August 31, 2010

The Dark Side of German Science Funding

Posted in Uncategorized at 7:16 pm by mariawolters

In the face of potential drastic cuts to UK higher education and research budgets, several bloggers have sung the praises of Germany’s decision to increase science funding – a prescient investment in the future. UK scientists quite rightly fear that massive cuts will lead to a lost generation of doctoral and postdoctoral researchers who can’t see a future in research.

But that does not mean the UK will be the only nation with a lost generation. Welcome to the club, Germany.

As all working scientists know, research has two pillars, permanent academic staff at higher education institutions and independent research institutes, and contract researchers who often apply for their own funding. Senior contract researchers can be a great boost to an institute’s research profile, as the RAE results of my academic home, the School of Informatics, University of Edinburgh, amply demonstrate. Both pillars rely on senior researchers being able to find long-term work.

In Germany, this is so fraught with difficulties that a long-term academic career is next to impossible. Let’s forget about the fact that assistant professors and professors at polytechnics in Germany earn less than teachers, let’s just concentrate on the hurdles to be overcome until one snags one of those permanent positions.

De facto, almost all permanent positions are full professorships – not lectureships, not associate professor positions. Lower permanent positions exist in the patriarchal pecking order of German academia, but they are the first to be cut in the latest round of savings when the office holder retires.

In order to become a professor, German researchers typically have to write a second “book” or large thesis called the Habilitation, where they show mastery of a field of inquiry. Yes, this Habilitation is in addition to a PhD. Some researchers managed to become a full professor by showing evidence of equivalent achievements, but this is relatively rare. The disadvantages of this system are obvious – a long time to qualification for a permanent position, and an equally long dependence on academic supervisors. Needless to say, this has highly predictable effects on the number of women in the upper echelons of German academia.

In the early Noughties, a reform was attempted. Juniorprofessuren were introduced. They were supposed to be modelled on the US model of assistant professor positions. Junior professors are in post for a maximum for 6-7 years, depending on the Bundesland. After the first three years, their performance is evaluated, and they can be made redundant if it is not satisfactory. After the end of their time in post, there is a final performance evaluation.

Now, let’s stop to think. What would sane people do?

  • They would ensure that capable junior professors are promoted to a permanent post
  • They would ensure that junior professorships or similar positions are the main route to a full professorship, obviating the need for a Habilitation
  • They would ensure a clear career path forĀ  young researchers by constantly creating junior professor positions until the new pathway has become self-sustaining

What did Germany do?

  • Only EIGHT PERCENT of junior professorships are full tenure track positions; for a further 18%, successful junior professors may apply for another position at the same university after their contract has ended.
  • Many disciplines, in particular law, are highly suspicious of that newfangled nonsense, so many junior professors write a Habilitation on the side, while people who follow the traditional path of the Habilitation earn significantly less than they used to, because the posts which were dedicated to them have been abolished and replaced with cheaper temporary positions, if at all.
  • The number of junior professorships needed to sustainably replace the greybeards who are forced into retirement at 65 is 6000. Right now, there are 800 junior professorships in the whole of Germany. To add insult to injury, junior professors whose posts were created after 2004 often have to make do without start-up funds and research assistants, because that’s when the special funding for these positions ran out.

Frankly, I don’t know what the thousands of doctoral students will make of this who are now busy doing all the work on the shiny new research grants. They will be able to spend a maximum of twelve years on uni-funded posts – this time includes their doctoral research. Exemptions can be granted for researchers who are self-funding, but I am not sure about the details. It would be great if an inhabitant of Mordor somebody who currently works at a German university could provide some more information. But somehow, I don’t see a future in German academia for all these researchers. Rather, I see a mass exodus of the best and the brightest to places where you don’t have to jump through a multitude of arcane hoops to have a future in science.

Like the UK.


August 30, 2010

Auditory interfaces on buses

Posted in Uncategorized tagged , , at 9:39 pm by mariawolters

This entry was motivated by @jobrodie’s recent musings on redesigning the way “Stop” buttons on London buses work

To quote the relevant part of Jo’s entry:

London buses do seem to vary in how much noise they make, and probably most of it is for the benefit of visually impaired people. Whenever someone presses the button to get off the action of pressing makes a ‘ding’ sound. But if someone else presses another / same button on the bus, as often happens when lots of people are getting off at the same stop, then each button press ‘dings’ too. Sometimes when people are impatient they repeatedly press the button to indicate their annoyance – fortunately not too often.

My argument is that this ‘ding’ need only happen once, as once the button’s been pressed the driver is going to stop the bus at the next stop and further button-pressing is redundant. There’s a bit sign that lights up at the front of the bus to say it’s stopping, and there’s usually another one halfway along the bus, and I think there’s one on the upper floor too. If the buttons themselves were able to light up once pressed (how difficult would it be?) then everyone could see that the bus was stopping.

