The low-information style in Hofstadter commentary

Since I dislike the intellectual poses of the Right-Thinking sorts, I have a natural sympathy for much of this essay on liberal smugness by Emmett Rensin.  Not all liberals are smug (and I don't disagree with all liberals) but I hate the happy-shiny smug liberal cool kids.  So I was primed to like this essay, and there's a lot to like.  For instance, this, on the denial that value judgments are real:

The studies, about Daily Show viewers and better-sized amygdalae, are knowing. It is the smug style's first premise: a politics defined by a command of the Correct Facts and signaled by an allegiance to the Correct Culture. A politics that is just the politics of smart people in command of Good Facts. A politics that insists it has no ideology at all, only facts. No moral convictions, only charts, the kind that keep them from "imposing their morals" like the bad guys do.

Since "is/ought" has been a recent interest of this blog, I approve!

Then they had to go and put this in:

The smug style has always existed in American liberalism, but it wasn't always so totalizing. Lionel Trilling claimed, as far back as 1950, that liberalism "is not only the dominant, but even the sole intellectual tradition," that "the conservative impulse and the reactionary impulse ... do not express themselves in ideas, but only in action or in irritable mental gestures which seek to resemble ideas."

Richard Hofstadter, the historian whose most famous work, The Paranoid Style in American Politics, this essay exists in some obvious reference to, advanced a similar line in writing not so well-remembered today. His then-influential history writing drips with disdain for rubes who regard themselves as victimized by economics and history, who have failed to maintain correct political attitudes.

Hofstadter's writing does contain considerable disdain for right-wing populism of many sorts.  If the only thing you've ever read by Hofstadter is The Paranoid Style in American Politics then it would be easy to read him as being part of the smug left.  However, if you read Anti-Intellectualism in American Life you'll see that he aimed far more fire at progressive educational ideas (most of them coming from lefty egalitarian impulses) than he ever aimed at conservatives and rubes.  You'd be hard-pressed to find a leftist who's more favorable toward the religion of the Puritans.

It is a hallmark of the Right-Thinking smug types (whom Rensin rightly derides) that they've all read exactly one work by Hofstadter, and it's The Paranoid Style in American Politics.  Unfortunately, Rensin has also read only one work by Hofstadter.  If you read a wider swath of his work you'll see that he's hardly convinced of the rightness of one "side" in our culture war.

Stephan, final thoughts

I've finished the book.  Here are some parting thoughts.

First, I want to mention an important point that she made earlier in the book but I forgot to blog:  Research is a classic public good, in economics jargon.  Once the results of research are out there it's impossible to control who will benefit from the information, which means that the producers of the good cannot capture all of the benefit.  In most cases this means that we have an incentives problem, because if people can't capture the benefits they won't produce it and then society won't benefit.  Science solved this with the priority system:  The first to publish something gets credit that will benefit their career and funding.  This thus incentivizes people to put information out there as quickly as possible, for the benefit of themselves as well as everyone else.

Second, as far as her recommendations later in the book, I largely agree that we need a looser coupling between the production of research and the production of scientists.  Ideally, all of our scientists should be produced in environments that produce research, but we don't need to produce all of our research in environments that produce scientists.  To that extent, I support the idea of research institutions that don't have graduate programs.  However, I would caution against using national labs as the model, as Stephan does in her final chapter.  While the national labs produce great research, being federal institutions they have absurd overhead rates and procurement bureaucracies that rival Soviet central planning for inefficiency.  I have no easy prescription for how to create effective research institutions that are not educational institutions but aren't federal either (a quick look at federal contracting shows that there are plenty of ways to set up bloated and inefficient systems outside of the federal government), but I do think we should be wary of encouraging DOE to metastasize even more than it already has.

Maybe one intermediate step would be to make it easier for university researchers to support technicians and staff scientists on grants.  This is easier said than done, but having it as a target would keep the academic science community churning out just as much research (if not more) without the wasteful by-product of PhD over-production.

On the other hand, I am deeply skeptical of her proposal to give fellowships to students and then let graduate programs compete for them.  Partly there's the fact that the programs would have an incentive to structure projects in a way that gets results out quickly and gets students out quickly (without the formative "time in the wilderness" that students spending in deep frustration but also deep learning).  However, I recognize that that may reflect my biases as an old man.  A bigger problem is that it would be tantamount to putting the federal funding agencies in charge of graduate student admissions.  While this would certainly be great from a research standpoint (putting all sorts of information in one central place for subsequent analysis) I think there would be all sorts of political insanity in what would follow.

All in all, this book was a good, insightful read.  For those who aren't academic scientists, the first several chapters do a good job of describing how the system works.  For those who are academic scientists, the last few chapters (starting with the one on the job market) do a good job of raising issues that we have not grappled with as well as we could/should.

