It seems that I have come up with a very simple but quite effective model for approximate assessment of the research strength of universities. I call it RFI, which is Research First Impression. Its essence is as follows. We go to Google Scholar, then write the domain name of the university (for example, for Yale University it would be @yale.edu), then click on Profiles in the top left corner inside the three horizontal lines. After doing these operations we can see the names and number of cited works of scientists. We take 10 top names, add up the number of their cited works, and then divide by 10. The result is the RFI index. This will be the average number of cited works of the top 10 scientists of this university.

For example, below I present the RFI index for 14 universities occupying different places in traditional rankings systems.

Harvard University: 363,500.
Stanford University: 312,379.1
MIT: 240,528.5
University of Chicago: 218,237,2.
Columbia University: 202,483.5.
Yale University: 195,508.3.
UCLA: 166,568.1.
Tufts University: 153,909.2.
Caltech: 144,100.8.
Fordham University: 21,488.9.
DePaul University: 20,327.4.
Northeastern State University: 4,669.9.
Montana Technological University: 2,918.7.
University of North Georgia: 2,301.6.

As this table shows, the RFI index, or the average number of cited papers of the top 10 Harvard scientists on Google Scholar is 363,500 while the RFI index of the University of North Georgia is 2,301.6. Of course, these numbers may change over time.

This is, obviously, a very simplified evaluation system. It does not consider many traditional indicators, such as the H-index (the Hirsch index). But in this case, this is not necessary since the task of the RFI is to give the first impression of the research strength of the university or universities. However, it should be noted, that even such a first impression turns out to be useful and quite correlates with the indicators of research activity and the university’s traditional ranking.

Of course, in such cases, there are also questions about the expediency of any kind of scientometrics assessment. Apparently, there are supporters and opponents of such assessments. However the proposed method does not claim to be accurate and reliable, it only speaks about impressions. Although, again, impressions can be quite consistent with reality.

Another question arises: why take only the first 10 scientists/professors? Indeed, we can try to take 20 and 30 or another number of scholars representing a particular university. But in universities, as in sports teams, the main impressions are created by stars, that is, leading scientists or athletes.