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.”

I take issue with some of the article being rather loosely written. For example, she states that during the admissions interviews, “I ask them [prospective students] what they want to do with their PhDs. They all reply that they want a tenure-track job at a research university.” (emphasis added). Now this may have something to do with psychology as a discipline, and she does comment that applied jobs in that field are in decline, but anecdotally I would say that a large portion of post-docs, let alone PhDs, are in those positions not to gain an academic post, but to acquire unique skills for an increasingly competitive private sector. To pull a number out of the air, I would say maybe 1 in 5 post-docs goes on to an academic post. And in the UK, this is all part of degree inflation: 1385 full-time doctorates where obtained in 1994/95 and 14165 in 2008/9, a 10.2 times increase! In the same period, the total number of full-time HE degrees obtained (only) rose by a factor of 6.7, from 15601 to 104260 (data from HESA). So in this case, we shouldn’t stress too much about providing everyone with tenured positions.

The corollary to the “all PhDs want academic jobs” thing is that, assuming consistent cohort sizes, it implies we should have the same number of PhDs as post-docs as lecturers as professors, lining up along a smooth career path. Clearly this isn’t the case: academia is inherently hierarchical, always has been and always will be.

But this, I think, is where things get interesting. Let’s make the heroic assumption that PhDs (and post-docs) are cheap labour. Is this such a bad thing, provided that these individuals enter into the arrangement with open eyes? This site is, after all, called academic productivity: if PhDs and post-docs can do teaching and research more cost-effectively than professors and tenured staff, wouldn’t that be better from a societal perspective?

For those of us in the UK, this may not be a hypothetical question. There is currently an “Independent Review of Higher Education Funding and Student Finance” underway, led by Lord Browne (ex-chairman of BP). It has a pretty broad remit to consider how higher education should be funded while ensuring access for talented individuals and one idea I’ve heard suggested is that professors should do less teaching and instead leave it to post-docs or dedicated teaching fellows. From an economic perspective, the appeal is obvious: post-docs earn a fraction of the salary of professors, who of course can better use their time securing grants etc. Indeed, this already happens to some extent with tutorials and labs, but why not lectures as well? Why should a world famous professor be teaching first year calculus?

Well there are a couple reasons. First, many professors enjoy it. Teaching enables them to keep in touch with students and the contact is not one way: students can often ask off-kilter questions that inspire new ideas for research. Second, for new lecturers, teaching is an essential part of professional development. It provides a valuable opportunity to practice presentational skills and, through the planning and preparation of course materials and activities, it can help lecturers to solidify their existing specialist knowledge while also learning new material.

Another rebuttal is that students will demand to be taught by professors. I can’t say the extent to which is true but clearly, higher education is increasingly being seen as a paid-for service with the accompanying “client” expectations. If I go to university X for course Y, it may be because of their Nobel prize winning professor and I may be very cross indeed if that person never sets foot in a classroom. To some extent, I think this is an issue of managing expectations. Universities should offer prospective students courses taught to the highest standards, supported by quality assurance mechanisms like training for teachers and regular feedback from students. But this does not mean that the professors should be doing the teaching per se. There’s no reason to think that a well-trained teaching fellow couldn’t develop and deliver a course as effectively (if not more) than a tenured professor who may excel at research but not teaching.

All of this is to say that calling academia a Ponzi scheme is (obviously) a bit sensational. However, academia is certainly a hierarchical institution and its functioning does depend on the cost-effective labour of PhDs and post-docs. Indeed under current budget constraints in the UK, this labour will become increasingly important and may substantially redefine the delivery of undergraduate higher education. It doesn’t mean that potential PhDs should be discouraged from entering the system but certainly there needs to be upfront clarity about their true role and career prospects.

After a few months of private testing, Mendeley announced the public release of their open API. This will allow developers and researchers to build applications and data analysis on top of a massive database of human-annotated scientific references.

