american community survey
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2021 ◽  
pp. 000276422110660
Author(s):  
Rogelio Sáenz

After several decades of Whites fleeing large metropolitan areas, they are now increasingly gentrifying urban neighborhoods and communities. This analysis uses data from the 2000 decennial census and the 2012 and 2017 American Community Survey to assess the growing presence of Whites in U.S. cities. The analysis examines the extent to which Whites have experienced an increase in their percentage share of the populations of 212 majority non-White communities with 50,000 or more inhabitants over two time periods (2000 to 2008–2012 and 2008–2012 to 2013–2017). The results show that 39 communities have experienced an expanding relative presence of Whites in one or both periods. Whites generally are growing at a faster pace than Blacks and Latinos in these communities and there are large socioeconomic gaps favoring Whites. The article concludes with a discussion of the policy implications of the findings.


2021 ◽  
pp. 008117502110575
Author(s):  
Nick Graetz ◽  
Kevin Ummel ◽  
Daniel Aldana Cohen

Quantitative sociologists and social policymakers are increasingly interested in local context. Some city-specific studies have developed new primary data collection efforts to analyze inequality at the neighborhood level, but methods from spatial microsimulation have yet to be broadly used in sociology to take better advantage of existing public data sets. The American Community Survey (ACS) is the largest household survey in the United States and indispensable for detailed analysis of specific places and populations. The authors propose a technique, tree-based spatial microsimulation, to produce “small-area” (census-tract) estimates of any person- or household-level phenomenon that can be derived from ACS microdata variables. The approach is straightforward and computationally efficient, based only on publicly available data, and it provides more reliable estimates than do prevailing methods of microsimulation. The authors demonstrate the technique’s capabilities by producing tract-level estimates, stratified by race/ethnicity, of (1) the proportion of people in the census-tract population who have children and work in an essential occupation and (2) the proportion of people in the census-tract population living below the federal poverty threshold and in a household that spends greater than 50 percent of monthly income on rent or owner costs. These examples are relevant to understanding the sociospatial inequalities dramatized by the coronavirus disease 2019 pandemic. The authors discuss potential extensions of the technique to derive small-area estimates of variables observed in surveys other than the ACS.


2021 ◽  
pp. 233264922110578
Author(s):  
Kate K. O’Neill ◽  
Ian Kennedy ◽  
Alexes Harris

Although recent scholarship has enumerated many individual-level consequences of criminal legal citations and sentences involving fines and fees, we know surprisingly little about the structural consequences of monetary sanctions or legal financial obligations (LFOs). We use social disorganization and critical race theories to examine neighborhood-level associations between and among LFO sentence amounts, poverty, and racial and ethnic demographics. Using longitudinal data from the Washington State Administrative Office of the Courts, and the American Community Survey, we find LFOs are more burdensome in high-poverty communities and of color, and that per-capita rates of LFOs sentenced are associated with increased future poverty rates across all neighborhoods.


2021 ◽  
pp. 001112872110475
Author(s):  
Marin R. Wenger

While social disorganization theory suggests the importance of change, most prior research examining macro-level criminological associations uses cross-sectional data. The current study examines the multilevel relationship between changes in disadvantage and changes in crime over time using four data sources: the National Neighborhood Crime Study, the 2000 U.S. Census, crime-incidents occurring between 2005 and 2009, and the 2005–2009 American Community Survey. Analyzing 6,068 census tracts within 53 large U.S. cities using multilevel models with time nested within tracts nested within cities, I parse out the contribution of changes in tract-level disadvantage from city-level disadvantage to changes in robbery and burglary rates. Results indicate the importance of both static and dynamic associations between disadvantage and crime, at both the neighborhood and city level.


Author(s):  
Dean Kyne

(1) Background: Cameron County, which is located in the Rio Grande Valley, holds historical records for storm surges with noticeable property damage, fatalities, and injuries; (2) Methods: using storm surge hazard datasets from the National Oceanic and Atlantic Agency (NOAA), and American Community Survey (ACS) 2019 datasets and Geographic Information System (GIS), the study estimates at-risk population and their socio-demographic attributes; (4) Conclusions: Estimated water levels of a storm surge could be reached up to 5 feet in category 1 event, 9 feet in category 2, 17 feet in category 3, and above 20 feet in category 4 and 5. In the category 5 event, there is an estimated 37% (159,659) of the total county’s population (434,294) will be under flooded water. Suggestions are made to better prepare and successfully evaluate.


2021 ◽  
Author(s):  
Julie Weeks ◽  
James Dahlhamer ◽  
Jennifer Madans ◽  
Aaron Maitland

This report examines differences in survey reports of disability between two sets of disability questions, the Short Set on Functioning (WG-SS) developed by the Washington Group on Disability Statistics (WG) and a set of disability questions developed for the American Community Survey (ACS).


2021 ◽  
Author(s):  
Krista Payne ◽  
Wendy Manning

Although approximately half of all marriages in the U.S. end in divorce (Amato, 2010; Cherlin, 2010), the remarriage rate has declined steadily in recent decades (Brown & Lin, 2013; Schweizer, 2019). In this profile, we examine the trend in the remarriage rate since 1990 (see Note) and investigate geographic variation in the remarriage rate by gender using recent American Community Survey (ACS) data. This profile is an update of a previous profile on the Geographic Variation in the Remarriage Rate (FP-15-08).


Author(s):  
Kate H. Choi ◽  
Marta Tienda

Over the past few decades, Hispanic young adults have made impressive gains in educational attainment, but improvements have not been even by gender, with Latinas now averaging more schooling than Latinos. These developments in education have implications for Latinx marital sorting behavior and the marriage conditions that they face. Using data from the American Community Survey, we examine intermarriage patterns of Hispanics ages 25 to 34, focusing on gender differences in assortative mating along ethnic and educational lines. We show that college-educated Latinos are less likely than both their lesser-educated peers and college-educated Latinas to marry partners who are less educated than themselves. We also reveal that highly educated Latinas are more likely than Latinos with comparable levels of education to intermarry. We discuss implications for the intergenerational maintenance of Hispanicity as an ethno-race, and for their ability to transmit the socioeconomic gains obtained via educational improvements to future generations of Hispanics.


2021 ◽  
pp. 0192513X2110182
Author(s):  
Kevin J. A. Thomas ◽  
Ashley Larsen Gibby

This study uses data from the American Community Survey to examine the relationship between race, family configurations, and inequalities in private school enrollment among adoptees. We find that private school enrollment is higher in transracial than in same-race families. This disparity is driven by the outcomes of adoptees in transracial families with zero rather than one same-race parent. Among adoptees themselves, there are diverging patterns of racial stratification in same-race and transracial families. White adoptees in same-race families are more likely to be enrolled in private school than Black, Asian, or Hispanic adoptees in such families. However, among adoptees in transracial families, the highest odds of private school enrollment are found among Asians. Finally, we argue that our findings have important implications for understanding how kinship cues, compensation, and social disadvantage shape parental investment in adopted children.


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