Black Americans have been underrepresented in the nation’s creative industries since the end of slavery. This column argues that the implications of that marginalization extend beyond career choices into homes and neighbourhoods, as cities with thriving arts sectors also lead in job creation, innovation, and trade. The authors recommend that financial support for black artists be pursued in a systematic way, with policies that provide emerging black artists with access not only to relevant artistic networks, but also to supply-related organisations such as gallerists and publishers.

Human-centered computing in cloud, edge, and fog is one of the most concerning issues. Edge and fog nodes generate huge amounts of data continuously, and the analysis of these data provides valuable information. But they also increase privacy risks. The personal sensitive data may be disclosed by untrusted third-party service providers, and the current solutions to privacy protection are inefficient, costly. It is difficult to obtain available statistics. To solve these problems, we propose a local differential privacy sensitive data collection protocol in human-centered computing. Firstly, to maintain high data utility, the selection of the optimal number of hash functions and the mapping length is based on the size of the collected data. Secondly, we hash the sensitive data, add the appropriate Laplace noise to the client side, and send the reports to the server side. Thirdly, we construct the count sketch matrix to obtain privacy statistics on the server side. Finally, the utility of the proposed protocol is verified by synthetic datasets and a real dataset. The experimental results demonstrate that the protocol can achieve a balance between data utility and privacy protection.

Low-skilled immigrants indirectly affect public finances through their effect on native wages & labor supply. We operationalize this general-equilibrium effect in the workhorse labor market model with heterogeneous workers and intensive and extensive labor supply margins. We derive a closed-form expression for this effect in terms of estimable statistics. We extend the analysis to various alternative specifications of the labor market and production that have been emphasized in the immigration literature. Empirical quantifications for the U.S. reveal that the indirect fiscal benefit of one low-skilled immigrant lies between $770 and $2,100 annually. The indirect fiscal benefit may outweigh the negative direct fiscal effect that has previously been documented. This challenges the perception of low-skilled immigration as a fiscal burden.

With the creation of interactive tasks that allow students to explore spatial ways of knowing in conjunction with their other ways of knowing the world, we create a space where students can make sense of information as they organize these new ideas into their already existing schema. Through the use of a Common Online Data Analysis Platform (CODAP) and data from Public Use Microdata Areas (PUMA), students can explore the communities in which they live and work, critically examining opportunities and challenges within a defined space

The population of adults in the District of Columbia (“D.C.” or “the District”) age 65 and older (“seniors” or “older adults”) is substantial and growing. In 2019, the District was home to approximately 83,600 older adults, and the population could rise as much as 24.4 percent by 2030. Nationally, the older adult population is expected to increase by more than 50 percent between 2015 and 2030. An aging population has broad implications for the District’s policymakers, health care providers, businesses, and families. This is the first report in a multi-part series called “The State of Older Adults in the District of Columbia”. The first report explores the demographic and economic characteristics of the District’s senior population by seeking to answer three questions: Who are D.C. seniors? Where do seniors live in D.C.? How do seniors in D.C. make ends meet? This report is centered on the Office of the Budget Director’s analysis of data from the U.S. Census Bureau’s 2017 American Community Survey, 5-Year Sample via microdata samples made available through the Integrated Public Use Microdata Series (IPUMS) USA. It also leverages research conducted by District and federal government agencies, universities, think tanks, and journalists. Increasing longevity, diverse lifestyle patterns, and delayed retirement mean that there is no single definition for old age. However, since many federally administered programs require applicants to be at least 65 years old to receive benefits, this series defines “senior” and “older adult” as individuals who are age 65 and older. The next reports in this series will consider the range of publicly provided benefits available to senior adults in the District and examine how these programs help close the gap between seniors’ living expenses and their earnings and savings.

