## How to study

I was reading this article on how to study. The article provides great advice, such as space out your study sessions and rely on retrieval practice. That made me reflect upon my own approach to studying and how it has changed over time. When I started studying (many years ago now!), I read every single word in every text to make sure I did not miss out on anything important. I read the text from A to Z, from the first to the last page (not including the list of references).1 However, this took a very long time and was definitely not a sustainable strategy.

Luckily, I found out that it was not only a waste of time to read everything, but also not the best way to engage with all the material. In the years where I was teaching, I gave a lot of students advice on how to study, and I told them again and again that what is important to learn is how to study rather than the specific content in the curriculum. Teach a man to fish and what have you.

Today, what I find interesting is the need to move from our traditional understanding of literacy to that of digital literacy. In brief, studying today is radically different than studying, say, 20 years ago. The table in the article From Written to Digital: The New Literacy covers the key differences between the two well:

This is not to say that reading is not important. It is. But when you study, you should focus on reading beyond the text at hand. Think about how it is connected to other studies, papers, books, ideas, etc. The important thing is not what you get out of a text – but where you store what you get out of it.

Time is a limited resource and you need to optimise your reading. I truly believe in slow reading, and the more time I spend with a text, the more time I will not only spend processing each paragraph, but also think about connections and implications. Books are like meals. You do not remember every aspect of any meal you eat, but they have an impact on your thinking, and you need to be very cautious with what you put into your body/brain. However, when studying, you cannot spend too much time with the same text as the marginal return will quickly decline.

So, how should you study? There are (at least) five different study strategies, namely (re)reading, highlighting, note-taking, outlining and flash cards (Miyatsu et al. 2018). I don’t think one strategy is intrinsically better, so I think it is more a question of finding the strategy that suits you best. Putnam et al. (2016) provide a set of specific strategies for how to optimise learning that are worth considering (from Table 1 in the paper):

• Study for a little bit every day, rather than cramming in one long session.
• Start studying early, and touch on each topic during each study session.
• Reading before class and reviewing lecture notes after class will help consolidate what was covered in class.
• Instead of writing a chapter summary as you read, write down what you remember after you read, recalling the details from memory. Then, check to see how well you did (the read-recite-review method).
• Answer the “end-of-chapter” questions both before and after you read a chapter.
• Use flash cards to learn key vocabulary. Retrieve the idea from memory (before looking at the answer) and use a larger (rather than a smaller) stack of cards. Put answers you missed back in the deck at an early place and the ones you got right at the end. Finally, aim to recall each item correctly multiple times before taking a card out of the deck.
• Be skeptical about what you think you know—testing yourself can provide a better picture about which concepts you know
well and which you might need to study further.
• Get the most out of your class sessions.
• Attend every class session.
• Stay focused during class by leaving your laptop at home; you’ll avoid distracting yourself and your classmates, and you may remember more by taking notes by hand.
• Ask your professor for a copy of any PowerPoint slides before class, so that you can take notes directly on the slide handout.
• Finally, write some of your own questions about tricky concepts: “What is an example of X in real life?” or “How is Theory X different from Theory Z?”
• Other general tips.
• Get organized early in the semester: Put major due dates and exams on your calendar, set reminders to get start studying early, and be sure to look at your calendar at least once a week so you can plan ahead.
• Get some exercise. Going for a 50-min walk in nature can enhance your ability to focus on difficult tasks.
• Sleep! Sleeping is critical for ensuring that memories are successfully stored in long-term memory.

There are different ways to study, and my own challenge over the years has primarily been one of finding the motivation. Interestingly, the motivation to study for me personally is often stronger when I have studied. For example, when I have accomplished something, my motivation to keep going is stronger. When I completed a module, my motivation to read through the papers and books again was stronger than prior to taking the module. I guess what I am trying to say is that finding a good way to study is not easy, and whatever works for you … works for you.

1. Ironically, today, I primarily consult the list of references when I read academic texts before actually reading anything beyond the title and abstract. []

## Updating the replication material for “Welfare Retrenchments and Government Support”

In 2017, I pushed the replication material for my article, ‘Welfare Retrenchments and Government Support’, to a GitHub repository. I had been working on the article for years and the code was not necessarily up to date. It worked perfectly, gave the exact estimates and was relatively easy to read. Accordingly, everything was good, life was simple and I felt confident that I would never have to look at the code again.

This turned out not to be the case. I recently got a mail from a student who was unable to get the exact estimates as reported in Table 1 in the paper, even when following my script and using the data I made publicly available. I went through the code and I noticed that I could not reproduce the exact estimates with my current R setup. Sure, the results were substantially identical but not the exact same – and the N was also different.

