Universal productivity patterns in research careers

TL;DR

This study uncovers six universal research productivity patterns across disciplines, revealing that most scientists peak mid-career, challenging common assumptions about early peaks and career decline.

Contribution

The paper identifies six universal productivity trajectories in scientific careers using advanced analysis methods, providing new insights into career development patterns.

Findings

Six universal productivity patterns identified

Most researchers peak mid-career rather than early

Productivity trajectories vary significantly across disciplines

Abstract

A common expectation is that career productivity peaks rather early and then gradually declines with seniority. But whether this holds true is still an open question. Here we investigate the productivity trajectories of almost 8,500 scientists from over fifty disciplines using methods from time series analysis, dimensionality reduction, and network science, showing that there exist six universal productivity patterns in research. Based on clusters of productivity trajectories and network representations where researchers with similar productivity patterns are connected, we identify constant, u-shaped, decreasing, periodic-like, increasing, and canonical productivity patterns, with the latter two describing almost three-fourths of researchers. In fact, we find that canonical curves are the most prevalent, but contrary to expectations, productivity peaks occur much more frequently around mid-career rather than early. These results outline the boundaries of possible career paths in science and caution against the adoption of stereotypes in tenure and funding decisions.