Conducting cross-linguistic research on reading: First lessons learned from my experience with recruiting international collaborators

 

Admittedly, I have yet to publish any large-scale cross-linguistic study. Actually, I have not even completed data collection for such a study yet. Cross-linguistic research on reading is hard. It is, however, very important, as has been argued in a couple of high-profile publications in the last years (Blasi et al., 2022; Huettig & Ferreira, 2022; Share, 2021; Siegelman et al., 2022; Vaid, 2022). So, despite not having anything to show in terms of a successfully completed study, I thought I would share my experiences with attempting to conduct cross-linguistic research, and specifically, recruiting collaborators in very different languages and cultures. Perhaps this will be useful for my fellow anglocentric or eurocentric researchers, or perhaps some of the readers of this blog post will have some ideas or insights about open questions or how I should do things better in the future.

 

Cognitive processing underlying reading across languages has been a focus of my research since my PhD. I’m afraid that I did not particularly contribute to overcoming the focus, in the published literature, on English and its close relatives, given that in my thesis, I compared reading in English and German. Afterwards, although I did some work on statistical learning and meta-science, I have found myself returning to the topic of reading across languages, as this topic has always fascinated me. A few years ago, I got a grant from the German Research Foundation to compare single-word reading aloud in a handful of European languages. In addition to working on this study, I am currently hoping to extend this work beyond Europe, and have by now reached out across a number of countries and continents to collect data in orthographies that, to date, we know relatively little about (relative to English, at any rate). For the purpose on this current blog post, I would like to talk about some of the challenges that I have come across. I don’t want to provide a list of all of the languages and countries where I have (successfully or unsuccessfully) approached potential collaborators: I don’t, by any means, want to imply that the challenges reflect anything bad, but I still prefer not to publicly map any of the challenges that I have experienced to any specific culture.

 

In conducting cross-linguistic research, finding collaborators is the first step. For pragmatic purposes, you need someone to recruit participants and co-ordinate the data collection. You also need someone who knows the language in question: Even if you are working with an amazing, high-quality corpus, you need someone to check your stimuli and remove any items that may be inappropriate for whatever reason (e.g., years ago, I heard a story about a non-English native speaker running a study with English-speaking children who had to get the “pseudoword” C*NT removed from her list of stimuli). You need to check if your instructions have been translated correctly, and if they even make sense. And, importantly, involving speakers of the language in question will allow you to identify aspects of the language that are of interest, but that may be so different from the features of your own language that you are not aware that they exist (Schmalz et al., 2024).

 

So, how does one go about finding collaborators? It is easy if the language is sufficiently well represented in your research community that you can approach people at conferences, or email researchers who have already published studies on your topic of interest in their respective language. However, the less well-represented the language is, the more difficult it becomes. I don’t want to pretend to know the best solution, but rather want to summarise the challenges that I have been facing, and some completely subjective thoughts about how to approach certain situations. Of course, international researchers are as diverse as the languages that they speak, and so are the cultures within which they live and work. Thus, the challenges that I list do not apply across the board, and other challenges may appear in different contexts. But as far as my experience goes, these are some considerations that I’ve come across:

 

1) Cognitive science is not established as a science everywhere. I study how children learn to read, what makes it challenging for them to read, and how reading works in adults. If I rattle off this elevator pitch, everyone, no matter their background, gets some idea of what I’m doing. However, the study of reading is not considered a science everywhere: In many places, the topic falls under “humanities”, and the attitude towards understanding how reading works may differ from our approach, which involves cognitive theories, computational models, and rigorous empirical testing. This may lead to some confusion about what it is that I’m doing exactly, and differences in our ideas about how to do experiments. I don’t have a solution to this, but have concluded that it is important to gauge in advance to what extent a collaborator is open towards a cognitive approach. After all, while there is value in more qualitative approaches, this just isn’t my expertise or research focus. Nevertheless, it is important to bear in mind that there will always be some differences in the scientific approach: After all, differences tend to increase with geographical distance, and unless your proposed collaborator has spent some time in the same lab as you, they will have different ideas about best practice in research. Incorporating fresh insights from their side will take your research to the next level.