The first interesting assumption is that sounds are mostly for the benefit of visually impaired people. Actually, they’re for the benefit of people who are not looking – because they’re watching out for the next stop, reading Shakespeare on their iPad, or debating policy on Twitter. (They could also be playing Sudoku, but let’s assume that all these people who can’t be bothered to use their eyes are being inattentive because they are distracted by something Very Worthwhile and Important.)

The annoying “ding” after the button press provides clear feedback that the button press was indeed successful. This is important, because many users like to get immediate feedback on the success of their actions. Having the button light up once it has been pressed would constitute visual feedback. But visual feedback only works if it can be seen. I have often cursed power-saving LEDs that could only be read from a strange angle, especially in direct sunlight. I have also often grabbed the pole behind or in front of me or beside me to indicate that the driver should kindly consider coming to a screeching halt at the next stop. Because in Edinburgh buses, not every pole has a stop button. Even worse, the button can only be seen properly if you sit right in front of it – I would probably have trouble detecting whether the button was lit from the window seat.

The solution Jo proposed would require a feedback loop from the central console to ensure all buttons light up once one has been pressed, and all lights need to be cleared once the bus has left the stop. A similar feedback loop would be required to stop the little bells from making a sound once one of the buttons has been pressed. Many steps, many potential causes of havoc, whereas the current sound is probably a simple little bell, completely localised, and easy to maintain.

The final nail in the coffin of the visual interface however are the commuters themselves. Jo mentions that there are several visual signs that indicate whether the bus will be stopping. Would the very same people who can’t be bothered to check the (presumably – hopefully) clear visual signage before they press bother to check the illumination on the button, especially if they have to contort their swan-like necks to see it?

So, people don’t care, people reach for the stop button in a reflex action, people don’t check, people are impatient, and one ding leads to another. The only consistent, easy-to-implement solution would be to abolish the “dings” altogether, or to make them softer without compromising their alert function. Somehow.

(The drivers probably learned how to tune out those beeps during their first week on the job. This may be one of the reasons why, on Edinburgh Lothian buses at least, the bell for the disabled space has a special, more insistent sound. Very annoying if it comes into repeated contact with a besuited commuter bottom during rush hour, I can tell you.)

The one tool I couldn’t live without

Posted in Uncategorized tagged , , at 8:37 pm by mariawolters

As part of the Scientiae carnival, Karina asks what tools we couldn’t live without. Although I’m an experimentalist, I don’t work with glass or microbes, like most of the science blogosphere I read, but with silicon and people (-> fanciful term for human-computer interaction).

My favourite tool is not an experimental platform – as a respondent to one of our project’s questionnaires noted sagely, “Technology breaks!”. Personally, I am a great fan of good old-fashioned pen-and-paper, which is extremely unlikely to crash and lose data of a whole experimental session. Rather, my favourite is a tool for analysing experimental results and modelling the resulting patterns of behaviour and preferences.

One letter: R

R is a programming language for everything statistical. It’s free, it’s open source, and it’s being maintained by statisticians for statisticians. Its origin means that it is a pain to learn. It takes a while until one has cleared a path through the data structures, including the various conventions for extracting information from objects that store the results of painstaking statistical analyses, and I am still often baffled myself.

But the payoff is magnificent. Clear (modulo coding ability), open, replicable analyses. R is the ultimate in replicable research. If you give people your data set and your source code, they can repeat every single step of your reasoning. There are no paywalls, no limits of affordability, no packages that are indispensable for the analysis, but that your department hasn’t paid for.

R’s free, open source origins are especially important when we’re talking about the analysis of data that is publicly available, data that can be – and should be! – analysed and reanalysed by citizen bloggers and journalists.

An excellent example are the comments on a recent Posterous post by Ben Goldacre on the reanalysis of a publicly available data set Several people are discussing their statistical analysis in terms of the code they used to generate it, which makes the whole discussion far more transparent. While both the Stata and the R code are useful, only the R analyses can be quickly replicated by anyone with a computer and an internet connection (download R, read in data, execute code, done).

R is even better when used in synergy with LaTeX – essentially, the resulting research papers are completely self-documenting. I don’t write any other way, except when forced to collaborate with first authors that insist on Microsoft Word. Even then, I try to document the main results of my analyses using R and LaTeX, although laziness sometimes gets the better of me and I copy percentages straight into Word.

Relying on free, open-source solutions like R and LaTeX is particularly important when you change institutions a lot. I have what could legitimately be called a patchwork career – after three years as a lecturer, I spent three years in industry, where there were no funds for SPSS, so I was glad I took the time to learn basic R at university. Afterwards, I worked for four different universities in two years, a jumble of small, part-time jobs. Using free software as much as possible made me independent of the particular budgetary constraints and preferences at each institution. Now that I have been in the same place exclusively for five years, I make a very conscious effort to stay independent. As we all know, science budgets wax and wane, and periods of relative dearth are common. So it’s even more important to ensure that you have the tools to keep publishing when the funds run dry and you need to beef up your CV for the next round of applciations.

