What's wrong with science?

I think I really need a holiday. 

Many of us are researchers because, in some way or another, we want to make science better. Yet, we rarely keep this goal in mind explicitly when planning a specific project. If we do, how would a research project look like? This seemingly simple question sent me on a downward spiral: What could I do that might really make a difference? Where do I want to make a difference? And why? And what is good science, anyway? Or science, for that matter? What is the purpose of it all? What am I doing with my life?

I spent Thursday afternoon ("Is it Friday yet?") quizzing my new friend, ChatGPT. Although ChatGPT was reluctant to answer the question "What am I doing with my life?", we had some interesting discussion about science and everything that's wrong with it. Setting aside existential angst, the three relevant questions are: (1) What is (good) science? (2) Which are some aspects where we still need improvement? (3) In the current discussions on how to improve science, how do the proposed solutions that are on the table relate to the aspects that need improvement? 

To summarise ChatGPT's response to the first question (phrased as "What is the aim of science?"): There is a list of eight goals:

1. Explanation
2. Prediction 
3. Understanding causality
4. Falsifiability
5. Reproducibility
6. Continuous improvement (self-correction)
7. Application and innovation
8. Unification of knowledge.

Some of these points may be contentious (is prediction without explanation really science?), but overall, it sounds at least reasonable. 

As a next step, I asked the less nuanced question: "What's wrong with science?" Again, ChatGPT provided a list of eight items:

1. Reproducibility crisis
2. Publication bias
3. p-hacking and cherry picking
4. Funding and conflicts of interest
5. Lack of diversity and inclusivity
6. Ethical concerns
7. Hypercompetitiveness and pressure to publish
8. Miscommunication and sensationalism.

So it seems that my social media bubble is representative of a broader population, or in any case, of ChatGPT's training data. All of these are important challenges that need to be addressed. For an ambitious researcher trying to make the world a better place, the question remains: What are still some gaps that might not have been addressed yet? 

Broadly, the aims of science according to ChatGPT can be divided into methodological/technical and theoretical aspects. Reproducibility, self-correction, and application and innovation fall into the former category. There are clearly things that are wrong on this technical level: The reproducibility crisis, publication bias, p-hacking, funding and conflict of interest, pressure to publish and miscommunication all relate to this. To put it bluntly: Given these issues, when one reads about a given finding, one is simply not sure whether this finding can be trusted or not. Without a doubt, this is the first general problem that needs to be tackled: I'm a firm believer of never trying to explain something unless one is sure that there is something to be explained (see my first ever blogpost).

Having replicable, reproducible, robust, and generalisable effects is still a far cry away of achieving the more theoretical aims of science. Sure, knowing that two variables correlate is useful for prediction, but just knowing that this correlation exists tells us nothing about the explanation or causality, nor does it allow for a unification of knowledge. A lack of diversity and inclusivity prevents us especially from achieving the goal of unification of knowledge, because it excludes many varying perspectives from the scientific discourse. Ethical concerns are an issue on the more basic level - these should be considered even before asking questions about methodological or technical aspects of a study. This still leaves us with a gap, though, between having a robust finding and making sense of it.

Of course, linking results to theory is not a novel question. Just in the last few months, I've come across this preprint by Lucy D'Agostino McGowan et al, and this blogpost by Richard McElreath. Still, in seeing how we do science in real life, I see room for improvement on this front. It's relatively easy to provide easy-to-follow rules for showing that your finding is credible (or, at least easy-to-follow-in-principle, if you have unlimited resources). It's more difficult for the less tangible question of linking your finding to an explanation.

The good news is: My summer holiday is starting next week. The bad news is: I'll probably spend it pondering and researching all of these questions.

A rant on bilingual books for toddlers

My toddler is growing up in a linguistic environment that I call multilingual and some people tell us is "confusing". Growing up with multiple languages is, of course, the norm in many places, and has the positive side effect of children being able to speak more than one language by the time they grow up.