The Justice Department began a number of suits in the 1970s and 1980s resulting in consent decrees that mandated increased hiring of minorities and women in police and fire departments. The author used Census data to compare representation in the departments of cities that were subject to consent decrees with those of cities that were not. Through a difference in difference regression model, the consent decrees were found to have a statistically significant impact on minority representation in police departments, minority representation in fire departments, and female representation in police departments (no significant impact was found on females in fire departments). Controlling for variables including location, age, poverty rate, and minority rates of sample cities confirm these results. The presence of a consent decree causes an additional 3.53% increase in minority police, 9.77% increase in minority firefighters, and 6.19% increase in female police according to the controlled model. This analysis suggests that using the judicial system may be an effective policy for federal agencies attempting to alter municipal policies.

This study examines whether health disparities between same-sex and different-sex cohabitors differ depending on socioeconomic status (SES). Previous research showed that SES mediates health disparities between different-sex and same-sex cohabitors, but less is known about its role as a potential moderator. Using data on cohabitors from the Integrated Public Use Microdata Series (IPUMS) National Health Interview Surveys (2007–2018), this study examines how the SES-health gradient shapes health disparities for same-sex and different-sex cohabitors. Average adjusted predictions from multinomial logistic regression models show that higher income-to-needs ratio is associated with improvements in self-rated health for same-sex cohabiting women relative to different-sex cohabiting women. However, results are mixed for men. As income-to-needs ratio increases, same-sex cohabiting men have higher probabilities of “excellent” or “very good” health than different-sex cohabitors; however, their risk of “poor” health increases significantly with higher income-to-needs ratios. Potential explanations related to minority stress, stress proliferation, gendered meanings of self-rated health, and selection are explored. Overall, disparities between same-sex and different-sex cohabitors differ by gender and SES, suggesting socioeconomic diversity should be considered in the study of sexual minority health.

The Covid-19 pandemic is causing a catastrophic increase in U.S. mortality. How does the scale of this pandemic compare to another U.S. catastrophe: racial inequality? Using demographic models, I estimate how many excess white deaths would raise U.S. white mortality to the bestever (lowest) U.S. Black level under alternative, plausible assumptions about the age patterning of excess mortality in 2020. I find that 400,000 excess white deaths would be needed to equal the best mortality ever recorded among Blacks. For white mortality in 2020 to reach levels that Blacks experience outside of pandemics, current Covid-19 mortality levels would need to increase by a factor of nearly 6. Moreover, white life expectancy in 2020 will remain higher than Black life expectancy has ever been unless nearly 700,000 excess white deaths occur. Even amid Covid-19, U.S. white mortality is likely to be less than what U.S. Blacks have experienced every year. I argue that, if Black disadvantage operates every year on the scale of whites’ experience of Covid-19, then so too should the tools we deploy to fight it. Our imagination and social ambition should not be limited by how accustomed the U.S. is to profound racial inequality.

Exploiting results from the literature on non-parametric identification, we make three methodological contributions to the empirical literature estimating the matching function, commonly used to map unemployment and vacancies into hires. First, we show how to non-parametrically identify the matching function. Second, we estimate the matching function allowing for unobserved matching efficacy, without imposing the usual independence assumption between matching efficiency and search on either side of the labor market. Third, we allow for multiple types of jobseekers and consider an “augmented” Beveridge curve that includes them. Our estimated elasticity of hires with respect to vacancies is procyclical and varies between 0.15 and 0.3. This is substantially lower than common estimates suggesting that a significant bias stems from the commonly-used independence assumption. Moreover, variation in match efficiency accounts for much of the decline in hires during the Great Recession.

Urban regions in the United States have been disproportionately hit hard by COVID-19. We compare employment transitions between urban and rural workers during the pre-pandemic and the lockdown periods. We find that urban workers are more affected by this crisis. However, some urban workers, including young adults and minorities, are better off than their peers living in rural areas. Policymakers should account for these facts when designing financial stimulus.

