On bibliometrics in academic promotions: a case study in computer science and engineering in Italy
| Autor: | Camil Demetrescu, Andrea Ribichini, Irene Finocchi, Marco Schaerf |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Research evaluation
academic recruitment media_common.quotation_subject Population education.educational_degree Library and Information Sciences Bibliometrics 050905 science studies Habilitation research productivity citations h-index Computer Science and Engineering Promotion (rank) education Academic recruitment Citations H-index Research productivity media_common education.field_of_study business.industry 05 social sciences General Social Sciences Public relations Computer Science Applications 0509 other social sciences 050904 information & library sciences business Discipline |
| Popis: | Due to its quantitative nature, bibliometrics is becoming increasingly popular among policy makers for academic hiring and career promotions. In this article, we quantitatively assess the impact that the granularity level in the classification of scientific areas would entail on research evaluation based on bibliometric indicators. We use as a case study the Italian national habilitation system (ASN), which classifies faculty members according to their academic discipline and relies on journal counts, citations, and h-indices as a basis for promoting tenure track researchers to associate professors and associate to full professors. The assessment checks whether the individual indicators of a researcher are above a certain threshold, e.g., the median over the population of researchers working in the same discipline. Our investigation focuses on two related, rather broad disciplines: computer science and computer engineering. We show that the ASN practice of using the same thresholds for all members of a scientific discipline can favor certain sub-communities that are characterized by higher bibliometric indicators, and disfavor others. We report evidence that up to 30% of Italian faculty members of certain sub-communities would see their indicators drop below the threshold, thus becoming not eligible for promotion, if the ASN were conducted on a more accurate, fine-grained classification. Conversely, in the same scenario, up to 11% of faculty members, in different sub-communities, would see their indicators rise above the threshold, granting them eligibility. Our data set includes 1685 authors, 89,185 distinct publications, and 262,286 author-publication pairs. |
| Databáze: | OpenAIRE |
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