations of federal resources often rely on data from the American Community Survey (ACS). However, this critical data source has high uncertainty in some of its most frequently used estimates. Using 2006–2010 ACS median household income estimates at the census tract scale as a test case, we explore spatial and nonspatial patterns in ACS estimate quality. We find that spatial pa…
Studying Neighborhoods Using Uncertain Data from the American Community Survey: A Contextual Approach
In 2010 the American Community Survey (ACS) replaced the long form of the decennial census as the sole national source of demographic and economic data for small geographic areas such as census tracts. These small area estimates suffer from large margins of error, however, which makes the data difficult to use for many purposes. The value of a large and comprehensive survey like the ACS is that it provides a richly detailed, multivariate, composi…
Identifying and Bounding Ethnic Neighborhoods
This study presents three novel approaches to the question of how best to identify ethnic neighborhoods (or more generally, neighborhoods defined any aspect of their population composition) and to define their boundaries. It takes advantage of unusual data on the residential locations of all residents of Newark, NJ, in 1880 to avoid having to accept arbitrary administrative units (like census tracts) as the building blocks of neighborhoods. For t…
Migration in the 1930s: Beyond the Dust Bowl
This paper analyzes in detail the role of environmental and economic shocks in the migration of the 1930s. The 1940 US Census of Population asked every inhabitant where they lived five years earlier, a unique source for understanding migration flows and networks. Earlier research documented migrant origins and destinations, but we will show how short-term and annual weather conditions at sending locations in the 1930s explain those flows, and how…
A Generalized Model of Activity Space
This article introduces the concept of a generalized activity space to bridge area-based and activity-based representations of geographic context. We argue that microscale space–time paths fail to account for contextual determinants of behavior, because they emphasize “contacts” over “contexts,” a problem that could be solved, in part, by using a broader “generalized” representation of geographic context. This article develops the idea of a gener…
Spatial collective intelligence? Credibility, accuracy, and volunteered geographic information
Collective intelligence is the idea that under the right circumstances collections of individuals are smarter than even the smartest individuals in the group (Suroweiki 2004), that is a group has an "intelligence" that is independent of the intelligence of its members. The ideology of collective intelligence undergirds much of the enthusiasm about the use of "volunteered" or crowdsourced geographic information. Literature from a variety of fields…
Dasymetric Modeling and Uncertainty
Dasymetric models increase the spatial resolution of population data by incorporating related ancillary data layers. The role of uncertainty in dasymetric modeling has not been fully addressed as of yet. Uncertainty is usually present because most population data are themselves uncertain, and/or the geographic processes that connect population and the ancillary data layers are not precisely known. A new dasymetric methodology - the Penalized Maxi…
A Method for Measuring Coupled Individual and Social Vulnerability to Environmental Hazards
Although models of social vulnerability to environmental hazards are commonly developed to support policy interventions in emergencies and disasters, their utility is hindered by a lack of contextual information on individuals exposed to and affected by hazards. We develop a novel approach to model social vulnerability that couples individuals and their varying forms of protective capacity with the social fabric of the communities in which they r…
The Impact of Covariance on American Community Survey Margins of Error: Computational Alternatives
Appropriate Use of the K Function in Urban Environments
There is clearly a need to understand neighborhood food environments and how they contribute to behavior. “Clustering of Fast-Food Restaurants Around Schools: A Novel Application of Spatial Statistics to the Study of Food Environments”1 is an interesting approach to understanding this important need. However, the article raises a number of methodological concerns about the use of spatial statistics in urban environments. First and foremost is tha…
The spatial dimensions of neighborhood effects
Identifying and Bounding Ethnic Neighborhoods
This study presents three novel approaches to the question of how best to identify ethnic neighborhoods (or more generally, neighborhoods defined any aspect of their population composition) and to define their boundaries. It takes advantage of unusual data on the residential locations of all residents of Newark, NJ, in 1880 to avoid having to accept arbitrary administrative units (like census tracts) as the building blocks of neighborhoods. For t…
Using High-Resolution Population Data to Identify Neighborhoods and Establish Their Boundaries
Neighborhoods are about local territory, but what territory? This paper offers one approach to this question through a novel application of "local" spatial statistics. We conceptualize a neighborhood in terms of both space and social composition; it is a contiguous territory defined by a bundle of social attributes that distinguish it from surrounding areas. Our method does not impose either a specific social characteristic or a predetermined spa…
