The Human Capital Characteristics and Household Living Standards of Returning International Migrants in Eastern and Southern Africa

Africa’s experience with return migration is not new. However, few empirical studies have examined the social and economic characteristics of returning migrants within the continent. In this study, the human capital endowments and household living standards of returning migrants in Uganda and South Africa are examined using recently available data. The study compares returnees in both countries with immigrants as well as the native‐born population with no international migration experience. It also investigates how factors such as previous country of residence, year of arrival, and other demographic factors predict levels of education and living standards among returning migrants. In Uganda, the results show that recently arrived returning migrants had better educational endowments than both immigrants and non‐migrants. Migrants who returned to Uganda following the fall of Idi Amin’s regime had the lowest educational levels and lowest living standards compared to other returnees. Furthermore, the results indicate that previous residence in countries in the West was associated with four additional years of schooling while returning migrants arriving from other African countries had the lowest levels of schooling among returning migrants. In South Africa, the study finds that returnees arriving almost immediately following the end of Apartheid had the highest levels of education compared to either immigrants or non‐migrants. Returnees on average also had the highest household living standards in South Africa. Among South African immigrants, the results indicate that those arriving towards the end of the century had lower educational endowments compared to immigrants who arrived in the country two to four years after the end of Apartheid.     

Coming Full Circle: Reoccurring Career Development Trends in Schools

Current state and national mandates focusing on academic achievement have drawn critical counseling resources away from career development. As the world of work radically changes and economic situations remain uncertain, the call for a return to school counseling roots based in career guidance has never been louder. The authors explore reoccurring career guidance trends throughout the history of school counseling to expand awareness of the basis of today's career and technical education discussions and increase understanding of the interconnectedness of career guidance and counseling and educational reform.     

Individual Differences in Infant Oculomotor Behavior During the Viewing of Complex Naturalistic Scenes

Little research hitherto has examined how individual differences in attention, as assessed using standard experimental paradigms, relate to individual differences in how attention is spontaneously allocated in more naturalistic contexts. Here, we analyzed the time intervals between refoveating eye movements (fixation durations) while typically developing 11‐month‐old infants viewed a 90‐min battery ranging from complex dynamic to noncomplex static materials. The same infants also completed experimental assessments of cognitive control, psychomotor reaction times (RT), processing speed (indexed via peak look during habituation), and arousal (indexed via tonic pupil size). High test–retest reliability was found for fixation duration, across testing sessions and across types of viewing material. Increased cognitive control and increased arousal were associated with reduced variability in fixation duration. For fixations to dynamic stimuli, in which a large proportion of saccades may be exogenously cued, we found that psychomotor RT measures were most predictive of mean fixation duration; for fixations to static stimuli, in contrast, in which there is less exogenous attentional capture, we found that psychomotor RT did not predict performance, but that measures of cognitive control and arousal did. The implications of these findings for understanding the development of attentional control in naturalistic settings are discussed.     

An Additive–Multiplicative Restricted Mean Residual Life Model

The mean residual life measures the expected remaining life of a subject who has survived up to a particular time. When survival time distribution is highly skewed or heavy tailed, the restricted mean residual life must be considered. In this paper, we propose an additive–multiplicative restricted mean residual life model to study the association between the restricted mean residual life function and potential regression covariates in the presence of right censoring. This model extends the proportional mean residual life model using an additive model as its covariate dependent baseline. For the suggested model, some covariate effects are allowed to be time‐varying. To estimate the model parameters, martingale estimating equations are developed, and the large sample properties of the resulting estimators are established. In addition, to assess the adequacy of the model, we investigate a goodness of fit test that is asymptotically justified. The proposed methodology is evaluated via simulation studies and further applied to a kidney cancer data set collected from a clinical trial.     

The Resilient Survivor—A Student Social Worker's Journey on Placement

This paper represents the continuation of my ‘personal and professional journey’ from social work student to social work practitioner focusing on my first Practice Learning Opportunity (PLO). Recognising the potential impact of childhood sexual abuse (CSA) in a classroom environment is as important as the potential impact on actual practice learning and practice. This is salient in the real world of social work practice as the potential misuse of a painful childhood experience has greater ramifications. Utilising the ideas and assumptions of social constructionism (including context and multivocality) the significance of silence from social work educators shall be examined in relation to self-disclosure as a means of aiding PLO learning and practice. This paper will also focus on the concept of critical reflection and its significance in exploring the transferability of a childhood experience such as CSA and personal and professional dilemmas regarding self-disclosure. This paper concludes by highlighting areas for consideration for both students and social work educators and conveys an important message regarding the importance of communication between students and social work educators.     

An Integrated Risk Assessment Model of Township‐Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory

Land subsidence risk assessment (LSRA) is a multi‐attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor‐level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster‐Shafer (D‐S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi‐Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information—quantitative or qualitative, complete or incomplete, and precise or imprecise—to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.     

The Box–Cox Transformation and Non‐Iterative Estimation Methods for Ordinal Log‐Linear Models

Recently Beh and Farver investigated and evaluated three non‐iterative procedures for estimating the linear‐by‐linear parameter of an ordinal log‐linear model. The study demonstrated that these non‐iterative techniques provide estimates that are, for most types of contingency tables, statistically indistinguishable from estimates from Newton's unidimensional algorithm. Here we show how two of these techniques are related using the Box–Cox transformation. We also show that by using this transformation, accurate non‐iterative estimates are achievable even when a contingency table contains sampling zeros.