Category Archives: The life of μ

Money for nothing, research grants for free

This really is not some value-neutral fascinating social phenomenon such as the currently  en vogue “academic acceleration“: it is a bad use of academic time! Sure, some of the literature discussing “acceleration” is good, but I have a feeling it dance s around the subject a bit too much. Thanks to Jan Blommaert for calling the spade a spade (and apologies for the distasteful crib of Dire Straits lyrics in the title):

After submitting, we heard that a total of 147 applications had been received by the EU. And that the EU will eventually grant 2 – two – projects. In a rough calculation, this means that the chance of success in this funding line is 1,3%; it also means that 98,7% of the applications – 145 of them, to be accurate – will be rejected. And here is the problem.

[M]any millions’ worth of (usually) taxpayers’ money will have been used – wasted – in this massive and mass grantwriting effort. Several hundreds of researchers will have been involved, each spending dozens if not hundreds of their salaried working hours on preparing the application, and hundreds of university administrators will have been involved as well, also spending salaried working hours on the applications. These millions of Euros have not been used in creative and innovative research – they weren’t spent on doing fieldwork, experiments or tests, nor on writing papers and holding presentations in workshops and symposiums. They were spent on – nothing.”

Jan Blommaert, “Rationalizing the unreasonable: there are no good academics in the EU”, 10 June 2015,

(Image: Milena Kremakova ®2007)

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Foggy thoughts

Warning for sociologists: This text is an intuition piece. It is replete with imperfect metaphors. It is the backstage of my thinking about my research. Please don’t cite.]

I have had this intuition for years now, but have not been able to put it in words.

The intuition is based on different “data”. The first layer of data is my subjective experience and affective responses when thinking about or doing mathematics, vs when thinking about or doing sociology*. I know that “own affective experience” is a very, very flawed source of data from a sociological perspective. Yet from a psychology or psychoanalysis perspective it does give some information. Perhaps it gives more information about the individual’s neuroses than about the subject; then, so be it: I’m sure that’s useful as well since I’m a researcher and it is helpful to know more about your own biases. Plus it has been nagging me for several years so I’d better write it down than continue ignoring it. The second layer of data is communications with sociologists vs communication with mathematicians. And the third layer is observations of other sociologists communicating to eath other and doing sociology vs mathematicians communicating to each other or doing mathematics.

So here it goes. I believe there’s something symptomatic about the shift that happens in my head when I think about mathematics. Thinking about maths brings a small surge of pure joy and curiosity. Math questions are like new games. They sound, for lack of a better word, “fun”. There is no anxiety about them, no need to prove myself. There is a curiosity about this “thing” that is entirely separate from me. In comparison, sociology makes me anxious, doubt my abilities, lost. Picture being in a fog. Like that old soviet “hedgehog in the mist” cartoon That’s what it’s like. When a sociology paper has one point to make and  is simple to understand, I find it boring. When it’s complex, I often don’t know where I am and is it bullshit, or am I stupid for not understanding it. With maths, there are terms I don’t understand, but in general maths is a clearer, less scary place.

It may be that I should do maths and not sociology, maybe that’s how my brain works. But I have no proof for such a simplistic view of human intelligence – I simply don’t believe that brains are so easily categorised, and even if they were, how am I to tell that I’m “good at math” more than I am “good at sociology”. Or it may be that the reason for my personal lack of anxiety is thatmaths maths is not my profession but my hobby. Given that I am a person who tends to get anxious about stuff, perhaps maths would cause me anxiety, if I were actually a mathematician? This may be so. But even if it is, I suspect that’s not the only reason. 

I think the crux of the reason is that social science comes with less intrinsic, existential security than maths. I am a human, and I realise that understanding how the complex entity made up by us humans involves constant feedback loops. I can pretend to be objective for a limited time or a particular question, but at the bottom of my pretense I know that it’s false. In contrast, maths is something that can be played with. It’s a dangerous animal with big teeth, but it is honest. Social science is a fluffy cuddlly animal which is however stealthy and able to manipulate your mental state. Playing with social science makes me anxious because there are not only areas that I don’t “yet” know. There are areas that are, by definition, unknowable. This freaks the hell out of me. I can imagine playing at maths with abandon if I had the skills. In fact, with my existing skills, at my level of knowledge, I have played with abandon [for example when struggling with the homeworks when I was following the undergraduate maths course in 2013, even when I could not do them, I still found them fun].