Especially when the tools are as excellent as R.

August 18, 2010

Musings on Research Ethics

Posted in Uncategorized tagged , , at 9:04 pm by mariawolters

The other day, Petra Boynton pointed to an interesting case study for training health professionals. The case study was designed to highlight issues around responsible use of mobile phone technology. (Head here for the full description). Briefly, Darrell, a physiotherapist, has taken photos on his mobile of one of his young clients, who has been making great progress. He shows the pics to his colleagues over lunch. Ethical? Professional?

Very clearly no – all data is confidental. This was immediately clear to me, but after a while, I realised it might not be all that clear to other researchers, in particular students doing their first experiments. What is confidentiality, anyway? So I thought of a fictitious (!) example that is drawn from my own research fields, speech science and human-computer interaction.

Sandy is an older person who has volunteered to try out a new voice interface. Sandy has consented to having her interaction with the voice interface recorded and transcribed. He has also allowed the research team to store her assessment of the voice interface. Finally, he has given permission to the researchers to share these recordings with others for the purpose of research. He has done so on the understanding that his data will be anonymised. When the time comes to interact with the interface, Sandy finds it very difficult and downright discouraging. He gets very anxious about his performance – even though it is not Sandy who is tested, but the interface. Some of his problems are due to his speech. He’s an older guy with a raspy voice, marked by fags and whisky, and speaks with a strong accent, being working class and Aberdeen born and bred. Which of the following are ethical:

  1. A member of the research team plays a short bit of the recording where Sandy is particularly confused at a conference to illustrate a common problem with the interface. She only identifies Sandy as a male older research participant.
  2. A member of the research team plays a short bit of the recording where Sandy is particularly confused at a conference to illustrate a common problem with the interface. She identifies Sandy as Sandy Smith from Aberdeen.
  3. A member of the research team copies a short bit of the recording where Sandy is particularly confused onto her phone and plays it to her mates in the pub.
  4. A member of the research team asks Sandy whether she can take a photo of him with the setup. She then uses this photo to illustrate the experiment at conferences and in scientific papers.
  5. A member of the research team, Kim, chats to another researcher over lunch. They swap stories about their current experiment, and Kim talks at length about Sandy and his problems with the software to illustrate some of the issues they’ve found. Kim also plays a little sample that she’s got on her netbook to illustrate Sandy’s dysphonia. Kim tells the other researcher Sandy’s name and mentions that he’s from Aberdeen.
  6. A member of the research team, Kim, chats to another researcher over lunch. They swap stories about their current experiment, and Kim talks at length about Sandy and his problems with the software to illustrate some of the issues they’ve found. Kim also plays a little sample that she’s got on her netbook to illustrate the degree of dysphonia. Kim does not name the participant nor does he mention where he is from.
  7. In a team meeting, the Chinese research student who works on speech input processing presents a list of all participants for whom the speech recognition scores were particularly bad. One of the other researchers, Kim, recognises Sandy’s ID. Kim explains that this is a person with a particularly strong accent, talks a little about Doric, the dialect of Scots which clearly colours this participant’s speech, and explains the symptoms and prevalence of dysphonia. Kim also tells the student that Sandy needed far more encouragement and support than other participants, because the system’s failure to understand him disconcerted Sandy so much. As a consequence, Sandy tried to enunciate particularly clearly, setting in motion a well-known vicious circle of misunderstandings. Kim illustrates all her points with samples from the indexed and transcribed recording.

Got your answers? Here are mine – feel free to disagree (or agree!) in the comments.

  1. Ethical – this use of Sandy’s data is covered by the consent form, and Sandy is not named.
  2. Unethical. Sandy is identified by name. This makes him traceable. If particular aspects of Sandy’s profile are of interest, they can be highlighted in a way that preserves anonymity. For example, Sandy could be characterised as an older male with a strong local accent.
  3. Unethical. Sandy’s data can only be shared for research purposes.
  4. Unethical. This type of data (photo) is not covered by the consent form, and no additional written consent was obtained. Often, it is the researchers themselves who pose for a picture of an experimental setup, so that there is no need to use participants.
  5. Unethical. Sandy is identified by name.
  6. Ethical, although opinions might be divided. Bouncing ideas off colleagues during lunch or coffee breaks is an important part of the research process, as long as anonymity and confidentiality are preserved.
  7. Ethical. This conversation is within the research team, and an important part of the research student’s training.

P.S.: Petra’s example hit quite close to home. I spent several years in physiotherapy (first single, then group therapy) for what I think might have been gross motor dyspraxia. Children with dyspraxia are an extremely easy target for bullies and ridicule, and therefore very vulnerable. If the physiotherapist is one of the few people who praises and supports them, they will be eager to please, and parents are unlikely to antagonise the person who has done so much for their poor wee darling.