2015/10/30 by Michael J. Kurtz, Edwin A. Henneken · 20 citations
Computer Science · Decision Sciences · Physics and Astronomy · Social Sciences · #Conferences and Exhibitions Management #Confidence interval #History and Developments in Astronomy #Longitudinal data #Measure (data warehouse) #Multiplicative function #Order (exchange) #Term (time) #astro-ph.IM #cs.DL #physics.soc-ph #scientometrics and bibliometrics research
paper · pdf · doi:10.1002/asi.23689
published in Journal of the Association for Information Science and Technology 68(3), 695-708 (Wiley) · Author's version of manuscript accepted for publication in the Journal of the Association for Information Science and Technology (JASIST); 35 pages 16 figures
arxiv created 2015/10/30 · openalex publication_date 2016/04/22 · openalex created_date 2016/06/24 · arxiv updated 2017/05/31 · openalex updated_date 2026/08/05
Citation measures, and newer altmetric measures such as downloads are now commonly used to inform personnel decisions. How well do or can these measures measure or predict the past, current, or future scholarly performance of an individual? Using data from the Smithsonian/NASA Astrophysics Data System we analyze the publication, citation, download, and distinction histories of a cohort of 922 individuals who received a U.S. PhD in astronomy in the period 1972‐1976. By examining the same and different measures at the same and different times for the same individuals we are able to show the capabilities and limitations of each measure. Because the distributions are lognormal, measurement uncertainties are multiplicative; we show that in order to state with 95% confidence that one person's citations and downloads are significantly higher than another person's, the log difference in the ratio of counts must be at least 0.3dex, which corresponds to a multiplicative factor of 2.