Mechanisms for (Mis)allocating Scientific Credit

Jon Kleinberg, Sigal Oren

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Scientific communities confer many forms of credit on their successful members. The motivation provided by these forms of credit helps shaping a community’s collective attention toward different lines of research. The allocation of scientific credit, however, has also been the focus of long-documented pathologies: certain research questions are said to command more credit then they deserve; and certain researchers seem to receive a disproportionate share of the credit. Here we show that each of these pathologies can actually increase the collective productivity of a community. We consider a model for the allocation of credit, in which individuals pick a project among projects of varying importance and difficulty levels, and compete to receive credit with others who choose the same project. Under the most natural allocation mechanism, in which credit is divided equally among those who succeed at a project in proportion to the project’s importance, the resulting selection of projects by self-interested, credit-maximizing individuals will in general be socially sub-optimal. However, we show that there exist ways of allocating credit both out of proportion to the true importance of the projects and out of proportion to the relative contributions of the individuals, that lead credit-maximizing individuals to achieve social optimality. These results therefore suggest how well-known forms of misallocation of scientific credit can in fact serve to channel self-interested behavior into socially optimal outcomes.

Original languageEnglish
Pages (from-to)344-378
Number of pages35
Issue number2
StatePublished - 1 Feb 2022


  • Algorithmic game theory
  • Credit allocation
  • Price of anarchy

ASJC Scopus subject areas

  • General Computer Science
  • Computer Science Applications
  • Applied Mathematics


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