Being Female: a handicap for researchers in the competion for NCCR.

The Swiss National Science Foundation made a call for National Centers fo Competence in Research (NCCR) for the first time in 1999 and 2004. Together, these announcements concerned all disciplines and led to 126 preproposals, which were put forward by 2134 men and women researchers. It can be assumed that this operation mobilised Swiss researchers who regarded themselves as particularly well qualified to conduct high-level research in their field. The article uses network analysis and regression analysis methods to examine to what extend women had a lower success rate than men in the two selection rounds because of their sex. On the whole, the findings attest the gender neutrality of the National Science Foundation's selection procedures. However, they also confirm the well-known fact that women scientists are less represented in the higher echelons of academia and concentrated in the social sciences and humanities, as well as showing that this concentration reduces women's chances of success in scientific competition. The article shows that unequal gender-specific success rates prior to the NCCR funding contest play a fairly significant role.

Statistics in science and in society: From a state-of-the-art to a new research agenda

Statistics occupies a prominent role in science and citizens' daily life. This article provides a state-of-the-art of the problems associated with statistics in science and in society, structured along the three paradigms defined by Bauer, Allum and Miller (2007). It explores in more detail medicine and public understanding of science on the one hand, and risks and surveys on the other. Statistics has received a good deal of attention; however, very often handled in terms of deficit - either of scientists or of citizens. Many tools have been proposed to improve statistical literacy, the image of and trust in statistics, but with little understanding of their roots, with little coordination among stakeholders and with few assessments of impacts. These deficiencies represent as many new and promising directions in which the PUS research agenda could be expanded.

Myths in science.

Review of : Fabulous Science: Fact and Fiction in the History of Scientific Discovery by John Waller Oxford University Press

Patterns of Subject Mix in Higher Education Institutions : A First Empirical Analysis Using the AQUAMETH Database

Teaching and research are organised differently between subject domains: attempts to construct typologies of higher education institutions, however, often do not include quantitative indicators concerning subject mix which would allow systematic comparisons of large numbers of higher education institutions among different countries, as the availability of data for such indicators is limited. In this paper, we present an exploratory approach for the construction of such indicators. The database constructed in the AQUAMETH project, which includes also data disaggregated at the disciplinary level, is explored with the aim of understanding patterns of subject mix. For six European countries, an exploratory and descriptive analysis of staff composition divided in four large domains (medical sciences, engineering and technology, natural sciences and social sciences and humanities) is performed, which leads to a classification distinguishing between specialist and generalist institutions. Among the latter, a further distinction is made based on the presence or absence of a medical department. Preliminary exploration of this classification and its comparison with other indicators show the influence of long term dynamics on the subject mix of individual higher education institutions, but also underline disciplinary differences, for example regarding student to staff ratios, as well as national patterns, for example regarding the number of PhD degrees per 100 undergraduate students. Despite its many limitations, this exploratory approach allows defining a classification of higher education institutions that accounts for a large share of differences between the analysed higher education institutions.