
arXiv: 1810.12635
handle: 20.500.14243/345348 , 2108/188949
The response by Benedetto, Checchi, Graziosi & Malgarini (2017) (hereafter "BCG&M"), past and current members of the Italian Agency for Evaluation of University and Research Systems (ANVUR), to Franceschini and Maisano's ("F&M") article (2017), inevitably draws us into the debate. BCG&M in fact complain "that almost all criticisms to the evaluation procedures adopted in the two Italian research assessments VQR 2004-2010 and 2011-2014 limit themselves to criticize the procedures without proposing anything new and more apt to the scope". Since it is us who raised most criticisms in the literature, we welcome this opportunity to retrace our vainly "constructive" recommendations, made with the hope of contributing to assessments of the Italian research system more in line with the state of the art in scientometrics. We see it as equally interesting to confront the problem of the failure of knowledge transfer from R&D (scholars) to engineering and production (ANVUR's practitioners) in the Italian VQRs. We will provide a few notes to help the reader understand the context for this failure. We hope that these, together with our more specific comments, will also assist in communicating the reasons for the level of scientometric competence expressed in BCG&M's heated response to F&M's criticism.
Statistics and Probability, N.A., FOS: Computer and information sciences, Applied Mathematics, Computer Science Applications1707 Computer Vision and Pattern Recognition, Computer Science - Digital Libraries, Management Science and Operations Research, 551, Settore ING-IND/35 - INGEGNERIA ECONOMICO-GESTIONALE, Statistics and Probability; Modeling and Simulation; Computer Science Applications1707 Computer Vision and Pattern Recognition; Management Science and Operations Research; Applied Mathematics, Modeling and Simulation, Digital Libraries (cs.DL)
Statistics and Probability, N.A., FOS: Computer and information sciences, Applied Mathematics, Computer Science Applications1707 Computer Vision and Pattern Recognition, Computer Science - Digital Libraries, Management Science and Operations Research, 551, Settore ING-IND/35 - INGEGNERIA ECONOMICO-GESTIONALE, Statistics and Probability; Modeling and Simulation; Computer Science Applications1707 Computer Vision and Pattern Recognition; Management Science and Operations Research; Applied Mathematics, Modeling and Simulation, Digital Libraries (cs.DL)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 13 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
