Meta-Research and Social Sciences

Cluster network of scientific publications in relation to Nobel prizes.

In ''Work honored by Nobel prizes clusters heavily in a few scientific fields'' by John P. A. Ioannidis, Ioana-Alina Cristea and Kevin W. Boyack (2020)

Meta-research is the newly-emerging scientific discipline of studying the incentives, processes and institutions that characterize the scientific production of knowledge itself. This article discusses what this discipline does and its scope for science. It is worth quoting a key phrase: "A research effort is needed that cuts across all disciplines, drawing from a wide range of methodologies and theoretical frameworks, and yet shares a common objective; that of helping science progress faster by conducting scientific research on research itself. This is the field of meta-research. "

The special characteristic of this meta-research is its interdisciplinarity. Interaction among research fields is key for sharing of tools and approaches that help us understand these aspects. By its nature, the problem of how best to organize the production of scientific knowledge interests scientists from many disciplines. A key focus of our work in the ERA Chair in Science and Innovation Policy and Studies is on the input of social and behavioral sciences in this effort. This includes primarily economics, but also management, psychology and other social disciplines.

The cross-fertilization between economic sciences and meta-research takes two main directions. This article discusses these possible directions. One direction is from established practices in meta-research in inspiring and informing social sciences (especially economics). For instance, research synthesis techniques have a great development in biomedicine an psychology, but not in economics and political science. On the other hand, economics has very mature tools to analyze incentives in science, which can contribute to the common goal of assessing reforms in scientific institutions and practices.

Further Resources:

In this discussion at the University of Chicago, I discuss our general research agenda on the problem of reproducibility and generalizability of experimental results.