Beki Grinter

Publications and the System of Publications

In academia, academic management, computer science on August 11, 2010 at 9:39 am

Recently the Chronicle of Higher Education carried a piece entitled “We Must Stop the Avalanche of Low-Quality Research“.

Everybody agrees that scientific research is indispensable to the nation’s health, prosperity, and security. In the many discussions of the value of research, however, one rarely hears any mention of how much publication of the results is best. Indeed, for all the regrets one hears in these hard times of research suffering from financing problems, we shouldn’t forget the fact that the last few decades have seen astounding growth in the sheer output of research findings and conclusions.

Just consider the raw increase in the number of journals. Using Ulrich’s Periodicals Directory, Michael Mabe shows that the number of “refereed academic/scholarly” publications grows at a rate of 3.26 percent per year (i.e., doubles about every 20 years). The main cause: the growth in the number of researchers.

The article then largely goes on to deal with the papers. More, especially low quality papers lead to increased reviewing loads, as well as more variable quality knowledge that students have to manage in their own learning process. It makes the recommendation that we limit the number of papers that can be evaluated at stages (hiring, tenure, promotion). They also suggest publishing in high impact journals, based on impact factors, and changing (i.e. lowering the page count—which I think makes the suggestion that research can be reported in uniform length, but I suspect that different fields need different amount of space to accomplish their community communication goals). I saw a similar discussion at Snowbird also.

For me though, I was struck by the last sentence of that quote. I thought it was worth more attention than it received in the article.

The main cause: the growth in the number of researchers.

And recently I read a piece that talked about this, the number of researchers, in more detail. While I found the avalanche piece interesting, it was this second piece that I found very thought provoking. (Side Bar: I also sent it to my colleague Mark Guzdial who blogged about it).

The hypothesis put forward by Beryl Lieff Benderly is that the science gap (between the number of people who enter science fields and the number of jobs in science) is actually a product of the types of jobs that come at the end of the Ph.D. experience. The long, underpaid time spent in school is increasingly less likely to result in the very job that inspires people to go into science, i.e., an academic faculty position or equivalent.

I found the piece fascinating. I did not know much about Bush’s role in creating the post-war University expansion in the United States.

But the system had a basic flaw that was revealed only gradually, as the expansion of academe slowed in the early 1970s: The system’s central feature — the “self-replicating” professor who produces a steady stream of new Ph.D.s as a byproduct of grant research — had no control over the job prospects for those graduates.


Today, only a handful of young scientists — the few lucky or gifted enough to win famous fellowships or score outstanding publications that identify them early on as “stars” — can look forward to such a future. For the great majority, becoming a scientist now entails a penurious decade or more of graduate school and postdoc positions before joining the multitude vainly vying for the few available faculty-level openings. Earning a doctorate now consumes an average of about seven years. In many fields, up to five more years as a postdoc now constitute, in the words of Trevor Penning, who formerly headed postdoctoral programs at the University of Pennsylvania, the “terminal de facto credential” required for faculty-level posts.

This article left me with the following questions.

Is this beginning to happen in Computing? If the self-replicating professor model is accurate, then does it depend on a marketplace of constant growth (even if there is some retirement, and even if that retirement frees up resources that can be used to hire more than one new faculty member given the differential between start and end salaries)? What does an academic marketplace that is designed on stasis or very limited growth for a substantial period of time look like?

On the other hand I think it positions postdocs in a particular way. The first job I had, at Bell Labs, was initially a postdoc (that’s how they described the two year offer they made me, it was subsequently extended and converted to full-time employment). I knew when I left graduate school that I was not ready to take a faculty position. I felt like that four years later when I declined the first offer that Georgia Tech would make me. I still felt I had some things I wanted to and could best learn from Industrial research. I am glad for all my experiences prior to becoming a faculty member, even though it came at the cost of waiting 15 years to get tenure.

But I still think my questions are interesting ones to ask and answer. Especially for faculty members.

  1. Computer science is different from the non-engineering sciences. I am pretty sure we have a significantly higher percentage of industry positions where one can go work and still be considered a “real computer scientist”. This helps keep us healthy by having multiple respectable tracks for graduates.

    But if we are looking to have a stable population, then we need to agree on one number: what percentage of people who graduate with a PhD want and are qualified for an academic job at a PhD-granting institution. Call that number q. The average faculty member should then graduate 1/q PhD students in their entire career. What percentage of students make it through a PhD program after they enroll in it? Call that p. Now, the average faculty member should take on 1/(pq) students in their career.

    In my program, 4/12 people from my starting group made it through to the end, so p=.25 . From conversations that I am recalling in biased hindsight, about half of them would have taken and enjoyed a professorship at a PhD-granting institution (not me: I like the SLAC model and am very happy teaching only undergrads). So q = .5 . Both of these numbers have big error bars, of course. But they do imply that (modulo the totally unknown error bars), if a professor graduates more than 8 students over the course of their career, there had better be a professor (or professors) graduating fewer, or else we will have an oversupply.

    This analysis is almost certainly overly simplistic, as almost nobody is average, and the resulting number is almost surely not an integer. But it seems like a reasonable ballpark estimate.

  2. And, of course, I screwed up on the math. 4/12 is 1/3 not 1/4. So the analysis suggests that 6 students should be the average. All the rest of the analysis stands. Feel free to edit the comment in situ.

  3. I also wonder how much of the lack of mandatory retirement is affecting things. There’s an interesting article on this here.

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