The Relationship Between Social Support, Loneliness, and Subjective Well-Being in a Spanish Sample from a Multidimensional Perspective

The aim of this study was to investigate the association between social support, loneliness and well-being from a multidimensional perspective for which two structural models are proposed. The study included 2042 participants from Malaga City (Spain) who were aged between 18 and 95 years. For the dimensions frequency of support and satisfaction with support, the results show that partner support, family support, and support from friends, respectively, significantly decrease romantic loneliness, family loneliness, and social loneliness. On the other hand, community support has little effect on reducing social loneliness. Of the three types of support analyzed (emotional, informational and instrumental), emotional support was significantly more effective in reducing loneliness (family, romantic and social) and increasing well-being. Loneliness partially acts as a mediator variable, although it is affected by social support, but at the same time decreases the effects of social support on subjective well-being. The three types of loneliness have a strong negative impact on subjective well-being. Implications of these results are discussed.     

Occupational Segregation and the Female–Male Wage Differentials: Evidence for Spain

Using matched employer–employee data from the Spanish labour market in 2010, we analyse the effects of industrial, establishment and occupational segregation on the gender wage differential, disaggregating the latter contribution by different groups of workers belonging to different occupational areas and responsibility levels. These workers are employed in 61 occupations within 26,492 establishments in 51 different industries. Since the matched employer–employee data exhibit a particular type of grouped structure, which contrasts the statistical properties of such data with the random sample case, we estimate the effects of each type of gender segregation on the wage gap using a robust specification. We find that the major part of the contribution of gender segregation is not explained by differences in the observable characteristics. Furthermore, the estimations show that the educational female advantage has helped to narrow the gender wage gap caused by occupational segregation within each establishment only for those groups of workers with the lowest educational requirements.     

Estimating Intraclass Correlation Coefficient and Identifying Influential Observations Under One-Way Random Effects Model

In this paper we consider the estimation of intraclass correlation coefficient and identification of influential observations under one-way random effects model. We introduce an approach to correct negative estimation values induced by the method of moments estimator, and provide an interval estimation for intraclass correlation coefficient. We present the diagnostic tools to identify influential observations through the uncorrected estimate of intraclass correlation coefficient. A simulation study is conducted to investigate the performance of our procedure for identifying influential observations. We also apply the method on a real data of repeated blood pressure measurements.     

Deploying for Deliverance: The Digital Divide in Municipal Wireless Networks

Abstract

The use of information technology (IT) is growing; access and use differ among those from different races, ethnicities, income and education levels, jobs, ages, and genders. Although some argue that broadband technology could be the platform for universal access, the benefits are still debatable for municipalities providing access. The authors discuss how public officials have decided to lead, support, and usher in an era of rapid IT development through wireless broadband networks to address digital divide concerns, and how these claims may meet—or fail to meet—expectations. The purpose of this paper is twofold: (1) to propose a fruitful investigative overview of U.S. cities claiming that a municipal wireless network will bridge the “digital divide”; and (2) to employ discourse analysis to examine the digital divide language 24 municipal wireless networks (MWNs) use.     

Phi-Divergence Statistics for Testing Linear Hypotheses in Logistic Regression Models

In this paper we introduce and study two new families of statistics for the problem of testing linear combinations of the parameters in logistic regression models. These families are based on the phi-divergence measures. One of them includes the classical likelihood ratio statistic and the other the classical Pearson's statistic for this problem. It is interesting to note that the vector of unknown parameters, in the two new families of phi-divergence statistics considered in this paper, is estimated using the minimum phi-divergence estimator instead of the maximum likelihood estimator. Minimum phi-divergence estimators are a natural extension of the maximum likelihood estimator.     

Mapping Our Way: New Formations in Technical Services: Ohio Valley Group of Technical Services Librarians Annual Conference

Abstract

The annual meeting of the Ohio Valley Group of Technical Services Librarians (OVGTSL) was held May 16–18, 2007, at the Holiday Inn-University Plaza in Bowling Green, Kentucky. One hundred twenty technical services librarians from Indiana, Ohio, Kentucky, and points beyond gathered for programming centered around the theme of “Mapping Our Way: New Formations in Technical Services.”     

A variability taxonomy to support automation decision-making for manufacturing processes

Abstract

Although many manual operations have been replaced by automation in the manufacturing domain in various industries, skilled operators still carry out critical manual tasks such as final assembly. The business case for automation in these areas is difficult to justify due to increased complexity and costs arising out of process variabilities associated with those tasks. The lack of understanding of process variability in automation design means that industrial automation often does not realize the full benefits at the first attempt, resulting in the need to spend additional resource and time, to fully realize the potential. This article describes a taxonomy of variability when considering the automation of manufacturing processes. Three industrial case studies were analyzed to develop the proposed taxonomy. The results obtained from the taxonomy are discussed with a further case study to demonstrate its value in supporting automation decision-making.     

Mapping Our Way: New Formations in Technical Services: Ohio Valley Group of Technical Services Librarians Annual Conference

The annual meeting of the Ohio Valley Group of Technical Services Librarians (OVGTSL) was held May 16–18, 2007, at the Holiday Inn-University Plaza in Bowling Green, Kentucky. One hundred twenty technical services librarians from Indiana, Ohio, Kentucky, and points beyond gathered for programming centered around the theme of “Mapping Our Way: New Formations in Technical Services.”     

Influence diagnostics in Gaussian spatial linear models

Spatial linear models have been applied in numerous fields such as agriculture, geoscience and environmental sciences, among many others. Spatial dependence structure modelling, using a geostatistical approach, is an indispensable tool to estimate the parameters that define this structure. However, this estimation may be greatly affected by the presence of atypical observations in the sampled data. The purpose of this paper is to use diagnostic techniques to assess the sensitivity of the maximum-likelihood estimators, covariance functions and linear predictor to small perturbations in the data and/or the spatial linear model assumptions. The methodology is illustrated with two real data sets. The results allowed us to conclude that the presence of atypical values in the sample data have a strong influence on thematic maps, changing the spatial dependence structure.     

Optimism in the Face of Despair: Black‐White Differences in Beliefs About School as a Means for Upward Social Mobility*

Objective. This study aims to provide a better understanding of how beliefs about the system of social mobility affect students' schooling outcomes. Previous studies reach conflicting conclusions because they conflate two forms of beliefs about social mobility (i.e., perceived value of school and perceived barriers despite schooling). Methods. The Maryland Adolescence Development In Context Study (MADICS) is used to examine black‐white differences in beliefs about the value of school and barriers to upward mobility despite schooling and how these beliefs predict academic achievement and educational attainment. Results. The analyses show that relative to whites, blacks hold stronger beliefs in both the value of school and barriers to social mobility, and have greater affective attitudes toward schooling. However, belief in barriers to social mobility is not consequential for academic outcomes. Conclusions. Beliefs about upward mobility are mechanisms by which the opportunity structure influences individuals' schooling behaviors and making clear distinctions between various beliefs about the system of social mobility can refine the understanding of this link. This study suggests that individuals make nuanced distinctions about the role of schooling for upward mobility, each with separate effects on academic outcomes.