Crowdsourced meta-analysis in psychological science: An open science approach to compiling and synthesizing scientific knowledge

Abstract

This article introduces the concept of an open science meta-analysis that functions through crowdsourced imputation of data and is thereby perpetually updating. This is proposed to supplement the current journal article-based system of knowledge storage and synthesis and will, a) increase the consumptive capabilities of researchers (i.e., the amount of research one is exposed to), b) minimize cognitive biases that influence scientific knowledge, c) reduce the file-drawer problem, and d) create new knowledge through mass synthesis of existing research. The proposed infrastructure, much like the recent norm of publicly available data, may be viewed as an industry standard in the near future.