Coaching und Mentoring

The program “Mentoring for female junior executives at schools” in Hamburg has the goal of recruiting more female executives for schools in Hamburg. As a headmaster of a high school the author has attended this program as a mentor. She discusses the following questions: What are the differences between mentoring and coaching? Where are the limits of mentoring? When is coaching the better method? The main result is, that the mentor has to be very attentively of his position as a member of the organization. He has to decide, if he can advise the mentee for example in conflicts with superiors or if a coach could do a better job. A missing link in the mentoring program is the analysis of the culture of organizations, because this is an important factor for a successful start into the new function.     

The disinterested state: negative diasporic policy as an expression of state inclusion and national exclusion

ABSTRACT

This article engages with the understudied phenomenon of the ‘disinterested, denouncing’ diaspora state (Levitt, P., and N. G. Schiller. 2004. “Conceptualizing Simultaneity: A Transnational Social Field Perspective on Society.” International Migration Review 38 (3): 1002–1039. doi:10.1111/j.1747-7379.2004.tb00227.x) or ‘indifferent’ diaspora state (Ragazzi, F. 2009. “Governing Diasporas.” International Political Sociology 3 (4): 378–397. doi:10.1111/j.1749-5687.2009.00082.x). Focusing on U.S. citizens abroad, the article argues that there is negative diasporic outreach on the part of the state – ‘disinterested’ from the state's perspective, but ‘denouncing’ from that of the diaspora. Negative diasporic outreach is exemplified by the 2010 FATCA legislation, which sought to root out tax evaders resident in the U.S., but has, instead, affected millions of American emigrants through increased financial control and the repercussions of those policies, and has resulted in sharply higher citizenship renunciation figures. Impact on an American diaspora was not considered in the law's proposal, debate and passage into law. Second, the article argues that this negative diasporic outreach, in combination with the continued facilitation of the right to vote, is a reflection of the inclusion of these American emigrants in the American state, but their simultaneous exclusion from the American nation.     

THE FAILURE TO PREDICT THE GREAT RECESSION—A VIEW THROUGH THE ROLE OF CREDIT

Much has been written about why economists failed to predict the latest crisis. Reading the literature, it seems that this crisis was so obvious that economists must have been blind not to see it coming. We approach this failure by looking at one of the key variables in this analysis, the evolution of credit. We compare the conclusions reached in the recent literature with those that could have been drawn from an ex‐ante analysis. We show that the effect of credit on the business cycle cannot be exploited from a policymaker's point of view.     

Testing Overdispersion in CUBE Models

A practical problem with large-scale survey data is the possible presence of overdispersion. It occurs when the data display more variability than is predicted by the variance–mean relationship. This article describes a probability distribution generated by a mixture of discrete random variables to capture uncertainty, feeling, and overdispersion. Specifically, several tests for detecting overdispersion will be implemented on the basis of the asymptotic theory for maximum likelihood estimators. We discuss the results of a simulation experiment concerning log-likelihood ratio, Wald, Score, and Profile tests. Finally, some real datasets are analyzed to illustrate the previous results.     

Influence diagnostics for the Weibull-Negative-Binomial regression model with cure rate under latent failure causes

In this paper, we propose a flexible cure rate survival model by assuming that the number of competing causes of the event of interest follows the Negative Binomial distribution and the time to event follows a Weibull distribution. Indeed, we introduce the Weibull-Negative-Binomial (WNB) distribution, which can be used in order to model survival data when the hazard rate function is increasing, decreasing and some non-monotonous shaped. Another advantage of the proposed model is that it has some distributions commonly used in lifetime analysis as particular cases. Moreover, the proposed model includes as special cases some of the well-know cure rate models discussed in the literature. We consider a frequentist analysis for parameter estimation of a WNB model with cure rate. Then, we derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and present some ways to perform global influence analysis. Finally, the methodology is illustrated on a medical data.     

Investigating impacts of complex sampling on latent growth curve modelling

We investigate the impacts of complex sampling on point and standard error estimates in latent growth curve modelling of survey data. Methodological issues are illustrated with empirical evidence from the analysis of longitudinal data on life satisfaction trajectories using data from the British Household Panel Survey, a national representative survey in Great Britain. A multi-process second-order latent growth curve model with conditional linear growth is used to study variation in the two perceived life satisfaction latent factors considered. The benefits of accounting for the complex survey design are considered, including obtaining unbiased both point and standard error estimates, and therefore correctly specified confidence intervals and statistical tests. We conclude that, even for the rather elaborated longitudinal data models that were considered, estimation procedures are affected by variance-inflating impacts of complex sampling.     

Barrios and burbs: residential context and health-risk behaviors among Angeleno adolescents

The increasing size of the Latino immigrant population in the United States underscores the need for a more complete understanding of the role that social context plays in influencing the health of immigrants and their children. This analysis explores the possibility that residential location influences the health-risk behaviors of Latino youth in Los Angeles County, California. The data come from the Los Angeles Family and Neighborhood Survey. We apply multivariate, multilevel Rasch models to two scales of adolescent health-risk behaviors (substance use and delinquency). The findings suggest that residence in Census tracts characterized by above-county-average levels of Latinos and above-county-average levels of poverty is associated with increased odds of health-risk behaviors for Latino adolescents, particularly for those born in the United States. The findings lend support to the contention, put forth in the segmented assimilation literature, that disadvantaged urban contexts increase the risk that U.S.-born children of immigrants will experience downward assimilation.     

SIMPCA: a framework for rotating and sparsifying principal components

We propose an algorithmic framework for computing sparse components from rotated principal components. This methodology, called SIMPCA, is useful to replace the unreliable practice of ignoring small coefficients of rotated components when interpreting them. The algorithm computes genuinely sparse components by projecting rotated principal components onto subsets of variables. The so simplified components are highly correlated with the corresponding components. By choosing different simplification strategies different sparse solutions can be obtained which can be used to compare alternative interpretations of the principal components. We give some examples of how effective simplified solutions can be achieved with SIMPCA using some publicly available data sets.     

Population Density is a Key Factor in Declining Human Fertility

In studying the complex determinants of human fertility, social scientists have given little attention to population density, although reproduction has been shown to be density-dependent for a wide variety of other species. Using fixed effects models on the time series of 145 countries and controlling for key social and economic variables, we find a consistent and significant negative relationship between human fertility and population density. Moreover, we find that individual fertility preferences also decline with population density. These findings suggest that population density should be included as a variable in future studies of fertility determinants.