Stephan: An alternative to the "alternative"

One periodically hears the Right-Thinking Classes talk about "alternative careers for PhDs."  This sort of talk is a joke on a number of levels.

For starters, some of them include "teaching at a 4-year college without a graduate program" as an "alternative career."  That just shows how narrow their conception of academia really is.

Of course they include working in industry as an "alternative."  It is rather strange that the most common job (when one finally lucks out after years of postdoc positions) is the "alternative."  They seem to be aware of this, and if they talk too much about industry in a roomful of postdocs somebody will eventually say "Oh, yeah?  Where are all of the companies clambering to hire us?"

But the true darlings of the Right-Thinking Classes are the trio of k-12 science teaching, science journalism, and science policy.  Now, yes, of course, we want to have scientifically literate k-12 teachers, especially (but not exclusively) in high schools.  And of course it would be nice if more journalists knew more about the science stories that they (sometimes) cover.  And who wouldn't like to know that the people making decisions about nuclear power regulation or approval of pharmaceuticals are knowledgeable about science?  Alas, there are only so many jobs in science journalism and science policy, and k-12 teaching requires a lot of other traits besides a science degree.  It isn't for everyone.

None of this stops the Right-Thinking Classes from periodically yammering about these paths.  I like Paula Stephan's response on page 181:

Yes, there is an apparent shortage of math and science teachers in the United States.*  But surely there is a more efficient way to increase the supply than by transforming people who have invested seven years of training in graduate school and another three to four as a postdoc into teachers.

Ooh, she is just ASKING to be disinvited from any further panels at funding agencies and professional societies.  Well, if she gets tired of those events, instead of getting herself disinvited she can just transfer the invite to me.  I'll be happy to consume fancy hors d'oeuvres while telling people things that they don't want to hear.

*To my knowledge, this is one of the few areas where the "shortage" rhetoric might have a factual basis, though the shortage has a lot more to do with the number of people who will accept those working conditions at the salary on offer than the number of people getting science degrees.

One more thing about Stephan and the economic return on a PhD

To her credit, Stephan's comparison of PhD earnings compared to BA/BS earnings is better than most I've seen.  For instance, she compares BA/BS holders who have been out of school for a few years to PhD holders who are new in the job market, to reflect opportunity cost. Not everyone does that. Also, she limits her analysis to PhDs and breaks them down into three categories, whereas I've seen analyses that lump together ALL doctorates.  As much as I'd love to think that my compensation is comparable to that of a dermatologist, the sad fact is that it isn't.

There is one weakness, though, albeit one that is common to all such analyses:  The average person with a PhD was probably more talented when they finished college than the average person who majored in the same subject but didn't get a PhD.  Note the "on average" part.  Of course there are dumb PhDs (just come to a faculty meeting...) and of course there are brilliant people who never went to grad school.  And of course there are people who never got a graduate degree but made outstanding use of people skills that aren't a direct part of a research degree (though they can of course contribute to research success) and there are people who got a PhD but can't work with others, and yadda yadda.

But with all of those necessary disclaimers out of the way (to head off a flood of anecdotes that people always feel the need to pour forth when you make a statement comparing two groups "on average"), it's likely that most (not all) of the people who get PhDs were in the upper tier of the talent pool before starting grad school, and they probably could have done quite well in the job market even without a PhD.  Her analysis doesn't account for that.  To be fair, nobody else does either, probably because it would be really, really hard to account for that.  Still, it's a caveat that needs to be applied when looking at those income premiums.  You don't know how much is a premium for the PhD itself and how much is a premium on traits that they possessed prior to the PhD and differentiate them from the average person with a BA/BS.

Seriously, guys, she's turning me into a Newt! Help! Help! I'm being transmuted!

Top of page 164:

Predictions of shortages of scientists and engineers occur with some frequency, despite evidence to the contrary. 

Later on that same page:

But getting egg on their face did not stop the forecast pundits.

Page 165:

Third, shortages are often predicted by groups who have a vested interest in atttracting more students to graduate school and into careers in science and engineering.

Wait, she thinks that people's pecuniary interests might affect their forecasts?  What is she, an economist or something?  Oh, right.

Page 168:

To quote the American Institute of Physics, "The proportion of new PhDs accepting postdoctoral positions has been a better job market indicator than the unemployment rate for PhDs, which is traditionally low and does not fluctuate a great deal."

AIP has always been good at putting out reliable statistical data.  The same cannot be said for APS.

Pages 168-169:

More generally, the proportion of new PhDs with definite plans to take a postdoc generally increases when the size of the graduating class increases, consistent with the idea that job market prospects are depressed due to an increase in supply.

She's just begging to be burned at the stake.

