Racial Diversity,Representative Bureaucracy,and Equity in Multiracial School Districts*

Objective. This study examines the conditions under which minorities will face policy inequity within the educational system. It turns to the theory of representative bureaucracy as one possible explanation, and extends the literature by considering whether African‐American students benefit from the presence of Latinos on teaching faculties and vice versa. This study also tests competing theories of how racial context influences minority educational policy outcomes. Methods. This study combines original survey data with data gathered by the U.S. Census to predict levels of academic grouping in U.S. school districts as reported by the Office of Civil Rights. Results. Minority teachers lower levels of discrimination among all minority students, not just co‐ethnics. Moreover, minority teachers do so consistently and with a substantive impact that occasionally rivals that of co‐ethnic teachers. The findings also suggest that greater levels of racial/ethnic diversity within a district are associated with lower levels of discrimination. Conclusion. Theories of race relations must move beyond black‐Anglo or Latino‐Anglo relations to consider how multiple racial/ethnic groups interact, and how such interactions affect the lives of minority groups differently.     

Partisan Reinforcement and the Poor: The Impact of Context on Explanations for Poverty*

Objective. Past research has demonstrated that Americans view poverty in racial terms, and that they often blame the poor for their situation. This article's objective is to determine if local contexts can influence these views. Methods. Synthesizing racial and political theories of contextual effects, I use two nationally representative surveys to explore Americans' explanations for poverty. Results. People living in areas where the poor are mostly white are less likely to attribute poverty to the failings of the poor themselves, as theories of racial threat would predict. However, a second finding is stronger: the percentage of the county that voted Republican in the last election consistently predicts less structural and more individualistic explanations of poverty. Conclusions. Local processes of partisan reinforcement play a key role in shaping explanations of poverty.     

Racing to Theory or Retheorizing Race? Understanding the Struggle to Build a Multiracial Identity Theory

Empirical research on the growing multiracial population in the United States has focused largely on the documentation of racial identification, analysis of psychological adjustment, and understanding the broader political consequences of mixed-race identification. Efforts toward theory construction on multiracial identity development, however, have been largely disconnected from empirical data, mired in disciplinary debates, and bound by historically specific assumptions about race and racial group membership. This study provides a critical overview of multiracial identity development theories, examines the links between theory and research, explores the challenges to multiracial identity theory construction, and proposes considerations for future directions in theorizing racial identity development among the mixed-race population.     

The two faces of independence: betweenness and homotheticity

This paper shows that expected utility belongs to the intersection of models satisfying betweenness and a homotheticity condition for risky choice. Betweenness models can accommodate variable risk attitudes, originally highlighted by the Allais paradox, by restricting indifference curves to be linear while allowing non-parallelism. Homotheticity, in contrast, restricts indifference curves to be parallel while permitting non-linearities, such as those highlighted by inverse-S probability weighting. Data from an experiment indicate that approximately 2/3s of participants satisfied homotheticity. Of this group, about half satisfied the expected utility hypothesis. The other half violated expected utility and therefore betweenness. These results indicate that homothetic preferences, and in particular those violating betweenness, can be empirically relevant for decision making under risk.

     

Inductive Risk,Science, and Values: A Reply to MacGillivray

The argument from inductive risk (AIR) is perhaps the most common argument against the value-free ideal of science. Brian MacGillivray rejects the AIR (at least as it would apply to risk assessment) and embraces the value-free ideal. We clarify the issues at stake and argue that MacGillivray's criticisms, although effective against some formulations of the AIR, fail to overcome the essential concerns that motivate the AIR. There are inevitable trade-offs in scientific enquiry that cannot be resolved with any formal methods or general rules. Choices must be made, and values will be involved. It is best to recognize this explicitly. Even so, there is more work to be done developing methods and institutional support for these choices.     

Remain,Return, or Re-migrate? The (Im)mobility Trajectory of Mainland Chinese Students after Completing Their Education in the UK

The migration of Chinese students to the UK has long been the focus of academic and policy-making attention. However, what happens to their transnational mobility after their education remains understudied. This article unpacks the migration decision-making process behind graduates' study-to-employment transition. We focus on individuals' on-going reinterpretation of capital convertibility between China and the UK and examine how the meaning of mobility changes in time and in the transnational socio-economic environment. In so doing, we draw on in-depth interviews with graduates who have remained in the UK, as well as with returnees. Our findings reveal our participants' periodic uncertainty about professional opportunities and attendant mobility choices in the context of fast-paced socio-economic change in China and in the UK. The article thus calls for a more supportive post-study work policy environment for international students in the UK, especially in the context of uncertainty about Brexit.     

The Association Between Infants’ Attention Control and Social Inhibition is Moderated by Genetic and Environmental Risk for Anxiety

Infant social inhibition is associated with increased risk for anxiety later in life. Although both genetic and environmental factors are associated with anxiety, little empirical work has addressed how developing regulatory abilities work with genetic and environmental risk to exacerbate or mitigate problem behaviors. The current study was aimed at addressing this gap in research by investigating an early emerging regulatory behavior, attention control, in association with genetic and environmental risk for anxiety. Participants included 9‐month‐old adopted infants, their birth mothers, and adoptive parents (N = 361). Lifetime diagnosis of birth mother social phobia was obtained using structured interviews. Adoptive parents completed self‐report measures of anxiety symptoms. Infant social inhibition and attention control were coded during a stranger interaction and a barrier task, respectively. Neither adoptive nor birth parent anxiety was directly associated with social inhibition. The association of attention control with social inhibition in infants was moderated by birth and adoptive parent anxiety symptoms. When infants of birth mothers with social phobia were raised by adoptive parents with high self‐reported anxiety symptoms, greater attention control was associated with greater social inhibition. However, when raised by adoptive parents with low self‐reported anxiety, greater attention control was associated with less social inhibition.     

Functional Autoregression for Sparsely Sampled Data

We develop a hierarchical Gaussian process model for forecasting and inference of functional time series data. Unlike existing methods, our approach is especially suited for sparsely or irregularly sampled curves and for curves sampled with nonnegligible measurement error. The latent process is dynamically modeled as a functional autoregression (FAR) with Gaussian process innovations. We propose a fully nonparametric dynamic functional factor model for the dynamic innovation process, with broader applicability and improved computational efficiency over standard Gaussian process models. We prove finite-sample forecasting and interpolation optimality properties of the proposed model, which remain valid with the Gaussian assumption relaxed. An efficient Gibbs sampling algorithm is developed for estimation, inference, and forecasting, with extensions for FAR(p) models with model averaging over the lag p. Extensive simulations demonstrate substantial improvements in forecasting performance and recovery of the autoregressive surface over competing methods, especially under sparse designs. We apply the proposed methods to forecast nominal and real yield curves using daily U.S. data. Real yields are observed more sparsely than nominal yields, yet the proposed methods are highly competitive in both settings. Supplementary materials, including R code and the yield curve data, are available online.     

Race/Ethnic and Socioeconomic Microaggressions Experienced by Low-Income Parents in Three US Cities

Race and Social Problems - Previous research on microaggressive experiences has focused primarily on those based on race/ethnicity. For the present study, we examined both race/ethnic and...