Analysis of sport psychology consultancy at three Olympic Games: Facts and figures

Objectives Despite many reports on best practises regarding onsite psychological services, little research has attempted to systematically explore the frequency, issues, nature and client groups of onsite sport psychology consultancy at the Olympic Games. The present paper will fill this gap through a systematic analysis of the sport psychology consultancy of the Swiss team for the Olympic Games of 2006 in Turin, 2008 in Beijing and 2010 in Vancouver. Design Descriptive research design. Methods The day reports of the official sport psychologist were analysed. Intervention issues were labelled using categories derived from previous research and divided into the following four intervention-issue dimensions: “general performance”, “specific Olympic performance”, “organisational” and “personal” issues. Data were analysed using descriptive statistics, chi square statistics and odds ratios. Results Across the Olympic Games, between 11% and 25% of the Swiss delegation used the sport psychology services. On average, the sport psychologist provided between 2.1 and 4.6 interventions per day. Around 50% of the interventions were informal interventions. Around 30% of the clients were coaches. The most commonly addressed issues were performance related. An association was observed between previous collaboration, intervention likelihood and intervention theme. Conclusions Sport psychologists working at the Olympic Games are fully engaged with daily interventions and should have developed ideally long-term relationships with clients to truly help athletes with general performance issues. Critical incidents, working with coaches, brief contact interventions and team conflicts are specific features of the onsite consultancy. Practitioners should be trained to deal with these sorts of challenges.

Do Information, Price, or Morals Influence Ethical Consumption? A Natural Field Experiment and Customer Survey on the Purchase of Fair Trade Coffee

We address ethical consumption using a natural field experiment on the actual purchase of Fair Trade (FT) coffee in three supermarkets in Germany. Based on a quasi-experimental before-and-after design the effects of three different treatments – information, 20% price reduction, and a moral appeal – are analyzed. Sales data cover actual ethical purchase behavior and avoid problems of social desirability. But they offer only limited insights into the motivations of individual consumers. We therefore complemented the field experiment with a customer survey that allows us to contrast observed (ethical) buying behavior with self-reported FT consumption. Results from the experiment suggest that only the price reduction had the expected positive and statistically significant effect on FT consumption.

Social Network Analysis and Qualitative Comparative Analysis: Their mutual benefit for the explanation of policy network structures

By switching the level of analysis and aggregating data from the micro-level of individual cases to the macro-level, quantitative data can be analysed within a more case-based approach. This paper presents such an approach in two steps: In a first step, it discusses the combination of Social Network Analysis (SNA) and Qualitative Comparative Analysis (QCA) in a sequential mixed-methods research design. In such a design, quantitative social network data on individual cases and their relations at the micro-level are used to describe the structure of the network that these cases constitute at the macro-level. Different network structures can then be compared by QCA. This strategy allows adding an element of potential causal explanation to SNA, while SNA-indicators allow for a systematic description of the cases to be compared by QCA. Because mixing methods can be a promising, but also a risky endeavour, the methodological part also discusses the possibility that underlying assumptions of both methods could clash. In a second step, the research design presented beforehand is applied to an empirical study of policy network structures in Swiss politics. Through a comparison of 11 policy networks, causal paths that lead to a conflictual or consensual policy network structure are identified and discussed. The analysis reveals that different theoretical factors matter and that multiple conjunctural causation is at work. Based on both the methodological discussion and the empirical application, it appears that a combination of SNA and QCA can represent a helpful methodological design for social science research and a possibility of using quantitative data with a more case-based approach.

Political Depolarization in German Public Opinion, 1980–2010

Little is known about political polarization in German public opinion. This article offers an issue-based perspective and explores trends of opinion polarization in Germany. Public opinion polarization is conceptualized and measured as alignment of attitudes. Data from the German General Social Survey (1980 to 2010) comprise attitudes towards manifold issues, which are classified into several dimensions. This study estimates multilevel models that reveal general and issue- as well as dimension-specific levels and trends in attitude alignment for both the whole German population and sub-groups. It finds that public opinion polarization has decreased over the last three decades in Germany. In particular, highly educated and more politically interested people have become less polarized over time. However, polarization seems to have increased in attitudes regarding gender issues. These findings provide interesting contrasts to existing research on the American public.

The FORA Framework - A Fuzzy Grassroots Ontology for Online Reputation Management