The second layer of data is talking to sociologists vs talking to mathematicians. Oversimplifying grossly, sociologists make me nervous, and mathematicians put me at ease. This is also a limited data source because, since I’m no mathematician, I’ve not had “real” math conversations at a professional level. The only conversations I’ve had have been me asking people to explain some late-school or beginner-undergraduate math to me; or non-professional conversations which are more like the stuff friendship is made of (even more curiously: friendly chats with mathematicians usually end up being about fascinating things, objects, facts or questions. Friendly conversations with sociologists – remember that I am a sociologist, so this complaint is as much about me, as about my other sociology friends, and perhaps it is fully my fault and not theirs! – are much more often conversations full of anxiety, worry, complaint, or gossip).

With this caveat (being a non mathematician, I can’t say what it is really like to be a mathematician talking to mathematicians) , I’ve found my own math conversations with mathematicians relaxing, while I find sociology conversations with sociologists make me nervous and I’m never sure whether and how much I understand (even when I’m the one explaining). And it’s not like math is binary: it is not true that you either understand or not. Quite the contrary, it’s full of intuitions, and for someone like me who knows very little, I often think I grasp the main gist, but can’t express it or remember it for very long. But when I understand, it feels satisfying, even if this understanding is fleeting and would require further work to solidify.  With sociological concepts, I never know really where I stand. To use some mathematical jargon: there is ALWAYS scope for a nasty counterexample; sociology problems are NEVER “well-posed problems”. 

Now that makes sense. What doesn’t really make sense is the following: why is it that mathematicians are so inventive and playful when they explain maths, and why are we sociologists, contrarily, so “up in arms” as if we are defending our baby and not just a piece of text? It’s like they don’t take math seriously. Sociologists talk like it’s super serious. This is my third layer of data, watching people talk shop among themselves. Mathematicians are almost always ready to crack a little joke. They are constantly on the hunt for the most colourful, excessive metaphor to verbalise their train of thought, even if it’s obviously an imperfect metaphor. And somehow, coupled with strict notation, these imperfect metaphors lead to more rigorous explanation than sociologists can achieve. Mathematicians simplify. They draw pictures on the blackboard and speak in simple words while being certain that they won’t be misunderstood by their audience. Sociologists (and here I lump together anthropologists, historians, philosophers, literature theorists) tend to choose the more complicated words. The more boring ones. The more clinical ones. Sociologists tend to talk in long convoluted sentences. We don’t like saying something that’s not true – but the result is that we end up entangling ourselves in our complicated strings of ambiguous thought. I’m being very uncharitable here. I’m speaking about sociologists like a mathematician would. Mathematicians think we should cut the bullshit and get to the point. That we overcomplicate simple things, and create a veil of magic about things that could be expressed simply – and that the fact that we overcomplicate for the very understandable reason that we are aware that we can never be perfectly clear about the social world, doesn’t make overcomplication right. I’ve been told by several mathematicians that they want to hear something that’s both surprising, and true, but often sociology is either boring, or untrue, or both [Granted, maybe mathematicians haven’t read/heard enough good social science , but I think we should take this accusation seriously just in case it’s true].

Part of this third layer of data is text (i.e. sociologists talking to each other in writing, and mathematicians talking to each other in writing, i.e. publications). In publications, this is even more clear. The amount of hilarious gems, jokes and informal expressions in math papers (amidst the hard stuff that I don’t understand because I don’t know the math) makes reading sociology papers, in comparison, like trying to chew dry bread. I say gems and dry bread…but perhaps a better [though of course still imperfect] metaphor is that math papers are unabashed and unadorned, while sociology papers tend to be self-conscious and uptight. Just as mathematicians are more like children and sociologists are more like self-conscious teenagers [metaphor warning!]. Importantly, this does not mean that math papers are imperfect and sociology papers aren’t. Quite the contrary. Math papers never reveal the actual train of thought. They show a cleaned up version of the proof, usually achieved through retracing the proof’s journey in reverse order. All the intuitions have been erased, all the blind alleys undone, all the errors swept under the carpet. A math paper is very much a cleaned up, polished performance. But somehow, despite this despotic form / format, well written math papers manage to sound genuine. To be fair, well written sociology papers are also crafted. But maybe because we sociologists are more verbose – and because we are judged by the quantity of papers by our institutions? – it is rare to find a sociology paper which is written tightly and does not go on about boring stuff in a stilted language for too long. I have read good sociology/anthropology texts, and my math friends tell me they have read plenty of atrociously written math papers. So maybe I’m wrong with this observation. But I’m yet to be convinced about being wrong!

I’m deliberately not going to polish and clean this up just yet. I want to sit and think about whether the main argument makes sense and then get down to expressing it better. And the main argument is that math’s intrinsic, existential security fosters certain behaviours which, compared to the behavious fostered by the social sciences, seem less neurotic and less self-referential. Ultimately, mathematicians play with objects; ultimately, we sociologists play with ourselves.

