“Trust Me”: Differences in expressed and perceived trust relations in an organization

The possibility of resolving the tension between trust as a psychological condition and trust as a general organizing principle depends on assumptions about the convergence of expressed and perceived trust relations. In empirical organizational research these assumptions are frequently left implicit and only rarely modeled directly. Using data that we have collected on trust relations within the top management team of a multiunit industrial group we specify and estimate multivariate exponential random graph models (ERGMs) that reveal important differences in the structural logics underlying networks of expressed and perceived trust relations. Results confirm that trust induces awareness and produces expectations of reciprocity – features that are consistent with the view of trust as a general organizing principle. Results also show that networks of perceived trust relations are characterized by tendencies toward reciprocity and generalized giving of trust. When multivariate network effects are introduced, however, expressed trust relations no longer show a significant tendency toward reciprocation. Interpreted together these results suggest that: (i) the distribution of expressed and perceived trust relations differs; (ii) expressed trust relations in organizations are more hierarchical than are perceived trust relations, and (iii) expressed and perceived trust relations need to be modeled jointly. These findings suggest caution in the adoption and interpretation of trust only as a general organizing principle, and suggest that psychological mechanisms also play an important role in the making and breaking of trust relations within organizations.     

Evidence of Skill and Strategy in Daily Fantasy Basketball

Using hand-collected data from DraftKings.com, a major daily fantasy sports website, we analyze draft selections of thousands of participants in daily fantasy basketball (DFB). In our study, the first thorough examination of DFB, we show that DFB is a game in which skill is necessary for success. Using econometric analysis, we find that winning participants utilize different strategies than losing participants; for example, winning participants more frequently select NBA rookies and international players. We also find that participants paying to enter more lineups in a given contest earn profits far more often than those entering few lineups, indicating that the number of lineups entered can serve as a proxy for skill. Additionally, we provide a thorough discussion of industry characteristics, prior literature, and gameplay, which should help readers familiarize themselves with this burgeoning fantasy sports variant. This study should further the literature on the contentious activity, which has been outlawed in many U.S. states and continues to elicit controversy.     

Communicating with children with autism spectrum disorder and their families: a practical introduction

Impaired communication and social interaction are symptoms central to autism spectrum disorder (ASD). Children or young people with ASD have varied intellectual ability, learning difficulty, and needs. For caregivers and health care professionals providing care to children with ASD, many challenges are encountered in everyday conversations. Enhanced knowledge of the spectrum and understanding the child or young person with ASD may improve conversation and social experiences. This article provides a practical introduction for health professionals seeking to improve their interaction with young people with ASD. Fictional vignettes, in which children with ASD are seeking care and support are presented, followed by discussion on communicating with children with ASD.     

For Bourdieu, Against Alexander: Reality and Reduction

Jeffrey Alexander argues that despite Bourdieu's considerable achievements ultimately his work is reductionist and determinist. He further argues that though Bourdieu is a middle range theorist he is implicitly realist in his meta-theoretical assumptions. This article accepts these conclusions but argues that Bourdieu's meta-theoretical realism is a virtue rather than a vice and that the manner in which he is a reductionist and determinist necessitate a re-thinking of what is meant by these notions. Alexander uses Bourdieu's concept of habitus to demon-strate a fundamental contradiction in Bourdieu's theorising. According to him habitus presents us with the oxymoron of unconscious strategisation. This article uses a discussion of habitus in order to demonstrate that in its relationship with the concept of field it instead produces a practical resolution of long standing theoretical problems concerning structural determination and human agency. It is also argued that these problems are resolved at the meta-theoretical level in the form of critical realist ontology and that it is Alexander's misunderstandings on this level which cause him to fail to appreciate the significance of Bourdieu's achievements.     

Medical Nemesis and Economic Health,or Economic Nemesis and Medical Health: The Modern Dilemma

Modern analyses of health trends recognize the importance of ‘life style’ or behavioural variables in health. But this has the effect of taking the emphasis off the real socioeconomic determinants of life style in modern society. In the present paper changing health patterns in Australia are examined and some explanations of these changes are considered. It is concluded that ‘life style’ explanations of modern ‘societal’ illness are a ‘cop-out‘. They ignore the deeper economic and social causes of life styles and in particular the dynamic relationship between these and a rapidly expanding growth economy. The question of whether medical health demands economic nemesis under a continuation of the growth system is considered in this light.     