I looked into the issue and I could see that changes were made to the defaults of set.seed() in R 3.6.0. As I ran the original analyses in R 3.3.1, and I am now using R 4.1.0, this could explain why the matching procedure I rely on is not returning the exact matches. For that reason, I decided to make some updates to the replication material so there now is a dataset with the matched data. The script is doing the same as before, but it is not relying on the matched data obtained with the setup in R 3.3.1. This should make it a lot easier to get the exact same estimates as provided throughout the paper.

To increase the changes of long-term reproducibility, I should consider using packrat or a Docker container (I primarily use Docker for my Shiny dashboards). However, as the analyses are mostly a few OLS regressions, I believe this would be overkill and would not necessarily make it easier for most people to easily download the data and script and play around with the results. And I don’t mind making extra updates in the future if needed in order to reproduce the results with different setups.

Interestingly, I did all of these analyses before I doubled down on tidyverse and for that reason I decided to make a series of additional updates to the material, including:

• More spaces to make the code easier to read. For example, instead of x=week, y=su it is now x = week, y = su.
• The use of underscores (snake cases) instead of dots. For example, the object ess.matched is now ess_matched.
• A significant reduction in the use of dollar signs (primarily by the use of mutate()).
• The use of pivot_longer() instead of gather().
• No double mention of the variable edulevel in the variable selection.
• Removing the deprecated type.dots argument from rdplot().
• The use of seq(0.01, 0.25, 0.01) instead of having 0.01, 0.02, 0.03, 0.04, etc. all the way to 0.25!
• The use of map_df() instead of a for loop.

And a series of other minor changes that makes the code easier to read and use in 2021. I have made the updated material available in the GitHub repository. There is a revised R-script for the analysis, a dataset with the matched observations and a file with the session info on the current setup I used to reproduce the results.

I have started using the new native pipe operator in R (|>) instead of the tidyverse pipe (%>%), but I decided not to change this in the current version to make sure that the script is also working well using the version of R I used to conduct the analysis years ago. In other words, the 2021 script should work using both R 3.3.1 and R 4.1.0.

I also thought about using the essurvey package to get the data from the European Social Survey (we have an example on how to do that in the Quantitative Politics with R book), but I find it safer to only work with local copies of the data and not rely on this package being available in the future.

In a parallel universe a more productive version of myself would spend time and energy on more fruitful endeavors than updating the material for an article published years ago. However, I can highly recommend going through old material and see whether and if it still works. Some of the issues you might encounter will help you a lot in ensuring that the replication material you create for future projects are also more likely to stand the test of time.

## 33

Thirty-three. Another year, same me ±95% CIs. One third of a hundred, give or take.

I read the post I wrote last year when I turned 32. It all seemed so recent. I could, in principle, repost my thoughts from last year and call it ’33’. There is not much of significance, if anything, to report on in my life now that I am 33. However, especially in the context of COVID-19, I guess it is a point in and by itself. It all feels like ‘no news’. It is the experience of waking up one morning and suddenly being a year older. One year of the one life I have to live. Definitely not a year wasted, but not a year “lived” either.

Of course, I have lived another year. In the grand scheme of things, I seriously cannot complain even one bit. I am very much aware of my privileges. I have had a lot of great experiences. I have not had any major setbacks. I have never worked this much. I have never relaxed this much. I have never read this much. I have never written this much. Et cetera. Maybe that’s the reason I felt like this year just … happened?

When I was younger I used to assume that the lifespan of a human being was 100 years, or, that my lifespan would be ~100 years. I knew that most people would not live to be 100, but it made sense to use 100 as a heuristic. That is the only way 33 stands out. 1/3 of 100. Based on the ONS ‘Life expectancy calculator‘, the average life expectancy for a 33-year-old male is 85 years. In other words, 52 years left (meaning that I – all else equal – have lived more than one third of my life now). My chance/risk of reaching 100 is 6.9%. Not 7.0 or 6.8%, but 6.9%:

This is ceteris paribus. With that in mind, I like the 6.9%. However, at this point, I don’t think I can do a lot more to increase my life expectancy at the margins. I live (relatively) healthy and there are no additional low-hanging fruits. What I can do is to have a subjectively longer life. Time seems more subjective as I get older, and if I had to live the rest of my life in pandemic mode, it would feel relatively shorter. New experiences – such as travelling – will make my life subjectively longer. In other words, to make my life as long as possible, I need to plan it in ways that feels longer – not by visiting the gym more often and eating less meat.

That being said, I am not sure I can do a lot. I can’t escape the fact that life, for the most part, is the day-to-day experience, and some days I feel like I am second-screening ‘the real life’. Getting shit done and calling it a day. Or as Stig Johansson formulated it, “All those days that came and went, little did I know that they were life.”