* I say “sociology” as a shortcut. I don’t mean all of sociology but only the type that I am doing in this project. What I mean is qualitative sociology, extensive case study method, reflexivity, ethnography, similar to what Burawoy does here

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Why no one can “have it all”

“Our gilded expat cages”
(The photo is intended to represent the sexes…)

This is just one example of the many articles on the web right now which continue a one-sided discussion that will never have a solution until we stop pretending that *anyone* can be independent. The men are just as dependent as the women (and that’s true of all kinds of relationships, as well as about singles). The ideal of independence is unattainable because it is trying to answer a badly defined question. In my research about matheamticians’ careers, I have met a lot of academic couples, and academics partnered with non-academics. The same mechanisms as described in this short article are visible in academic careers, as well. Many more female academics who are in relationships with children tend to default to the housewife optio, compared to our male colleagues. My hypothesis is that there are several main culprits. These come in order of importance, with 1 and 2 being probably equally important, and 3 and 4 being contingent upon them. i would be very thankful if anyone shoots down any of my ideas or adds better ones!

1. the way gender roles within the household snd in the workplace are defined in contemporary Western society, and the way these definitions are adopted, un-challenged, passed on to children and perpetuated by (a) institutions and (b) both men and women. These gender expectations/roles/conventions are by far not obvious or universal across time and space! An example of a different gender role distribution is socialist and postsocialist Eastern Europe where the proportion of female scientists was, and remains (though to a smaller extent after 1989), higher than in the west. in fact, Germany is a very interesting one-country example where women born in the [former] GDR are socialised in a noticeably (though by far not completely) more gender-equal way of thinking. aS someone who grew up in Eastern Europe, and has been in the uK for 9 years, I am still often shocked by occasional day-to-day revelations of micro- and macro-gender inequalities I was never aware of.
2. The “scaffolding” which enables people to go about their daily lives outside of work. This includes but is not limited to transport infrastructure, healthcare, childcare and all stages of education but especially early-age education, family structure (extended families in one geographical locality enable more women to spend more time on paid employment), the urban landscape (a funny detail such as the preference for houses in the UK vs apartments in Germany makes UK cities much less dense in comparison, meaning more driving and less access to social spaces outside the work-home nexus, which in turn makes it more likely that one of the partners will stay at home with the children), parental leave laws and practices.
3. Historical inertia
4. Counterproductive initiatives! Small UK example: I don’t know how useful are all the “women in academia” events is the Athena SWAN initiative, though they are certainly very well intentioned. I am yet to be convinced that Athena SWAN is contributing, instead of taking up time and cluttering the debate space… I am pretty sure I am being unfair here and I really hope to see positive change brought about by this initiative… (i am just using this blog as a space to think aloud, so don’t take this particular statement as very serious). But a bigger German example is the law which requires university employers to employ the woman if there are two equally qualified candidates. This one seems both hard to implement and badly received by men and women academics, and in some cases creates a bad attitute towards any female academics employed anywhere because their colleagues begin to harbour suspicions of what they see as “unfair” appointment. This one also needs a more extended discussion, but I am sligtly more convinced of it than by my Athena swan comment above.

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being (a girl) in physics

Just stumbled across this lovely blogpost. Marion Erpelding, a professional physicist who, after a three year postdoc, left academia to devote herself to science communication ( and other more fun pursuits, talks about gender segregation in schools, and of the segregation of sciences from humanities on university campuses. This made me think of how important the physical landscape of science is. It also reminded me of my anger the other day when reading once again about gender stereotypes in science: these stereotypes which Marion’s post so nicely links to the physical landscape of a university campus. (And which are just as contingent, and hard, yet not impossible, to shift and rebuild!)

Brief and evocatively written!

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Girls, math, and bullshit

After 9 years in the UK, I’ve reconciled myself to the realisation that I will always remain a foreigner. When I’m stressed, like when speaking to my bank on the phone today, my spoken expression and listening comprehension skills in English go out of the window. If someone woke me up at night, I’d speak to them in Bulgarian (my native language), but if I were really fast asleep, it would be Russian (my mother’s tongue which I learnt first).  But what is especially hard for a social scientist is that I am unable to overcome some taken-for-granted ideas that I had before coming here, and get used to their opposites which should be obvious to me. This evening I’m reminded of one: women and maths. This stuff is doing my head in. Each time I read about it, I get a headache. You know that peculiar blackout feeling when you hear something that is either blatantly, in-your-face, unjust or untrue, or something whose premises are so flawed that it’s not even wrong. I get that each time I encounter the obvious, common knowledge that women and math don’t mix. I just found an article about Shirley Conran’s new project aiming to make maths attractive to girls by convincing them that it will help them manage their personal finances. The article had the awesome title “Math is a feminist issue”, and it linked to what must be a very interesting and useful new report on women and the fear of mathematics. I’m sure it’s a very useful report. I must read it for my research. But I am stuck with the pdf like a horse in front of a river. I can’t read it because just reading the chapter titles makes me wince:

