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.

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.

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.

The Math Myth, final thoughts

The last chapter of Hacker's book is about a numeracy course that he designed and taught.  I think it's a fine course that would admirably serve the needs of students in many majors.  I have no problem with that.  However, it's the wrong way to end this book.  Hacker would not characterize his argument this way, but it's not as much a book about math as it is a book arguing for tracking on multiple levels.

On the college level, I think his point is mostly correct:  Outside of the science and engineering disciplines, a lot of fields can and should modify their math requirements to be less abstract and more practical.  It is still an argument for tracking to some extent--if you are a social science major who takes a lot of calculus and statistics you keep open the option of career paths that in which you're an early adopter of new tools, one who customizes them for the specific needs of your field.  Every field has a few people like that.  If you are a social science major who doesn't take those classes there are still plenty of things you can do in the workforce as a numerate person who understands a lot of things about people and societies, but you are closing certain doors.  Still, I take his point:  Most people just need to be numerate.

I still think that a broadly-educated person should attempt at least one real calculus or statistics class (as opposed to a "numeracy" class) if they are majoring in a subject that has highly quantitative sub-fields.  But I see the point that most people will do fine in life if they don't take that class, or they try it but it doesn't work.  I think most people are, on some level, fine with this sort of compromise, because college students are adults and choosing a major is all about turning away from most of the options in front of you to focus on a few closely-related possibilities.

But the other half of his argument is about high school, and here Americans tend to be much more ambivalent.  For a number of reasons, I am OK with starting tracking in high school, partly because I think we unjustly devalue vocational education and partly because I see the consequences of pretending that we need everyone to be a STEM major.  However, while I might personally be OK with it, this is a Big Issue.  It's a significant departure from current practice, it involves educational issues that go well beyond math education (e.g. writing instruction for aspiring college students should be different from the writing instruction for people who plan to enter the workforce right after high school), and it hits on fundamental questions about democratic values.  Emphasizing vocational education can do a lot for the middle class, but it will also lock a lot of people onto paths at a young age.  There's a massive value judgment to be made there, and this book does not do justice to that issue.  I can tell you that Hacker's argument would be a complete non-starter with most of my colleagues, and not just the mathematicians.  Even the social scientists who would stand to benefit from greater emphasis on "numeracy" (which they might teach more effectively than most pure mathematicians) would have concerns about the equity issues in putting more people on non-STEM tracks.

Finally, while Hacker clearly respects math for its intellectual significance, I wish that he had shown that respect more openly, by taking the conversation one step beyond numeracy, at least at the college level.  Let's grant that "college algebra" or a traditional statistics class should not be the gatekeeper courses for most non-STEM majors.  Why should "numeracy" be the first and last encounter with math?  Besides the fact that many people might benefit from a second course on statistics, what about math as a liberal arts discipline?  The history of geometry encompasses agriculture, architecture, art (e.g. perspective drawing), and philosophy (via the Greeks' development of mathematics as a formal, logical, deductive discipline).  Why not a general education course on that?  Or a course on number theory (at an elementary level) and cryptography?  I'm not talking about teaching humanities majors to do cryptography in any hard, formal, abstract sense, but why not have courses that try to give educated citizens a sense of what this tremendously important technology is really about, and why it ties into seemingly elementary ideas about arithmetic?  How about formal logic courses taught one step down from what a math, philosophy, or computer science major might take, with the goal of getting the students to understand some aspect of the profound insights that Godel and Turing arrived at?  I'd cheer for a school that required the non-STEM majors (and maybe even the STEM majors) to take a "numeracy" course plus one more math course from a menu that might include some of the ideas that I outlined here.

We have found a witch; may we burn him?

On pages 155-156, Hacker says that a country that is as unequal as ours cannot expect strong math performance across the board.  Usually people assume that success in STEM classes will fix inequality, but  Hacker dares to say that fixing inequality is what it would take to get more success in STEM.  That is about as heretical as an Imam drinking bacon-flavored vodka.  Then he goes on to question whether beating the rest of the world in math is even a valid goal.  Saying that in the current climate of higher education in America is like pissing on the Virgin of Guadalupe in Mexico.  Well done, sir.

The Math Myth: Progressing on the Track

Tracking is generally considered to be a horribly regressive idea, one for evil conservatives.  It thus warms my heart that Hacker, having endorsed tracking in chapter 8, uses chapter 9 to endorse progressive "Discovery Mathematics" ideas. Not my cup of tea, but I appreciate when people break out of dichotomies.

Chapter 8: Now we are on track

In chapter 8, nominally about Common Core, Hacker says little about how math is taught under Common Core but much about why math is taught under Common Core. He goes into the history and politics behind this program, and the goal of getting as many people as possible "college ready" while also pretending that algebra (as opposed to, say, a practical statistics course) makes one "career ready." In taking on these assumptions he tackles the biggest issue of all:  Tracking.  If you don't take a few years of algebra and related subjects in high school you are closing the door on a range from scientific and technical majors.   Even if colleges followed Hacker's suggestion and reduced the math requirements for many fields, there would still be paths that properly do require a lot of math, and by not taking the right math prerequisites in high school you are closing a door.

Hacker's response is that there is nothing wrong with tracking, that high schools that prepare most of their students for a blue collar job are doing a useful thing.  I completely agree, but I think that this issue is so fundamental to so many problems in our educational system that it needs more than just a few pages.  I do not dispute that the average person needs numeracy more than algebra, but until we confront the question of when people should confront that fork in the road and make a choice with heavy consequences, we are just dancing around the edges of the issue.  I wish that Hacker had written a book on that, not on math. That is a much bigger issue than just math education.

Also, while I think I would support more emphasis on vocational tracks for more students, I have to freely concede that there would be drawbacks to vocational tracking. Giving people the opportunity to try many things before making a major choice can be a very good thing, and tracking would mean losing that. I think those drawbacks are still worth it, or at least I think that even with the warts such a system would be better than what we currently have.  However, this is ultimately a value judgment.  We need to confront these questions and weigh the pros and cons.

Finally, I think Hacker makes one absolutely essential point: As much as we resist tracking, when we make a high school diploma contingent on algebra and geometry we are tracking some people to not attain a basic credential.  That is a real cost that a lot of people pay.  There might be fine arguments to insist on algebra anyway (personally, I think everyone should be required to try algebra), but we need to confront the bigger questions here.  This really deserves a book of its own.