Infusing Career Development to Strengthen Middle School English Language Arts Curricula

An approach is presented for strengthening middle school standards‐based English language arts (ELA) classroom instruction by infusing theory‐ and research‐supported career development constructs and practices. Over an 8‐week period, 90 urban 7th graders participated in an integrated ELA–career development curriculum. Career agency emerged as an important construct for students. It was related to key markers of ELA achievement (i.e., standardized test scores, grades, and positive change in 6th‐ to 7th‐grade test scores) and elaborated on in nuanced ways by students in their written narratives. Four themes related to career agency were identified in student writings: time perspective, challenges of self‐direction, career development, and social and emotional development. Advantages for students and schools related to synergy, scale, and sustainability are discussed.     

Trauma and health risk behaviors in people with severe mental illness

The current study tests the association between a composite measure of unsafe sex and sharing syringes for drug use with six of the more common lifetime traumatic/stressful events in 421 community mental health clients with severe mental illness (SMI) while controlling for psychiatric symptoms and related problems. A small but significant proportion of respondents said they had injected drugs with a shared needle in their lifetime (30, 7.2%), and a much larger proportion of respondents had engaged in unprotected sex (165, 39.2%). Unprotected sex and needle sharing were significantly correlated (Spearman’s rho = .20, p < .01). Frequency of lifetime traumatic events that occurred at least once was reported by one third to three quarters of clients depending on type of trauma. Regression analysis revealed that substance abuse and lifetime homelessness were significantly correlated with health risk behaviors. Practitioners need to be continuously vigilant to comorbid substance use and the housing needs of people with SMI. Limitations of the study include its cross-sectional design.     

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.     

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.     

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.