This article explores the factors that influence the volume and structure of science programming by European television broadcasters, focussing on differences among channel patterns. It proposes three factors as relevant to understanding differences in science programming: A) the segmentation/fragmentation of television markets; B) the presence of middle sized commercial channels; C) the dependency of public service TV channels on commercial income (trading/advertising). We identified countries whose channel patterns encourage a varied picture of science – namely Sweden, Finland and Germany. They are distinguished from those which show a less differentiated picture and present a smaller volume of science content on television – such as Great Britain and Ireland. Finally, we identified countries whose channel patterns don’t encourage a varied picture of science – namely Spain, Greece, Bulgaria and Estonia – and these countries present their small volume of science content at off-peak hours, in contrast to patterns in Great Britain and Ireland.

Based on the decision-theoretical conditions underlying the selection of events for news coverage in science journalism, this article uses a novel input-output analysis to investigate which of the more than eight million scientific study results published between August 2014 and July 2018 have been selected by global journalism to a relevant degree. We are interested in two different structures in the media coverage of scientific results. Firstly, the structure of sources that journalists use, i.e. scientific journals, and secondly, the congruence of the journalistic selection of single results. Previous research suggests that the selection of sources and results follows a certain heavy-tailed distribution, a power law. Mathematically, this distribution can be described with a function of the form C*x-α. We argue that the exponent of such power law distributions can potentially be an indicator to describe selectivity in journalism on a high aggregation level. In our input-output analysis, we look for such patterns in the coverage of all scientific results published in the database Scopus over four years. To get an estimate of the coverage of these results, we use data from the altmetrics provider Altmetric, more precisely their Mainstream-Media-Score (MSM-Score). Based on exploratory analyses, we define papers with a score of 50 or above as Social Impact Papers (SIPs). Over our study period, we identified 5,833 SIPs published in 1,236 journals. For both the distribution of the source selection and the distribution of the selection of single results, an exponentially truncated power law is a better fit than the power law, mostly because we find a steeper decline in the tail of the distributions.

Based on 21 individual case studies, this article inventories the ways journalism deals with scientific uncertainty. The study identifies the decisions that impact a journalist's perception of a truth claim as unambiguous or ambiguous and the strategies to deal with uncertainty that arise from this perception. Key for understanding journalistic action is the outcome of three evaluations: What is the story about? How shall the story be told? What type of story is it? We reconstructed the strategies to overcome journalistic decision-making uncertainty in those cases in which they perceived scientific contingency as a problem. Journalism deals with uncertainty by way of omission, by contrasting the conflicting messages or by acknowledging the problem via the structure or language. One finding deserves particular mention: The lack of focus on scientific uncertainty is not only a problem of how journalists perceive and communicate but also a problem of how science communicates.

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At the time of the COVID-19 pandemic, scientific expertise was and is more in demand than perhaps ever before. Scientific “experts” serve as an important source of information for journalists and for society. Our study analyzes, which experts get a chance to speak in German news coverage of COVID-19 compared to other pandemics, how diverse the spectrum of selected experts is and how their scientific expertise is to be assessed. Our findings show that the COVID-19 coverage is dominated by actors from the political executive and less than in previous pandemics by scientific experts. In addition, the coronavirus debate is characterized by a greater diversity of expert voices and the journalistic selection of scientific experts is biased in favor of those who have a high scientific expertise. On average, COVID-19 coverage seems to be biased more pronouncedly in favor of reputable scientific experts compared to previous debates on pandemics.