How I work, Part V: Zettlr and Academic Markdown
Some of you who are following me mainly via the project’s official Twitter account might have waited for this piece on Zettlr. But all of you who don’t know me will also find today’s part of my How I work-series interesting: Because it’s all about leaving your comfort zone of Word and entering a world that is still in flux, but nevertheless more powerful than anything before it. So read on to see why I think Markdown, and not Word Processors, will mark the future of academic writing!
How I work, Part IV: Reference Management & Reading Literature
Today’s article of my series on how I work deals with my reference management. As you can see, we’re closing in on the “big” app Zettlr, which is my central hub for writing. However, even before I write any sentence, it’s important to read something and sort that into a decent reference manager. Mine is Zotero, and in this article I want to shed light upon why it’s almost without any alternative, and how I use it to read many papers in a short amount of time – and also, why I neglect many features of Zotero.
How I work, Part III: Data Science and Programming
Some of you might’ve expected that the second-most used app on my computer is Zettlr. However, two reasons prevent me from introducing it just now: For one, I’m still in the middle of having ripped it apart, so that I don’t feel I can write about it, since many features are currently creeping into the app. But secondly, Zettlr isn’t actually the most-used app right now. Since I’m coming freshly from a course on Natural Language Processing (NLP), the most used app right now is my code editor. Enter Visual Studio Code.
How I work, Part II: Browsing the Web
In the second part of my series on how I work, I begin pretty much basic: with my web browser. Although the browser wars are more or less over, there are still some choices involved. For browsing the web, I exclusively use Google Chrome, and I recommend everyone to also use it. In this post, I describe why.
How I work, Part I: My Desk
The previous weeks were filled with littered thoughts about Facebook, Python, Sociology, and a lot of other stuff. Today, I want to begin a short series exploring how I work. The reasons for this are threefold. First and foremost, I have been asked a lot of times to explicate my workflow a little bit better. Many people are interested in how I work. Second, it seems to be a trend on Twitter for quite some time now, and people are engaging in serious debates on different workflows. And third, I currently have a lot of work going on behind the scenes with my own research and making Zettlr 2.0 a reality, so this series gives me the chance to plan a few articles ahead of time to give myself some space to finish more important work. So be prepared!
Implicit knowledge
A few days ago I had an inspiring video chat with three aspiring researchers. While talking to them, I realised that a lot of what I take for granted is actually heavily inaccessible knowledge that one only gets either through intensive research, or through a supportive supervisor. Here I ponder a little bit about this kind of implicit knowledge that makes up large parts of academia.
What is Wrong With This Company?
Facebook is a common target for both government regulation and user complaints. Being around for over a decade, Facebook certainly had its zenith long ago. However, as the world’s legislative bodies slowly catch up to the evolution of the digital realm and begin to recognise users’ rights around the globe, instead of adapting its business model, Facebook seems to choose the second-best option. Instead of adapting their business model, the company apparently attempts to force the globe back into the “good ol’ days” when user data was still just prey lying around to be eaten by a lion from silicon valley.
Methodological Scepticism
It took several weeks for me to write this article. Not so much because I don't think that today's topic is important, but rather because I felt I would do injustice to the cited papers here. I still have that vague feeling, but I am convinced that I did my best to honour the work of my fellow researchers. This article deals with methodological scepticism, or, for short: Never trust your methods.
What is a Generator?
This week, we implemented a classifier in our first lab-session of the Natural Language Processing course that I currently take at LiU. To pass the course, we actually have to write a lot of Python code, and as we – the PhD students from the Institute for Analytical Sociology – do not have any formal education in programming and computer science, it is proving hard to receive good results. One question my colleague had during the week was: “What is a generator?” Here’s the answer I gave her. (Probably a better one, because I had a few days to think about it.)
Setting up Python, numpy, and PyTorch natively on Apple M1
The new Apple M1 devices have received quite the attention in the past months. However, data scientists and engineers have been wary of upgrading too soon, and in my opinion rightfully so. However, it is possible to run a development setup natively on the ARM-architecture. In this post, I describe how.