I am taking it for granted that people experience a lot of significant changes in their lifetime, such as technological and societal developments. It was only when I read the following passage from Matt Ridley’s book, How Innovation Works, that I got to think about how this is the exception rather than the norm: “Before the last two centuries, innovation was rare. A person could live his or her whole life without once experiencing a new technology: carts, ploughs, axes, candles, creeds and corn looked the same when you died as when you were born.”

I have lost count of the new technologies that have seen the light of day since I was a kid. Even at the age of 33 I have experienced a lot more new technologies than my ancestors experienced in a lifetime. This and the fact that the average life expectancy was, historically speaking, much lower in the past, made me conclude (yet again) that I should not complain. I have on all accounts already had a longer life, both in objective and subjective terms, than what most people could expect to experience in the past. I guess that puts history in perspective.

I remember watching Good Bye Lenin! in the cinema in 2003. That is 18 years ago now. The movie came out less than 14 years after the fall of the Berlin Wall. That’s weird to me. I was closer to the historic event depicted in the movie at that time than I am to me watching the movie for the first time. At some point in the future, assuming I get to live to I am 75 (the odds are good!), the events depicted in Der Untergang will be closer to when I first watched the movie than the time that has passed me since then. I guess that puts history in perspective, too. I was also reading this article in The Atlantic that makes it clear that 2050 is closer to today than 1990, and significant changes to the climate will happen within our lifetime: “A child born today won’t enter the professional workforce until 2043; under the current timeline, decarbonization will be just about licked by the time they turn 30. Their job will be to live with climate change: They will see Antarctica’s crucial 2050s in the prime of their career.” Damn.

Well, for now we can focus on the present. The pandemic as we know it is (hopefully) over. It has been a weird year and a half, and I definitely lost faith in multiple things during the pandemic. Shaking hands, airports, the United States (or, whatever faith that was left), nine to five, time more generally, John Ioannidis, menu cards, etc. However, there is at least one thing I have gained faith in during the pandemic: QR codes.

What’s up for the next year? I don’t know. More of the same, I guess. I don’t have big dreams and mountains to climb. I definitely don’t seek or need fame – or convince the world of my individual brilliance. More importantly, I really enjoy working within a great team. In general, at least in my case, I believe reliable consistency beats occasional brilliance. However, my biggest fear is still to be complacent, especially because that is what I gravitate towards.

All this also confirmed that it was a good move to leave academia. Actually, this has been the first full year without an academic job since I got my PhD. I found it surprisingly easy to give up a permanent academic position and I have not considered even once looking into ways of getting back. None of my parents are academics, and I never had the feeling that being an academic was part of my identity. More importantly, I do not look at my academic friends and see lives that inspire me. That’s totally fine. I am sure it is great for a lot of people, but it did not do it for me. I also found John Williams’ Stoner depressing when I read it years ago and I doubt that would change upon a second reading.

More than anything, I enjoy that I am 33 and not 23. I don’t miss being younger. As I get older, I am quite confident that I will develop certain peculiar quirks (as most people do). Hopefully, I can do that with a certain level of open-mindedness and self-awareness. The good thing about getting older is that I am much more selective in terms of what I spend time on and what I care about. I do not let trivialities live rent free in my head to the same extent as I did ten years ago. I think I think a lot more about what I think about. What do I remember? What do I forget? I obviously don’t see hyperthymesia as a good thing, or even an option in my case, and I don’t want my memories to be a random sample of what I experience – but a carefully curated selection (to the best possible extent).

The bad thing about getting older is that it will be a slow process characterised by physical and cognitive decay, at least at some point and to some extent. The body I am in now will be the body I have to stay in when I am 43. Accordingly, I have to prepare for my 40s in my 30s while still enjoying my 30s. And I have to do that in a way that I did not have to do when I was in my 20s. I have to hit the gym and think about exercise in a different way. I am not there yet, but I could sympathise with, and maybe even relate to, the following lines from one of my favourite albums from 2020, Open Mike Eagle’s ‘Anime, Trauma and Divorce‘: “Started doing more pushups, back pain when I look up/ taking down what I put up, knee hurt when I stood up”. I had a few osteopathic appointments this year – not because I needed it, but because I want to do what I can to make sure that I will not need it in the future.

To reiterate what I said in my previous post: I write this for nobody but myself. I write this primarily to have something for myself to go back and read in the future. In some ways this is pretty similar to the FutureMe service where you can send a letter to your future self. I read old blog posts and I don’t recognise the person writing them, and I fear that if I don’t write a post like this, I will not be able to recall what was on my mind at a certain point in time in the future.