To conclude this series of posts, I’ll start with a quote that my good friend Chris is fond of.
C: “Ben, do you know who wins the rat race?”
B: “I don’t know, who wins the rat race, Chris?”
C: “A rat.”
Of course, Chris has long realized that to even play in the rat race that is our modern society, one must become a rat in order to succeed. Joining the rat race is certainly essential to a career in academia in its current state.
This idea crystallized for me this morning when I found a new paper by Brischoux and Angelier. This paper has suggested something crazy, that I suspect might be broadly true. During the time period that I have been a graduate student and a postdoc (2005-2015), the number of scientific papers required to obtain a permanent academic job in evolutionary biology in France has doubled. Doubled. What’s more depressing is that the number of years spent in temporary employment has also doubled during this time. If their findings are more broadly applicable across the sciences, this represents a fundamental shift in academia that I’m fairly certain nobody would have predicted a decade ago. From the time that I decided academics might be an appropriate career choice for me, until now, the rat race has changed entirely. The cause of the increase in publication stats and temporary work is complex, but I suspect it doesn’t have to do with increased absolute productivity. People applying for faculty positions today aren’t twice as smart, or twice as productive as people ten years ago.
One of the obvious reasons for the increase in number of papers is the relentless drive toward quantitative metrics for scientific output. Indeed there has been a great deal of discussion about scientific metrics (references within the linked manuscript), and essentially the problem boils down to one idea: it’s really hard to measure the impact of scientific output. However, hiring committees, promotion and tenure committees, and awards committees must all conduct their business, and being quantitative scientists, they are looking for ways to score, or rank scientists’ output, and justify their decisions to administration. There are flaws in every scoring system, whether one ranks candidates by number of papers, patents and reports produced, the number of times these works are cited (h-index), or some other arbitrary assessment of quality. However, despite the flaws of this approach, metrics provide something that’s easy to understand for university administration—the numerical rank of Candidate A is higher than Candidate B.
Consider Job Candidate A who has written an impressive 16 papers that have been cited by 135 other papers. On the surface, Candidate A appears to have greater scientific impact than Candidate B who has only written 8 papers with 92 citations. Candidate A has an h-index of 10, whereas Candidate B has an h-index of 8. Using quantitative metrics alone, one is unable to determine that most of the citations of Candidate A’s work were from other scientists refuting the findings of a single controversial manuscript in a more popular sub-discipline, and the remainder of his/her papers were only cited a handful of times. However, Candidate B had made a series of important discoveries in a smaller sub-discipline which redefined the field, and are indicative of a truly rising star. This is an extreme example, of course, but highlights some of the problems with quantitative metrics of scientific output.
Second, an evaluation system based on number of papers and citations inevitably splits science into thinner “salami” slice manuscripts and “least publishable units.” Additionally, some papers may be important but not widely cited in the academic literature. An important discovery in applied science may have broad reaching implications for an industry, but little “importance” in terms of scientific literature citations.
Third, and interestingly, the most cited papers in science consist almost entirely of methods papers. While these papers are most certainly important, they didn’t directly change our understanding of the world we live in. Hence number of citation isn’t always a measure of creativity or thought provoking work. So the quantitative system may not be measuring what a hiring committee might want, which is groundbreaking scientific work that makes an impact on society in the near or distant future. My favorite fortune cookie this year read “The purpose of education is not knowledge, it is action.” Impact on broader society (on an admittedly nebulous time scale) is essential for good scientific work.