We have found a witch; may we burn her?

On page 163 Paula Stephan questioned the premise of the sweet, sweet "STEM pipeline" money:

The number of individuals receiving PhDs also depends on underlying demographics and college graduation patterns.  For example, the large increase  in the number of women receiving PhDs is due in large part to the increase in the number of women graduating from college, not to a change in the propensity of those going to college to get a PhD.41 The same is true for underrepresented minorities.  Indeed, the most effective way to increase the supply of underrepresented minorities receiving PhDs is to increase the number receiving bachelor's degrees.  This is not a trivial observation: a policy maker would achieve larger increases by building the base of students eligible to go to graduate school than by investing, as many institutions do, in changing the propensity of those who graduate to go to graduate school.

In other words, the best way to make progress at the graduate level is to make progress at the undergraduate level.  But the best way to make progress at the undergraduate level would be to make progress in k-12.  And progress in k-12 would be easier if we improved underlying social conditions, because there are plenty of things in a person's environment that matter more than their school.  And that takes us to problems that are hard for anyone to solve and are impossible for the scientific community to solve.

Also, the 41 in the quote is for a footnote, in which Stephan breaks it down more precisely and says:

Richard Freeman estimates that 70 percent of the increase in the ratio of women to men getting PhDs is due to growth in the ratio of women receiving bachelor's degrees relative to men receiving bachelor's degrees.  Likewise, 63 percent of the increase in the ratio of underrepresented minorities to non-minority PhDs is due to growth in the ratio of minority to non-minority bachelor's degree recipients.  Source: Freeman's tabulations from data obtained from the Survey of Earned Doctorates (National Science Foundation 2011c and the Appendix) and the U.S. Department of Health, Education, and Welfare.  See Stephan 2007b.

"Stephan 2007b" refers to a presentation at this meeting, but I cannot find a link to the presentation itself.

Stephan, Chapter 7

I'm several pages into the chapter on the job market for scientists.  Full credit to Stephan:  She tries to make her comparisons as apples-to-apples as possible.  For instance, on page 155 she doesn't show data comparing the salary of a new PhD with a new BA/BS recipient.  Rather, she compares PhDs 0-9 years out of grad school with BA/BS recipients ages 25-34, when they have a few years of work experience.

A few interesting things so far:
1) Although engineering PhDs generally make more than physical science PhDs, who generally make more than life science PhDs, the early-career income ratios (PhD salary in each category divided by BA/BS salary in each category) pretty much track each other over time.  All three types of PhDs can seek employment in multiple sectors, so they all seem to track the overall economy in tandem rather than the fortunes of any one particular sector.

UPDATED: 2) The PhD premium (relative to a BA/BS) is real but volatile and (apparently) declining.  She has data through 2006, showing that the PhD premium for an early-career life science PhD was barely 5%.  For physical science it was about 25% in 2006, and for engineering it was about 40% in 2006.

The volatility makes sense for a specialized credential attained by small numbers of people.  You'd expect it to be risky.

3) The later-career PhD premium is also real and somewhat more stable but still not what it used to be.  The ratios also converge, probably because people in every category branch out into more types of jobs (including management) as they progress in their careers.  An engineer working in management at a biomedical device firm probably doesn't make much more than a similarly skilled manager who works in the same firm but has a PhD in biology.  Either they know how to make their teams succeed or they don't.

4) You're still better off with an MBA.

5) For all the talk of scientists only caring about science, PhD production tracks the unemployment rate several years earlier (people are more likely to stay in school if jobs are hard to get) and the salary prospects for their field several years earlier.

It's almost as though scientists were human beings who responded to resource scarcity and incentives.

Stephan, chapter 6

Chapter 6 focuses on grant funding for university research.  The main takeaway is freaking obvious but needs repeating: The US system is highly competitive and keeps people on their toes to be productive, but it also discourages risk-taking.  The European system tends to be less competitive and may leave more room for risk-taking, but it also leaves room for sloth, and it puts the power in the hands of the senior scientists because of it is easy to keep getting funded then it is easy to get entrenched.  And it sounds all well and good and idealistic to just say "On, we will just take the best of both!" but you can't easily separate upside from downside.  If I could separate upside from downside then instead of designing a better science funding system I would design a chocolate cake that tastes incredible but doesn't make you fat no matter how much you eat.  And then I'd put Zombie Reagan in charge of balancing the budget.

Stephan also notes that "MOAR MONEY!" is no panacea.  The NIH budget doubled and it was great while the party lasted, but it also led to schools building up massive infrastructure to cash in on a growth model that didn't last. Which, in the end, made the pyramid scheme worse rather than better.

Damn those unintended consequences! This chapter should be required reading for everyone in every field ever.