These are some books we bought in York on the way home from our Scottish holiday in August, some undatabased books I discovered when I packed up my office in October, plus a few maths books related to a potential retirement project I'm thinking about.
We've recently removed a lot of bamboo from the garden, as it was getting rather large and overgrown. We had a silver birch sapling growing on the edge of the thicket, but hadn't noticed quite how tall it had grown, desperate to find light next to the tall bamboo until the latter had been cleared away.
Today, despite that early pink sky, the weather has been glorious, and has highlighted the tree in glorious low winter sunshine against a brilliant blue sky. Beautiful, if in a slightly etiolated way.
Looking west this morning, three minutes before sunrise (in the east, of course), a slightly frosty scene, with a pale pink sky.
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Stefan Collini. This book may be over a decade old, and some of the essays included even older, but it is more relevant today than ever. The first half is a thoughtful discussion of the history and purpose of universities in general. This is followed by a series of reprinted essays, dissecting various governmental initiatives in higher education.
The historical overview of the role, size and funding of universities from their inception is fascinating. My personal experience is confined to being a student in the late 70s and early 80s, and an academic during the 2000s. Collini points out most people tend to think that universities had always been the way they experienced them as a student, and only changed since then. But of course, they have always been changing. I am myself guilty of this view! My seven year tenure as a student was during the time of no fees and full grant (and fewer students and universities overall): so no student debt, and only vacation-time jobs. I would almost certainly not have gone to university under the current scheme, as getting into any debt, let alone that much, would have been too terrifying. I feel very lucky, but not guilty: I have certainly since paid enough in taxes from good jobs to cover the costs! I do think that current students should be similarly lucky, particularly as the number of good jobs has not kept pace with the increase in student numbers. (Even jobs that in the past would have required A-levels now seem to require not just a Bachelors, but even a Masters degree: surely they are not that much more complex? I often wonder if this degree-inflation is deliberately used to force people to go to university and get into debt, so making them more willing to take rubbish jobs, or if it is merely an unanticipated side-effect benefical to corporations and governments.)
Collini has a wide ranging and thoughtful discussion of what universities should be for. What should students be taught? How should they be educated? And why? He comes from the Humanities, which some argue are not “useful” subjects, because they do not contribute directly to the economic health of the country. I’m a scientist, and he thinks the arguments for these subjects are easier there. They may be easier, but I think that makes them more damaging, as it tends to encourage a focus on the economic, rather than educational or intellectual, benefits: graduate employability, rather than better, more thoughtful, well-rounded citizens. (If it’s just about job-specific skills, why not raise the status of apprenticeships instead?) Caving to that economic focus can unintentionally strengthen the argument against the humanities.
In particular, Collini’s point is that at university, the student should “study”, rather than be taught, or learn, a subject. This perspective puts the onus on the student to do the work, in depth, and not be a mere passive recipient of whatever the lecturer deems important, merely regurgitating it for assessment. The current insistence on increased “contact hours” (rather than private study) and ever-increasingly detailed assessment encourages this attitude of regurgitation, which helps parrots, but not growth. We are now encouraged to treat students as “customers”, where they pay a fee for the product of a degree certificate. Many students will focus on the certificate outcome, not the process they need to go through to get it. Rather than certificate seller, I prefer the metaphor of “personal trainer”: the lecturers are providing opportunities, resources, and direction, but the student has to do the (sometimes painful) work to achieve the desired goal. No-one goes to a gym to get a certificate (maybe some do? I’ve never been to a gym!), but rather to achieve fitness, understanding that this will require effort on their part.
After this excellent review of the state of universities, and their goals, Collini fills the rest of the book with reprints of earlier articles, which eviscerate various government schemes to measure the “quality” of universities’ performance. These essays are also excellent, and pull no punches. Collini argues that we should not measure (rigid metrics designed by unqualified beancounters), but rather judge (thoughtful analysis by qualified peers), performance.
There is a lot more excellent, thoughtful (and very well-written) material here. I have just pulled out a few points that resonate most strongly with me. Read this, and have good arguments to support universities beyond mere economic gain.
Susan Stepney. Physical reservoir computing: a tutorial.
Natural Computing, 2024. doi: 10.1007/s11047-024-09997-y
A decade ago (I was going to write "a few years ago", then looked at the date!) my colleagues and I wrote a paper entitled "When does a physical system compute?", which gives a framework to distinguish systems that are computing, from ones that are just doing their thing.
Recently, I was invited to write a tutorial for Natural Computing on Physical Reservoir Computing. That's about using weird physical materials, like a glob of carbon nanotubes, or a sheet of magnetic material, or whatever, to compute directly, according to the "reservoir computing" model, which is a form of neural network.
I decided to use the framework we previously developed to structure the tutorial. This framework provides five things you need to consider: (1) the abstract computational model, here, reservoir computing; (2) the physical computing substrate, here, the purported reservoir computer; (3) how to encode abstract inputs and physically inject them into the computer; (4) how to observe physical outputs and decode them to abstract results; (5) and last but certainly not least, how to validate that the physical system is faithfully implementing the abstract model.
If you want to see more of the details, have a look at the paper: it's open access.
Our Edinburgh bookshops purchases: (yes, I am very behind in databasing new books, but hoping to catch up soon!)
Amusingly, on that one morning we bought two different books, in two different bookshops, by two different Daniel Chandlers. Neither appears to have a disambiguating middle name.
As of yesterday, I am officially retired, and now Professor Emerita at York. The "Emerita" status grants me facilities that will help me continue to do research more readily: I keep my IT account (email, cloud storage, Overleaf, PaperPile, ...), library access, and a form of affiliation with the University. In exchange, they get to claim any publications of mine as associated with them.
So what did I do on my first day of official retirement? Well, I went for my daily walk, and got a bit of a fright. But the rest of the day I spent on zoom, on an interview panel. A colleague and I recently won an Aria "Nature Computes Better" project called LoCoMo (Lossy Computational Models). This was submitted before I had decided to retire, and awarded after. As Emerita, I can still work on the project ... for free! Yesterday we were interviewing for the two PostDocs.
So, starting as I mean to go on!
Hallowe'en decor on a nearby house that gave me pause this morning.
