Current Reading

This blog is primarily for me to blog my responses to books that I'm reading. Sometimes I blog about other stuff too, though.

I'm currently reading Reaganland by Rick Perlstein.

Word cloud

Word cloud

Saturday, April 16, 2016

Stephan, first few chapters: Workforce issues

Paula Stephan's book is hard to blog because it is detailed and descriptive rather than argumentative.  It's an interesting read, painting a very wide and detailed picture of how science works, but it's hard to pick out points to ponder or grapple with because it's not about Big Points (which is fine).  The part about intellectual property was interesting:  According to page 50, data shows that universities get more patent revenue for themselves when they let their faculty keep a larger share of the revenue (because their faculty have more incentives to commercialize) but the universities that give a larger share of revenue to faculty don't actually produce more patents.  The difference, then, must be the type and quality of research that they generate, its commercial feasibility, and the aggressiveness of their faculty in going beyond the patent office and actually pushing their idea to market.

On page 68 I learned that one reason (though hardly the only reason) why US university labs rely more on grad students and postdocs while Europeans rely more on staff scientists and similar sorts of personnel is that in the 1980's NSF started pushing faculty to put grad students on their grants rather than technicians.  I suspect that part of the reason was economic, but only partly so:  While a grad student will just about always receive less in salary and benefits than a technician (especially an experienced technician), some universities charge massive tuition for grad students and that tuition then gets covered by the research grant supporting the student.  Consequently, while at some schools the economics will favor the use of students by a wide margin, at others the margin may not be quite as wide.  Moreover, depending on their level of training, level of experience, personal abilities, and opportunities for development, a technician may be more useful than a grad student--the grad students may ultimately go farther as scientists, but it takes a while to get them there, whereas a good technician can keep a project moving forward on a consistent basis.  I suspect that part of the reason for NSF's preference is that they have long had a mandate to expand the scientific workforce because of an alleged crisis in STEM, and supporting students will do that, whereas supporting technicians will simply keep the labs humming along and producing mere science.  And this focus on students apparently started in the 1980's, which is when "A Nation At Risk" came out.

(And let me assure you that I don't buy into a dichotomy:  Clearly the world needs good lab techs AND students training to be scientists, but the answer then is to fund projects that have people in whatever mix of roles makes sense for the success of the project, not a mandate to endlessly expand the STEM workforce.)

ADDENDUM: I decided to look for the original source for the assertion about NSF.  It's a 1998 interview with then-NSF Director Rita Colwell by Science magazine.  Here's the key quote:
On a recent report of a Ph.D. glut in the life sciences: 
In the 1980s, NSF asked investigators to put graduate students on their research budgets, saying that it preferred to fund graduate students rather than technicians. But as often happens, the pendulum swung too far. There needs to be a balance. Well-trained technicians are needed to run equipment and labs, and what better way to provide opportunities for them than to build it into research grants. 
There's great respectability for those who want to be technicians, but we don't give them the opportunity. We've made it a sign of failure if you don't get a Ph.D. Other countries don't have this [negative] attitude. … With all the emphasis on graduate students, I'm not so sure that the question we're facing is one of overproduction. I think we have to look more closely at how we're using our resources. We've created a situation in the career pipeline where there is a bulge at the end of a postdoc and no place to go.
Even in 1998, people were talking about PhD gluts.  All of this has happened before and will happen again.  Of course, that was around the time that NIH doubled its research spending, so for a while things were good for life sciences PhDs.  But exponential growth can only go on for so long.

Thursday, April 14, 2016

Anti-Intellectuals want high school to never end

This morning's Chronicle has an interview with a UCLA professor who believes that admissions processes for academic programs need to pay less attention to academic measures.  There are lots of understandable motives for that: Academic measures aren't perfect, and we all know This One Guy who totally out-performed people with a better track record coming in.  Of course, no measure is perfect, policy designed around "This One Guy" will actually help fewer people than policy based on statistics (running counter to his stated sympathies for the masses), and while it's true that college is very different in form from the SAT/ACT the correlations should not be dismissed easily.

But there's another thing here, besides the arguments about predictive power and fairness:  As noted in the comments, a selective college is a place where the kids who always did really well in high school can suddenly find themselves in classes that are actually hard, and with classmates who are smarter than them.  UCLA and Berkeley currently function as those sorts of places.  There's some value in that.  If you open up UCLA and Berkeley to a wider cross-section of 18 year-olds, you might achieve certain types of fairness goals, but you'll also have to teach the classes at a level where a wider cross-section of students can succeed.  Yes, yes, some of the new additions will outperform expectations, and for those who out-perform you won't need to lower the level of anything.  But the definition of a statistical expectation is that those who out-perform will be balanced by those who under-perform, and you'll have to choose between either failing them or accommodating them.

If the only conversation is a normative one about whether to fail or accommodate the students who aren't at the top, well, I guess the question answers itself.  But if you expand the conversation, you'll note that we still have these top academic achievers in the classroom.  If you don't accommodate them they will be in the same spot that they were in during high school.  They will remain the smartest kids in the room, and that will have its own effects going forward.  Even from a 100% anti-intellectual standpoint, wouldn't you want those kids taken down a notch?  That won't happen when the classes are being taught in such a way as to ensure the success of their less-accomplished classmates.  Similarly, kids who might have been closer to the top in a less selective school will be only middling at UCLA or Berkeley.  There's no real need to weep over that, but please ponder the implications of a world where nobody's self-perceptions change after high school.

Sunday, April 10, 2016

Next book: How Economics Shapes Science by Paula Stephan

The next book will be How Economics Shapes Science by Paula Stephan.  I am told that it's an excellent read, and talks a lot about job markets and research funding in science.