Finally, there is a demographic component to this problem that I think boils down to an availability of cheap labor. The number of postdocs and grad students has increased substantially relative to the number of faculty over the past couple decades, and it appears that we’re near the breaking point of the academic ponzi scheme that has developed. It means that early career scientists are spending many more years in postdoctoral purgatory than in the past. Living contract to contract, moving from city to city. Perhaps this is broadly reflective of larger society where full time permanent employment seems like a relic of the 20th century. Quote from a senior faculty member, “As I got older and developed more outside responsibilities . . . it became easier to have more postdocs than graduate students because they didn’t need as much supervision. You could have a bigger lab that way without occupying more of your time.” And maybe more importantly, “In 1970, scientists typically received their first major federal funding when they were 34. In 2011, those lucky enough to get a coveted tenure-track faculty position and run their own labs, at an average age of 37, don’t get the equivalent grant until nearly a decade later, at age 42.” This is unsustainable, and the end result will be a lost generation of scientists who mistakenly thought there was a career path laid out for them because the positions to train them existed. Picture a medical school that asked students to go hundreds of thousands of dollars in debt, only to have jobs for about 15% of its graduates. There certainly wouldn’t be students lining up to pay tuition after a few years. So why do people continue to start PhD and postdoctoral programs? I suspect it’s because lost opportunity cost is generally invisible to a green 22 year old potential graduate student. It’s hard to think that far into the future and see what might lie ahead, especially when you have a professor that you like and respect telling you how good you can be at science if you only went to grad school. What else could you have done with those 20 years (between grad school and first grant) that would have contributed more to society? There is an enormous lost opportunity cost to the individuals and to society that they might have served. In retrospect, there are no easy solutions for the current supply glut, given the time and resources that have been invested into training these talented people. However, maybe we should stop training so many people in the first place?
I have spent a lot of time recently thinking about careers in science, so I’d like to ask you one question if you’ve made it this far without closing your browser: if you were advising an undergraduate student about careers after graduation, could you honestly recommend a PhD and academia as a viable option, given the current state of science? Could you recommend a prolonged underpaid adolescence (grad school, postdoc), while working toward a rare, and even more intensely competitive (but equally underpaid) junior faculty position that may or may not exist when you’re done? I’m certain I could not recommend this path to a student starting today. If I were a tenured faculty member right now, I could not justify taking on a graduate student. I’m not sure it would be ethical. Ten years ago, when I started on this path, things were a little different. I saw postdocs in my lab, and in my large interdisciplinary project getting good jobs, and saw scientists doing interesting work (one out of three attained a TT position). I saw a reasonable career pathway that would be challenging but rewarding. Today’s students should (hopefully) see the numbers from studies like the one I’ve highlighted today, and run away screaming from an academic path that offers little in the way of job prospects, salary, or future job security. The current labor supply glut is far greater than the system can absorb into permanent positions in the near future, and a silent majority of trained scientists have dropped off the academic track along the way. The tenure track has become a war of attrition, rather than a fair competition among young scientists with the best new ideas, and that is a big problem.
So given my current position as a postdoc, I suppose the question is: what now? Before I started my job, I laid out a set of concrete rules that I’ve followed perfectly so far. These rules help me manage and accept the major structural problems in academic science that I see around me. I took my current position with three ideas in mind: 1) this is an exciting project, in a field I always wanted to explore (I changed disciplines entirely following my PhD), 2) this position would be the only postdoc I’d ever have, and 3) if I didn’t have an academic TT job by the time this postdoc was over, I’d find a different career. So far #1 has been great success. I’ve learned a ton, contributed a solid paper that helps understand “Snowball Earth” (an undergraduate fascination of mine), and will continue to work hard to understand triple oxygen isotopes in the geologic record, at least until funding runs out. I’m still awaiting results of #2, as I’ve applied for a number of jobs recently and interviews are still being conducted at a number of schools. As for #3, I’m funded until the end of July, and we’ll see where things go after that. As much as I’d love an academic career, there are a lot of other paths in life, and I’m not so one-track focused that I’d do “whatever it takes.” At the end of the day, it’s just a job like any other, and there are things that are important in life outside of science.
Perhaps most of all, when I’m old and grey and look back on my career, I hope I can confidently say that I didn’t win the rat race. I think Chris would be proud of me for saying so.