Construct Validity of the Emotion Matching Task: Preliminary Evidence for Convergent and Criterion Validity of a New Emotion Knowledge Measure for Young Children

Current emotion knowledge (EK) measures examine only one component of the multifaceted construct. We examined the reliability and the construct validity of a new measure of EK, the emotion matching task (EMT). The EMT consists of four parts which measure the components of receptive EK, expressive EK, emotion situation knowledge, and emotion expression matching. First, we compared the EMT and its parts to two widely used EK measures—the Kusche emotional inventory (KEI) and Denham's affective knowledge test (AKT, 1986) in order to establish convergent validity. The EMT and its four parts were strongly correlated with both measures of EK. Regression analyses revealed moderate to strong predictive validity for EMT. Compared with KEI and AKT, the EMT was a more robust predictor of teacher-rated emotion regulation and parent reported effortful control. Compared with KEI and AKT, the EMT correlated similarly with verbal ability and age.     

Social Inclusion or Market Competitiveness? A Comparison of Rural Development Policies in the European Union and the United States

The language of EU rural development policy appears more interested in social inclusion and that of US policy more interested in market competitiveness. We seek to determine why policies directed at rural development in the EU and the USA differ. In both contexts new rural development policies emphasize partnership and participation but we find local participation is used to promote social inclusion in the EU and market competitiveness in the USA. An examination of these dimensions illustrates important transcontinental differences and similarities in rural development policies. We explore the socio‐historical reasons for differences in the commitment to social inclusion, while also noting similarities in the priority of market competitiveness.     

Friends of the Circuits: Interest Group Influence on Decision Making in the U.S. Courts of Appeals*

Objective. Though there is an extensive literature focused on the participation and efficacy of interest group amici curiae in the U.S. Supreme Court, there is little rigorous analysis of amici curiae in the U.S. Courts of Appeals. Here, we systematically analyze the influence of amicus curiae briefs on U.S. Court of Appeals decision making to provide insights regarding both judicial decision making and the efficacy of interest groups. Methods. We use a probit model to capture influences on appellant success in the courts of appeals from 1997–2002. Results. We find that amicus briefs filed in support of the appellant enhance the likelihood of that litigant's probability of success, but that amicus briefs filed in support of the appellee have no effect on litigation outcomes. Conclusion. Amici can help level the playing field between appellants and appellees by serving to counter the propensity to affirm in the U.S. Courts of Appeals.     

Organizational strengths and challenges of Kenyan NGOs serving orphans and vulnerable children: a template analysis

This qualitative study of Kenyan non-governmental organizations (NGOs) identified strengths and challenges associated with service provision to orphans and vulnerable children (OVC). From September to December 2006, data were collected by Kenyan research assistants in 34 NGOs in Nairobi and Eldoret. In-depth interviews were used to explore the perceptions of directors and staff in relation to organizational strengths and challenges in serving OVC. Structuration theory and template analysis were used to identify higher-order codes related to strengths and challenges of human agents, organizations and societal forces. Emergent themes and supporting interview quotations are presented to highlight common patterns across organizations, including strengths such as staff commitment, client outcomes, and resourceful communities, as well as challenges such as lack of staff, funding, and parental involvement. Through the analysis we uncover insights about the recursive relationship between micro and macro realities in Kenyan NGOs and the accompanying human and social transformations that result from providing services to OVC.     

A location analysis approach for military maintenance scheduling with geographically dispersed service areas

This research uses a two-stage maximal covering location problem (MCLP) model to develop Inter continental ballistic missile (ICBM) maintenance schedules for the US Air Force. Solutions are compared to actual missile maintenance activities accomplished at F. E. Warren Air Force Base (AFB), Wyoming in May 2005. Sensitivity analysis is performed to determine the impact of altering security response times and the number of security patrol areas on the quality of daily maintenance schedules and personnel usage. Results indicate marked improvement over traditional Air Force scheduling methods. In addition sensitivity analysis identifies the levels at which the quality and quantity of maintenance performance is impacted.     

Schulleitungscoaching – Konzeption und Ausbildungsevaluation

Since principals in schools are increasingly turning into managers of educational institutions, coaching approaches have an increasing importance. Accordingly, the Bavarian Ministry for Education and Culture in cooperation with the National Institute for Quality in Schools and Educational Research and the Academy of Teacher Education and Personnel Management has introduced the project ?Coaching – an Instrument to Professionalise School-based Leadership“. The project involves exemplary coachings of school management teams and the training of coaches with a focus on school-related issues at the University of Innsbruck. The training of coaches is based on a special curriculum, which was evaluated using a multi-methods approach. The outcomes show that the coaching model is accepted by coaches and that the training is of high quality     

Restricted most powerful Bayesian tests for linear models

Uniformly most powerful Bayesian tests (UMPBTs) are a new class of Bayesian tests in which null hypotheses are rejected if their Bayes factor exceeds a specified threshold. The alternative hypotheses in UMPBTs are defined to maximize the probability that the null hypothesis is rejected. Here, we generalize the notion of UMPBTs by restricting the class of alternative hypotheses over which this maximization is performed, resulting in restricted most powerful Bayesian tests (RMPBTs). We then derive RMPBTs for linear models by restricting alternative hypotheses to g priors. For linear models, the rejection regions of RMPBTs coincide with those of usual frequentist F‐tests, provided that the evidence thresholds for the RMPBTs are appropriately matched to the size of the classical tests. This correspondence supplies default Bayes factors for many common tests of linear hypotheses. We illustrate the use of RMPBTs for ANOVA tests and t‐tests and compare their performance in numerical studies.     

Unconditional Quantile Regressions

We propose a new regression method to evaluate the impact of changes in the distribution of the explanatory variables on quantiles of the unconditional (marginal) distribution of an outcome variable. The proposed method consists of running a regression of the (recentered) influence function (RIF) of the unconditional quantile on the explanatory variables. The influence function, a widely used tool in robust estimation, is easily computed for quantiles, as well as for other distributional statistics. Our approach, thus, can be readily generalized to other distributional statistics.