Open Science Practices – a theoretical reflection

Purpose of this paper
More and more articles discussing a “crisis of science” (Saltelli & Funtowicz, 2017). The crisis is identified by seven symptoms: First, the replication crisis, which means that published studies cannot be replicated by other researchers or lead to different results (Open Science Collaboration, 2015). Second, the deficit in statistical training and good statistical designs/models (Young, 2018) which for example leads to not useful research in medicine (Ioannidis, 2016). Third, the manipulation of p-values (or 'p-hacking') is identified as a problem. For example, Simmons et al. (2011) state: ”In many cases, a researcher is more likely to falsely find evidence that an effect exists than to correctly find evidence that it does not.” Since only positive and significant results are published results in the creation of a bias in scientific literature (Bruner & Holman, 2019). Fourth, ”journal-based metrics, such as journal impact factors, should not be taken as a surrogate measure for the quality of research, and, above all, should not be used in hiring, promotion, or funding decisions.” (Ioannidis, 2014) At the same time, especially early career scientists must comply to the metric system if they want to survive in academia (Fanelli, 2009). Fifth, complying with the metric system implies publishing in peer reviewed journals, which according to Frey (2003) is tantamount to prostitution: ”Authors only get their papers accepted if they intellectually prostitute themselves by slavishly following the demands made by anonymous referees who have no property rights to the journals they advise.” Sixth, the metric system motivates scientists to producing as many articles as possible, which leads to the “publish or perish” effect of splitting research into as small parts as possible (Saltelli & Funtowicz, 2017). Seventh, Fanelli (2009) refers to a poll in which 2/3 of the interviewed scientists “admitted having recurred to ‘questionable’ research practices” because of the publish
or perish culture. In sum, these symptoms contribute to science being under increasing pressure as the ”public trust in the evidence produced by science and its institutions“ decreases (Saltelli & Funtowicz, 2017
). So far, little has changed in the practices of scientists, even though politics exerts pressure, for example by linking funding to the re-use of data (Horizon 2020) or by open access strategies (Plan S). However, and this is the thesis of this paper, scientific practices will only change connected to disciplinary cultures (Becher, 1981) and their values, norms and patterns of acting, thinking and perceiving (Bourdieu, 1977).