This chapter reviews the different dimensions of disadvantage associated with disability while emphasizing the social structures that create and maintain such disadvantages. We review quantitative research demonstrating disadvantage in education, employment, income, wealth, and economic security, while noting the drawbacks of deficit accounts that fail to consider the structural dimensions of inequality. Drawing on relational inequality theory, we discuss how ableism, as an institution, supports the unequal distribution of status, resources, and opportunities around disability. We then provide examples of how ableism leads to disparities in higher education, employment, and wealth among people with disabilities, while also emphasizing potential paths for change within these organizations.

We demonstrate an important complementarity between patriotism and public good provision. After 1933, the New Deal led to an unprecedented expansion of the US federal government’s role. Those who benefited from social spending were markedly more patriotic during WW II: they bought more war bonds, volunteered more and, as soldiers, won more medals. This pattern was new – WW I volunteering did not show the same geography of patriotism. We match military service records with the 1940 census to show that this pattern holds at the individual level. Using geographical variation, we exploit two instruments to suggest that the effect is causal: droughts and congressional committee representation predict more New Deal agricultural support, as well as bond buying, volunteering, and medals.

Differential privacy is the state-of-the-art formal definition for data release under strong privacy guarantees. A variety of mechanisms have been proposed in the literature for releasing the output of numeric queries (e.g., the Laplace mechanism and smooth sensitivity mechanism). Those mechanisms guarantee differential privacy by adding noise to the true query's output. The amount of noise added is calibrated by the notions of global sensitivity and local sensitivity of the query that measure the impact of the addition or removal of an individual on the query's output. Mechanisms that use local sensitivity add less noise and, consequently, have a more accurate answer. However, although there has been some work on generic mechanisms for releasing the output of non-numeric queries using global sensitivity (e.g., the Exponential mechanism), the literature lacks generic mechanisms for releasing the output of non-numeric queries using local sensitivity to reduce the noise in the query's output. In this work, we remedy this shortcoming and present the local dampening mechanism. We adapt the notion of local sensitivity for the non-numeric setting and leverage it to design a generic non-numeric mechanism. We provide theoretical comparisons to the exponential mechanism and show under which conditions the local dampening mechanism is more accurate than the exponential mechanism. We illustrate the effectiveness of the local dampening mechanism by applying it to three diverse problems: (i) percentile selection problem. We report the p-th element in the database; (ii) Influential node analysis. Given an influence metric, we release the top-k most influential nodes while preserving the privacy of the relationship between nodes in the network; (iii) Decision tree induction. We provide a private adaptation to the ID3 algorithm to build decision trees from a given tabular dataset.

Nuclear energy occupies a conspicuous place in the global energy transition. In the United States, civilian nuclear power plants are shutting down before their licenses expire, leaving nuclear host communities struggling to cope with the unexpected change. This study focuses on the socio-economic dimensions of the effects of nuclear power plant shutdowns in nuclear host communities in the United States. Our study attempts to strike a balance between intensive case studies, which often fail to disentangle place-specific factors from broader trends and to put observations in perspective, and large-sample-based quantitative analyses, which seeks a general impact of decommissioning without paying sufficient attention to local variations. We adopt a quasi-experimental approach, which compares communities with decommissioned plants to their control neighbors, to assess the diverse trajectories of socio-economic well-being of nuclear host communities before and after plant closure. These communities are analyzed in terms of their population, per capita income, education, poverty levels, and unemployment. The findings provide a starting point from which more detailed case studies can be conducted, and nuclear host communities can better navigate the decommissioning process.

This study was a literature review, and it focused on native language attrition among immigrants. For many years, immigrants’ families have moved to places such as United States and Europe as well as Canada because of war, abuse, persecution, environmental degradation, and poverty from their home countries. Once immigrant families arrived at their designated country, their children were placed in school. Due to the struggle with the language barrier, kids and adults quickly started to focus extensively on learning the English language. The research took place due to the raised concerns of parents regarding their children's inabilities to communicate in their first language (L1) with families after learning English. Having worked with adult language learners at Project English and Giving Plus Learning, I witnessed the rise in parents’ frustration, concern, and confusion when their children could no longer speak, formulate sentences, or enjoy conversation with relatives in their home language. These parents did not understand why their children constantly spoke in English and rejected their native tongue. The literature review aimed to shed light on the significance of maintaining L1 among immigrants’ families while learning and speaking English. The review brought together all the available resources related to my project topic in place, and the resources were evaluated closely. In the review, there were six essential themes divided into sections. Each chapter focused on the method and findings of the themes. Major findings from the research studies highlighted that L1 attrition can take place instantly when the L1 is not being utilized. The studies showed that age plays a vital role in L1 loss because the earlier children were exposed to the English language, the higher the possibility of L1 deterioration, particularly with children who began English from age three to seven. Older children who spoke the native language from birth to age 12 and then learned English continued communicating in the L1 much better. The studies further pointed out that the English immersion environment helped immigrants practice and improved their communication in the L2. However, the L1 was hindered because immigrants’ children had less opportunity to speak in the L1and more in L2, as if it was their L1.