Purpose The prognosis for gastric carcinoma (GC) remains challenging with less than 35% of patients surviving 5 years. GC survival varies greatly by anatomical site, cardia and non-cardia. However, these important differences have not been thoroughly studied in relation to the increasing diversity in US populations such as Florida. In this study we examined, for the first time, the effect of race-ethnicity on risk of death from GC controlling for potential risk factors separately for cardia and non-cardia GCs. Methods Data on GCs diagnosed in Florida from 2005-2016 were obtained from the statewide cancer registry. Age-standardized GC-specific 5-year survival was computed by anatomical site and race-ethnicity. In addition, a competing risk analysis was performed to assess prognostic factors and to estimate subdistribution hazard ratios of death from GC. Results Whites had high proportions of cardia GC (43.9%) compared to all racial/ethnic minorities (10.9%, 19.6%, and 13.8% in Blacks, Hispanics, and Asians, respectively; p < .0001). Among 12,302 cases included, there were 7534 deaths from GC and 1179 from other causes. Age standardized GC-specific 5-year survival was significantly lower for Whites (28.0%) compared to Blacks (31.6%), Hispanics (37.6%), and Asians, (39.6%) and significantly lower for cardia GC (25.0%, 95% CI 23.4-26.6) compared to non-cardia GC (37.0%, 95% CI 35.5-38.4). Multivariable competing risk analysis in patients with non-cardia GC showed that Asians (sHR: 0.64, 95% CI 0.51-0.80), Hispanics (sHR 0.71, 95% CI 0.64-0.78), and Blacks (sHR 0.83, 95% CI 0.75-0.92) all had lower risks of death from GC compared to Whites. In patients with cardia GC, only Hispanics had statistically significant lower risk of death from GC than Whites (sHR 0.84, 95% CI 0.74-0.95, p = 0.005). Conclusions The study of racial/ethnic survival disparities in patients with GC in Florida reveals Whites as the most disadvantaged group. Whites are more afflicted by cardia GC, which is associated with higher risk of death than non-cardia GC. However, even within non-cardia GC, Whites had higher risk of death than the other racial-ethnic groups. Commonly assessed survival determinants do not adequately explain these unusual disparities; thus, further investigation is warranted.

The modern world moves fast, as the cliché goes, but in the U.S. today, people move less frequently than their parents did a generation ago. The decline in mobility is much more than an academic curiosity. Economists widely view labor mobility as the principal mechanism by which regions adjust to local economic shocks. If local industries fall on hard times, workers can leave; in places where labor demand is high, new residents flow in. The decline has therefore generated concern that the economy is less adaptable to local shocks, ultimately resulting in labor misallocation, unrealized output, and lower productivity.

Poverty is a key indicator of economic hardship. By providing a geographic adjustment for cost of living, the recently developed Supplemental Poverty Measure has upended long-held views that poverty is higher in rural compared to urban America. In this study, we unpack the geographic adjustment underlying the Supplemental Poverty Measure and find that most of the difference is explained by the median rent index component rather than the housing tenure component. Further, we find that six states (Alabama, Georgia, Kentucky, Mississippi, North Carolina, and Ohio) account for over a third of the nonmetro poverty drop due to the median rent adjustment. We demonstrate that the demographic composition of the rural poor remains relatively unaffected despite this large drop, but find that the prevalence of poverty within demographic groups varies considerably. As a result, while the SPM is largely considered a more complete measure of poverty, the use of the median rent adjustment has important implications for the demographic understanding of rural poverty.

