Metascientific

Metascientific is an adjective relating to metascience, the systematic study of science as a process. Metascientific research investigates how scientific knowledge is produced, communicated, and validated, and seeks to understand the effectiveness of scientific methods and institutions.

Topics commonly examined include replication and reproducibility, statistical practices and error rates, research incentives and career structures, publication bias and selective reporting, peer review, data sharing, preregistration, and open methods. Researchers in this area use empirical methods to evaluate practices, often conducting cross-disciplinary studies, surveys, and controlled experiments to test how different approaches affect reliability and efficiency.

Methods used in metascience include meta-research, systematic reviews, and large-scale replication programs. Notable projects have tested the replicability of findings in psychology, economics, and biomedicine, and have spurred discussions about statistical standards and incentives. The field also studies how funding, collaboration, and publication norms influence scholarly outcomes.

Impact and scope: the goal of metascientific work is to improve the trustworthiness and efficiency of science. Findings inform reforms such as preregistration, registered reports, open data and materials, preregistration of analysis plans, and better reporting standards. While influential, metascientific claims are themselves subject to evaluation and debate, and the field emphasizes humility about its own limitations.

History: metascience emerged more prominently in the late 20th and early 21st centuries. It has grown through collaborations across disciplines, with prominent voices such as John Ioannidis and organizations like centers for open science contributing to its development.