In 2010 the American Community Survey (ACS) replaced the long form of the United States decennial census. The ACS is now the principal source of high-resolution geographic information about the U.S. population. The margins of error on ACS census tract-level data are on average 75 percent larger than those of the corresponding 2000 long-form estimate. The practical implications of this increase is that data are sometimes so imprecise that they are difficult to use. This paper explains why the ACS tract and block group estimates have large margins of error. Statistical concepts are explained in plain English. ACS margins of error are attributed to specific methodological decisions made by the Census Bureau. These decisions are best seen as compromises that attempt to balance financial constraints against concerns about data quality, timeliness, and geographic precision. In addition, demographic and geographic patterns in ACS data quality are identified. These patterns are associated with demographic composition of census tracts. Understanding the fundamental causes of uncertainty in the survey suggests a number of geographic strategies for improving the usability and quality ACS.

No abstract

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 Maximum Entropy Dasymetric Model (P-MEDM) - is presented that enables these sources of uncertainty to be represented and modeled. The P-MEDM propagates uncertainty through the model and yields fine-resolution population estimates with associated measures of uncertainty. This methodology contains a number of other benefits of theoretical and practical interest. In dasymetric modeling, researchers often struggle with identifying a relationship between population and ancillary data layers. The PEDM model simplifies this step by unifying how ancillary data are included. The P-MEDM also allows a rich array of data to be included, with disparate spatial resolutions, attribute resolutions, and uncertainties. While the P-MEDM does not necessarily produce more precise estimates than do existing approaches, it does help to unify how data enter the dasymetric model, it increases the types of data that may be used, and it allows geographers to characterize the quality of their dasymetric estimates. We present an application of the P-MEDM that includes household-level survey data combined with higher spatial resolution data such as from census tracts, block groups, and land cover classifications.

Community scholars increasingly focus on the linkage between residents' sense of cohesion with the neighborhood and their own social networks in the neighborhood. A challenge is that whereas some research only focuses on residents' social ties with fellow neighbors, such an approach misses out on the larger constellation of individuals' relationships and the spatial distribution of those relationships. Using data from the Twin Communities Network Study, the current project is one of the first studies to examine the actual spatial distribution of respondents' networks for a variety of relationships and the consequences of these for neighborhood and city cohesion. We also examine how a perceived structural measure of cohesion-triangle degree-impacts their perceptions of neighborhood and city cohesion. Our findings suggest that perceptions of cohesion within the neighborhood and the city depend on the number of neighborhood safety contacts as well as on the types of people with which they discuss important matters. On the other hand, kin and social friendship ties do not impact cohesion. A key finding is that residents who report more spatially dispersed networks for certain types of ties report lower levels of neighborhood and city cohesion. Residents with higher triangle degree within their neighborhood safety networks perceived more neighborhood cohesion.

Although personal network size ultimately declines with age, we find that increases for some relations extend well into late-midlife and most elders still maintain numerous contacts across diverse relations. The evidence we present suggests that older people tap into an wider variety of different network members for different types of relations than do younger people. This is true even for populations in rural settings, for whom immediate access to potential alters is more limited.

No abstract

In this study, we examine how different features of the built environment -density, diversity of land uses, and design -have consequences for personal networks. We also consider whether different features of the built environment have consequences for the spatial location of persons to whom one is tied by considering their distribution in local area, broader city region, and a more macro spatial scale. We test these ideas with a large sample of the Western United States for three different types of ties. Our findings suggest that the built environment is crucial for personal network structure, both in the number of social ties and where they are located.Keywords: neighborhoods, social networks, spatial effects, built environment, land use 3 Bio Adam Boessen is an Assistant Professor in the department of Criminology and Criminal Justice at the University of Missouri, St. Louis. His primary research interests include neighborhoods and crime, geography and space, and social networks.John R. Hipp is a Professor in the departments of Criminology, Law and Society, and Sociology, at the University of California Irvine. His research interests focus on how neighborhoods change over time, how that change both affects and is affected by neighborhood crime, and the role networks and institutions play in that change. He approaches these questions using quantitative methods as well as social network analysis. He has published substantive

No abstract