Patterns and causes of uncertainty in the American Community Survey
Spatial collective intelligence? Credibility, accuracy, and volunteered geographic information
Collective intelligence is the idea that under the right circumstances collections of individuals are smarter than even the smartest individuals in the group (Suroweiki 2004), that is a group has an "intelligence" that is independent of the intelligence of its members. The ideology of collective intelligence undergirds much of the enthusiasm about the use of "volunteered" or crowdsourced geographic information. Literature from a variety of fields…
Dasymetric Modeling and Uncertainty
Dasymetric models increase the spatial resolution of population data by incorporating related ancillary data layers. The role of uncertainty in dasymetric modeling has not been fully addressed as of yet. Uncertainty is usually present because most population data are themselves uncertain, and/or the geographic processes that connect population and the ancillary data layers are not precisely known. A new dasymetric methodology - the Penalized Maxi…
Studying Neighborhoods Using Uncertain Data from the American Community Survey: A Contextual Approach
In 2010 the American Community Survey (ACS) replaced the long form of the decennial census as the sole national source of demographic and economic data for small geographic areas such as census tracts. These small area estimates suffer from large margins of error, however, which makes the data difficult to use for many purposes. The value of a large and comprehensive survey like the ACS is that it provides a richly detailed, multivariate, composi…
Migration in the 1930s: Beyond the Dust Bowl
This paper analyzes in detail the role of environmental and economic shocks in the migration of the 1930s. The 1940 US Census of Population asked every inhabitant where they lived five years earlier, a unique source for understanding migration flows and networks. Earlier research documented migrant origins and destinations, but we will show how short-term and annual weather conditions at sending locations in the 1930s explain those flows, and how…
Spatial Variation in the Quality of American Community Survey Estimates
Social science research, public and private sector decisions, and allocations of federal resources often rely on data from the American Community Survey (ACS). However, this critical data source has high uncertainty in some of its most frequently used estimates. Using 2006–2010 ACS median household income estimates at the census tract scale as a test case, we explore spatial and nonspatial patterns in ACS estimate quality. We find that spatial pa…
Point Pattern Analysis
Point pattern analysis is a set of methods for the detection of patterns in maps that contain a set of locations. Typically, these locations are points where some sort of event has occurred – the location of a car crash, a crime, a seed germinating. Point pattern analysis is used to determine the presence or absence of structure in a map of locations. Point pattern analysis is a statistical enterprise involving formal statistical tests of null hy…
Evaluating social vulnerability indicators: Criteria and their application to the Social Vulnerability Index
A Generalized Model of Activity Space
This article introduces the concept of a generalized activity space to bridge area-based and activity-based representations of geographic context. We argue that microscale space–time paths fail to account for contextual determinants of behavior, because they emphasize “contacts” over “contexts,” a problem that could be solved, in part, by using a broader “generalized” representation of geographic context. This article develops the idea of a gener…
A Method for Measuring Coupled Individual and Social Vulnerability to Environmental Hazards
Although models of social vulnerability to environmental hazards are commonly developed to support policy interventions in emergencies and disasters, their utility is hindered by a lack of contextual information on individuals exposed to and affected by hazards. We develop a novel approach to model social vulnerability that couples individuals and their varying forms of protective capacity with the social fabric of the communities in which they r…
The Impact of Covariance on American Community Survey Margins of Error: Computational Alternatives
Geodemographics and residential differentiation: A methodological review and future directions for learned representations of the social landscape
Residential differentiation reflects the complex patterns by which social groups distribute themselves across urban spaces, fundamentally shaping social, economic, and spatial structures. This paper reviews the methodological development of geodemographic classification, tracing its evolution from early social area analysis and factorial ecology through to contemporary approaches. We critically evaluate this lineage of methods for quantifying res…
Geography (12 works) · Computer Science (10 works) · Population (9 works) · Sociology (9 works) · Demography (8 works) · Mathematics (8 works) · Urban, Neighborhood, and Segregation Studies (8 works) · Census (6 works) · Econometrics (6 works) · Regional science (6 works)