We are excited to see our friends at Mendeley push forward on the open science front by making their database accessible to third parties and I look forward to seeing what developers will build on top of this data goldmine. In the meantime, check out the Mendeley Developer Portal or follow the dedicated twitter account for updates.

There is only a bunch of tickets left for one of the most exciting annual events in the area of ICT for science. Hosted by Mendeley, Nature and the British Library, the second edition of Science Online London (3-4 September 2010) promises to bring together hackers, academics, publishers and startups in the field of software/services for scientists to discuss “how the Web is changing the way we conduct, communicate, share, and evaluate research”. I will be attending and would love to meet other AcaProd readers there.

Donald Knuth announced he would make an earthshaking announcement at TUG 2010. The breaking news is the plan to release the next-generation TeX engine. Read the comments and a brief summary of the announcement in perfect Stevenote style from Slashdot.

Using HTML5 features, this is the kind of obvious tool that makes symbol lookup faster than doing it by hand.

Just draw the symbol in the box and up comes the LaTeX code, and the package name that contains it.

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.

Project SOAP (Study of Open Access Publishing) is a two-year project, funded by the European Commission under FP7. The project is currently running a survey to understand the perception of Open Access publishing in the academic/research community. You can participate in the survey by following this link. Participants sharing their email address for further collaboration with the project automatically enter a prize draw for an Apple iPad.

“Incrementing productivity” is oftentimes framed in terms of incentives. The simpler incentives are, of course, monetary incentives. Academia is in this respect not so different from the business world – or so think many university managers and administrators. Some well endowed universities pay a premium to productive researchers: for instance, €3,000 for an article in an A+ journal, or maybe a lighter teaching load. The intrinsic value of discovery, and the thrills of fame, are no longer or not only the principal movers for scientific production. Not everyone agrees.

Brian Martin, a social scientist at Wollolong, Australia, suggests to explore “less traveled paths”, starting from the observation that research is not the preserve of a few superproductive superstars, but of a more distributed system. If monetary incentives can indeed motivate a superstar, it is also a fact that they can discourage those who do not receive the incentives. Below a certain threshold, the less productive researcher can be so de-motivated that she does not invest anymore in innovating, considering that she is not really up to the job. Thus, in order to uncover the research potential below the superstar level, other paths ought to be followed. To enlist them: preferring regular, day-to-day writing to binge writing, using creativity improving techniques, accepting that chance plays a role and even considering oneself as a lucky researcher, pursuing individual happiness, doing physical exercise, trusting the wisdom of the crowds and encouraging group work. Martin relies on recent results of the cognitive sciences about creativity and optimal working conditions.

Consider, as an example, the first path. Writing is a necessity in scientific production, but the prototypical production sequence puts writing at the end of the “idea-planning-research-result-writing” process, as a mere expression or documentation of the work done. The alternate path consists in considering writing a s a “way of thinking”, which should start early in the research project. Martin quotes work from Robert Boice, showing that the scientific output of junior faculties with a habit of writing 15-30 minutes per day can be four to nine times higher than that of binge writers.

Research Productivity: some paths less traveled. Australian Universities’ Review, vol 51, 1, 2009, 14-20.

[ CC-licensed image courtesy of milopeng]

Imagine a world where real-time search is the norm. You will get just the information you seek landing on your lap the exact minute it becomes available, without you having to explicitly search for it. Will this change the way you do science? SciSurfer thinks it will.

The release cycle of scientific knowledge is slow. It may take up to 2 years for a paper to get accepted in a journal. The publishing process in itself will add a buffer of a few months (arguably because of the time cost of having a paper edition, even though most people will never use it). So, for some of us, it doesn’t feel like we are missing much if we do not get the latest updates on our field the very same minute they are published. Just going to conferences yearly feels like more than enough. But there is a portion of the academia that needs constant updates on their field, as close to real-time as possible. If you are in the life sciences, getting the latest paper about a molecule or a gene you work on before your competitor does may make or break your career.