We examine the causes and consequences of an important cultural and psychological trait: the extent to which one views the world in zero-sum terms. We implement a survey among approximately 15,000 individuals living in the United States that measures zero-sum thinking, one’s political and policy views, and a rich set of characteristics about their ancestry. We find that a more zero-sum view about how benefits to one person or group tend to come at the cost of others is strongly correlated with a host of policy views about the importance of government, the value of redistributive policies, the value of immigration, and one’s political orientation. We find that zero-sum thinking can be explained by experiences of an individual’s ancestors (parents, grandparents, great-grandparents), including the amount of intergenerational upward mobility experienced, whether they immigrated to the United States, and whether they were ever enslaved.

Immigrant children represent a significant share of the U.S. population. However, foreign-born children are often disadvantaged compared to their native-born peers due to differences in language skills, schooling and cultural integration. I use historical Census Data to analyze the differences in schooling and labor market outcomes between U.S-born and foreign-born sib-lings to understand the long-term effects of nativity. Children observed in the 1910 decennial Census are linked to their 1940 Census records using a unique method of linking individuals across Census waves. Compared to their native-born siblings, those born abroad are 10.5, 4.1 and 1.7 percentage points less likely to complete eighth grade, high-school and college respectively. The effects are larger for children who arrived at older ages. I do not find a significant impact on wages, employment, and other labor market outcomes. These findings indicate that foreign-born status is a significant determinant of long-term outcomes of children.

Between 2010 and 2017, 42 U.S. states added work requirements as a food assistance eligibility criterion for Able-Bodied Adults Without Dependents (ABAWDs). Another U.S. public assistance program, Supplemental Security Income (SSI), provides food assistance without a work requirement, along with cash transfers and health insurance. Therefore, individuals for whom working is difficult may be induced to opt out of the labor force and into SSI in order to maintain access to food assistance. This study is the first to examine whether work requirements associated with food assistance eligibility lead to an increase in SSI applications and receipts. Based on difference-in-differences and event study analyses of comprehensive administrative claims data from the Social Security Administration and survey data from the Current Population Survey, this study finds evidence of lagged effects on SSI applications overall, and reduced Supplementary Nutritional Assistance Program (SNAP) receipts followed by a delayed smaller increase in SSI receipts among individuals with self-reported disabilities. While most SSI applications induced by SNAP-related work requirements appear to be unsuccessful, a small, vulnerable population may move out of the workforce and into SSI in response to the implementation of work requirements.

Gentrification occurs when a low-income neighborhood, with a high minority population experiences a sudden change through the arrival of high income, educated, and white individuals. The effects that gentrification has on residents are still debated. This paper intends to expand on the existing literature by examining the effects that gentrifi-cation has on the health outcomes of census tracts in three Texas cities: Austin, Dallas, and San Antonio. I use census tract level data to measure the gentrification status of tracts along with the CDC's 500 Cities/PLACES Project data on health outcomes to find if living in a gentrified census tract is positively or negatively associated with health. I identify the effects of gentrification by employing a difference-indifference approach to find if living in a gentrified neighborhood is consistent with increased negative health outcomes. Contrary to expectations, I find that the average health profile in gentrified communities is better than that in non-gentrified communities. Whether these differences are attributable to the gentrification process, selection, or other effects remains an open research question.

Abstract Introduction: This report documents the evolution of commuting times in the United States between 1990 and 2018, focusing on disparities with respect to race and ethnicity, sex, marital status, income, and poverty status Methods: This report uses the American Community Survey PUMS (Public Use Microdata Series) data for all years released by the Census Bureau and reorganized for public use by the Minnesota Population Center, University of Minnesota, IPUMSusa, (https://usa.ipums.org/usa/index.shtml). See Public Use Microdata Series Steven Ruggles, J. Trent Alexander, Katie Genadek, Ronald Goeken, Matthew B. Schroeder, and Matthew Sobek. Integrated Public Use Microdata Series: Version 5.0 [Machine-readable database]. Minneapolis: University of Minnesota, 2019. Discussion: There are two main findings. First, about half of the population in the country took between 10 and 30 minutes to commute to work—a figure consistent over time. That said, the second finding is that the proportion of people taking more than half an hour to get to work has been increasing steadily. In terms of race, non-Hispanic whites have the highest proportion of people in the shorter commuting times (less than 30 minutes) compared to other racial and ethnic groups. For example, by 2018, 25.4% of non-Hispanic white workers took less than 10 minutes to get to work, compared to 18.2% of Asians in the same category. Latinos (21.3%) and non-Hispanic blacks (19.5%) were in between of the other two racial and ethnic groups.These data are pre-COVID-19. Other trends by sex, income, marital status, and poverty status are further analyzed in the report.

