Scheduling science on television: A comparative analysis of the representations of science in 11 European countries

While science-in-the-media is a useful vehicle for understanding the media, few scholars have used it that way: instead, they look at science-in-the-media as a way of understanding science-in-the-media and often end up attributing characteristics to science-in-the-media that are simply characteristics of the media, rather than of the science they see there. This point of view was argued by Jane Gregory and Steve Miller in 1998 in Science in Public. Science, they concluded, is not a special case in the mass media, understanding science-in-the-media is mostly about understanding the media (Gregory and Miller, 1998: 105). More than a decade later, research that looks for patterns or even determinants of science-in-the-media, be it in press or electronic media, is still very rare. There is interest in explaining the media’s selection of science content from a media perspective. Instead, the search for, and analysis of, several kinds of distortions in media representations of science have been leading topics of science-in-the-media research since its beginning in the USA at the end of the 1960s and remain influential today (see Lewenstein, 1994; Weigold, 2001; Kohring, 2005 for summaries). Only a relatively small amount of research has been conducted seeking to identify factors relevant to understanding how science is treated by the mass media in general and by television in particular. The current study addresses the lack of research in this area. Our research seeks to explore which constraints national media systems place on the volume and structure of science programming in television. In simpler terms, the main question this study is trying to address is why science-in-TV in Europe appears as it does. We seek to link research focussing on the detailed analysis of science representations on television (Silverstone, 1984; Collins, 1987; Hornig, 1990; Leon, 2008), and media research focussing on the historical genesis and current political regulation of national media systems (see for instance Hallin and Mancini, 2004; Napoli, 2004; Open Society Institute, 2005, 2008). The former studies provide deeper insights into the selection and reconstruction of scientific subject matters, which reflect and – at the same time – reinforce popular images of science. But their studies do not give much attention to production constraints or other relevant factors which could provide an insight into why media treat science as they do. The latter scholars inter alia shed light on distinct media policies in Europe which significantly influence national channel patterns. However, they do not refer to clearly defined content categories but to fairly rough distinctions such as information versus entertainment or fictional versus factual. Accordingly, we know more about historical roots and current practices of media regulation across Europe than we do about the effects of these different regimes on the provision of specific content in European societies

Solution Repair/Recovery in Uncertain Optimization Environment

Operation management problems (such as Production Planning and Scheduling) are represented and formulated as optimization models. The resolution of such optimization models leads to solutions which have to be operated in an organization. However, the conditions under which the optimal solution is obtained rarely correspond exactly to the conditions under which the solution will be operated in the organization.Therefore, in most practical contexts, the computed optimal solution is not anymore optimal under the conditions in which it is operated. Indeed, it can be "far from optimal" or even not feasible. For different reasons, we hadn't the possibility to completely re-optimize the existing solution or plan. As a consequence, it is necessary to look for "repair solutions", i.e., solutions that have a good behavior with respect to possible scenarios, or with respect to uncertainty of the parameters of the model. To tackle the problem, the computed solution should be such that it is possible to "repair" it through a local re-optimization guided by the user or through a limited change aiming at minimizing the impact of taking into consideration the scenarios

Intrinsic Motivation in Open Source Software Development

This papers sheds light on the puzzling evidence that even though open source software (OSS) is a public good, it is developed for free by highly qualified, young and motivated individuals, and evolves at a rapid pace. We show that once OSS development is understood as the private provision of a public good, these features emerge quite naturally. We adapt a dynamic private-provision-of-public-goods model to reflect key aspects of the OSS phenomenon. In particular, instead of relying on extrinsic motives (e.g. signaling) the present model is driven by intrinsic motives of OSS programmers, such as user- programmers, play value or 'homo ludens' payoff, and gift culture benefits. Such intrinsic motives feature extensively in the wider OSS literature and contribute new insights to the economic analysis.open source software, public goods, homo ludens, war of attrition

Basic Polyhedral Theory

This is a chapter (planned to appear in Wiley's upcoming Encyclopedia of Operations Research and Management Science) describing parts of the theory of convex polyhedra that are particularly important for optimization. The topics include polyhedral and finitely generated cones, the Weyl-Minkowski Theorem, faces of polyhedra, projections of polyhedra, integral polyhedra, total dual integrality, and total unimodularity.Comment: 14 page

Gradual Program Analysis

Dataflow analysis and gradual typing are both well-studied methods to gain information about computer programs in a finite amount of time. The gradual program analysis project seeks to combine those two techniques in order to gain the benefits of both. This thesis explores the background information necessary to understand gradual program analysis, and then briefly discusses the research itself, with reference to publication of work done so far. The background topics include essential aspects of programming language theory, such as syntax, semantics, and static typing; dataflow analysis concepts, such as abstract interpretation, semilattices, and fixpoint computations; and gradual typing theory, such as the concept of an unknown type, liftings of predicates, and liftings of functions