Argumenta – Journal of Analytic Philosophy

One of the many peculiar phenomena that the Covid-19 pandemic has brought about is the engagement of non-scientists with specific questions surrounding the interpretation of epidemiological data and models. Many of them have even begun to get involved in the collection, analysis, and presentation of the data themselves. A reason for this might be that the insights that science can provide in a situation of crisis are often inconclusive or preliminary, motivating many people to look for the answers to pressing questions themselves. Moreover, public engagement is facilitated by the easy availability of up-to-date information, of the computational methods to process and analyze it, and of the infrastructure to share and communicate it with like-minded people. This raises epistemological questions about the status of such activities. Can they be considered scientific, and do they meet the standards of scientific inquiry? Or are they harmful because they add to the already loud chorus of voices spreading misinformation and increasing skepticism about the conventional scientific process? We propose to approach this question by looking at a concrete example: A community of active non-professionals has formed in Italy on the software development platform GitHub, where the Italian government’s epidemiological data are made publicly available. This represents a well-defined and coherent case study on which detailed information is readily available.

The Covid-19 pandemic has changed the lives of people all over the world and has altered the way people work, meet, spend their free time, and get healed. And it has also, at least temporarily, changed scientific practice. It is undeniable that research has witnessed an enormous drive to produce results that could help understand the mechanism of transmission of the SARS-Cov2 virus, contain its spread and develop an effective vaccine, all much faster than would have been the case under normal circumstances. At the same time, the traditional scientific method has come under pressure: the conventional peer-review process has been struggling to keep up with the need for fast advancement; the rush to publish often leads to partial results or premature conclusions; and…


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