Given my convictions about the benefits of growing up multilingually, I was excited to find bilingual books for toddlers: Picture books with picture names or stories written in two languages. Identical books exist for different languages that are commonly spoken in Germany, such as German/Turkish or German/Arabic. I ordered some books in German/Russian. I would like to note that they were absolutely not cheap, but I love books, I love languages, and I love my toddler, so I figured it's worth it. 

I was disappointed when the books arrived. They were just so obviously written in German and probably google-translated into Russian. There are some blatant grammatical mistakes (it should be "нет", not "не"):

I'm pretty sure this is not even Russian*:

 And things that are linguistically awkward:

(Grandmother, grandfather, and ... grandmother and grandfather.)

Can I blame these books for being, basically, really bad teachers of the Russian language? I guess not, if we consider the probable reason why these publishers publish the books: To teach children with a migrant background better German and integrate them into German society, rather than to support their knowledge of a foreign language. 

And yet, isn't it also very important, for an individual, to have the possibility to retain ties to their culture of origin and to their family members who might not speak German? And for the society, isn't it important to have individuals who speak multiple languages, especially such languages that are spoken by a substantial number of people in Germany? 

And would it really be so difficult to find a Russian speaker in Germany who would be able to write a good translation?

* Edit: So it seems I didn't do enough research before publishing the blog post: "Витать в облаках" is, indeed, a Russian expression that I didn't know (https://ru.wiktionary.org/wiki/%D0%B2%D0%B8%D1%82%D0%B0%D1%82%D1%8C_%D0%B2_%D0%BE%D0%B1%D0%BB%D0%B0%D0%BA%D0%B0%D1%85). Just shows the potential that these books have: to also teach new expressions to mummies and daddies.

References

 I don't want to name-and-shame (because the general idea behind the books is amazing, and I would like to thank both the publishers and authors for taking the step of publishing such books!), but my academic background dictates that I name the sources from which I took the pictures above:

"Wie schön!/Как здорово!" by Petra Girrbach/Schmidt & Cornelia Ries, publisher Bi:Libri

"Bildwörterbuch für Kinder und Eltern Russisch Deutsch", no author listed, publisher Igor Jourist

On graphomania

As we're moving flats soon, I threw out a pile of papers, about half a meter tall when all stacked up. I've accumulated these papers over the last 6 years that we've been living in our current flat. They include different types of papers:

1) Papers that I started reading but then realised they weren't as relevant or interesting as I thought.

2) Papers that I printed because the title and abstract sounded (and still sound) fascinating - but as I haven't read them while they've been lying around for years, I should give up on my wishful thinking and acknowledge the fact that I will probably never have the time to read them.

3) Papers that I've read but mostly forgotten about.

If it sounds discouraging that, as part of our academic jobs, we don't really have the time to read papers, it gets worse when you consider the implication that our very own papers are probably getting treated in the same way. Indeed, I have found that I myself am starting to forget what I wrote in various papers where I'm the first author. For example, I spent hours writing a discussion section for a paper I'd started writing months previously, only to discover that past me had already incorporated most of my arguments and examples in the introduction section! 

Of course, this is not a new problem, and I'm not the first one to talk about it. Dorothy Bishop wrote a more detailed blogpost with more than anecdotal observations here: http://deevybee.blogspot.com/2020/01/research-funders-need-to-embrace-slow.html. Here, she basically showed that a researcher studying autism and ADHD would need to read about 8 papers a day to keep up with all the new literature in the field (assuming they're already up-to-date with all papers that have previously been published). 

The reason why I'm writing so much is also obvious. I need publications so that I get a job and so that my department gets money. And yet, as much as I love writing, and more generally, working as a researcher, I wonder if there isn't a better way to spend my time, and hereby the taxpayers' money that is paying for my time...

In the meantime, I'll try to practice the art of minimalist writing.