This analysis documents U.S. racial/ethnic and gender differences in life expectancies with different self-reported sleep durations among adults aged 50 and older. We used self-reported sleep duration and linked mortality information from the 2004–2015 National Health Interview Survey (n = 145,015) to calculate Sullivan Method Lifetables for life expectancies with different self-reported sleep duration states: short (≤6 hours), optimal (seven to 8 hours), and long (≥9 hours) sleep duration per-day by race/ethnicity and gender. Non-Hispanic Black men (35.8%, 95% CI: 34.8%–36.8%) and women (36.5%, 95% CI: 35.7%–37.1%) exhibited the highest proportion of years lived with short sleep duration followed by Hispanic men (31.1%, 95% CI: 29.9%–32.3%) and women (34.1%, 95% CI: 33.1%–35.1%) and Non-Hispanic White men (25.8%, 95% CI: 25.4%–26.2%) and women (27.4%, 95% CI: 27.0%–27.7%). These results highlight how race/ethnic inequality in sleep duration and life expectancy are intertwined among older adults in the U.S.

Purpose: Rural registered nurses (RNs) play an integral role in providing care for an underserved population with worse health outcomes than urban counterparts. However, little information is available on the profile of this workforce, which is necessary to understand the capacity of these nurses to provide quality and demanded care presently and in the future. Methods: We utilize data from the American Community Survey to provide a contemporary analysis on the supply of rural RNs in the United States. Findings: While the number of physicians serving rural populations has decreased in recent years, and rural nurse practitioners (NPs) remain in short supply, rural RNs have steadily grown in numbers at a rate comparable to urban RNs. Rural RNs are markedly less diverse than the populations they serve and only half of rural RNs had a bachelor's degree or higher compared to over 70% for urban RNs. In their supply, young rural nurses appear on pace with urban nurses to adequately replace older nurses and continue to grow the workforce, based on data through 2019. Conclusions: The rural RN workforce is projected to steadily grow amidst declining rural physicians and limited rural NPs. The burgeoning investments in the rural health workforce present opportunities to help diversify, increase educational access, and further rural readiness for rural RNs moving forward.

This article provides a comprehensive analysis of the increase in gender inequality in paid work during the pandemic to unpack the relative relevance of labor market and work-family conflict processes. Using panel data from the United States Current Population Survey, we examine four mechanisms in an integrated analysis that explicitly includes singleparent households and assesses the moderating role of women’s economic position relative to their partners. The results indicate that increases in gender inequality during the pandemic were heavily concentrated in households with children but also partly connected to gender differences in prepandemic labor market positions and to the higher prevalence of women in lower earner position relative to their partners. Single parents were more negatively impacted than partnered parents, but the disproportionate concentration of this impact on women does not contribute much to increases in overall gender inequality due to the relatively smaller size of this group.

Objective: To examine whether the Affordable Care Act's (ACA's) Medicaid expansions affected health insurance coverage for individuals in same-sex couples. Data Sources and Study Setting: We used data on adults aged 18–64 years in same-sex couples (n = 33,512) from the 2008–2018 American Community Survey (ACS). Study Design: To estimate the effect of the impact of the state Medicaid expansions under the ACA on health insurance coverage for sexual minorities, we utilize a standard difference-in-differences approach to leverage the variation across geography and time in expanding Medicaid. Data Collection: Secondary and publicly available ACS data were obtained from IPUMS at the University of Minnesota. Principal Findings: We find that Medicaid expansion significantly increased health insurance coverage among low-income men and women in same-sex couples by 4.9 (standard error [SE] = 1.75) and 6.5 (SE = 1.96) percentage points, respectively. We find increases in the likelihood of having Medicaid and reductions in private health insurance from an employer or privately purchased insurance. Effects on Medicaid take-up are consistently larger for low-income women in same-sex couples as compared to low-income men in same-sex couples. Conclusions: We provide the first evidence on the relationship between state Medicaid expansions under the ACA and health insurance coverage among sexual minority adults, a group that has been understudied in past research. Our results confirm that sexual minority adults benefitted from the ACA's Medicaid expansions with respect to increased health insurance coverage.