 

2) There are cultural differences in communication. These go beyond the stereotypes that one may think of: when I started a large-scale international collaboration, I found myself wondering if I will need to give different deadlines to different countries to make sure that everyone will submit their work by the actual deadline; however, the speed at which the collaborators completed the task was not at all related to any stereotypes. Instead, one striking example of cultural differences was in providing feedback. Some cultures are more straight in providing feedback (e.g., “This is wrong, you made a mistake” vs. “I’m sure I’m missing something, but I’m wondering if you have considered the possibility…”). In addition, in some cultures, people might not want to express any criticism at all, whether it is because they assume that you know what you are doing, or that it’s your responsibility to take the consequences for your own mistakes (i.e., that you’re an idiot, but that’s none of their business), or because they see you as someone whose authority should not be challenged. In other cultures, people cannot stand watching someone else doing something that they consider wrong without providing unwanted advice or a not very diplomatic commentary (I’m guilty of this myself, and I blame my German half for this).

 

Then there are more subtle differences that may come across as rude or inconsiderate, without us even being able to put our finger on them. The way we address people when writing emails is very variable, with many personal pet peeves and cultural differences. Some people may automatically put an email to the spam folder if it addresses them without mentioning their names; in some cultures, starting an email with “Dear colleague” is considered very polite. Perhaps you have received emails from international students with unconventional formulations – I strongly encourage everyone to look past their personal pet peeves and potential spelling mistakes in their names, and respond to each email, taking the time and respect that they would show any other colleague. After all, a student enquiring about the possibility of doing a research thesis with you may be your international collaborator tomorrow, regardless if you are able to help them at the time.

 

3) Bureaucracy. Communicating with cross-linguistic collaborators has been stimulating, insightful, and fun. I can absolutely not say this about my local administration. If you have some funding for cross-linguistic research, you need to consider the bureaucracy that goes into transferring that money abroad to your collaborators. In my case, my local university’s administration stalled this process for over two years, because the relevant department is chronically understaffed. Maybe you are lucky and things are different at your department. But in any case, it may be worth doing some research about the relevant procedures in advance, and plan a very, very generous buffer in your planning. None of my collaborators’ universities have taken as long as my own institution to process the paperwork, but even here, processing times have varied, especially if any action was required at the time when most people in the country were on holidays (obviously, the timing and duration of the university holidays vary).  

 

4) Language is more than just language. You might be super enthusiastic about a language that you are about to examine. But the native speakers of this language are very likely to have a deeper attachment to the language. For example, maybe their language is a part of a cultural identity that was historically repressed. Maybe I am stating the obvious (though I call myself a psycholinguist, my background and education are in psychology, not in linguistics). Nevertheless, it is important to treat each language with respect and to be mindful of people’s potential attachment to their language.

 

An example is a recent experience that I had in a non-academic context. When it comes to reading in Arabic, I know that there is some research showing the effect of diglossia: As most people in the Arabic world speak a dialect that has varying degrees of divergence from Modern Standard Arabic, they learn to read in a language that is different than what they learn at home. I mentioned this to an Arabic speaker, who started explaining to me why his dialect is the closest to Modern Standard Arabic. As it turns out, there seems to be (at least for some people) prestige associated with a dialect being closer to MSA, probably also for religious reasons. Being mindful of the importance that people (yes, researchers are people, too!) attach to their languages is important. At the same time, to avoid looking like you have a hidden agenda, it might be worth emphasising that you are neutral about certain aspects, and have a reason for studying a language that does not aim to either support or dispute a contentious claim.

 

5) People might be self-conscious about some things that you are not aware of. The previous point relates to attitudes that researchers may have towards their languages, but there may also be other beliefs and attitudes that may affect your communication with an international collaborator, or their willingness to collaborate with you. There may be some issues that have not even crossed your mind but that affect how a potential collaborator will evaluate you and your research proposal. If you are of European descent, people might be a priori suspicious about your coming in and pushing your own research idea. As an example, I once wanted to start a research project in collaboration with a country where multilingualism is the norm, and for reasons that have to do with colonialism, most people grow up with a language of instruction that is different from their home language. Unfortunately, that collaboration didn’t work out. In retrospect, I’m afraid that the reason for this is as follows: The way that I presented the project may have come across as wanting to show that it’s problematic that the people in that country study in a different language than they speak at home, or that people speak a different language than what is used at school and university. This was not my intention, as I genuinely believe that multilingualism brings nothing but benefits. It simply did not occur to me, at the time, that my project idea may be construed that way.