“1 Why maths and maths ability for women matter 13

2 Why confidence about maths ability matters 19

3 How do we know that women fear maths? 25

4 Why is maths perceived to be innately male? 29

5 Being female 37

6 Women’s education in history and the place of maths within it 47

7 Attacking the Maths Myth that drives the Fear Factor”

Clearly, I must have grown up with a different Myth. I grew up with the conviction, supported by empirical observations, that girls are better at all subjects. I don’t know why. And because I never had a reason to question this belief at the time I was at school or university, now I’m finding it really hard to accept that things are so obviously not the case. I don’t even know if my belief was justified about Bulgaria in general, or about Bulgarian “elite” primary and secondary schools. I may not be. Maybe I grew up in a bubble (a bubble in which all but one of my maths teachers were women, like almost all my other teachers; and in which schoolkids who were good at maths were equally likely to be girls or boys, and those who weren’t were more likely to be boys).

But I like having grown up in a bubble. I like the fact that the obviousness of “girls don’t like math, girls are no good at math” pisses me off. The really painful thing is that with each new item of information on the “women and maths” subject, doubt and desperation trickle in. I fear the thought that, if I had heard of this at a younger age, this belief might have turned into a self-fulfilling prophecy, and would have made me worse at maths – and worse at believing in my own capabilities, talents and worth. I hate the thought that there are young people out there growing up right now who entertain the freaking insane belief that interest and talent in various parts of human culture may have anything to do with their genitals.

Even less rationally, reading stuff which generalises a whole gender into one box according to a negative criterion, such as lack of ability or fear, makes me uncontrollably angry. When you, as a woman, read something like this, you just can’t win. If you happen to be bad at maths or hate it, well, there, there, little darling, we said it first, women suck at math. If you happen to be good at maths or like it, then you are not a woman, you’re an honorary man. &%£$@£$&?{}$£% Rage is not a good companion to research. Imagine, my research isn’t even about gender, actually, it’s about all mathematicians regardless of their gender. Imagine how angry I’d be if I were actually studying gender.

Incidentally, most of the female professional mathematicians I have talked to say that they were never aware of a negative gender stereotype in relation to maths when they were little. When they did realise it (often upon arriving to university), it was not a pleasant realisation.Some say that they were aware, but consciously rebelled or ignored it.

Perhaps we ought to not just combat the stereotype, but also shield from it those young kids who are lucky to don’t know about it yet…at least until they are old enough to be brave and rebellious rather than conformist?

P.S. Upon rereading, this sounds like an unusually personal and non-rational research-related blogpost. Unprofessional pubic expressions of unpolished thoughts, tut-tut. But it will have not been in vain, if it helps me at least read that report which, I’m sure, has lots of interesting and depressing data…

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Semantic Scholar: the AI which, knows your field better than you (and a Short Rant to Science Policy-makers)

“What if a cure for an intractable cancer is hidden within the tedious reports on thousands of clinical studies? In 20 years’ time, AI will be able to read — and more importantly, understand — scientific text. These AI readers will be able to connect the dots between disparate studies to identify novel hypotheses and to suggest experiments which would otherwise be missed.

AI-based discovery engines will help find the answers to science’s thorniest problems.”

— Oren Etzioni

“Semantic Scholar” is a better idea than the REF. But wait, what do they have in common? Here’s what.  Semantic scholar looks through existing scholarship and lets you use it and build up on it. It may uncover an article which no one has read many years after it was published, and let a new researcher learn something. It helps cut through the bullshit – perhaps not in the best possible way, but AIs are work in progress and will surely evolve into cleverer versions. The REF, conversely, fosters the production of bullshit. Its existence scares scientists into producing more crap (sorry, dear colleagues) because that’s the way in which we, and our university departments, are assessed. We all know it’s a game, and some refuse to play it, but people in their early careers have more incentive to play along than to protest by producing fewer, better pieces of work – even though it actually is in our long-term interests, we are fooled by fear. And so we write, and publish, instead of thinking and publishing less, better stuff.

If I were a science policy-maker, I’d put my money on tools that facilitate tedious, or downright impossible, tasks such as sifting, navigating and organising existing knowledge and debates.  And I would leave scientists with a bit more freedom to actually think, be curious, produce ideas, hypotheses and sometimes even knowledge, and – very importantly – also to make mistakes in the process. Oh, and having access to jobs that last longer than a year or two before having to move continent with or without your significant other, or instead of deciding to have children, would help. But that’s another rant, perhaps for a future post entitled “If I were a science policy-maker”.

For more about Semantic Scholar, see:

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