For those academics, sciSurfer may be a very valuable tool. The basic idea of sciSurfer is to integrate all journal feeds and search over them. Note that they do not archive RSS, so only the latest articles are available. This is a different way to think about search, closer to twitter’s than to Google’s.

In use

If you are used to RSS feed readers, the interface will look familiar. Left side there’s a list of journals and searches. Every time there’s a new unread item the containing ‘folder’ turns bold. On the right side there’s a list of articles (title, authors, and abstract). The journal it comes from is shown in green. The interface resembles Google reader (in fact, sciSurfer is built on app engine, so it may share code with reader).

What is the advantage of scisurfer over simply subscribing to the RSS feed of the journals? Search. Scisurfer does searches over all the journals they are indexing. This is pretty impressive, because I don’t know of any search engine that works on RSS feeds. Using an RSS reader, the equivalent to scisurfer would be to subscribe to the RSS of all journals, and apply searches over those. This is beyond the capabilities of most destop RSS readers. Implementing search by author, abstract, etc is also beyond the feature set of a normal RSS reader. In fact, it’s not that easy to deal with author names. We all have had the experience of getting papers by people with the same lastname and initials as our intended query term that are NOT the person we are looking for. Thomson Reuters has a solution: researcher ID. Researcher ID is based on the simple idea that each individual would get a unique identification (ID) number acting as a digital “calling card” that the researcher can place anywhere, such as a personal home page, a CV, or a university page. It has been out for more than two years now, so it’s still too early to say whether it has been adopted successfully.

Apart from the reader, there are two other tools, news and journals. Searching journals by name integrates the RSS feeds of otherwise disperse journals. Still, I haven’t found a good use for this tool.

Navigating trends

The main use I can think of for sciSurfer is monitoring Trending topics. We are getting used to explosions in popularity thanks to twitter and Facebook updates. Good twitter clients show you ‘what’s hot’ together with an explanation on why. Even Mendeley is getting status updates these days, making it look more and more like ‘facebook for scientists’.

There are several things to like about sciSurfer.  It integrates with your Google account, so it’s one less login to remember. The devs show that they are on top of things and the result is a fast turnaround when I requested changes. They are very open about feature requests. In my experience, when a journal was not in sciSurfer’s list, the devs added it within hours.

But by far the best result of using sciSurfer is that it makes you aware of what is going on in your field in a way that feels different and pleasant. The most similar feeling that I got online is when I found a neat Phd. student tagging articles in citeUlike that are relevant for me (it’s like finding a gold mine).

Mendeley uses a similar real-time approach in their statistics. For example, they show what are the most read papers per discipline at a given point in time.

I’m not sure one can do searches according to popularity just yet on any of these tools, implementing a real-time soft peer review.

How does sciSurfer plan to make money? The free tool is limited to ten saved searches. They will charge for extra functionality. There’s an iPhone version coming, which may well be another source of funds.

Conclusion

As the number of publications grows, it becomes more and more difficult to follow the latest scientific trends. The approach that sciSurfer takes is that if you know your keywords then it should be trivial to filter the fire hose of information, by doing a trivial keyword match. While keyword match could go a long way, I’m skeptical that the future of search lies in dumb matching. The way I currently filter information is very social, that is, I’m surrounded by people I respect and I ‘feel’ what they believe is good research. If I’m like most researchers, then social filtering would be a natural fit. However, I rarely get value from social networks online (science-wise; no matter how hard social networks try to capture my attention!). It may well be that to form a reputation, scientists need to do far more than posting interesting updates in their microblogging feeds. And for us to follow their recommendations…

I’m not sure how big of a problem selecting classes is for students, and how much it can be automated, but now there’s a tool specifically solving this problem. CourseRank tracks scheduling conflicts, together with some other Interesting features. For example, it gathers course/professor reviews, workload estimations and aggregates questions and answers.

Right now the selection of universities is not that great. It makes sense since the service is specifically tailored to each university, so I can imagine the implementation can take a while.