African American MSW Students: Personal Influences on Social Work Careers and Factors in Graduate School Selection

The research is an empirical examination of who the individuals were that influenced 207 African American respondents to pursue graduate social work education, and what enrollment decision factors (EDFs) led them to select a social work program. Statistically significant relationships between EDFs are also isolated. The purposive sample consisted of MSW graduates from three predominantly White universities in two southeastern states in the United States. Almost 80% were females, the mean age was 44.5 years, and 45% majored in social work as undergraduates. Individuals who reportedly had ‘a great deal of influence’ in their selection of graduate social work education included social work practitioners, family members, and undergraduate professors. The ‘very important’ EDFs included geographical location, type of social work program, class scheduling, and cost of tuition. The strongest EDF correlations were between (1) number of minority students and number of minority faculty (r?=?0.662, p?=?0.000, 0.01 level, 2‐tailed); (2) academic reputation and type of social work program (r?=?0.590, p?=?0.000, 0.01 level, 2‐tailed); and (3) number of minority faculty and school climate toward minorities (r?=?0.523, p?=?0.000, 0.01 level, 2‐tailed). Findings suggest that graduate school recruitment strategies for African Americans and other under‐represented groups should include use of social work practitioners and educators, as well as more informed and deliberate marketing approaches with respect to school curricula and how it translates into future career options.     

On the Use of the Cause Table in Handling Common Cause Events in System Analysis

A method is presented for applying the cause table concept to the problem of common cause events. This method can be regarded as an alternative to the approach in which these events are included directly into the system fault trees. In comparison with this approach, the cause table method offers the advantage of simple fault trees, convenient visibility of the contributions of causes, and the ability to truncate the numerical calculation conveniently by aggregating small terms into an "other" category. Generally speaking, the cause table method can be said to handle common causes at the level of arithmetic (i.e., numbers) rather than at the level of algebra (determining cutsets and frequency equations).     

Re-thinking a systemic approach to child welfare: A critical response to the framework for the assessment of children in need and their families

The Framework for the Assessment of Children in Need was introduced by the Department of Health (England and Wales) in 2000. Offering guidance to social workers in child and family settings, it came as a watershed in three main ways. First, it emphasized the connection between child poverty and developmental delay. Second, it advocated a systemic approach to child welfare by drawing on a number of related theories, including Bronfenbrenner's (1979) model of human development. Third, it overturned a restricted preoccupation with child abuse that had dominated much of child and family social work in the past. These developments aside, the systemic basis of the framework is problematic because it fails to explain how power operates within society. Without this understanding, social workers will not be in a position to tackle the inequalities which the framework rightly targets. This paper seeks to remedy these deficits by drawing on the critical systems theory of Jürgen Habermas.     

Reproducibility of the Dose-Response Curve of Steroid-Induced Cleft Palate in Mice

Pregnant CD-1 mice were exposed to cortisone acetate at doses ranging from 20 to 100 mg/kg/ day on days 10-13 by oral and intramuscular routes. Multiple replicate assays were conducted under identical conditions to assess the reproducibility of the dose–response curve for cleft palate. The data were fitted to the probit, logistic, multistage or Armitage-Doll, and Weibull dose-response model separately for each route of exposure. The curves were then tested for parallel slopes (probit and logistic models) or coincidence of model parameters (multistage and Weibull models). The 19 replicate experiments had a wide range of slope estimates, wider for the oral than for the intramuscular experiments. For all models and both routes of exposure the null hypothesis of equality of slopes was rejected at a significant level of p < 0.001. For the intramuscular group of replicates, rejection of slope equality could in part be explained by not maintaining a standard dosing regime. The rejection of equivalence of dose-response curves from replicate studies showed that it is difficult to reproduce dose-response data of a single study within the limits defined by the dose-response model. This has important consequences for quantitative risk assessment, public health measures, or development of mechanistic theories which are typically based on a single animal bioassay.     

Building resilience in a children's home: results from an action research project

This paper reports on the findings of an action research project aimed at building resilience in young people in a residential children's home. Daniel and Wassell's six domains for promoting resilience in young people were adopted as a conceptual framework to guide the residential social workers as they engaged in successive cycles of reflection and action. Two core areas were explored: (a) the approaches deemed to be helpful in building resilience; and (b) the background factors that enabled and constrained the social workers' interventions. The findings showed that the participants acted creatively to use resources and tools both within the system of State‐mandated parenting and the informal, meaning‐oriented world of the young people.     

How smart is smart? Theoretical and empirical considerations on implementing smart city objectives – a case study of Dutch railway station areas

The current widespread attention on the concept of smart city in both policy and practice has stimulated academic discussion regarding the scope and applicability of this concept. An important question is whether cities and regions are truly advanced in implementing the concept in their policies and practices relative to its conceptual elaborations in academia. The aim of this paper is to analyse this congruence between theory and practice in the context of the ongoing transformations of railway station areas in European urban regions. Based on in-depth interviewing using aspects of Q-methodology, this paper investigates whether and how smart city concepts are implemented by stakeholders in three station redevelopment projects in the Netherlands. The results show that the current implementation of smart city concepts in practice is varied but modest and not (yet) very advanced. Knowledge exchange and innovations are currently hampered by a lack of acceptance and know-how among stakeholders, as well as by institutional and competitive constraints. For instance, stakeholders stress that data privacy regulations should be well organized before further implementation can occur. Transparency about how and what data are used may create more willingness among users to assist in developing and accepting new data technologies. However, the technologies are not yet completely developed, and concerns about the “loss” of personal privacy are holding back the widespread and advanced use of data supplied technologies. Although stakeholders seem to be aware of the opportunities the smart city concept offers, for now, the widespread implementation of innovative and advanced smart city concepts remains in the future.     