An introduction to exponential random graph (p) models for social networks

This article provides an introductory summary to the formulation and application of exponential random graph models for social networks. The possible ties among nodes of a network are regarded as random variables, and assumptions about dependencies among these random tie variables determine the general form of the exponential random graph model for the network. Examples of different dependence assumptions and their associated models are given, including Bernoulli, dyad-independent and Markov random graph models. The incorporation of actor attributes in social selection models is also reviewed. Newer, more complex dependence assumptions are briefly outlined. Estimation procedures are discussed, including new methods for Monte Carlo maximum likelihood estimation. We foreshadow the discussion taken up in other papers in this special edition: that the homogeneous Markov random graph models of Frank and Strauss [Frank, O., Strauss, D., 1986. Markov graphs. Journal of the American Statistical Association 81, 832–842] are not appropriate for many observed networks, whereas the new model specifications of Snijders et al. [Snijders, T.A.B., Pattison, P., Robins, G.L., Handock, M. New specifications for exponential random graph models. Sociological Methodology, in press] offer substantial improvement.     

Recent developments in exponential random graph (p*) models for social networks

This article reviews new specifications for exponential random graph models proposed by Snijders et al. [Snijders, T.A.B., Pattison, P., Robins, G.L., Handcock, M., 2006. New specifications for exponential random graph models. Sociological Methodology] and demonstrates their improvement over homogeneous Markov random graph models in fitting empirical network data. Not only do the new specifications show improvements in goodness of fit for various data sets, but they also help to avoid the problem of near-degeneracy that often afflicts the fitting of Markov random graph models in practice, particularly to network data exhibiting high levels of transitivity. The inclusion of a new higher order transitivity statistic allows estimation of parameters of exponential graph models for many (but not all) cases where it is impossible to estimate parameters of homogeneous Markov graph models. The new specifications were used to model a large number of classical small-scale network data sets and showed a dramatically better performance than Markov graph models. We also review three current programs for obtaining maximum likelihood estimates of model parameters and we compare these Monte Carlo maximum likelihood estimates with less accurate pseudo-likelihood estimates. Finally, we discuss whether homogeneous Markov random graph models may be superseded by the new specifications, and how additional elaborations may further improve model performance.     

NEW SPECIFICATIONS FOR EXPONENTIAL RANDOM GRAPH MODELS

The most promising class of statistical models for expressing structural properties of social networks observed at one moment in time is the class of exponential random graph models (ERGMs), also known as p * models. The strong point of these models is that they can represent a variety of structural tendencies, such as transitivity, that define complicated dependence patterns not easily modeled by more basic probability models. Recently, Markov chain Monte Carlo (MCMC) algorithms have been developed that produce approximate maximum likelihood estimators. Applying these models in their traditional specification to observed network data often has led to problems, however, which can be traced back to the fact that important parts of the parameter space correspond to nearly degenerate distributions, which may lead to convergence problems of estimation algorithms, and a poor fit to empirical data.
This paper proposes new specifications of exponential random graph models. These specifications represent structural properties such as transitivity and heterogeneity of degrees by more complicated graph statistics than the traditional star and triangle counts. Three kinds of statistics are proposed: geometrically weighted degree distributions, alternating k -triangles, and alternating independent two-paths. Examples are presented both of modeling graphs and digraphs, in which the new specifications lead to much better results than the earlier existing specifications of the ERGM. It is concluded that the new specifications increase the range and applicability of the ERGM as a tool for the statistical analysis of social networks.     

Obesity-related behaviors in adolescent friendship networks

This study examines obesity-related behaviors within adolescent friendship networks, because adolescent peers have been identified as being important determinants of many health behaviors. We applied ERGM selection models for single network observations to determine if close adolescent friends engage in similar behaviors and to explore associations between behavior and popularity. Same-sex friends were found to be similar on measures of organized physical activity in two out of three school-based friendship networks. Female friends were found to engage in similar screen-based behaviors, and male friends tended to be similar in their consumption of high-calorie foods. Popularity (receiving ties) was also associated with some behaviors, although these effects were gender specific and differed across networks.