 

6) Political issues. Your research may be completely unpolitical, but unfortunately, political issues may affect if and how you can do cross-linguistic studies. For example, my funder no longer allows for its money to be used in a way that involves exchanging data with researchers based in Russia. Such sanctions affect collaborations on a formal level, even if all researchers involved share the same values as you, and might even be keen to build connections to escape an oppressive regime. If a project involves a collaboration with researchers in numerous countries, there may also be sanctions between the respective countries, and some may explicitly prohibit a researcher from Country X to collaborate with any researcher based in Country Y. If this is the case, you might end up with the dilemma: Do I exclude the researcher from Country X, the researcher from Country Y, or do I salami slice the project and make two separate publications out of it? The restrictions may be formal, issued by a funding body or university, but they may also be more subtle. Some people may be very nervous about being in contact with colleagues of a certain nationality, even in the absence of any official sanctions. From the outside, we cannot judge the extent to which this nervousness is justified. I see our role as trusting our collaborators, asking, when necessary, so we understand the limitations and boundary conditions, showing our moral support, and – above all – ensuring that we do not put collaborators into unpleasant or even dangerous situations.

 

On the personal level, my experience has been exclusively positive: Even when I’ve been working together with researchers whose home countries don’t get along at all, the individuals have been very respectful and friendly towards each other: as always, it is important not to assume that the actions of a government reflect the attitudes of the people.

 

The bottom line. All around the world, children start off with the same broad cognitive structures. The way that these structures deal with the different scripts and orthographies is a fascinating question, which we are only beginning to investigate systematically. There are certainly many reasons why the science of reading is focussed on English and its European relatives. Are researchers studying reading in English and other European orthographies reaching out to researchers abroad? My suspicion is that the answer to this question is “no”. A lack of experience with people from other cultures may be a major reason. In the past few years, I have worked with people from all continents aside from Antarctica, which has been a very enriching but humbling experience. Despite having started off as someone from a bicultural family and having lived on three different continents, I continue to learn from my international collaborators, both about how to be a better colleague and a better researcher. This is why I, despite being far from an expert on cross-cultural collaboration, have decided to write up my experiences. I hope that my experience report will encourage cross-cultural collaboration, increased awareness of things to think about when approaching or communicating with potential collaborators, and discussions about how to act in a culturally sensitive and open-minded way.

 

References

Blasi, D. E., Henrich, J., Adamou, E., Kemmerer, D., & Majid, A. (2022). Over-reliance on English hinders cognitive science. Trends in Cognitive Sciences.

Huettig, F., & Ferreira, F. (2022). The Myth of Normal Reading. Perspectives on Psychological Science, 17456916221127226.

Schmalz, X., Breuer, J., Haim, M., Hildebrandt, A., Knöpfle, P., Leung, A. Y., & Roettger, T. B. (2024). Let’s talk about language—and its role for replicability. https://osf.io/preprints/metaarxiv/4sb7c

Share, D. L. (2021). Is the science of reading just the science of reading English? Reading Research Quarterly, 56, S391-S402.

Siegelman, N., Schroeder, S., Acartürk, C., Ahn, H.-D., Alexeeva, S., Amenta, S., Bertram, R., Bonandrini, R., Brysbaert, M., & Chernova, D. (2022). Expanding horizons of cross-linguistic research on reading: The Multilingual Eye-movement Corpus (MECO). Behavior Research Methods, 1-21.

Vaid, J. (2022). Biscriptality: a neglected construct in the study of bilingualism. Journal of Cultural Cognitive Science, 6(2), 135-149.

 

Is Open Science passé?

I recently got a grant rejection - but I swear this blog post won't be whinging about rejections. Rather, I'd like to start by sharing a reviewer's comment that surprised me: The proposal is not novel, they wrote, because it's all about replicability and open science and blah blah blah, and we already know all about that since the Ioannidis 2005 paper, published almost 20 years ago now! Yes, I replied to the reviewer in my head. But have we actually solved this issue?

In a way, I understand where the reviewer is coming from. The other day, I opened the latest issue of the German academic journal, "Forschung und Lehre". On the first page was an article about the p-value, and how it doesn't mean what many researchers seem to think it means. "But we've been talking about that for decades now, surely everyone already knows this!", I thought and skipped to the next page. 

Today, I taught a workshop on Open Science for a masters programme. I've been doing similar courses for similar audiences for a number of years now. Every year, I show a slide with the results of the Open Science Collaboration (2015) replication efforts. "Who has heard of this study before?" I ask. I started teaching in about 2016, and found that most students, including bachelor students, were familiar with the study and its provocative results. Today, what I was presenting seemed to be new to many students. On the one hand, that's good for me - I was able to tell the students something new, rather than repeating things they already knew, anyway. On the other hand, I wondered, do people not care about replicability any more?

