Sources,Characteristics and Effects of Mass Media Communication on Science: A Review of the Literature,Current Trends and Areas for Future Research

A significant amount of science coverage can be found nowadays in the mass media and is the main source of information about science for many. Accordingly, the relation between science and the media has been intensively analyzed within the social scientific community. It is difficult to keep track of this research, however, as a flurry of studies has been published on the issue. This article provides such an overview. First, it lays out the main theoretical models of science communication, that is, the ‘public understanding of science’ and the ‘mediatization’ model. Second, it describes existing empirical research. In this section, it demonstrates how science’s agenda‐building has improved, how science journalists working routines are described, how different scientific disciplines are presented in the mass media and what effects these media representations (might) have on the audience. Third, the article points out future fields of research.     

How Managers Talk about their Consumption of Popular Management Concepts: Identity,Rules and Situations

This paper analyses how top managers account for their consumption of popular management concepts. By ‘consumption’ we refer to managers acting as active users of popular management concepts within their organizations. After reviewing the relevant literature, we argue that the logic of appropriateness is a better theoretical perspective to view, understand and analyse managers' accounts of concept consumption than is the logic of consequence. We apply this perspective to extensive interviews we conducted with top managers in Germany. Based on the managers' own accounts of how they understand and apply popular management concepts, we identified four discourse categories: (1) learning from others' experiences, (2) controlling organizational change, (3) gaining external legitimacy and (4) collective sensemaking. We argue that these discourse categories all draw on the social norm of rationality central to managerial identity, while differing in socially defined rules about how rationality is realized in typical management situations. Our findings strongly encourage researchers, when investigating popular management concepts in the future, to take into account the situational nature of rationality that circumstantiates the consumption of concepts.     

The influence of different dimensions of social comparison on performance measure choice and team composition

Empirical research in the economic literature is increasingly addressing the implications of social comparison on incentive contracts by using analytical principal-agent models. Contrary to the existing investigations, which are primarily based on the assumption that individuals exclusively compare monetary income, theories of behavioral science suggest that monetary income and effort represent different dimensions of social comparison, which are weighted individually. Using a LEN framework, the present study focuses on this aspect of social comparisons and discusses how these dimensions and their individual weights affect optimal contract design and contract efficiency. I consider status-seeking agents who compare themselves to each other and differ with regard to their intensity of social preferences and the specific relevance of dimensions. Finally, I draw conclusions for the drafting of contracts with respect to (1) the choice of performance measures and (2) an optimal team composition.     

Upgrading local operations for global arbitrage

This study shows that upgrading sales operations in host countries towards production allows MNCs to perform global arbitrage in their networks of foreign subsidiaries and thereby contributes to a strategy of reaping the benefits of multinationality. We predict and find that operation upgrades follow opportunities of improving resource flows in the subsidiary network to exploit the advantages of host countries in tax rates, investment incentives, and technological knowledge across borders. Performance effects on the level of the MNC network give evidence of these benefits from global arbitrage.     

Sequential Monte Carlo on large binary sampling spaces

A Monte Carlo algorithm is said to be adaptive if it automatically calibrates its current proposal distribution using past simulations. The choice of the parametric family that defines the set of proposal distributions is critical for good performance. In this paper, we present such a parametric family for adaptive sampling on high dimensional binary spaces. A practical motivation for this problem is variable selection in a linear regression context. We want to sample from a Bayesian posterior distribution on the model space using an appropriate version of Sequential Monte Carlo. Raw versions of Sequential Monte Carlo are easily implemented using binary vectors with independent components. For high dimensional problems, however, these simple proposals do not yield satisfactory results. The key to an efficient adaptive algorithm are binary parametric families which take correlations into account, analogously to the multivariate normal distribution on continuous spaces. We provide a review of models for binary data and make one of them work in the context of Sequential Monte Carlo sampling. Computational studies on real life data with about a hundred covariates suggest that, on difficult instances, our Sequential Monte Carlo approach clearly outperforms standard techniques based on Markov chain exploration.     

A method for consideration of conditional dependencies in the Fellegi and Sunter model of record linkage

An objective of Record Linkage is to link two data files by identifying common elements. A popular model for doing the separation is the probabilistic one from Fellegi and Sunter. To estimate the parameters needed for the model usually a mixture model is constructed and the EM algorithm is applied. For simplification, the assumption of conditional independence is often made. This assumption says that if several attributes of elements in the data are compared, then the results of the comparisons regarding the several attributes are independent within the mixture classes. A mixture model constructed with this assumption has been often used. Within this article a straightforward extension of the model is introduced which allows for conditional dependencies but is heavily dependent on the choice of the starting value. Therefore also an estimation procedure for the EM algorithm starting value is proposed. The two models are compared empirically in a simulation study based on telephone book entries. Particularly the effect of different starting values and conditional dependencies on the matching results is investigated.     

Assessing goodness-of-fit for evaluation of dose-proportionality

For the clinical development of a new drug, the determination of dose-proportionality is an essential part of the pharmacokinetic evaluations, which may provide early indications of non-linear pharmacokinetics and may help to identify sub-populations with divergent clearances. Prior to making any conclusions regarding dose-proportionality, the goodness-of-fit of the model must be assessed to evaluate the model performance. We propose the use of simulation-based visual predictive checks to improve the validity of dose-proportionality conclusions for complex designs. We provide an illustrative example and include a table to facilitate review by regulatory authorities.     

Allometry and photosynthetic capacity of poplar (Populus deltoides) along a metal contamination gradient in an urban brownfield

The value of urban green space has become an increasingly controversial issue. In particular, development of novel vegetative assemblages on vacant lands may have many formerly unrecognized benefits. However, questions remain regarding the functional impairment of these assemblages due to degraded soils. We investigated the effects of elevated concentrations of soil metals on allometry and photosynthetic capacity of naturally colonized poplars (Populus deltoides Michx.) growing at Liberty State Park, New Jersey. We found that allometries of harvested trees did not differ significantly between the low metal load (LML) and high metal load (HML) sites suggesting that metal contamination did not negatively affect carbon allocation patterns of the target species. Likewise, photosynthetic parameters did not differ significantly between the LML and HML sites, suggesting that soil metal contamination did not negatively affect photosynthetic capacity. However, trees from the LML site were significantly younger for a given size than trees from the HML site. Trees from the medium metal load site (MML) differed significantly in allometry and photosynthetic parameters from the other two sites suggesting other edaphic and ecological factors are a stronger driver for carbon allocation patterns and photosynthetic capacity in these trees. Taken together, this research suggests that sapling establishment and growth may be impaired by heavy metals and that trees in HML sites may incur more maintenance costs than trees in LML sites. However, given enough time, poplars can provide considerable rehabilitation of urban brownfields, particularly those that exhibit soil metal contamination.