Collective credit allocation in science

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, because 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.Reflecting the increasing complexity of modern research, in the last decades, collaboration among researchers became a standard path to discovery (1). Collaboration plays a particularly important role in multidisciplinary research that requires expertise from different scientific fields (2). As the number of coauthors of each publication increases, science’s credit system is under pressure to evolve (3–5). For single-author papers, which were the norm decades ago, credit allocation is simple: the sole author gets all of the credit. This rule, accepted since the birth of science, fails for multiauthor papers (6). The lack of a robust credit allocation system that can account for the discrepancy between researchers’ contribution to a particular body of work and the credit they obtain, has prompted some to state that “multiple authorship endangers the author credit system” (7). This situation is particularly acute in multidisciplinary research (8, 9), when communities with different credit allocation traditions collaborate (10). Furthermore, a detailed understanding of the rules underlying credit allocation is crucial for an accurate assessment of each researcher’s scientific impact, affecting hiring, funding, and promotion decisions.Current approaches to allocating scientific credit fall in three main categories. The first views each author of a multiauthor publication as the sole author (11, 12), resulting in inflated scientific impact for publications with multiple authors. This system is biased toward researchers with multiple collaborations or large teams, customary in experimental particle physics or genomics. The second assumes that all coauthors contribute equally to a publication, allocating fractional credit evenly among them (13, 14). This approach ignores the fact that authors’ contributions are never equal and hence dilutes the credit of the intellectual leader. The third allocates scientific credit according to the order or the role of coauthors, interpreting a message agreed on within the respective discipline (15–17). For example, in biology, typically the first and the last author(s) get the lion’s share of the credit, and in some areas of physical sciences, the author list reflects a decreasing degree of contribution. An extreme case is offered by experimental particle physics, where the author list is alphabetic, making it impossible to interpret the author contributions without exogenous information. Finally, there is an increasing trend to allocate credit based on the specific contribution of each author (18, 19), specified in the contribution declaration required by some journals (20, 21). However, each of these approaches ignores the most important aspect of credit allocation: notwithstanding the agreed on order, credit allocation is a collective process (22–24), which is determined by the scientific community rather than the coauthors or the order of the authors in a paper. This phenomena is clearly illustrated by the 2012 Nobel prize in physics that was awarded based on discoveries reported in publications whose last authors were the laureates (25, 26), whereas the 2007 Nobel prize in physics was awarded to the third author of a nine-author paper (27) and the first author of a five-author publication (28). Clearly the scientific community operates an informal credit allocation system that may not be obvious to those outside of the particular discipline.The leading hypothesis of this work is that the information about the informal credit allocation within science is encoded in the detailed citation pattern of the respective paper and other papers published by the same authors on the same subject. Indeed, each citing paper expresses its perception of the scientific impact of a paper’s coauthors by citing other contributions by them, conveying implicit information about the perceived contribution of each author. Our goal is to design an algorithm that can capture in a discipline-independent fashion the way this informal collective credit allocation mechanism develops.