Exploring trust and distrust as conceptually and empirically distinct constructs: Association with symmetrical communication and public engagement across four pairings of trust and distrust

Existing relationship research has interpreted low trust as being equivalent to high distrust and high trust as the evidence of low distrust, which has failed to capture the full scope of the functions of trust and distrust in organization–public relationships. Recent research in this area suggests that trust and distrust might simultaneously exist during relational interactions and might play uniquely positive and negative functions in certain social contexts. The main purpose of this study was to offer a new insight in trust–distrust research by providing distinctions in conceptualization and operationalization between trust and distrust. This study also empirically tested the functions of four pairings of trust and distrust on two core public relations concepts (i.e., symmetrical communication and public engagement). The results from the surveys (N = 704; in 20 companies) of US consumers showed sound discriminant validity of trust and distrust. Further, the statistical results revealed that symmetrical communication and public engagement were most strongly associated with the high trust and high distrust pairing, supporting the utilities of distrust in public relations and the coexistence of trust and distrust in social interactions.     

Agenda-Building role of state-owned media around the world: 2014 Hong Kong protest case

ABSTRACT

This study aimed to advance theoretical and practical knowledge of political public relations and mediated public diplomacy through analyzing the agenda-building relationships between state-owned media and foreign news coverage in 16 countries during the 2014 Hong Kong protest. The results indicated significant correlations of issues and stakeholders between the Chinese state-owned media and the English language media outlets of 16 foreign countries, thereby supporting the international agenda-building role of Chinese state-owned media. An exploratory analysis was conducted to test the role of intercultural or international relations variables in the agenda-building process.     

On the distribution of linear combinations of the components of a Dirichlet random vector

On making use of a result of Imhof, an integral representation of the distribution function of linear combinations of the components of a Dirichlet random vector is obtained. In fact, the distributions of several statistics such as Moran and Geary's indices, the Cliff‐Ord statistic for spatial correlation, the sample coefficient of determination, F‐ratios and the sample autocorrelation coefficient can be similarly determined. Linear combinations of the components of Dirichlet random vectors also turn out to be a key component in a decomposition of quadratic forms in spherically symmetric random vectors. An application involving the sample spectrum associated with series generated by ARMA processes is discussed.     

Should a Second Demographic Transition Follow the First? Demographic Contrasts: Canada and South Korea

Social Indicators Research -     

Single Session Thinking 2020

This update presents key developments since Talmon’s original (1990) publication, including an account of the three international symposia which have taken place since the last ANZJFT special edition on single session therapy in 2012, and the major compilations that followed the symposia. Underlying elements that unite different single session approaches are explored, and an attempt is made to provide a terminology that is inclusive and coherent. As reflected in the title, the term ‘single session thinking’ is suggested as an over-arching term for the approach that is no longer limited to the therapy room, but reaches into many different contexts. In conclusion, possible future clinical and research developments in the field of single session thinking and practice are reflected upon, and the implications for contemporary health care delivery considered.     

Likelihood inference for dynamic linear models with Markov switching parameters: on the efficiency of the Kim filter

The Kim filter (KF) approximation is widely used for the likelihood calculation of dynamic linear models with Markov regime-switching parameters. However, despite its popularity, its approximation error has not yet been examined rigorously. Therefore, this study investigates the reliability of the KF approximation for maximum likelihood (ML) and Bayesian estimations. To measure the approximation error, we compare the outcomes of the KF method with those of the auxiliary particle filter (APF). The APF is a numerical method that requires a longer computing time, but its numerical error can be sufficiently minimized by increasing simulation size. According to our extensive simulation and empirical studies, the likelihood values obtained from the KF approximation are practically identical to those of the APF. Furthermore, we show that the KF method is reliable, particularly when regimes are persistent and sample size is small. From the Bayesian perspective, we show that the KF method improves the efficiency of posterior simulation. This study contributes to the literature by providing evidence to justify the use of the KF method in both ML and Bayesian estimations.     

Bayesian curve fitting and clustering with Dirichlet process mixture models for microarray data

In the field of molecular biology, it is often of interest to analyze microarray data for clustering genes based on similar profiles of gene expression to identify genes that are differentially expressed under multiple biological conditions. One of the notable characteristics of a gene expression profile is that it shows a cyclic curve over a course of time. To group sequences of similar molecular functions, we propose a Bayesian Dirichlet process mixture of linear regression models with a Fourier series for the regression coefficients, for each of which a spike and slab prior is assumed. A full Gibbs-sampling algorithm is developed for an efficient Markov chain Monte Carlo (MCMC) posterior computation. Due to the so-called “label-switching” problem and different numbers of clusters during the MCMC computation, a post-process approach of Fritsch and Ickstadt (2009) is additionally applied to MCMC samples for an optimal single clustering estimate by maximizing the posterior expected adjusted Rand index with the posterior probabilities of two observations being clustered together. The proposed method is illustrated with two simulated data and one real data of the physiological response of fibroblasts to serum of Iyer et al. (1999).     

A comparative study on the relationship between social networking site use and social capital among Australian and Korean youth

Social network sites (SNS) have become increasingly pervasive in the daily lives of adolescents. This study explores the relationship between SNS use and perceived online social capital among adolescents using survey data from Australia and Korea. We conducted a face-to-face survey of adolescents (12–15-year-olds) in major cities in Australia (N?=?401) and Korea (N?=?644) in 2013. There was no significant difference in time spent on SNS between adolescents in the two countries; however, significant differences in the way adolescents use SNS were found. Australian adolescents tended to use SNS for group activities, whereas Koreans used it for social monitoring. There was a positive relationship between SNS use and online social capital in both countries. However, the types of social capital that were found to have a strong relationship to SNS use were different. Among Australian adolescents, SNS activities had a higher correlation with bonding social capital compared to bridging capital, whereas the result was contrasting among Korean adolescents. The impact of SNS use on online social capital differed between the two countries, showing that Australian adolescents reporting low SNS use gained online social capital if they used SNS more intensely. Finally, the impact of SNS use and culture on perceived online social capital was examined by conducting hierarchical multiple regressions. Interpersonal communication and group activities emerged as significant predictors of online social capital.