Academic Productivity

Just a quick follow-up to last week’s post on changes in higher education. The New York Times published an article on Friday, highlighting two new books on the future of the American academy and picking up some of the points I discussed last time:

The labor system, for one thing, is clearly unjust. Tenured and tenure-track professors earn most of the money and benefits, but they’re a minority at the top of a pyramid. Nearly two-thirds of all college teachers are non-tenure-track adjuncts like Matt Williams, who told Hacker and Dreifus he had taught a dozen courses at two colleges in the Akron area the previous year, earning the equivalent of about $8.50 an hour by his reckoning. It is foolish that graduate programs are pumping new Ph.D.’s into a world without decent jobs for them.

But the real meat of the article is an overview of some interesting, but slightly terrifying, proposed solutions:

As for the humanities, let professors do research after-hours, on top of much heavier teaching schedules. “In other occupations, when people feel there is something they want to write, they do it on their own time and at their own expense,” the authors declare.

The authors being “Andrew Hacker, a professor emeritus of political science at Queens College, and Claudia C. Dreifus, a journalist (and contributor to the science section of The New York Times)”. You can thank them below.

There’s nothing like an overtly contentious statement to bring in the traffic. And as they go, this is a pretty good one: “Why higher education is like a Ponzi scheme“.

The linked post is actually for a radio program, the content of which was based on this original article by a professor of psychology from the University of Kentucky. In it, she argues that there aren’t enough tenure-track jobs to support the PhD students coming through the system and that students are exploited to prop up the teaching and research of over-stretched professors:

“In short, I think academia shares many of the classic elements of a social trap: It is in most faculty members’ and departments’ best interests to recruit a lot of graduate students. Churning out PhDs is one of the major metrics of departmental ‘success’. Departments need graduate students to teach their classes, and faculty members need them to run their labs. Yet, as in any social trap, when everybody acts in their self-interest, a negative collective outcome ensues.”

Her solution? Not to accept any more PhDs:

“I’m no longer willing to pin my students’ prospects for their futures on an ephemeral job market that shines in the distance like a mirage … I don’t want to be part of the problem any more, and I think I will sleep better knowing that I am no longer contributing to an academic job market that bears an uncomfortable resemblance to a Ponzi scheme on the verge of falling apart.”

(more…)

I just found this presentation, and thought it’s worth bringing it to the attention of ap.com readers:

Anita de Waard is the director of Disruptive Technologies at Elsevier. A company that has a position with such a name has my sympathy. Looks like publishers are slowly realizing that they can have a huge impact on how science is done, and how fast it moves, if they simply paid more attention to modern trends.

Only habit prevents us researchers from realizing that the media we use the most, a paper article with a review cycle of years, is woefully wrong in this day and age.

A somewhat related idea are the 5 stars of open linked data:

★ make your stuff available on the web (whatever format)

★★ make it available as structured data (e.g. excel instead of image scan of a table)

★★★ non-proprietary format (e.g. csv instead of excel)

★★★★ use URLs to identify things, so that people can point at your stuff

★★★★★ link your data to other people’s data to provide context

If scientists and publishers have opendata in mind (and the trend is there!) doing research becomes more fun immediately (no more mails to the authors asking for data that get no response). Seeing that the academic publishing industry has at least one person (Anita) that gets it makes me feel good. Looks like Elsevier has a head-start.

Peter Drucker: "There is nothing so useless as doing efficiently that which should not be done at all."

Sometimes I wonder why many humans (me included) have trouble understanding probability. In cognitive science, probabilistic models are taking over most areas. Still, most people struggle with them. Could it be that the notation is just hard to swallow? What’s Wrong with Probability Notation? is a magnificent post that gives some basic reasons:

The first two issues arise in the usual expression of the first step of Bayes’s rule,

,

where each of the four uses of corresponds to a different probability function! In computer science, we’re used to using names to distinguish functions. So and are the same function applied to different arguments. In probability notation, and are different probability functions, picked out by their arguments.

This is one clear communication problem. Ideally we want more people to follow probabilistic reasoning. Doctors, judges, etc all show significant struggles when given probabilities (see e.g., Helping Doctors and Patients Make Sense of Health Statistics).

But how do we tackle this problem? Changing notation is easier said than done. In fact, anyone departing from traditional notation will have to convince reviewers that his notation is better… and add to the risk of cause a less-than-ideal impression.

Any ideas?