Explainable Science | Hendrik Erz

Abstract: Two weeks into my PhD here at Linköping University, and I can finally shift to more "scientifically salient" blog posts. What this means? This post is all about what I learned within these two weeks on how to conduct testable, causal research.

It’s Friday the 13th, and the second week for me here at IAS is over. Don’t get me wrong: I’m not at all susceptible to folklore such as seeing any Friday the 13th as a bad day. To the contrary, I feel a little bit of delight every time, as each one of these days disproves those who still try to explain simple, bad luck with a date on the calender.

I’m more and more grooving with Norrköping and getting used to the huge portion sizes of Swedish produces — it’s hard to get any amount of cheese under 1kg, and about the same amount seems to be the default for minced meat over here, not to speak of the 15-egg-packages that are custom in Swedish supermarkets. At the same time, I am diving deep into the basic literature required for a PhD in Analytical Sociology. While revisiting texts I’ve read during my Bachelor’s degree, I was also pointed to two texts I’ve (re-)read during the past two weeks which deserve a closer look.

Since I finished my Master’s thesis, I’ve been somewhat out of the loop with regard to research. Having spent two years as a purely administrative assistant, the past year of being a researcher at IFSH was especially hard, as I have been alienated somewhat from academic work. Nevertheless, I’m finally getting back to reading large amounts of text every day, and it’s a relief to see that you can indeed not unlearn science – it’s just like riding a bike.

This was one of the fundamental reasons why I laid out a very detailed plan of reading which I currently hope to complete before returning home for Christmas. I began the reading by focusing on theoretical texts that deal with science as such. The first notable text in this regard is “Studies in the Logic of Explanation” by Carl Hempel and Paul Oppenheim. It’s quite old (1948), but it addresses something I took for granted for basically all my academic life: that, as soon, as we have some explanation for a phenomenon, we have addressed the cause. But, as they correctly state, “it may be explained that a car turned over on the road ‘because’ one of its tires blew out while the car was travelling at high speed” (p. 138f).

This analogy was some kind of an eye-opener for me, as my theoretic explanations in past papers followed kind of a similar logic. In my paper on Gustave Le Bon’s influence on how riots are viewed in sociology, the fundamental problem I addressed was the fact that most of (German) sociological tradition treats crowds indiscriminately, and followed that this was because Gustave Le Bon was the first to deal with crowds and hence set the general scientific framing of riots as events. Was this a scientific explanation? Not according to scientific theory, because what is missing here is some attribute that generalises this explanation. In Hempel/Oppenheim’s words, my explanation was particular.

Fortunately, due to a very meticulous reviewer, I added the necessary attributes and generalisations: Upon reviewing the literature, I found two peculiarities with regard to the literature: First, the literature was bipolar – one strand of literature fundamentally treated crowds as their own distinctive being, and hence was unable to account for the agency of individual rioters. The other strand focuses solely on the individual rioters and was thus unable to take a look at possible outcomes of these events (the “big picture”).

Hempel/Oppenheim propose some simple formal criteria which any explanation must fulfil in order to be of any scientific salience (p. 137), and in this paper originates the notion of explanans and explanandum that we are being taught so casually nowadays:

  • R1: “The explanandum must be a logical consequence of the explanans […]”
  • R2: “The explanans must contain general laws, and these must actually be required for the derivation of the explanandum.”
  • R3: “The explanans must have empirical content; i.e., it must be capable, at least in principle, of test by experiment or observation.”
  • R4: “The sentences constituting the explanans must be true.”

This paper has had such a profound “Take on me” “A-ha”-effect on me because of another one I’ve read this week: Duncan Watts’ “Common Sense and Sociological Explanations” (2014), where he in general says that sociology would focus too much on “intuitive” explanations rather than scientific ones. While there has been some legitimate controversy around this exclusivity he opens up (see this comment and the response by Watts), I tend to agree that many sociological findings are rather particular and not predictive. (For instance, I am not able to predict any other scientific development based on my paper.)

You know what the best thing is? All of these problems of explanation and predictability are well-lit within the discourse of Analytical Sociology as far as I can tell; so possibly I’ll learn quickly how to bridge the aforementioned micro-macro gap of sociological explanations and be able to conduct testable research so that there’s less space for interpretability, and much more for trial & error!


  • Erz, H. (2019). Der lange Schatten von Gustave Le Bon. Zum sprachlichen Einfluss der Crowd Science auf die Soziologie der Gewalt. Soziologiemagazin, 2019(2), 71–88. https://doi.org/10.3224/soz.v12i2.06
  • Hempel, C. G., & Oppenheim, P. (1948). Studies in the Logic of Explanation. Philosophy of Science, 15(2), 135–175. https://doi.org/10.1086/286983
  • Watts, D. J. (2014). Common Sense and Sociological Explanations. American Journal of Sociology, 120(2), 313–351. https://doi.org/10.1086/678271
Suggested Citation

Erz, Hendrik (2020). “Explainable Science”. hendrik-erz.de, 13 Nov 2020, https://www.hendrik-erz.de/post/explainable-science.

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