A glimpse into the abyss of psychology prelims

Over the past month, I endured the crucible of the so-called "preliminary exams", or as they are more affectionately called, "prelims".  These exams go by different names in different areas ("qualifying exams" or "quals", "comprehensive exams" or "comps"), but across institutions, the intent is the same: complete an exam (or more rarely, write a paper) to prove your mastery of a body of knowledge.  Following prelims, graduate students are allowed to begin their dissertation research and, eventually, their PhD.

Needless to say, taking prelims is an intense and exhausting process.  While the specifics vary from place to place, it usually involves studying for months, followed by a multi-day exam with a strict deadline.  My own prelims consisted of a five-hour in-class test, followed by a six-day period in which I wrote four six-page essays.  I studied for my own exams for around five months and, according to my prelims notebook, I read some 75 papers and book chapters.  By the end of prelims I felt like I was leaking social psychology out the ears.

Six graphs answer questions about the PhD labor market

In my experience, getting an honest, straightforward answer about the post-PhD labor market from most professors in graduate school is about as easy as extracting teeth from the mouth of a sparrow.  Even when an answer is forthcoming, it is too often clouded by unrealistic expectations about the types of careers graduate students want and / or attempts to boost morale in order to increase research productivity.

Fortunately, no less an authority than the National Science Foundation has been conducting rigorous, nationally representative surveys on the US PhD labor market since 1993.  On top of that, the NSF has made the results from its biannual surveys open to the public, both in the form of raw data and in the form of summary statistics.  For a quantitative geek like me, the data are a little slice of heaven.

Thus, both to satisfy my own curiosity and for the benefit of other people who want hard data about PhD labor outcomes, I created the following six graphs with the goal of answering common questions about the STEM PhD labor market.  I will structure my graphs around three questions in particular:

(1) How successful are PhDs at finding the jobs they want?
(2) Where do PhDs go for their jobs and what do they do on the job?
(3) How well compensated are PhDs for the work they do?