New Year's Resolutions of an Early-Mid-Career Researcher in Germany

Three years ago (before COVID and the birth of my now toddler, which have put my academic life on hold in some ways), I wrote a New Year's post summarising my year and my new year's resolutions. Though I see it as a kind of superstition, I still like to take this time of the year to think about my achievements so far, and about what I need to do next to get where I want to get (and, of course, about where I want to get in the first place). In some years, it's easy: it is clear what I need to focus on. In other years, it's hard: Either there are too many things to focus on, or I decide that, actually, everything is going well, and I don't need to change anything. This year, it's hard in a different sense: It's not really clear what I can do to get any closer to my goals. 

My current position is not untypical for an early-to-mid-career researcher in Germany. In some ways, it is clear where I need to get to. The goal for most researchers here is a professorship. The timing is clear, too: there is a limit on the number of years one can work as a postdoc (a controversial German law, with a beautiful compound word for a name: Wissenschaftszeitvertragsgesetz). This means that I need to get a professorship (or other permanent academic position) within ca. 2 years, or else leave academia. Getting a permanent position would be good in any case, when trying to lead a stable family life and after having taken out a mortgage for a flat. Professorship positions are very competitive, especially if you are not too flexible with moving to a different city and even more so if the city where you would like to stay is Munich. 

With the high competition, finding a way directly to a professorship (i.e., applying for a professorship position and getting it) is very unlikely. The professorship application process is rather intimidating, and relies a lot on insider knowledge from other academics ("hidden curriculum"). The procedure is often not very transparent, so it is difficult to know just how far I am from getting shortlisted or even selected as the winner. The alternative is to try some other things to increase the probability of getting a professorship. This includes applying for prestigious grants or publishing high-profile papers. At some stage, my university guaranteed a professorship to any winner of an ERC Starting Grant, but they have now cancelled this policy. Some funding bodies allow one to apply for financing for a professorship position, but this requires the university to commit to paying the new professor's salary after the end of the funding period. In any case, applying for prestigious grants in itself is very competitive, so to increase the chances here, one needs to apply for less competitive grants and publish papers. In short, one just has to repeatedly try various things that cost a lot of resources and have a relatively low chance of success. This does not lend itself as a good new year's resolution, because there is no single action that I could commit to doing, either as a one-off or as a repeated activity.

Of course, my ambitions are not simply to get a professorship for the sake of getting a professorship, but primarily I would like to continue with my research agenda, and getting a professorship is one of the not-so-many ways to do this. Having a stable job to build up my research team is a necessary condition for doing good research, but it's not sufficient. There are skills that I still need to improve to keep up-to-date with the best research practices. Picking a skill to improve would be a good new year's resolution, but it may not help me to get any closer to a professorship position. Such skills could be learning a new language or improving my programming skills, for example, by learning more about Natural Language Processing. If I pick one such skill to focus on in 2023, I may find that I'll have to abandon it, because it will be more advantageous, in the short-term, to focus on writing a paper or grant proposal. On top of that, I also somehow keep my head above water with student supervision, family life (which I will not compromise on), and bureaucratic duties (unlike the former two duties, something that I don't enjoy doing at all but that keeps increasing as I progress in my academic career). Keeping my head above water could be a good new year's resolution, but - well - it sounds a bit depressing.

With what I have written above, some (myself included) might wonder if my ambitions are too high. In the German system, an academic career is almost an all-or-none affair (leaving academia vs. becoming a full professor, who, in Germany, have a lot more freedom and power than professors in many other countries). There are options in between a professorship in Munich and leaving academia, though. These include: applying for professorships at universities outside of Munich (which would be an inconvenience, but not a disaster for my family life), though these are also very competitive. There are non-university tertiary education institutions which hire professors, but I've heard that there is such a high teaching load that, in practice, there is just no time for research. There might be research positions outside of universities that could interest me, though I haven't found anything convincing yet. Maybe I should make it my new year's resolution to decide what I really want, and whether my ambitions are realistic. But this kind of decision is likely to change a lot, with incoming information, such as future successes or failures, and is unlikely to be completed by the end of the year. 

In the end, I think I'll just stick to eating more vegetables as my new year's resolution for 2023.