Small area estimation of socioeconomic indicators for sampled and unsampled domains

Socioeconomic indicators play a crucial role in monitoring political actions over time and across regions. Income-based indicators such as the median income of sub-populations can provide information on the impact of measures, e.g., on poverty reduction. Regional information is usually published on an aggregated level. Due to small sample sizes, these regional aggregates are often associated with large standard errors or are missing if the region is unsampled or the estimate is simply not published. For example, if the median income of Hispanic or Latino Americans from the American Community Survey is of interest, some county-year combinations are not available. Therefore, a comparison of different counties or time-points is partly not possible. We propose a new predictor based on small area estimation techniques for aggregated data and bivariate modeling. This predictor provides empirical best predictions for the partially unavailable county-year combinations. We provide an analytical approximation to the mean squared error. The theoretical findings are backed up by a large-scale simulation study. Finally, we return to the problem of estimating the county-year estimates for the median income of Hispanic or Latino Americans and externally validate the estimates.

“Divide, Divert, & Conquer” Deconstructing the Presidential Framing of White Supremacy in the COVID-19 Era

Based on the analysis of President Donald J. Trump’s social media, along with excerpts from his speeches and press releases, this study sheds light on the framing of white supremacy during the first months of the COVID-19 pandemic in the United States. Our findings reveal that the triad of divide, divert, and conquer was crucial to Trump’s communications strategy. We argue that racist nativism—or racialized national threats to American security—is key to comprehending the external divisiveness in this strategy. When Trump bitterly cast China as the cause of America’s pandemic fallout and Mexico as the source of other key American problems (i.e., crime and low-paid jobs for U.S.-born Americans), he sowed clear racialized divisions between the United States (U.S.). and these two nations. We further argue that nativist racism—or the framing of descendants from those nations as incapable of ever being American—is key to comprehending the internal divisiveness in the former President’s pandemic rhetoric. Trump’s framing of China and Mexico as enemies of America further found its culprits in Asian and Latino Americans who were portrayed as COVID-19 carriers. Trump’s narrative was ultimately geared to diverting attention from his administration’s mishandling of COVID-19, the dismal structural conditions faced by detained and undocumented Latinos, and the anti-Asian bias faced by some of his Asian American constituents. In the conclusions, this article makes a call for countering white supremacy by developing comparative approaches that pay more attention to how different racisms play out for different groups.

Academic Library Leadership

Nearly 80% of American librarians are women. Similarly, the majority of American librarians are White; people of color – e.g., African Americans, Asian Americans, and Latino Americans – represent a small percentage of the U.S. library work-force. Throughout history, library leadership positions, regardless of the type of library (e.g., academic, public, or special), have been held by White males. This library leadership landscape was significantly altered following the enactment of a number of progressive laws and affirmative action programs, starting with the passage of Title VII of the Civil Rights Act of 1964. The problem, however, is that not every underrepresented group benefits from these laws and programs (hereafter policies). In fact, based on the present study, it appears that these policies have done little to help increase the number of people of color who are library directors in some of America’s largest and most prestigious academic libraries.

Beyond Behavior: Prevalences, Penalties, and Ethno-racial Inequalities in Poverty

Ethno-racial differences in poverty are substantial and persistent in the US. To explain these differences, scholars have relied largely on behavioral explanations, which argue that poverty is the result of high prevalences of problematic behaviors or “risks.” Given substantial differences in the prevalence of risks, scholars intuit that ethno-racial differences in poverty are explained by disproportionately high prevalences of risks in Black and Latino populations. However, these approaches rely heavily on untested assumptions regarding the relationship between risks and poverty rates. Using the 1993-2016 Current Population Survey and the Urban Institute’s TRIM3 model to derive high-quality estimates of income and poverty, I confirm persistent and substantial ethno-racial differences in poverty. Next, I employ a prevalences and penalties framework to compare risks in Black, Latino, and white-lead households. This framework is then leveraged to estimate counterfactual models to predict Black and Latino poverty rates given alternative prevalences of risks. The findings demonstrate that if the prevalence of risks for Black and Latino Americans was equal that of whites, poverty rates would remain over twice as high for Black and Latino individuals compared to whites. Furthermore, even when risks are eliminated for Black and Latino Americans, poverty remains substantially higher compared to whites. These findings undermine behavioral approaches to understanding poverty and point to the need for scholars to pursue alternatives, including structural and political explanations.

US Latino vote bloc will be increasingly important

Significance Democrats accuse the Republicans under President Donald Trump of adopting unduly harsh immigration policies and of pandering to race politics. Trump and the Republicans deny these assertions, but they still have an uphill battle to win votes from a fast-growing demographic in the November 3 election, and beyond: Latino Americans. Impacts Latino voters are a growing bloc in Texas and Florida, two states crucial to the Republicans' chances in November’s elections. The Democrats are likely to be the main beneficiaries of Latino votes this November. Latino political participation will grow as the community ages and attains citizenship, education and wealth.

Religion and Mental Health in Racial and Ethnic Minority Populations: A Review of the Literature

Religion has been an important source of resiliency for many racial and ethnic minority populations. Given the salience, sociohistorical context, and importance of religion in the lives of black and Latino Americans, this literature review focuses on the mental health and well-being outcomes of religion among black and Latino Americans across the adult life course and specifically in later life. This review provides an overview of religious participation and religiosity levels and an in-depth discussion of extant research on the relationship between the multiple dimensions of religiosity and mental health in these 2 populations. Racial differences between blacks, Latinos, and non-Latino whites are also examined. Suggestions for limitations of the current literature and future directions for research on religion and mental health in racial/ethnic minority populations, especially older minorities, are proposed.