GINI DP 20: Does Income Inequality Negatively Affect General Trust? Examining three potential problems with the inequality-trust hypothesis

Many studies on the consequences of income inequality find that where inequality is high, trust is low. There are, however, reasons to examine the relation between inequality and trust more closely. First, previous research does not differentiate between the effect of income inequality and that of national wealth. Furthermore, the underlying mechanism is often unclear. Finally, the association might be dependent on non-Western countries where income inequality is extremely high. In this paper, we evaluate whether there is a relation between income inequality and trust in a sample of Western developed economies when taking into account national wealth. Theoretically, we distinguish between stratification effects and perception effects of inequality. Empirically, besides actual income inequality and national wealth, we include a measurement of perceived inequality on the basis of individual level earnings estimations for stereotypical jobs. We find no significant effect of inequality on trust when taking into account national wealth, suggesting that in Western countries the amount of resources rather than its distribution explains trust. Key words: trust, income inequality, perceived inequality, national wealth, comparative research.

Social capital and economic growth in Polish regions

There is an ongoing debate on social capital resources in Poland, where the density of associational activities and the level of social trust is low when compared to West European countries. Moreover, some researchers claim that Polish economy is developing despite low resources of social capital. This paper examines spatial patterns of various forms of social capital (networks and trust; bonding and bridging social capital; family, friendship, neighbourhood and associational ties) in Poland and determinants of their distribution. It analyses relations between resources of social capital and regional growth.social capital, regional growth, Poland

“They’re All the Same!” Stereotypical Thinking and Systematic Errors in Users’ Privacy-Related Judgments About Online Services

Given the ever-increasing volume of online services, it has become impractical for Internet users to study every company’s handling of information privacy separately and in detail. This challenges a central assumption held by most information privacy research to date—that users engage in deliberate information processing when forming their privacy-related beliefs about online services. In this research, we complement previous studies that emphasize the role of mental shortcuts when individuals assess how a service will handle their personal information. We investigate how a particular mental shortcut—users’ stereotypical thinking about providers’ handling of user information—can cause systematic judgment errors when individuals form their beliefs about an online service. In addition, we explore the effectiveness of counter-stereotypic privacy statements in preventing such judgment errors. Drawing on data collected at two points in time from a representative sample of smartphone users, we studied systematic errors caused by stereotypical thinking in the context of a mobile news app. We found evidence for stereotype-induced errors in users’ judgments regarding this provider, despite the presence of counter-stereotypic privacy statements. Our results further suggest that the tone of these statements makes a significant difference in mitigating the judgment errors caused by stereotypical thinking. Our findings contribute to emerging knowledge about the role of cognitive biases and systematic errors in the context of information privacy

Identifying Influential Agents In Social Systems

This dissertation addresses the problem of influence maximization in social networks. In- fluence maximization is applicable to many types of real-world problems, including modeling contagion, technology adoption, and viral marketing. Here we examine an advertisement domain in which the overarching goal is to find the influential nodes in a social network, based on the network structure and the interactions, as targets of advertisement. The assumption is that advertisement budget limits prevent us from sending the advertisement to everybody in the network. Therefore, a wise selection of the people can be beneficial in increasing the product adoption. To model these social systems, agent-based modeling, a powerful tool for the study of phenomena that are difficult to observe within the confines of the laboratory, is used. To analyze marketing scenarios, this dissertation proposes a new method for propagating information through a social system and demonstrates how it can be used to develop a product advertisement strategy in a simulated market. We consider the desire of agents toward purchasing an item as a random variable and solve the influence maximization problem in steady state using an optimization method to assign the advertisement of available products to appropriate messenger agents. Our market simulation 1) accounts for the effects of group membership on agent attitudes 2) has a network structure that is similar to realistic human systems 3) models inter-product preference correlations that can be learned from market data. The results on synthetic data show that this method is significantly better than network analysis methods based on centrality measures. The optimized influence maximization (OIM) described above, has some limitations. For instance, it relies on a global estimation of the interaction among agents in the network, rendering it incapable of handling large networks. Although OIM is capable of finding the influential nodes in the social network in an optimized way and targeting them for advertising, in large networks, performing the matrix operations required to find the optimized solution is intractable. To overcome this limitation, we then propose a hierarchical influence maximization (HIM) iii algorithm for scaling influence maximization to larger networks. In the hierarchical method the network is partitioned into multiple smaller networks that can be solved exactly with optimization techniques, assuming a generalized IC model, to identify a candidate set of seed nodes. The candidate nodes are used to create a distance-preserving abstract version of the network that maintains an aggregate influence model between partitions. The budget limitation for the advertising dictates the algorithm’s stopping point. On synthetic datasets, we show that our method comes close to the optimal node selection, at substantially lower runtime costs. We present results from applying the HIM algorithm to real-world datasets collected from social media sites with large numbers of users (Epinions, SlashDot, and WikiVote) and compare it with two benchmarks, PMIA and DegreeDiscount, to examine the scalability and performance. Our experimental results reveal that HIM scales to larger networks but is outperformed by degreebased algorithms in highly-connected networks. However, HIM performs well in modular networks where the communities are clearly separable with small number of cross-community edges. This finding suggests that for practical applications it is useful to account for network properties when selecting an influence maximization method