Approximations for Estimating Change in Life Expectancy Attributable to Air Pollution in Relation to Multiple Causes of Death Using a Cause Modified Life Table

There is considerable debate as to the most appropriate metric for characterizing the mortality impacts of air pollution. Life expectancy has been advocated as an informative measure. Although the life‐table calculus is relatively straightforward, it becomes increasingly cumbersome when repeated over large numbers of geographic areas and for multiple causes of death. Two simplifying assumptions were evaluated: linearity of the relation between excess rate ratio and change in life expectancy, and additivity of cause‐specific life‐table calculations. We employed excess rate ratios linking PM_2.5 and mortality from cerebrovascular disease, chronic obstructive pulmonary disease, ischemic heart disease, and lung cancer derived from a meta‐analysis of worldwide cohort studies. As a sensitivity analysis, we employed an integrated exposure response function based on the observed risk of PM_2.5 over a wide range of concentrations from ambient exposure, indoor exposure, second‐hand smoke, and personal smoking. Impacts were estimated in relation to a change in PM_2.5 from 19.5 μg/m³ estimated for Toronto to an estimated natural background concentration of 1.8 μg/m³. Estimated changes in life expectancy varied linearly with excess rate ratios, but at higher values the relationship was more accurately represented as a nonlinear function. Changes in life expectancy attributed to specific causes of death were additive with maximum error of 10%. Results were sensitive to assumptions about the air pollution concentration below which effects on mortality were not quantified. We have demonstrated valid approximations comprising expression of change in life expectancy as a function of excess mortality and summation across multiple causes of death.     

Predictor relative importance and matching regression parameters

Predictor importance in applied regression modeling gives the main operational tools for managers and decision-makers. The paper considers estimation of predictors' importance in regression using measures introduced in works by Gibson and R. Johnson (GJ), then modified by Green, Carroll, and DeSarbo, and developed further by J. Johnson (JJ). These indices of importance are based on the orthonormal decomposition of the data matrix, and the work shows how to improve this approximation. Using predictor importance, the regression coefficients can also be adjusted to reach the best data fit and to be meaningful and interpretable. The results are compared with the robust to multicollinearity, but computationally difficult, Shapley value regression (SVR). They show that the JJ index is good for importance estimation, but the GJ index outperforms it if both predictor importance and coefficients of regression are needed; hence, this index (GJ) can be used in place of the more computationally intensive estimation by SVR. The results can be easily estimated by the considered approach that is very useful in practical regression modeling and analysis, especially for big data.     

The Job Demand-Control (-Support) Model and psychological well-being: A review of 20 years of empirical research

The Job Demand-Control (JDC) model (Karasek, 1979) and the Job Demand-Control-Support (JDCS) model (Johnson, and Hall, 1988) have dominated research on occupational stress in the last 20 years. This detailed narrative review focuses on the JDC(S) model in relation to psychological well-being. It covers research from 63 samples, published in the period 1979-1997. In the review a distinction is drawn between two different hypotheses prevailing in research on the models. According to the strain hypothesis of the JDC model, employees working in a high-strain job (high demands-low control) experience the lowest well-being. The buffer hypothesis states that control can moderate the negative effects of high demands on well-being. Translating these hypotheses to the expanded JDCS model, the iso-strain hypothesis predicts the most negative outcomes among workers in an iso-strain job (high demands-low control-low social support/isolation), whereas the buffer hypothesis states that social support can moderate the negative impact of high strain on well-being. Although the literature gives considerable support for the strain and iso-strain hypotheses, support for the moderating influence of job control and social support is less consistent. The conceptualization of demands and control is a key factor in discriminating supportive from nonsupportive studies. Only aspects of job control that correspond to the specific demands of a given job moderate the impact of high demands on well-being. Furthermore, certain subpopulations appear to be more vulnerable to high (iso)strain, whereas others benefit more from high control. On the basis of the results of this review, suggestions for future research and theoretical development are formulated.     

Three methods of estimating births averted nationally by contraception

This paper compares the performance of three methods applicable to national-level demographic data of estimating births averted as a consequence of contraceptive practice. Two are based on the relationship between the general fertility rate (GFR) or total fertility (TFR) and contraceptive prevalence, while the third uses Bongaarts' proximate determinants (PD) model. Estimates of the number of births averted and the percentage by which the number would have increased in the absence of contraception are consistent between the GFR-based and TFR-based methods, but in general lower than the estimates generated by the PD-based method, except for a few high-contraceptive-prevalence countries. For 156 countries and areas around the world the estimated number of births that would have occurred in a recent year in the absence of contraception--the average of the estimates of the three methods--is approximately 230 million, which is more than the estimated 129 million births that actually occurred.