Background: While optimal cardiovascular risk factor (CRF) profile is associated with lower mortality, morbidity, and healthcare expenditures among individuals with atherosclerotic cardiovascular disease (ASCVD), less is known regarding its impact on financial hardship from medical bills. Therefore, we assessed whether an optimal CRF profile is associated with a lower burden of financial hardship from medical bills and a reduction in costrelated barriers to health. Methods: We used a nationally representative sample of adults between 18 and 64 years from the National Health Interview Survey between 2013 and 2017. We assessed ASCVD status and the number of risk factors to categorize the study population into 4 mutually exclusive categories: ASCVD (irrespective of CRF profile) and non-ASCVD with poor, average, and optimal CRF profile. Adjusted logistic regression model was used to determine the association of ASCVD/CRF profile with financial hardship from medical bills and cost-related barriers to health (cost-related medication non-adherence (CRN), foregone/delayed care, and high financial distress). Results: We included 119,388 non-elderly adults, representing 189 million individuals annually across the United States. Non-ASCVD/optimal CRF profile individuals had a lower prevalence of financial hardship and an inability paying medical bills when compared with individuals with ASCVD (24% vs 45% and 6% vs 19%, respectively). Among individuals without ASCVD and an optimal CRF profile, the prevalence of each cost-related barrier to health was <50% compared with individuals with ASCVD. Poor/low income and uninsured individuals within non-ASCVD/average CRF profile strata had a lower prevalence of financial hardship and an inability paying medical bills when compared with middle/high income and insured individuals with ASCVD. Non-ASCVD individuals with optimal CRF profile had the lowest odds of all barriers to health. Conclusion: Optimal CRF profile is associated with a lower prevalence of financial hardship from medical bills and cost-related barriers to health despite lower income and lack of insurance.

Drawing on millions of court records of eviction cases filed between 2012 and 2016 in 39 states, this study documents the racial and gender demographics of America's evicted population. Black renters received a disproportionate share of eviction filings and experienced the highest rates of eviction filing and eviction judgment. Black and Latinx female renters faced higher eviction rates than their male counterparts. Black and Latinx renters were also more likely to be serially filed against for eviction at the same address. These findings represent the most comprehensive investigation to date of racial and gender disparities among evicted renters in the United States.

Importance Individuals with low socioeconomic status (SES) bear a disproportionate share of the coronary heart disease (CHD) burden, and CHD remains the leading cause of mortality in low-income US counties. Objective To estimate the excess CHD burden among individuals in the United States with low SES and the proportions attributable to traditional risk factors and to other factors associated with low SES. Design, Setting, and Participants This computer simulation study used the Cardiovascular Disease Policy Model, a model of CHD and stroke incidence, prevalence, and mortality among adults in the United States, to project the excess burden of early CHD. The proportion of this excess burden attributable to traditional CHD risk factors (smoking, high blood pressure, high low-density lipoprotein cholesterol, low high-density lipoprotein cholesterol, type 2 diabetes, and high body mass index) compared with the proportion attributable to other risk factors associated with low SES was estimated. Model inputs were derived from nationally representative US data and cohort studies of incident CHD. All US adults aged 35 to 64 years, stratified by SES, were included in the simulations. Exposures Low SES was defined as income below 150% of the federal poverty level or educational level less than a high school diploma. Main Outcomes and Measures Premature (before age 65 years) myocardial infarction (MI) rates and CHD deaths. Results Approximately 31.2 million US adults aged 35 to 64 years had low SES, of whom approximately 16 million (51.3%) were women. Compared with individuals with higher SES, both men and women in the low-SES group had double the rate of MIs (men: 34.8 [95% uncertainty interval (UI), 31.0-38.8] vs 17.6 [95% UI, 16.0-18.6]; women: 15.1 [95% UI, 13.4-16.9] vs 6.8 [95% UI, 6.3-7.4]) and CHD deaths (men: 14.3 [95% UI, 13.0-15.7] vs 7.6 [95% UI, 7.3-7.9]; women: 5.6 [95% UI, 5.0-6.2] vs 2.5 [95% UI, 2.3-2.6]) per 10 000 person-years. A higher burden of traditional CHD risk factors in adults with low SES explained 40% of these excess events; the remaining 60% of these events were attributable to other factors associated with low SES. Among a simulated cohort of 1.3 million adults with low SES who were 35 years old in 2015, the model projected that 250 000 individuals (19%) will develop CHD by age 65 years, with 119 000 (48%) of these CHD cases occurring in excess of those expected for individuals with higher SES. Conclusions and Relevance This study suggested that, for approximately one-quarter of US adults aged 35 to 64 years, low SES was substantially associated with early CHD burden. Although biomedical interventions to modify traditional risk factors may decrease the disease burden, disparities by SES may remain without addressing SES itself.