Expertise in unexpected places: Children’s acceptance of information from gender counter-stereotypical experts

The current study examined children’s willingness to accept novel information from expert informants with nontraditional gender role interests. Four- to 8-year-olds heard conflicting information about traditionally feminine or masculine domains from a gender counter-stereotypical expert (e.g., a boy with expertise in ballet) and a layperson of the other gender (e.g., a girl with little knowledge about ballet). Participants were asked which informant was correct, who they would prefer to learn from in the future, and to rate their liking of each informant. Overall, participants selected the gender counter-stereotypical expert as correct. Four- to 5-year-olds reported a preference to learn from same-gender participants in the future irrespective of expertise, whereas 6- to 8-year-olds reported wanting to learn from counter-stereotypical experts. Boys showed relatively greater acceptance of information from a male counter-stereotypical expert than from a female counter-stereotypical expert. Although participants reported greater liking of same-gender informants, liking evaluations were largely positive irrespective of gender norm deviations. Implications for children’s acceptance of gender nonconforming activities are discussed

Entrepreneurs as parents : the antecedents and consequence of parenting stress

Purpose The purpose of this paper is to understand parenting stress of entrepreneurs and to attempt to extend the empirical evidence on the predictors and consequences of parenting stress for entrepreneurs. Design/methodology/approach This study draws on data from the Household, Income and Labour Dynamics in Australia Survey. The quantitative research method was used. Drawing on the data of 2,051 entrepreneurs, a model was tested using structural equation modeling. Findings The results reveal that social support is a strong predictor of parenting stress and that there is a direct effect between parenting stress and family to work interference (FWI). In addition, parenting stress partially mediates the relationship between social support and FWI. Adding a direct path from social support to FWI substantially improves the validity in a revised model. No effects of gender stereotypes are found. Originality/value This study attempts to extend previous work on parenting and vocational behavior by investigating the perceptional and stereotypical antecedents of parenting stress and examining the impact of parenting stress on FWI. To the challenges of parenting, many entrepreneurs face constant pressure to achieve a positive return in their business venture and work hard, for long hours. Therefore, a better understanding of entrepreneurs’ parenting roles and stress can shed some light on the challenges faced by self-employed individuals and contributes to the vocational behavior and career development literature and practical experiences

Gendering Human Rights: Threat and Gender Perceptions as Predictors of Attitudes towards Violating Human Rights in Asymmetric Conflict

We introduce, in this study, a gendering human rights model in which perceiving outgroups as having stereotypical feminine traits predicts decreased support for violating their human rights through the mediation of threat perception. This model is tested in the context of the asymmetrical protracted Israeli-Palestinian conflict using Jewish-Israeli public opinion polling data (N=517). In line with our expectations, the findings indicate that Jewish-Israeli perceptions of Palestinians as having stereotypical feminine traits predict lower levels of threat perception from Palestinians and consequently less support for violating their human rights. We discuss the implications of our findings for understanding factors that attenuate support for violation of human rights of an outgroup in other situations of violent asymmetric conflict