What`s wrong with verification in social sciences, and how IT can improve it

Researchers in sciences such as sociology or medicine face a multitude of problems. From the practical impossibility of blind testing in certain situations resulting in voluptuous but unrepresentative sampling, to the difficulties of accounting for all the potential factors that may impact outcomes and the effect of publication bias on the meta-analysis results.

Many of these problems became especially prominent during the COVID-19 era, which saw numerous, often contradicting, scientific publications analyzing the virus’ behavior or vaccine efficacy.

In this report, we’ll:

• look at the reasons behind the reproducibility crisis in social sciences;
• explore what criteria help the authors of systematic reviews discern credible academic works from those that should be ignored;
• discuss how a regular IT specialist can make a change and support science.