Rates of labor force participation in the US in the second half of the nineteenth century among free women were exceedingly (and implausibly) low, about 11 percent. This is due, in part, to social perceptions of working women, cultural and societal expectations of female’s role, and lack of accurate or thorough enumeration by Census officials. This paper develops an augmented free female labor force participation rate for 1860. It is calculated by identifying free women (age 16 and older) who were likely providing informal and unenumerated labor for market production in support of a family business, that is, unreported family workers. These individuals are identified as not having a reported occupation, but are likely to be working on the basis of the self-employment occupation of other relatives in their households. Family workers are classified into three categories: farm, merchant, and craft. The inclusion of this category of workers more than triples the free female labor force participation rate in the 1860 Census, from 16 percent to 56 percent, which is comparable to today’s rate (57 percent in 2018).

During the 19th and early 20th century about 220,000 Dutch born persons migrated to the USA. The Historical Sample of the Netherlands (HSN) contains about 85,500 persons born in the Netherlands between 1812 and 1922. In this article we report the way we have matched persons from the HSN with the American censuses from the period 1850 till 1940. For this purpose, a linking process was designed, comprising of three stages: harmonization, matching and validation. The different nature of the two datasets (HSN and the USA Censuses) asked for some harmonization prior to the matching. Once the data had been properly prepared, two strategies were applied in order to link the data sets. The first one, called Similarity Approach, matched individuals from both datasets by comparing on the basis of resemblance of first and last names. The second approach, called Transformation Approach, made use of dictionaries with Anglicized versions of Dutch first and last names and their most common or most likely Dutch original(s). Because of the sample character of the HSN even exact matches showed ambiguity that needs to be resolved. For this reason, a validation process comparing the household context was run to provide a more trustworthy result. In the end we identified 484 individuals present in the HSN database with reliable links to the American censuses. We also evaluated the result in the light of what we know from emigration patterns to the USA over time and period and we concluded that our efforts have produced a reasonable result. Nevertheless, we are aware that we may have missed links. We also found that at least 45% of the emigrants returned to the Netherlands at some point during their life course.

Previous literature on climate change and human population dynamics has mainly focused on how population growth affects greenhouse gas emissions. Much less research has analyzed how climatic variability influences the size of human populations, despite reasonable expectations of such effects. Evidence of climate-fertility linkages, or lack thereof, is needed to refine understandings of adaptive behaviors. It is also needed to refine models of the demographic drivers of greenhouse gas emissions, which tend to assume climatic changes will not feedback to impact population dynamics. We test this relationship using birth histories from 23 sub-Saharan African countries and high-resolution climate data. Our analyses show that exposure to climatic variability is associated with fertility in sub-Saharan Africa, albeit in complex ways. Women exposed to hot-and-dry spells experience significant reductions in the annual probability of fertility, while exposure to above-average temperatures and precipitation is associated with increased fertility over baseline. These associations vary between demographic and geographic groups, revealing important differences in vulnerability and adaptive behavior

Over the last years several states have enacted policies granting undocumented immigrants access to driver's licenses. We exploit the state and temporal variation in the issuing of state driver's licenses to undocumented immigrants to estimate their impact on labor market outcomes. Using 2005 through 2017 data from the American Community Survey, we show that likely undocumented men increase their weekly hours of work in response to the availability of driver's licenses. Perhaps due to their already high labor force participation, the impact is somewhat moderate. We also find no similar impacts among similarly skilled foreign-born Hispanic men who have naturalized. The policy slightly raises commuting time, suggesting changes in work patterns, as well as likely undocumented immigrants’ propensity to have an occupation that requires driving. At a time when anti-immigrant sentiments are at an all-time high, understanding how these policies impact targeted groups and similarly skilled citizens is crucial for maintaining an informed immigration policy debate.