The annual list of "top" scientists compiled
by Clarivate Analytics remains a subject of ongoing controversy.
Following the year 2018, and in response to significant criticism
from the scientific community, Clarivate Analytics introduced a new
category called "Cross-Field." In addition, they made the
decision to exclude articles featuring more than 30 affiliations.
This year, a fresh alteration to their methodology has come to light.
Clarivate Analytics decided to remove (evil) articles with more than 30 authors.
However, the question arises: why
specifically 30, and not 29, 28, 27, 26, 25, and so on?
Curiously, Clarivate Analytics provides no insight into this choice,
possibly due to the inherent secrecy that appears to be central to
its operations. Alternatively, it may be reluctant to acknowledge
that its methodology is fundamentally flawed, a sentiment expressed
by numerous researchers in the field., such as Docampo & Cram (2019), Asknes &Aagaard (2021), or more recently Koltun &Hafner (2021) https://pacheco-torgal.blogspot.com/2021/11/evaluating-researchers-in-fast-and.html
To Clarivate Analytics' great misfortune, some Stanford University researchers went out of their way to try to solve the aforementioned shortcomings. And fortunately, they successfully generated a list of top scientists that markedly enhances the scientific reliability. https://elsevier.digitalcommonsdata.com/datasets/btchxktzyw/3?fbclid=IwAR1vdz
This new list of top scientists
effectively addresses the significant issue of articles with numerous
authors, ranging from tens to hundreds or even thousands. Moreover,
it rectifies the deficiencies present in Clarivate Analytics' list,
which often combines researchers from different fields, overlooking
the distinct citation patterns, as thoroughly demonstrated by
Lillquist and Green.https://link.springer.com/article/10.1007/s11192-010-0162-3
Last but not least, the Stanford University researchers'
list (in contrast to the flawed Clarivate Analytics list) upholds a
commitment to transparency by providing open access to raw data for
all interested parties.
