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Academia as a d-index measuring contest
Social scientists are victims of the quantification trap. We do things, countable things, so those things are counted, and the resulting numbers are taken to mean something; any number beats no number. Nowhere is this more apparent than in how we evaluate ourselves, and especially how university administrators evaluate us, for hiring, tenure and promotion. “Deans can’t read, but they can count,” the old joke goes: we’re not rewarded for the quality of what we write but for the sheer amount of it, and for the amount that what we write is cited.
The “Impact Factor” product sold by the for-profit Clarivate corporation (NYSE: CLVT) is the most established quantification technique, but the most-used is undoubtedly Google Scholar, both because it’s free and because it gives every academic who registers a score we can use to be compared against others. You get a total citation count, an h-index, an i-10 index – and all of those numbers restricted to the past 5 years.
Working academics I know grumble about each of these metrics. The primary problem with the Impact Factor is that different disciplines produce widely varying numbers of academic outputs per year; in Psychology, Communications and CS, 5 papers a year is on the low end, and 15-20 is not uncommon; journals and proceedings in these disciplines then naturally have higher Impact Factors than do outlets in Sociology, Political Science and Economics. So when deans compare by looking at the Impact Factors and number of publications, it looks like the psychologists are all superstars and the sociologists slouches.
The issue with Google Scholar citation counts is more personal. The unit of aggregation is the individual, and the total citations are summed across all of her papers, but there’s no real accounting for the number of co-authors on those papers. As research has gotten larger and more complex, like in computational social science, the number of co-authors has (justifiably) ballooned, especially for the highest-profile, most-cited papers. Members of large lab-style teams thus have “inflated” Google Scholar counts relative to their actual personal influence.
So, grumpy colleagues, if you don’t like those metrics, I’ve got good news: Research.com just rolled up and slammed their D-index on the table.
Research.com sounds like it would’ve been a very valuable internet domain in 1994, when that sort of thing mattered. In 2026 it’s a bit on the nose, though downright subtle compared to the name of their metric. The veil has dropped; the putatively pure pursuit of knowledge is revealed to be nothing more than a D-index measuring contest.
But the good folks at Research.com (btw, if a website introduces itself as “a leading academic platform for researchers,” it isn’t), in promoting their own, distinctive for-profit metric, may have inadvertently gone a step too far. The proliferation of boutique metrics is dangerous for the legitimacy of metrics in general.
When metrics are expensive to produce, proprietary, and thus scarce (the Clarivate (NYSE: CLVT) Impact Factor), they are easily legitimated, the only game in town. On the other end of the spectrum, when metrics are free to consume and thus ubiquitous (Google Scholar, the cost a rounding error for Alphabet and the data now somehow surely feeding Gemini and other AI products), they are easily naturalized, taken for granted as a good enough measure that people cease to even think about the gap between the measure and the complex reality.
The D-index reveals that there are different metrics that can be used to represent that reality – thereby de-naturalizing any one of those metrics and revealing that metrics are no longer scarce. Now we are forced to think about what goes into those metrics to decide which is best at capturing what we really care about. Research.com’s intervention in this space argues that the problem with Google Scholar’s h-index is that it’s too lowercase and too interdisciplinary; the big D-index is a di