Monday I attended a conference session on the metrics academics use to rate and rank people, journals, departments, etc.:
Eugene Garfield developed the journal impact factor a half-century ago based on a two-year window of citations. And more recently, Jorge Hirsch invented the h-index to quantify an individual’s productivity based on the distribution of citations over one’s publications. There are also several competing “world university ranking” systems in wide circulation. Most traditional bibliometrics seek to build upon the citation structure of scholarship in the same manner that PageRank uses the link structure of the web as a signal of importance, but new approaches are now seeking to harness usage patterns and social media to assess impact. (agenda; video)
Session speakers discussed such metrics in an engineering mode, listing good features metrics should have, and searching for metrics with many good features. But it occurred to me that we can also discuss metrics in social science mode, i.e., as data to help us distinguish social theories. You see, many different conflicting theories have been offered about the main functions of academia, and about the preferences of academics and their customers, such as students, readers, and funders. And the metrics that various people prefer might help us to distinguish between such theories.
For example, one class of theories posits that academia mainly functions to increase innovation and intellectual progress valued by the larger world, and that academics are well organized and incentivized to serve this function. (Yes such theories may also predict individuals favoring metrics that rate themselves highly, but such effects should wash out as we average widely.) This theory predicts that academics and their customers prefer metrics that are good proxies for this ultimate outcome.
So instead of just measuring the influence of academic work on future academic publications, academics and customers should strongly prefer metrics that also measure wider influence on the media, blogs, business practices, ways of thinking, etc. Relative to other kinds of impact, such metrics should focus especially on relevant innovation and intellectual progress. This theory also predicts that, instead of just crediting the abstract thinkers and writers in an academic project, there are strong preferences for also crediting supporting folks who write computer programs, built required tools, do tedious data collection, give administrative support, manage funding programs, etc.
My preferred theory, in contrast, is that academia mainly functions to let outsiders affiliate with credentialed impressive power. Individual academics show exceptional impressive abstract mental abilities via their academic work, and academic institutions credential individual people and works as impressive in this way, by awarding them prestigious positions and publications. Outsiders gain social status in the wider world via their association with such credentialed-as-impressive folks.
Note that I said “impressive power,” not just impressiveness. This is the new twist that I’m introducing in this post. People clearly want academics to show not just impressive raw abilities, but also to show that they’ve translated such abilities into power over others, especially over other credentialled-as-impressive folks. I think we also see similar preferences regarding music, novels, sports, etc. We want people who make such things to show not only that they have have impressive abilities in musical, writing, athletics, etc., we also want them to show that they have translated such abilities into substantial power to influence competitors, listeners, readers, spectators, etc.
My favored theory predicts that academics will be uninterested in and even hostile to metrics that credit the people who contributed to academic projects without thereby demonstrating exceptional abstract mental abilities. This theory also predicts that while there will be some interest in measuring the impact of academic work outside academia, this interest will be mild relative to measuring impact on other academics, and will focus mostly on influence on other credentialed-as-impressives, such as pundits, musicians, politicians, etc. This theory also predicts little extra interest in measuring impact on innovation and intellectual progress, relative to just measuring a raw ability to change thoughts and behaviors. This is a theory of power, not progress.
Under my preferred theory of academia, innovation and intellectual progress are mainly side-effects, not main functions. They may sometimes be welcome side effects, but they mostly aren’t what the institutions are designed to achieve. Thus proposals that would tend to increase progress, like promoting more inter-disciplinary work, are rejected if they make it substantially harder to credential people as mentally impressive.
You might wonder: why would humans tend to seek signals of the combination of impressive abilities and power over others? Why not signal these things separately? I think this is yet another sign of homo hypocritus. For foragers, directly showing off one’s power is quite illicit, and so foragers had to show power indirectly, with strong plausible deniability. We humans evolved to lust after power and those who wield power, but to pretend our pursuit of power is accidental; we mainly just care about beauty, stories, exciting contests, and intellectual progress. Or so we say.
So does anyone else have different theories of academia, with different predictions about which metrics academics and their customers will prefer? I look forward to the collection of data on who prefers which metrics, to give us sharper tests of these alternative theories of the nature and function of academia. And theories of music, stories, sport, etc.
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