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Metrics of Scholarly Impact

Assessments of scientific contribution are important for a variety of reasons. For individuals early in their career, metrics of scientific work can provide valuable feedback about where they stand and the progress they have made. For departmental faculty seeking to hire a new member, such metrics can simplify the task of wading through hundreds of applications to identify a subset of applicants whom they might wish to interview. For departmental chairs, these metrics may influence annual raises and the allocation of limited resources. For university administrators, these metrics help identify faculty who warrant promotion and tenure, and departments that warrant concern. For scientific societies, these metrics influence the selection of award recipients across the course of careers. For public and private funding agencies, assessments of science help identify areas of progress and vitality that may warrant support as well as a means of documenting performance, ensuring accountability, and evaluating the return on their research investment. Measures of science can also be used for a variety of other purposes, such as to identify the structure of science, impact of academic journals, influential fields of research, and factors that may contribute to the likelihood of discoveries. Ruscio and colleagues (Ruscio, Seaman, D’Oriano, Stremlo, & Mahalchik, this issue) provide a thoughtful empirical analysis of 22 different measures of individual scholarly impact. The simplest metric is number of publications, which Simonton (1997) found to be a reasonable predictor of career trajectories. There are numerous variants on this metric, such as the number of peer-reviewed articles, the number of first-authored publications, the number of articles published in a specific premier journal in a field, the number of articles without more-senior collaborators, and the number of publications across years (publication trajectories). Although the assessment of the scholarly contribution of a candidate for tenure is unlikely to be favorable if there are no or very few scientific publications, the number of publications is a far-from-perfect index of scientific contribution. Moreover, the incentives created by a metric such as number of publications may not promote the quality, innovativeness, programmatic nature, and cumulative impact of the research. Ruscio et al. (this issue), therefore, used five criteria to evaluate metrics of science: (1) ease of understanding, (2) accuracy of calculation, (3) effects of incentives, (4) influence of extreme scores, and (5) validity. Given the computational aids available today, the first 2 metrics are perhaps the least important and the third and fifth are most important. Most of the indices examined by Ruscio et al. (this issue) are based on citation data, which may provide a better incentive structure for scientific contribution than simple publication counts.