Migration,race and ethnicity, 1960-1980

"This article compares racial and ethnic patterns in interstate and interregional migration in the years 1960 to 1980.... This research looks at geographical assimilation--the extent to which patterns of migration and regional distribution of minority groups resemble those of whites. Attention is directed to United States-born Asian Americans, blacks, Hispanics, Native Americans and whites, and attempts to answer the following questions: 1) To what extent do the patterns of interstate migration of these groups resemble one another? 2) To what extent do the regional distributions and patterns of net regional migration of these groups resemble one another?" This is a revised version of a paper originally presented at the 1988 Annual Meeting of the Population Association of America (see Population Index, Vol. 54, No. 3, Fall 1988, p. 495).     

Tolerance of Uncertainty: Links to Happenstance,Career Decision Self‐Efficacy,and Career Satisfaction

This study investigated the extent to which tolerance of uncertainty affects the relationship between happenstance skills and career satisfaction via career decision self‐efficacy. Moderated mediation analysis was conducted on data collected from 321 graduates (175 men, 146 women) of Korean universities making the school‐to‐work transition. Results showed that career decision self‐efficacy fully mediated the relationship between happenstance skills and career satisfaction. Furthermore, the moderation effect of tolerance of uncertainty had a significant impact on the relationship between happenstance skills and career decision self‐efficacy. Tolerance of uncertainty should be considered an important variable in happenstance career theory and intervention. Unplanned influences should also be considered important factors in the career decision‐making process.     

Context Matters: Differential Effects of Discrimination by Environmental Context on Depressive Symptoms Among College Students of Color

Clinical Social Work Journal - Experiences with more subtle racism – which have been called microaggressions – have a host of negative effects on health, mental health, educational...     

A Necessary Condition for the Strong Oracle Property

A problem of using a non‐convex penalty for sparse regression is that there are multiple local minima of the penalized sum of squared residuals, and it is not known which one is a good estimator. The aim of this paper is to give a guide to design a non‐convex penalty that has the strong oracle property. Here, the strong oracle property means that the oracle estimator is the unique local minimum of the objective function. We summarize three definitions of the oracle property – the global, weak and strong oracle properties. Then, we give sufficient conditions for the weak oracle property, which means that the oracle estimator becomes a local minimum. We give an example of non‐convex penalties that possess the weak oracle property but not the strong oracle property. Finally, we give a necessary condition for the strong oracle property.     

An exploratory data analysis in scale-space for interval-valued data

We propose an exploratory data analysis approach when data are observed as intervals in a nonparametric regression setting. The interval-valued data contain richer information than single-valued data in the sense that they provide both center and range information of the underlying structure. Conventionally, these two attributes have been studied separately as traditional tools can be readily used for single-valued data analysis. We propose a unified data analysis tool that attempts to capture the relationship between response and covariate by simultaneously accounting for variability present in the data. It utilizes a kernel smoothing approach, which is conducted in scale-space so that it considers a wide range of smoothing parameters rather than selecting an optimal value. It also visually summarizes the significance of trends in the data as a color map across multiple locations and scales. We demonstrate its effectiveness as an exploratory data analysis tool for interval-valued data using simulated and real examples.     

The Effects of Early Institutionalization on the Discrimination of Facial Expressions of Emotion in Young Children

The current study examined the effects of institutionalization on the discrimination of facial expressions of emotion in three groups of 42‐month‐old children. One group consisted of children abandoned at birth who were randomly assigned to Care‐as‐Usual (institutional care) following a baseline assessment. Another group consisted of children abandoned at birth who were randomly assigned to high‐quality foster care following a baseline assessment. A third group consisted of never‐institutionalized children who were reared by their biological parents. All children were familiarized to happy, sad, fearful, and neutral facial expressions and tested on their ability to discriminate familiar versus novel facial expressions. Contrary to our prediction, all three groups of children were equally capable of discriminating among the different expressions. Furthermore, in contrast to findings at 13–30 months of age, these same children showed familiarity rather than novelty preferences toward different expressions. There were also asymmetries in children’s discrimination of facial expressions depending on which facial expression served as the familiar versus novel stimulus. Collectively, early institutionalization appears not to impact the development of the ability to discriminate facial expressions of emotion, at least when preferential looking serves as the dependent measure. These findings are discussed in the context of the myriad domains that are affected by early institutionalization.     

Developmental Trajectories and Predictors of Social Exclusion Among Older Koreans: Exploring the Multidimensional Nature of Social Exclusion

The purpose of this paper was to investigate the developmental patterns of social exclusion among older Koreans over time. In addition, we identified the significant determinants that may increase the risk of social exclusion among older Koreans. The analyses were based on the panel data from the Korean Longitudinal Study of Ageing and included older adults from 2008 to 2012 (N?=?24,074) for the final analysis. Social exclusion was categorized into four different sub-dimensions: financial, social relational, social cultural, and emotional. The analysis was based on a semi-parametric group-based approach followed by multinomial logistic regression. The results showed considerable variations and different developmental trajectories by the social exclusion sub-dimensions among older Koreans; in particular, the results showed that being older, male, and less educated were significant indicators of social exclusion. This study adds to the limited body of literature on longitudinal studies of social exclusion among older Koreans, and the results will help develop interventions for older Koreans who are socially isolated.

     

Compromise Allocation in Univariate Stratified Sampling

To reduce the loss of efficiency in the Neyman allocation caused by using the estimators instead of the unknown strata standard deviations of population, we suggest a compromise allocation that the Neyman allocation using an estimator of the pooled standard deviation of combined strata and the proportional allocation are used together. It is shown that the compromise allocation makes the estimator more efficient than the proportional allocation and the Neyman allocation using the estimated strata standard deviations. Simulation study is carried out for the numerical comparison and the results are reported.