Non-response in social networks: The impact of different non-response treatments on the stability of blockmodels

Discerning the essential structure of social networks is a major task. Yet, social network data usually contain different types of errors, including missing data that can wreak havoc during data analyses. Blockmodeling is one technique for delineating network structure. While we know little about its vulnerability to missing data problems, it is reasonable to expect that it is vulnerable given its positional nature. We focus on actor non-response and treatments for this. We examine their impacts on blockmodeling results using simulated and real networks. A set of ‘known’ networks are used, errors due to actor non-response are introduced and are then treated in different ways. Blockmodels are fitted to these treated networks and compared to those for the known networks. The outcome indicators are the correspondence of both position memberships and identified blockmodel structures. Both the amount and type of non-response, and considered treatments, have an impact on delineated blockmodel structures.     

Are there domino effects between consumers' ordinary and ‘green’ practices? An analysis of quantitative data from a sensitisation campaign on personal carbon footprint

This paper studies how consumers' reported practices related to food, energy use in housing, daily mobility, and tourism are combined and structured. Social practice theories are the main theoretical framework of this research. Data are drawn from a sensitisation campaign run by the WWF-Belgium and the methods developed to attempt to translate the theoretical focus to practices. Results show that both the low number of ‘green’ practices reported and the multiplicity of combinations of practices indicate a rather important compartmentalisation of ‘green’ practices and seem to refute the hypothesis of vast domino effects in these four different areas. In addition, a wider openness to information on environmentally friendlier practices is associated with a larger number of such practices, which raises questions about the design of such campaigns. Finally, there is no conventionalised way of linking practices and commitments taken by the respondents to reduce their environmental impact. A few policy recommendations are derived for sensitisation campaigns that often assume domino effects between ‘green’ practices, and for tools dealing with personal carbon awareness.     

Role Conflict and Self‐Efficacy Among Employed Parents: Examining Complex Statistical Interactions

In response to growing concerns with explaining how work and family interfere with each other and with statistical approaches that do not capture the way in which predictors interact, this study tested statistical interactions involving personal and social resources of 410 full‐time employed women and men. The results indicate that self‐efficacy is a strong predictor of family interfering with work (FIW) and work interfering with family (WIF). Gender moderates the relation between supervisor support and WIF moderates the impact of efficacy beliefs and instrumental support at home on FIW. Specifically, while supervisor support is negatively related to WIF in women and men, high levels of support more strongly affected men's perceptions of WIF. In low self‐efficacy men, high levels of support at home improved their perceptions of FIW but these perceptions worsened in women. These findings contrast with earlier research that focus predominantly on the predictive value of structural demands (for example, the number of hours worked per week and family size). This study shows that gender plays a critical yet intricate role as a predictor of the successful management of work and family roles: it is not gender per se but its interaction with personal and social variables that informs us about differences in the experience of employed parents.     

INDIVIDUAL WELFARE WHEN CONSUMERS CAN SHOP FOR HEALTH INSURANCE

The statewide system of health insurance exchanges established by the Affordable Care Act (ACA) of 2010 will allow millions of U.S. citizens to change their health care policies more easily than they can switch automobile or homeowner insurance coverages, because deniability based on prior claim history is illegal. Focusing on this consumer endogeneity of health insurance policy choice, we examine the individual moral hazard welfare implications of a reduction in the price of medical care, which is a potential consequence of the ACA. We show that endogenous policy choice plays a key role in determining the welfare outcome. While moral hazard welfare improvement is not precluded, a distinctly possible outcome is that the consumer revises his/her choice of insurance policy so as to retain some portion of the reduction in expenditure risk caused by the medical care price decrease. In this event, moral hazard welfare loss is higher than it was before the price decrease, although the increased loss is tempered by the endogenous contract choice effect. This result resuscitates an old conventional wisdom. (JEL I11, I13, I30)     

Supporting the Caliph's Project: Bosnian Muslims and the Hejaz Railway

This article will analyse Bosnian Muslims response and contribution to the construction of the Hejaz Railway. Based on primary sources during the 1900–1908 period, the article will argue that Bosnian Muslims actively followed news about the progress of the railway and financially contributed to its construction. Bosnian Muslim contribution took the form of establishing committees for the collection of voluntary donations in a number of Bosnian towns in 1905 and 1906. The active involvement of Bosnian Muslims in the construction of the Hejaz Railway shows that the spiritual bonds between Bosnian Muslims living in Austria-Hungary and their Caliph in Istanbul were not completely severed by the Austro-Hungarian occupation of Bosnia in 1878. Following a brief survey of Bosnian Muslim history within the Austro-Hungarian Empire, the article describes the Hejaz Railway project and surveys the Bosnian Muslim contribution to the project.     

An optimal search procedure

Consider the following problem. There are exactly two defective (unknown) elements in the set X={x₁, x₂,…,x_n}, all possibilities occuring with equal probabilities. We want to identify the unknown (defective) elements by testing some subsets A of X, and for each such set A determining whether A contains any of them. The test on an individual subset A informs us that either all elements of the tested set A are good, or that at least one of them is defective (but we do not know which ones or how many). A set containing at least one defective element is said to be defective. Our aim is to minimize the maximal number of tests. For the optimal strategy, let the maximal test length be denoted by l₂(n). We obtain the value of this function for an infinite sequence of values of n.     

A novel feature selection scheme for high-dimensional data sets: four-Staged Feature Selection

Classification of high-dimensional data set is a big challenge for statistical learning and data mining algorithms. To effectively apply classification methods to high-dimensional data sets, feature selection is an indispensable pre-processing step of learning process. In this study, we consider the problem of constructing an effective feature selection and classification scheme for data set which has a small number of sample size with a large number of features. A novel feature selection approach, named four-Staged Feature Selection, has been proposed to overcome high-dimensional data classification problem by selecting informative features. The proposed method first selects candidate features with number of filtering methods which are based on different metrics, and then it applies semi-wrapper, union and voting stages, respectively, to obtain final feature subsets. Several statistical learning and data mining methods have been carried out to verify the efficiency of the selected features. In order to test the adequacy of the proposed method, 10 different microarray data sets are employed due to their high number of features and small sample size.     

Poverty Among The Elderly: An Application of a Collective Consumption Model in Brazil

Social Indicators Research - The growth of the elderly population and changes in household composition raise important questions regarding the level of well-being of the elderly in developing...     

Trajectories of Breadth of Participation in Organized Activity During Childhood

This study aimed to identify the trajectories of breadth of participation in organized activities during childhood and to examine the predictors of membership in these trajectories (child's individual and family characteristics measured in Kindergarten). A sample of 1038 children, recruited in Kindergarten, was assessed yearly between Kindergarten and grade 4. Semiparametric group‐based modeling brought out four trajectories: the no participation group (13.5 percent), the increasing group (26.4 percent), the decreasing group (14.1 percent), and the high group (46.1 percent). Prosociality predicted membership in the no participation group, as compared with the increasing group. Social withdrawal predicted membership in the no participation group, as compared with the high group. High family income and higher maternal education predicted membership in the increasing, decreasing, and high trajectory groups, as compared with the no participation group. Higher paternal education predicted membership in the high group, as compared with the increasing group. Overall, family variables had a greater impact than individual variables on the probability that the child would participate in a broader range of organized activities.