Publications

Repeated calls for responsible research metrics and professional codes of conduct in evaluative bibliometrics highlight the need to investigate which qualifications and competencies enable a proficient application of bibliometric methods and indicators. Taking competence research as a point of departure, this chapter delineates salient dimensions of professional competence in bibliometric research evaluation by reviewing a selected subset of the literature. The reviewed literature focuses on handbooks, monographs, and scholarly and practitioner articles that introduce theory and methodology of bibliometrics and showcase applications to scholars and practitioners mainly outside of the scientometric research community.

Grant selection and decision-making generally take place in panels. Therefore, the main focus of the project is to measure the level of gender bias at the panel level, and to explain the differences in gender bias using characteristics of the panels and of the (organizational) context of the panels. A second source of gender bias addressed in the project is the application process. The project also investigates the factors influencing the decision to apply for research grants, and the possible gender differences emerging from that. Finally, the question is addressed whether possible bias in grant allocation translates into gender bias in the subsequent academic career.

We conduct an independent cluster validation study on published clustering solutions of a research testbed corpus, the Astro dataset of publication records from astronomy and astrophysics. We extend the dataset by collecting external validation data serving as proxies for the latent structure of the corpus. Specifically, we collect (1) grant funding information related to the publications, (2) data on topical special issues, (3) on specific journals’ internal topic classifications and (4) usage data from the main online bibliographic database of the discipline. The latter three types of data are newly introduced for the purpose of clustering validation and the rationale for using them for this task is set out.