Online reputation management deals with monitoring and influencing the online record of a person, an organization or a product. The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly have a disastrous influence on the online reputation of some of the entities. This dissertation can be split into three parts: In the first part, possible fuzzy clustering applications for the Social Semantic Web are investigated. The second part explores promising Social Semantic Web elements for organizational applications,while in the third part the former two parts are brought together and a fuzzy online reputation analysis framework is introduced and evaluated. Theentire PhD thesis is based on literature reviews as well as on argumentative-deductive analyses.The possible applications of Social Semantic Web elements within organizations have been researched using a scenario and an additional case study together with two ancillary case studies—based on qualitative interviews. For the conception and implementation of the online reputation analysis application, a conceptual framework was developed. Employing test installations and prototyping, the essential parts of the framework have been implemented.By following a design sciences research approach, this PhD has created two artifacts: a frameworkand a prototype as proof of concept. Bothartifactshinge on twocoreelements: a (cluster analysis-based) translation of tags used in the Social Web to a computer-understandable fuzzy grassroots ontology for the Semantic Web, and a (Topic Maps-based) knowledge representation system, which facilitates a natural interaction with the fuzzy grassroots ontology. This is beneficial to the identification of unknown but essential Web data that could not be realized through conventional online reputation analysis. Theinherent structure of natural language supports humans not only in communication but also in the perception of the world. Fuzziness is a promising tool for transforming those human perceptions intocomputer artifacts. Through fuzzy grassroots ontologies, the Social Semantic Web becomes more naturally and thus can streamline online reputation management.

Cognitive Interventions with Children with Special Needs - Transfer effects and multidisciplinary perspectives

Our last study with regularly developed children demonstrated a positive effect of working memory training on cognitive abilities. Building upon these findings, the aim of this multidisciplinary study is to investigate the effects of training of core functions with children who are suffering from different learning disabilities, like AD/HD, developmental dyslexia or specific language impairment. In addition to working memory training (BrainTwister), we apply a perceptual training, which concentrates on auditory-visual matching (Audilex), as well as an implicit concept learning task. We expect differential improvements of mental capacities, specifically of executive functions (working memory, attention, auditory and visual processing), scholastic abilities (language and mathematical skills), as well as of problem solving. With that, we hope to find further directions regarding helpful and individually adapted interventions in educational settings. Interested parties are invited to discuss and comment the design, the research question, and the possibilities in recruiting the subjects.

Estimating Intra-Party Preferences: Comparing Speeches to Votes

Well-established methods exist for measuring party positions, but reliable means for estimating intra-party preferences remain underdeveloped. While most efforts focus on estimating the ideal points of individual legislators based on inductive scaling of roll call votes, this data suffers from two problems: selection bias due to unrecorded votes and strong party discipline, which tends to make voting a strategic rather than a sincere indication of preferences. By contrast, legislative speeches are relatively unconstrained, as party leaders are less likely to punish MPs for speaking freely as long as they vote with the party line. Yet, the differences between roll call estimations and text scalings remain essentially unexplored, despite the growing application of statistical analysis of textual data to measure policy preferences. Our paper addresses this lacuna by exploiting a rich feature of the Swiss legislature: on most bills, legislators both vote and speak many times. Using this data, we compare text-based scaling of ideal points to vote-based scaling from a crucial piece of energy legislation. Our findings confirm that text scalings reveal larger intra-party differences than roll calls. Using regression models, we further explain the differences between roll call and text scalings by attributing differences to constituency-level preferences for energy policy.

Three Experimental Approaches to Measure the Social Context Dependence of Prejudice Communication and Discriminatory Behavior

Empirical research on discrimination is faced with crucial problems stemming from the specific character of its object of study. In democratic societies the communication of prejudices and other forms of discriminatory behavior is considered socially undesirable and depends on situational factors such as whether a situation is considered private or whether a discriminatory consensus can be assumed. Regular surveys thus can only offer a blurred picture of the phenomenon. But also survey experiments intended to decrease the social desirability bias (SDB) so far failed in systematically implementing situational variables. This paper introduces three experimental approaches to improve the study of discrimination and other topics of social (un-)desirability. First, we argue in favor of cognitive context framing in surveys in order to operationalize the salience of situational norms. Second, factorial surveys offer a way to take situational contexts and substitute behavior into account. And third, choice experiments – a rather new method in sociology – offer a more valid method of measuring behavioral characteristics compared to simple items in surveys. All three approaches – which may be combined – are easy to implement in large-scale surveys. Results of empirical studies demonstrate the fruitfulness of each of these approaches.

Relative Distribution Methods in Stata

The concept of the relative density seems like a fruitful nonparametric approach to studying distributional differences between groups (Handcock and Morris 1999), yet it appears that the technique has gone more or less unnoticed in applied social science research. A scarcity of canned software might be one of the reasons the method is underutilized. Therefore, I present a new Stata command called reldist to plot the relative density, decompose distributional differences into location and shape effects, and compute relative distribution summary measures. The command is illustrated by an application comparing earnings by sex.

Moral Opinion Polarization and the Erosion of Trust

Since Puntam's seminal work on declining levels of social capital, the question of how social trust is formed has reached unprecedented heights of critical enquiry. While most of the current research concentrates on ethnic diversity and income inequality as the main influences driving down generalized trust, we focus on opinion polarization as another potential impact factor on trust. In more detail, we investigate the extent to which polarization over morally charged issues such as homsexuality, abortion and euthanasia affects individuals' likelihood to trust others. We hypothesize that moral issues have a natural tendency to divide societies' opinions into opposing poles and, thus, to challenge social cohesion in modern civil societies. Based on hierarchical analyses of the fifth wave of the World Values Survey (WVS) — comprising a sample of 39 countries — our results reveal that individuals living in countries characterized by more opinion polarization tend to have less trust in other people.