The Open Science community, at the beginning, was a close-knit group on twitter. My reputation in academia (such as it is) is largely thanks to this community: from the beginning, I was active by tweeting and writing blog posts about Open Science, and within the community, such posts were spread widely. However, long before this community was scattered across various alternative platforms such as Mastodon and BlueSky, it had grown into fractions that spent a lot of their time fighting each other. Fashions come and go - I have learned that in my teenage years, after which I made the conscious decision to ignore all clothing trends. So maybe Open Science is just not cool anymore.

This raises the question: Has the open science movement failed in it mission to improve science? Or, on the contrary, did it solve the issues so efficiently that it is no longer needed? The first scenario is, unfortunately, more likely. I myself am guilty of having been too dogmatic and over-simplifying, in my mind, the ways in which Open Science can, and should, improve science. But has Open Science really unleashed its full potential in improving science? I sincerely believe that this is not the case. I feel like the discussions about how Open Science works and, indeed, what outcome we want to achieve, is only just starting to take shape. Many questions remain, such as: What is important for good research? Via what mechanisms do Open Science practices impact the research quality (positively or negatively)?

This blog post, again, has more open questions than answers. So, dear Reviewer 2, if you're reading this blog post: When you review proposals involving reproducibility and Open Science, please don't reject them on the basis that we already know everything already.

Why working as a postdoc under WissZeitVG is not compatible with family: An experience report

I had to force my hand to sign my last work contract. A work contract for 12 more month, plus an additional document with a justification that my activities will contribute to my further qualifications, so that the contract can fall under the Wissenschaftszeitvertragsgesetz - a blatant lie, as I've already finished my habilitation, the highest qualification one can achieve. I bit my tongue, knowing that any cynical comment from my side would achieve nothing but ruining the day of the admin lady. I left her office, not feeling happy, as I previously had whenever I signed a contract that enabled me to get paid for doing what I love. My main thought was that I'd drawn yet another line in a perverse game of hangman. 

The Wissenschaftszeitvertragsgesetz - WissZeitVG - limits the amount of time that one can work as a postdoc. One has 6 years to either get a professorship or to quit academia. Of course, it's not easy to get a professorship at all, let alone one that doesn't require the uprooting and moving of the whole family. Having a realistic chance of a professorship comes with a lot of pressure to publish and get grants. Additionally, in my case, all of my salary - and that of my PhD students - is paid from grants. This puts existential pressure to receive even more grants. At the same time, of course, don't neglect the publications, which you need not only to get a position, but also to get more grants. In short, a vicious cycle. 

Even without the additional factor of family, being in a senior postdoc position seems incompatible with doing high-quality research: I have to write strong, innovative grants, but don't have the time to write proposals that are strong enough that even I myself find them convincing. On top of that, I have to work on my ongoing project and publish as much as possible from them. Add to that the standard admin tasks, and one ends up with a bunch of half-finished projects and very little time to drive any of them forward.

I used to take pride in my ability to work efficiently. I didn't think that having a child would make a huge difference to this ability, but it does. I returned from parental leave after only 4 months. I gradually increased my working hours to 80%. In reality, I work more than that, but I still get less done that I would have BC (before child). I think what I miss most is having a large stretch of time. Now, it is no longer an option to spend all of Saturday working on a paper, or to stay in the office till 8pm to finish writing a grant section. It just isn't. And that seems to make the difference between working in a demanding, but fulfilling job, and constantly feeling like one is failing at juggling with raw eggs. 

On the surface, these may seem to be unrelated problems - working in academia is hard, and being a working mum is hard. Academia has never been a walk in the park, but I don't make choices in life because I want to make things easy. Why I came to the conclusion that family life and working under the WissZeitVG is incompatible for me is that my productivity took a large hit - precisely at the time when I have to work harder than I ever did to have any chance to climb to the top. I'd love for someone to tell me: "While you have a small child, you *won't* be as productive as you were previously - and that's OK!" But it's not OK - because by the time he'll grow up and I'll be able to return to my previous levels of efficiency, I'll have been kicked out of the system a long time ago by the WissZeitVG. 

I made a decision after I'd signed my last work contract: I will never sign another contract under the WissZeitVG again. And if this means I'll have to leave academia, then so be it. The alternative would be to stick around for yet another year, again and again, apply for more grants, hoping that something will come along. Maybe I'd win the lottery, but maybe I wouldn't. And in the meantime, I wouldn't have any time to do what I love, anyway, which is producing research of a quality that I'm happy with.

Like a love-sick teenager, I can't help but wonder: Can this really be it? How can it be over when it was so nice while it lasted? Would I give academia another chance if it wants me back? Of course, if I got a permanent position, the equation would change. But at some stage, the conclusion that some things are not worth it becomes inevitable.

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.