This article examines the effects of two types of entrepreneurship – new firm formation versus self-employment – on income inequality within cities in the United States. Regression analysis based on metropolitan areas between 2005 and 2015 shows that an increase in new firm formation decreases household income inequality. In contrast, more self-employment increases inequality. These results are consistent across different measures of income inequality and model specifications. This study highlights the need for differentiating entrepreneurship in understanding its role in regional development. It further confirms vibrant start-up activity as a key strength of a regional economy.

Garden suburbs are a particular type of residential development that flourished in the late 19th and early 20th centuries, in the U.S. and globally. Using census data of 283 garden suburbs in the U.S., I investigated the exclusivity of the garden suburb by looking at income, housing value, race, and age. I found that garden suburbs had more Whites, single-family housing, and higher family income in all time periods. Income levels were significantly higher whether the comparison was between garden suburbs and the immediately surrounding area (1mile), or between garden suburbs and a wider context.

Increasing numbers of students require internet access to pursue their undergraduate degrees, yet broadband access remains inequitable across student populations. Furthermore, surveys that currently show differences in access by student demographics or location typically do so at high levels of aggregation, thereby obscuring important variation between subpopulations within larger groups. Through the dual lenses of quantitative intersectionality and critical race spatial analysis, we use Bayesian multilevel regression and census microdata to model variation in broadband access among undergraduate populations at deeper interactions of identity. We find substantive heterogeneity in student broadband access by gender, race, and place, including between typically aggregated subpopulations. Our findings speak to inequities in students’ geographies of opportunity and suggest a range of policy prescriptions at both the institutional and federal level.

Purpose Youth suicide is increasing at a significant rate and is the second leading cause of death for adolescents. There is an urgent public health need to address the youth suicide. The objective of this study is to determine whether adolescents and young adults residing in states with greater mental health treatment capacity exhibited lower suicide rates than states with less treatment capacity. Methods We conducted a state-level analysis of mental health treatment capacity and suicide outcomes for adolescents and young adults aged 10–24 spanning 2002–2017 using data from Centers for Disease Control and Prevention, U.S. Bureau of Labor Statistics, Federal Bureau of Investigation, and other sources. Multivariable linear fixed-effects regression models tested the relationships among mental health treatment capacity and the total suicide, firearm suicide, and nonfirearm suicide rates per 100,000 persons aged 10–24. Results We found a statistically significant inverse relationship between nonfirearm suicide and mental health treatment capacity (p = .015). On average, a 10% increase in a state’s mental health workforce capacity was associated with a 1.35% relative reduction in the nonfirearm suicide rate for persons aged 10–24. There was no significant relationship between mental health treatment capacity and firearm suicide. Conclusions Greater mental health treatment appears to have a protective effect of modest magnitude against nonfirearm suicide among adolescents and young adults. Our findings underscore the importance of state-level efforts to improve mental health interventions and promote mental health awareness. However, firearm regulations may provide greater protective effects against this most lethal method of firearm suicide.

During the nineteenth century manufacturing increased its share of the labor force in the United States, and manufacturing became more urban, as did the population. Our survey of the literature and analyses of census data suggests that a key reason was the development of a nationwide transportation system, especially the railroad. Coupled with changes in manufacturing technology and organizational form, the “transportation revolution” increased demand for manufacturing labor in urban locations. Labor supply responded and because of agglomeration economies, population density and the size and number of urban places increased. Although our focus is on the US experience, a causal role for transportation is likely for other economies that experienced historical industrialization and urbanization.

While differentially private query release has been well-studied, research in this area is commonly restricted to data that do not exhibit hierarchical structure. However , in many real-world scenarios, individual data points can be grouped together (e.g., people within households, taxi trips per driver, etc.), begging the question-what statistical properties (or queries) are important when considering data of this form? In addition, although synthetic data generation approaches for private query release have grown increasingly popular, it is unclear how one can generate synthetic data at both the group and individual-level while capturing such statistical properties. In light of these challenges, we formalize the problem of hierarchical query release and provide a set of statistical queries that capture relationships between attributes at both the group and individual-level. Furthermore, we propose and implement a novel synthetic data generation algorithm, H-GEM, which outputs hierarchical data subject to differential privacy to answer such statistical queries. Finally, using the American Community Survey, we evaluate H-GEM, establishing a benchmark for future work to measure against.