Collective credit allocation in science

TL;DR

This paper introduces a novel credit allocation algorithm that captures the perceived contributions of coauthors in scientific publications, aligning with community practices and enabling fairer assessment of individual impact.

Contribution

The paper develops a new method to quantify individual contributions in multi-author papers based on community perception, validated with Nobel-winning research.

Findings

Successfully identifies authors of Nobel-winning papers regardless of author order.

Enables comparison of researcher impact within the same field.

Reproduces the informal, field-dependent credit allocation process of science.

Abstract

Collaboration among researchers is an essential component of the modern scientific enterprise, playing a particularly important role in multidisciplinary research. However, we continue to wrestle with allocating credit to the coauthors of publications with multiple authors, since the relative contribution of each author is difficult to determine. At the same time, the scientific community runs an informal field-dependent credit allocation process that assigns credit in a collective fashion to each work. Here we develop a credit allocation algorithm that captures the coauthors' contribution to a publication as perceived by the scientific community, reproducing the informal collective credit allocation of science. We validate the method by identifying the authors of Nobel-winning papers that are credited for the discovery, independent of their positions in the author list. The method can also compare the relative impact of researchers working in the same field, even if they did not publish together. The ability to accurately measure the relative credit of researchers could affect many aspects of credit allocation in science, potentially impacting hiring, funding, and promotion decisions.